Computer Servers in Germany: A Strategic Reference, 2006
Edited by
Philip M. Parker, Ph.D. Eli Lilly Chair Professor of Innovation, Business and Society INSEAD (Fontainebleau & Singapore)
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About Icon Group International, Inc. Icon Group International, Inc.’s primary mission is to assist managers with their international information needs. U.S.-owned and operated, Icon Group has field offices in Paris, Hong Kong, and Lomé, Togo (West Africa). Created in 1994, Icon Group has published hundreds of multi-client databases, and global/regional market data, industry and country publications. Global/Regional Management Studies: Summarizing over 190 countries, management studies are generally organized into regional volumes and cover key management functions. The human resource series covers minimum wages, child labor, unionization and collective bargaining. The international law series covers media control and censorship, search and seizure, and trial justice and punishment. The diversity management series covers a variety of environmental context drivers that effect global operations. These include women’s rights, children’s rights, discrimination/racism, and religious forces and risks. Global strategic planning studies cover economic risk assessments, political risk assessments, foreign direct investment strategy, intellectual property strategy, and export strategies. Financial management studies cover taxes and tariffs. Global marketing studies focus on target segments (e.g. seniors, children, women) and strategic marketing planning. Country Studies: Often managers need an in-depth, yet broad and up-to-date understanding of a country’s strategic market potential and situation before the first field trip or investment proposal. There are over 190 country studies available. Each study consists of analysis, statistics, forecasts, and information of relevance to managers. The studies are continually updated to insure that the reports have the most relevant information available. In addition to raw information, the reports provide relevant analyses which put a more general perspective on a country (seen in the context of relative performance vis-à-vis benchmarks). Industry Studies: Companies are racing to become more international, if not global in their strategies. For over 2000 product/industry categories, these reports give the reader a concise summary of latent market forecasts, pro-forma financials, import competition profiles, contacts, key references and trends across 200 countries of the world. Some reports focus on a particular product and region (up to four regions per product), while others focus on a product within a particular country.
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Table of Contents 1
INTRODUCTION & METHODOLOGY.............................................................................1
1.1
What Does This Report Cover?
1
1.2
How to Strategically Evaluate Germany
1
1.3
Latent Demand and Accessibility in Germany
3
2
COMPUTER SERVERS IN GERMANY .............................................................................5
2.1
Latent Demand and Accessibility: Background
5
2.2
Latent Demand: Market Composition
5
2.3
Latent Demand: Dynamics
6
2.4 Latent Demand: Leading Segments 7 2.4.1 Blade Servers.............................................................................................................................................. 8 2.4.2 Operating Systems and Software................................................................................................................ 9 2.4.3 Storage Area Network (SAN) and Network-Attached Storage (NAS) .................................................... 10 2.5 Market Issues and Obstacles 10 2.5.1 Import Viability........................................................................................................................................ 10 2.5.2 WEEE and RoHS Legislation .................................................................................................................. 10 2.6
Accessibility: Trade Events
11
2.7
Key Contacts
12
3 FINANCIAL INDICATORS: COMPUTER PROGRAMMING, DATA PROCESSING AND COMPUTER RELATED SERVICES..............................................................................13 3.1 Overview 13 3.1.1 Financial Returns and Gaps in Germany.................................................................................................. 14 3.1.2 Labor Productivity Gaps in Germany....................................................................................................... 17 3.1.3 Limitations and Extensions ...................................................................................................................... 17 3.2 Financial Returns in Germany: Asset Structure Ratios 18 3.2.1 Overview .................................................................................................................................................. 18 3.2.2 Assets – Definitions of Terms .................................................................................................................. 18 3.2.3 Asset Structure: Outlook .......................................................................................................................... 21 3.2.4 Large Variances: Assets ........................................................................................................................... 22 3.2.5 Key Percentiles and Rankings .................................................................................................................. 25 3.3 Financial Returns in Germany: Liability Structure Ratios 40 3.3.1 Overview .................................................................................................................................................. 40 3.3.2 Liabilities and Equity – Definitions of Terms .......................................................................................... 40 3.3.3 Liability Structure: Outlook ..................................................................................................................... 42 3.3.4 Large Variances: Liabilities ..................................................................................................................... 43 3.3.5 Key Percentiles and Rankings .................................................................................................................. 46 3.4
Financial Returns in Germany: Income Structure Ratios
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Contents 3.4.1 3.4.2 3.4.3 3.4.4 3.4.5
v
Overview .................................................................................................................................................. 59 Income Statements – Definitions of Terms .............................................................................................. 59 Income Structure: Outlook ....................................................................................................................... 62 Large Variances: Income.......................................................................................................................... 63 Key Percentiles and Rankings .................................................................................................................. 66
3.5 Financial Returns in Germany: Profitability Ratios 81 3.5.1 Overview .................................................................................................................................................. 81 3.5.2 Ratios – Definitions of Terms .................................................................................................................. 81 3.5.3 Ratio Structure: Outlook .......................................................................................................................... 83 3.5.4 Large Variances: Ratios ........................................................................................................................... 84 3.5.5 Key Percentiles and Rankings .................................................................................................................. 87 3.6 Productivity in Germany: Asset-Labor Ratios 102 3.6.1 Overview ................................................................................................................................................ 102 3.6.2 Asset to Labor: Outlook ......................................................................................................................... 103 3.6.3 Asset to Labor: International Gaps......................................................................................................... 104 3.6.4 Key Percentiles and Rankings ................................................................................................................ 107 3.7 Productivity in Germany: Liability-Labor Ratios 122 3.7.1 Overview ................................................................................................................................................ 122 3.7.2 Liability to Labor: Outlook .................................................................................................................... 123 3.7.3 Liability and Equity to Labor: International Gaps.................................................................................. 124 3.7.4 Key Percentiles and Rankings ................................................................................................................ 127 3.8 Productivity in Germany: Income-Labor Ratios 140 3.8.1 Overview ................................................................................................................................................ 140 3.8.2 Income to Labor: Outlook ...................................................................................................................... 141 3.8.3 Income to Labor: Gaps ........................................................................................................................... 142 3.8.4 Key Percentiles and Rankings ................................................................................................................ 145
4 4.1
MACRO-ACCESSIBILITY IN GERMANY....................................................................160 Executive Summary
160
4.2 Economic Fundamentals and Dynamics 161 4.2.1 Social Security Reforms......................................................................................................................... 161 4.2.2 Labor Market.......................................................................................................................................... 161 4.3 Political Risks 162 4.3.1 Basic Government Structure .................................................................................................................. 162 4.4 Marketing Strategies 163 4.4.1 Services .................................................................................................................................................. 163 4.4.2 Trade Fairs ............................................................................................................................................. 164 4.4.3 Advertising Options ............................................................................................................................... 164 4.4.4 Associations ........................................................................................................................................... 165 4.4.5 Public Procurement ................................................................................................................................ 165 4.4.6 Marketing to the New Federal States ..................................................................................................... 165 4.5 Import and Export Regulation Risks 166 4.5.1 Self-Certification.................................................................................................................................... 167 4.5.2 Value Added Tax/Turnover Tax ............................................................................................................ 169 4.5.3 VAT Applicable to Online Sales............................................................................................................ 169
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Custom Regulations/Tariffs ................................................................................................................... 169
4.6 Investment Climate 170 4.6.1 Openness to Foreign Investment ............................................................................................................ 170 4.6.2 Conversion and Transfer Policies........................................................................................................... 170 4.6.3 Expropriation and Compensation ........................................................................................................... 170 4.6.4 Dispute Settlement ................................................................................................................................. 170 4.6.5 Performance Requirements and Incentives ............................................................................................ 171 4.6.6 Right to Private Ownership and Establishment ...................................................................................... 172 4.6.7 Intellectual Property Risks ..................................................................................................................... 173 4.6.8 Transparency of Regulatory System ...................................................................................................... 173 4.6.9 Capital Market Risks .............................................................................................................................. 174 4.6.10 Political Violence ................................................................................................................................... 174 4.6.11 Corruption .............................................................................................................................................. 174 4.6.12 Bilateral Investment Agreements ........................................................................................................... 175 4.6.13 OPIC and Other Investment Insurance................................................................................................... 175 4.6.14 Labor ...................................................................................................................................................... 175 4.6.15 Free Trade Zone Options........................................................................................................................ 176 4.7
Trade and Project Financing
176
4.8 Travel Risks 177 4.8.1 Country Data .......................................................................................................................................... 177 4.9 Key Contacts 178 4.9.1 Trade Associations and Chambers of Commerce................................................................................... 179 4.9.2 Market Research Firms .......................................................................................................................... 180 4.9.3 Commercial Banks ................................................................................................................................. 181 4.9.4 Other Contacts........................................................................................................................................ 182 4.9.5 Contacts in Washington D.C. ................................................................................................................. 182 4.9.6 U.S.-Based Multipliers ........................................................................................................................... 183 4.9.7 Useful Web Sites .................................................................................................................................... 184
5
DISCLAIMERS, WARRANTEES, AND USER AGREEMENT PROVISIONS .........185
5.1
Disclaimers & Safe Harbor
185
5.2
Icon Group International, Inc. User Agreement Provisions
186
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1 1.1
INTRODUCTION & METHODOLOGY WHAT DOES THIS REPORT COVER?
The primary audience for this report is managers involved with the highest levels of the strategic planning process and consultants who help their clients with this task. The user will not only benefit from the hundreds of hours that went into the methodology and its application, but also from its alternative perspective on strategic planning relating to computer servers in Germany. As the editor of this report, I am drawing on a methodology developed at INSEAD, an international business school (www.insead.edu). For any given industry or sector, including computer servers, the methodology decomposes a country’s strategic potential along four key dimensions: (1) latent demand, (2) micro-accessibility, (3) proxy operating pro-forma financials, and (4) macro-accessibility. A country may have very high latent demand, yet have low accessibility, making it a less attractive market than many smaller potential countries having higher levels of accessibility. With this perspective, this report provides both a micro and a macro strategic profile of computer servers in Germany. It does so by compiling published information that directly relates to latent demand and accessibility, either at the micro or macro level. The reader new to Germany can quickly understand where Germany fits into a firm’s strategic perspective. In Chapter 2, the report investigates latent demand and micro-accessibility for computer servers in Germany. In Chapters 3 and 4, the report covers proxy operating pro-forma financials and macro-accessibility in Germany. Macro-accessibility is a general evaluation of investment and business conditions in Germany.
1.2
HOW TO STRATEGICALLY EVALUATE GERMANY
Perhaps the most efficient way of evaluating Germany is to consider key dimensions which themselves are composites of multiple factors. Composite portfolio approaches have long been used by strategic planners. The biggest challenge in this approach is to choose the appropriate factors that are the most relevant to international planning. The two measures of greatest relevance to computer servers are “latent demand” and “market accessibility”. The figure below summarizes the key dimensions and recommendations of such an approach. Using these two composites, one can prioritize all countries of the world. Countries of high latent demand and high relative accessibility (e.g. easier entry for one firm compared to other firms) are given highest priority. The figure below shows two different scenarios. Accessibility is defined as a firm’s ease of entering or supplying from or to a market (the “supply side”), and latent demand is an indicator of the potential in serving from or to the market (the “demand side”).
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Framework for Prioritizing Countries Demand/Market Potential Driven Firm
High
Highest Priority
High Priority Latent Demand
Moderate Priority Low Priority
Low
Lowest Priority Low
High Relative Accessibility
Accessibility/Supply Averse Firm High Highest Priority High Priority Latent Demand
Moderate Priority Low Priority Lowest Priority
Low High
Low Relative Accessibility
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Introduction & Methodology
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In the top figure, the firm is driven by market potential, whereas the bottom figure represents a firm that is driven by costs or by an aversion to difficult markets. This report treats the reader as coming from a “generic firm” approaching the global market – neither a market-driven nor a costdriven company. Planners must therefore augment this report with their own company-specific factors that might change the priorities (e.g. a Canadian firm may have higher accessibility in Canada than a German firm).
1.3
LATENT DEMAND AND ACCESSIBILITY IN GERMANY
This report provides a detailed overview of factors driving latent demand and accessibility for computer servers in Germany. Latent demand is largely driven by economic fundamentals specific to computer servers. This topic is discussed in Chapter 2 using work carried out in Germany on behalf of American firms and authored by the United States government (typically commercial attachés or similar persons in local offices of the U.S. Department of State). I have included a number of edits to clarify the information provided. Latent demand only represents half of the picture. Chapter 2 also deals with micro-accessibility for computer servers in Germany. I use the term “micro” since the discussion is focused specifically on computer servers. Chapter 3 is also a stand-alone report that I have authored. It covers proxy pro-forma financial indicators of firms operating in Germany. I use the word “proxy” because the provided figures only cover a “what if” scenario, based on actual operating results for firms in Germany. The numbers are only indicative of an average firm whose primary activity is in Germany. It covers a vertical analysis of the maximum likelihood balance sheet, income statement, and financial ratios of firms operating in Germany. It does so for a particular Standard Industrial Classification (SIC) code. That code covers “computer programming, data processing and computer related services”, as defined in Chapter 3. Again, while “computer programming, data processing and computer related services” does not exactly equate to “computer servers”, it nevertheless gives an indicator of how Germany compares to other countries for a proxy adjacent category along various dimensions. Chapter 4 deals with macro-accessibility and covers factors that go beyond computer servers. A country may at first sight appear to be attractive due to a high latent demand, but it is often less attractive when one considers at the macro level how easy it might be to serve that entire potential and/or general business risks. While accessibility will always vary from one company to another for a given country, the following domains are typically considered when evaluating macroaccessibility in Germany: •
Openness to Trade in Germany
•
Openness to Direct Investment in Germany
•
Local Marketing and Entry Strategy Alternatives
•
Local Human Resources
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Introduction & Methodology •
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Local Risks
Across these domains, a number of not-so-obvious factors can affect accessibility and risk. These are covered in the Chapter 4, which is a general overview of investment and business conditions in Germany. Chapter 4 is also presented from the perspective of an American firm, though is equally applicable to most firms entering Germany. This chapter is also authored by local offices of the U.S. government, as is Chapter 2. Likewise, I have included a number of edits to clarify the provided information as it relates to the general strategic framework mentioned earlier.
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2
COMPUTER SERVERS IN GERMANY
2.1
LATENT DEMAND AND ACCESSIBILITY: BACKGROUND
Europe’s largest server market has continued to exhibit slow but steady growth. The increase in sales of cheaper servers indicates a move toward large-volume deployment, a good sign, as companies seem willing to spend to meet exponentially increasing data-movement needs in spite of tight budgets. After four years of economic stagnation and a subsequent reluctance to invest, German firms face a pent-up demand for investments in IT communications infrastructure, including a demand for more powerful server systems (RISC/UNIX). Renewal cycles and price reductions have had a positive impact on mid-range and x86 server sales. However, blade servers are the fastest growing sector and will continue to flourish as infrastructure investments are improving and blades and related concepts are gaining greater acceptance in the German market.
2.2
LATENT DEMAND: MARKET COMPOSITION
According to the recent research, German business reached its highest level since the post-reunification boom. This has helped to fuel the market’s steady growth. Sales of mid-range to high-end servers are likely to increase even more in 2006 as firms plan to make major purchases before the Value Added Tax increases from 16% to 19% on January 1, 2007. The favorable EUR-USD exchange rate has also prompted a considerable increase in German demand for U.S. IT products and services.
Market Value Growth, 2005-2006
8
6.8
6.7
7 6
4.4
5 4
3.1
3.4
4.7 4
3.9
4.7 2005 3.7
2006
4.1
4.4
2.3
3 2
1
percent
1 0
Country
Source: IDC, 10/2005 Europe’s largest economy expanded at a weak 0.9% in 2005, after experiencing flat growth in the fourth quarter. However, with consumer and business expectations reaching fifteen-year highs, the economy is expected to grow at a healthier 2% this year. As a result of these positive trends, total IT spending in Germany is forecast to climb by 3.6% in 2006. Governments (both state and federal) and the healthcare industry are expected to be the driving forces behind IT growth in the near future. Industry analysts believe that because Europe still lags behind the United States in Internet penetration, there is room for continuous and stable growth for IT in general and server systems in particular. The number of Internet users in Germany continues to grow with 63% of the total population using the Internet in 2005 a figure expected to rise to approximately 80% by 2007.The German IT market grew by EUR 3.3 www.icongrouponline.com
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billion from 2004 to 2005 and an increase of EUR 3.6 billion is expected for 2006. However, Germany’s growth rate remains below the EU average.
2.3
LATENT DEMAND: DYNAMICS
The server market is generally divided up into three categories, the high-end, the mid-range and the low-end, or volume, server. It is important to mention that the categories for server-classification have been changed from previous reports.
Server Market in Three Categories (USD) Server Category Volume Server (Low-End) Mid-Range Server High-End Server
Price 24,999 25,000-499,999 500,000
In Germany, volume-servers hold the largest share of market revenue, which continued to increase by 6% in 2004. Revenues for mid-range servers grew 3%, marking the fourth consecutive quarterly increase in that segment, but revenues for high-end servers declined by 1.2%. Sales of mid-range servers have lost ground due to the increased power of volume servers that are usually adequate for a large percentage of companies’ needs. The roughly EUR 4.7 billion German server market in total is estimated to grow at a rate of 2.4% in 2006 and 7.8% in 2007.
Percentage Share of Total Server Revenues in Europe, 2005 (%) High End Medium Range Low End Share of Total European Market
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32.8 32.6 21.1 26.3
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Hardware Shipments, 2003-2007 (Units) Total
2003 363,590
2004 414,594
2005 410,818
2006* 420,822
2007* 453,702
*Projected
2.4
LATENT DEMAND: LEADING SEGMENTS
Germany remains the most important European market for high-end servers, although only 1,306 of the 363,590 servers sold in Germany in 2003 were high-end. Representing just 0.003% of total units sold, they generated EUR 1.235 billion or 38.3% of total revenues. Low-end servers with 98.5% of unit sales generated EUR 1.374 billion or 46.5% of revenues. In 2005, revenue growth in the overall server market increased by 4.3% but it is expected to only increase by 0.4% in 2006. Companies tend to buy high-end servers during periods of expansion and invest in lowerend hardware during other times. Due to the economic downturn over the last few years, companies have been under constant pressure to lower costs, and in many cases have generally opted for more cost efficient products. This trend continued throughout 2004 resulting in a 14% increase in unit sales of low-end servers and a corresponding 6% increase in revenues. Volume servers lead the market in sales due to competitive pricing and declining production costs. High-end hardware shipments grew only by 3% and the prognosis for 2006 shows a decline of 1.5%. In addition to the higher purchase costs, high-end servers have more complex maintenance, require more IT know-how, and often have more compatibility issues with other equipment. The consumer has become convinced that volume servers offer the same scope of supply and services as high-end servers.
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Server Revenues in Germany, 2002-2006 (EUR Millions) 2002 1,436 960 1,186 2,582
High-End Servers Mid-Range Servers Low-End Servers Total
Units
2003 1,235 884 1,103 3,222
2004 1,136 813 1,247 3,196
2005 1,159 854 1,321 3,334
2006* 1,130 854 1,374 3,358
High-End Servers Unit Sales
1,500
1,457
1,435
1,414
1,450 1,400 1,350
1,306
1,300 1,250 Year
1,200 2003
2004
2005 *
2006 *
Total Unit Sales Units 500,000 450,000 400,000 350,000 300,000 250,000 200,000 150,000 100,000 50,000 0
488,691 414,594
443,655
363,590
Year 2003
2004
2005 *
2006 *
Source: European Information Technology Observatory, 2005
2.4.1
Blade Servers
Blade servers are the fastest growing server segment and it is projected that by 2008, 29% of all servers sold will be blade servers. Universities and research facilities were the first main purchasers of blade servers in the German market. Large financial firms and a growing number of mid-sized companies then began moving to blade servers. The complexity of these servers made them initially unattractive to smaller firms, but with more simplified systems
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on the market, smaller companies and organizations are recognizing the advantages such technology can bring to their firm. The worldwide server blade market shows continued impressive growth, with shipments increasing by 72.1% and factory revenue gaining 96.8% year over year. Lower pricing and their versatile functionality have helped push demand for these segments. Overall, blade servers, including x86, EPIC and RISC blades, accounted for EUR 474 million in the third quarter of 2005. That represents 4.6% of the quarterly server market revenue. IBM maintained the number one spot in terms of server blade revenues, with a 42.0% market share, followed by HP with 31.6%. Dell held the number three position with a 9.0% share of factory blade revenues. According to IDC, the number of blade units sold in Western Europe will increase to 565,000 units by 2009 amounting to EUR 1.74 billion, with an average growth rate of 30.6% per year. The electricity consumed by a server over its lifetime is likely to cost as much as the server itself if energy costs continue to rise, according to some analysts. Blade servers draw up to 20 times the electrical power per rack, and generate up to 20 times the heat per rack, compared with what the average data center was designed for. Because this often requires the power and cooling infrastructure in a data center to be upgraded, many smaller firms are still reluctant to upgrade. While the true value of blade servers lies in better resource management and utility computing, German firms are still investing in blades with the goal of saving money and space.
2.4.2
Operating Systems and Software
There is a growing tendency in Germany, especially in the public sector, to seek alternatives to Microsoft products. This has lead to changes in the structure of the server software market with users looking for independent software. Mid-range and high-end systems are dominated by the Unix OS, which has also been successful in increasing its market share in the volume server market, and it is still regarded as the key OS for core IT infrastructure. By 2008, approximately 25% of all servers sold will be equipped with Linux for a total volume of EUR 7.5 million. In the same year, 60% of server sales will be delivered with Windows Server totaling some EUR 18.9 million. The most popular server operating systems on the German market are Microsoft Windows, Linux, Unix and NetWare. OS/400, S/390, and OpenVMS only comprise 2% of the market share.
Server Operating System Shipments, 2004 Other NetWare (21,397) Unix (55,646)
Linux (55,652)
Windows (205,760)
Source: Fujitsu-Siemens, 2005
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Storage Area Network (SAN) and Network-Attached Storage (NAS)
Low cost, high capacity storage is becoming of increasing importance to the German market as companies continue to adopt more data-intensive applications, expand web-enabled applications, and stress security issues and disaster recovery strategies. Direct Attached Storage (DAS) solutions held a market share of nearly 80% in 1998, but that number has fallen to less than 10%. Currently, Storage Area Networks (SANs) comprise about 60% of the storage market and about half of all Germany companies use SANs, leaving considerable growth potential. With their high bandwidth, SANs are especially attractive to customers for whom both performance and security are of high importance. iSCSI, a relatively new technology, has received the attention of many IT purchasers. Strong growth markets include File/Print-Server solutions. Small and middle-sized companies have shown interest in this technology mainly due to its ease of implementation. Network-Attached Storage (NAS) holds 30% of the market share with demand steadily increasing. Small and midsized companies often prefer Window-Server-Systems and HP has chosen to use standard-based elements for its custom solutions, and by reducing costs, has helped it to become the market leader in NAS.
2.5 2.5.1
MARKET ISSUES AND OBSTACLES Import Viability
Although there are no import tariffs on servers in Germany, there is a 16% import turnover tax, which is levied on all imported servers. This tax is passed on in later distribution stages to the end-user as a value-added tax, which is applied to all domestic products as well. Most servers sold in Germany are produced domestically or elsewhere in the EU. Therefore, there is little direct importing done from the United States and instead any importing generally happens on a micro-level with trade mainly in server components. However, the big four firms have other production or subsidiary facilities in the United States, which makes the measurement of direct import/export between Germany and the U.S. difficult to measure. Overall, the U.S. market share is very small for servers, but it is rather sizeable for server components.
2.5.2
WEEE and RoHS Legislation
The EU enacted “Waste Electrical and Electronic Equipment” (WEEE) and the Restriction of the Use of Certain Hazardous Substances (RoHS) Directives were implemented with the aim of the avoidance and reduction of waste from electrical and electronic equipment. The product developer should consider the recycle ability from the beginning of the design process. The directive now places responsibility on the producer and the importer for the finance of waste treatment, such as collecting, and recycling the electrical and electronic equipment. The directive covers among other things household appliances, IT and Telecom equipment, medical equipment or monitoring and control instruments. Electrical and electronical equipment is considered to be all equipment dependent on electric currents or electromagnetic fields or electrical equipment that can not fulfill its primary function without electrical current. Companies are encouraged to design their product as green as possible in order to save disposal costs down the road. All manufacturers, re-sellers and importers must register with the German “Elektro-Altgeraete Register” (EAR). The RoHS directive supports the aims of the WEEE in reducing the amount of dangerous chemicals used in the production process. From July 1, 2006 onwards, any new Electrical or Electronic Equipment product (EEE) put on the market cannot contain more than 0.1% lead, mercury, hexavalent chromium, polybrominated biphenyls (PBB)
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and polybrominated diphenyl ethers (PBDE) and 0.01% cadmium. This measure is meant to reduce the risk of exposure to those dangerous substances and to require less special handling. The national law conforming to the EU legislation, the “Act of Governing the Sale, Return and Environmentally Sound Disposal of Electrical and Electronic Equipment”, known as the ElektroG, was passed in Germany on March 23, 2005. The ElektroG is an incorporation of the WEEE and RoHS directives. Its main purpose is to prevent waste from electrical and electronic equipment and to promote reuse, recycling and other forms of recovery to reduce the volume of waste for disposal and the inclusion in waste of harmful substances from waste electrical and electrical equipment (WEEE). By December 31, 2006, an average of at least 4 kg per capita per year of electronic and electrical waste must be collected separately from private households. It is the producer’s responsibility to take back, recycle, and reuse or dispose of a product. In addition, they are required to register with the official German Clearinghouse, the EAR foundation (www.stiftung-ear.de) and are to provide an annual deposit to be used in case of insolvency to finance the waste disposal of products placed on the market by the producer after August 13, 2005. Producers are now required to take responsibility for the whole life cycle of their products, not just when a consumer buys their product. All American manufacturers wishing to supply the German market must comply with the directives. For more in-depth information, contact: BITKOM- Federal Association for Information Technologies, Telecommunications and New Media Albrechtstrasse 10 10711 Berlin Phone: +49 030 27576 0 Web site: www.bitkom.org For the Actual Legislation (in German), go to: www.umwelt-online.de/cgibin/parser/Drucksachen/drucknews.cgi?texte=0053_2D05#h19.
2.6
ACCESSIBILITY: TRADE EVENTS
Trade fairs play a major role in the marketing of ICT products in Germany. The world’s premier ICT show, “CeBIT,” is held annually in Hannover. Deutsche Messe AG Messegelaende D-30521 Hannover, Germany Tel: +49 511 89 0 Fax: +49 511 89 32 626 Web site: www.cebit.de Art Parades Hannover Fairs USA, Inc. Los Angeles Office 5757 Century Blvd. Los Angeles, CA 90045, USA Tel: 310 410-91 91 ext. 202 Fax: 310 410-93 96 E-mail:
[email protected]
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KEY CONTACTS
•
German E-Commerce Association: www.eco.de
•
Association for Electrical, Electronic and Informational Technologies: www.vde.de
•
European Committee for Standardization: www.cenorm.de
•
National Institute of Standards and Technology: www.nist.gov
•
European Committee for Electro technical Standardization: www.cenelec.org
•
German Association for the Information Industry: www.viw.de
•
German E-Commerce Association: www.eco.de
•
Federal Information Technology Association: www.bvit.de
•
Information Technology Association: www.itaa.org
•
Context-European Source for IT Market Info: www.context1.com
•
Verband deutscher Elektrotechniker: www.vde.de
•
European Committee for Standardization: www.cenorm.be
•
German Electro technical Commission: www.dke.de
•
European Committee for Electro technical Standardization: www.cenelec.org
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13
3
3.1
FINANCIAL INDICATORS: COMPUTER PROGRAMMING, DATA PROCESSING AND COMPUTER RELATED SERVICES OVERVIEW
Is Germany competitive? With the globalization of markets, the increased mobility of corporate assets, and the need for productive human resources, this question has become all the more complex to answer. The financial indicators section was prepared to tackle this question by focusing on certain fundamentals: financial performance and labor productivity. Rather than focus on the economy as a whole, the analysis presented here considers only one sector: computer programming, data processing and computer related services. We are essentially interested in the degree to which firms operating in Germany have fundamentally different financial structures and performance compared to firms located elsewhere. With respect to this view of competitiveness, if one were to invest or operate in Germany, how would the firm’s asset structure likely vary compared to a firm operating in some other country in Europe or average location in the world? In Germany, do firms typically hold more cash and other short term assets, or do they concentrate their assets in physical plant and equipment? On the liability side, do firms operating in Germany have a higher percent of payables compared to other firms operating in Europe, or do they hold a higher concentration of long term debt? The structure of the income statement is also telling. Do firms operating in Germany have relatively higher costs of goods sold, operating costs, or income taxes compared to firms located elsewhere in the region or the world in general? Are returns on equity higher in Germany? Are profit margins greater? Are inventories held longer? The financial indicators section was designed to answer these and similar questions that naturally affect one’s decision to invest or operate in Germany. Again, we are particularly interested in computer programming, data processing and computer related services, and not the economy as a whole. In many instances, people make all the difference. In addition to financial competitiveness, we consider the extent to which labor deployment and productivity in Germany differs from regional and global benchmarks. In this case, we are interested in the amount of labor required to operate a typical business in Germany and the likely returns on this human investment. What is the typical ratio of short-term and long-term assets to employee (employed in computer programming, data processing and computer related services operations)? What are typical capital-labor ratios? How different are these ratios to those in Europe in general and the world as a whole? What are the average sales and net profits per employee in Germany compared to regional benchmarks? The goal of this section is to assist managers in gauging the competitive performance of Germany at the global level for computer programming, data processing and computer related services. With the globalization of markets, greater foreign competition, and the reduction of entry barriers, it becomes all the more important to benchmark Germany against other countries on a worldwide basis. Doing so, however, is not an obvious task. This report generates international benchmarks and measures gaps that might be revealed from such an exercise. First, data is collected from companies across all regions of the world. For each of these firms, data are standardized into comparable categories (assets, liabilities, income and ratios), by country, region and on a worldwide basis. From there, we eliminate all currency effects by standardizing within each category. Global benchmarks are then compared to those estimated for computer programming, data processing and computer related services in Germany. Though we heavily rely on historical performance, the figures reported are not historical but are forecasts and projections for the coming fiscal year.
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Financial Indicators
3.1.1
14
Financial Returns and Gaps in Germany
The approach used in this report to evaluate operating performance for computer programming, data processing and computer related services in Germany is called "vertical analysis." For those unfamiliar with this type of analysis, frequently taught in graduate schools of business, the reader is recommended Jae K. Shim and Joel G. Siegel’s recent book titled Financial Management.1 In their discussion of financial statement analysis and ratios, Skim and Siegel (p. 42-43), describe common-size statement (vertical analysis) as follows: A common-size statement is one that shows each item in percentage terms. Preparation of common-size statements is known as vertical analysis, in which a material financial statement item is used as a base value and all other accounts on the financial statement are compared to it. In the balance sheet, for example, total assets equal 100 percent, and each individual asset is stated as a percentage of total assets. Similarly, total liabilities and stockholders’ equity are assigned a value of 100 percent and each liability or equity account is then stated as a percentage of total liabilities and stockholders’ equity, respectively. … For the income statement, a value of 100 percent is assigned to net sales, and all other revenues and expense accounts are related to it. It is possible to see at a glance how each dollar of sales is distributed among various costs, expenses, and profits. The authors suggest that vertical analyses involve industry-based comparisons. Such a comparison “allows you to answer the question, ‘How does a business fare in the industry?’ You must compare the company’s ratios to… industry norms.” (p. 43-44) This approach is extended to country competitiveness (in this case Germany) for a particular sector (in this case computer programming, data processing and computer related services). This involves calculating country, regional and global norms. This introduction will describe the seven-stage methodology used to perform this analysis. Each stage should be seen as a working assumption behind the numbers presented in later chapters. Stage 1. Industry Classification. This stage begins by classifying the company into an industry. For this, we have relied on a combination of the North American Industry Classification System (NAICS pronounced “Nakes”), a relatively new system for classifying business establishments, and the older Standard Industrial Classification (SIC) system. Adopted in 1997, NAICS codes are the new industry classification codes used by statistical agencies of the United States. NAICS was developed jointly by the U.S., Canada, and Mexico to provide comparability in statistics about business activity across North America. After 60 years of service, the outdated SIC system was retired on October 1, 2000, leaving only the NAICS codes for official use. The NAICS classification system adds some 350 new industries and represents a revision to over 60% of the previous SIC industries. Despite its official retirement, the SIC system is still commonly used (and often reported in firm’s financial statements). For most companies in the world, classification within either the new NAICS or older SIC systems is a rather straight forward exercise. For some, however, it can be problematic. This is true for several reasons. The first being that the SIC or NAICS classification systems are rather broad for many product and industry categories (a firm’s products or services may be only a minor aspect of the classification’s definition). The second is that some firms’ activities span multiple codes. Finally, it is possible that a firm is classified by one source using its SIC code, and by another using its NAICS code, and by a third using both. Furthermore, some sources do not report either code, but instead use qualitative statements of the firm’s activities. Nevertheless, if one wishes to pursue a vertical analysis, some classification needs to take place which selects a peer group. In making this classification, one can rely on a number of sources. In some countries, firms must “self” classify in official periodic reports (e.g. annular reports, 10Ks, etc.) to public authorities (such as the Securities and Exchange Commission). These reports are then open for public scrutiny (e.g. EDGAR filings). In other cases, commercial data vendors or private research firms provide SIC/NAICS codes for specific companies. These include: •
Bloomberg - www.bloomberg.com
1
Skim and Siegel (2000), Financial Management published by Barron’s Educational Series, Inc. (BARON’S BUSINESS LIBRARY Series), ISBN: 0-7641-1402-6. www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators •
15
Datastream (Thomson Financial) - www.datastream.com
•
Dun & Bradstreet - www.dnb.com
•
Hoovers - www.hoovers.com
•
HarrisInfoSource - www.HarrisInfo.com
•
InfoUSA - www.infousa.com
•
Investext (Thomson Financial) - www.investext.com
•
Kompass International Neuenschwander SA. – www.kompass.com
•
Moody's Investors Service - www.moodys.com
•
Primark (Thomson Financial) - www.primark.com
•
Profound (The Dialog Corporation – A Thomson Company) - www.profound.com
•
Reuters - www.reuters.com
•
Standard & Poor's - www.standardandpoors.com
It is interesting to note that commercial vendors often report different qualitative descriptions and industrial classifications from one to another. These descriptions and classifications may also be different from those reported by the firm itself. Anyone hoping to perform a benchmarking study, therefore, has to make a judgment call across these various sources in order to determine a reasonable classification. In this report, we have decided a metaanalytic process, by combining various sources (including linking a classification’s keywords to qualitative descriptions of the firm’s product line). In cases of inconsistency, the most recent or globally comparable available is chosen. Again, the overall goal is to classify firms, which either produce similar products, offer similar services, or are in the same stage of the value chain for a particular industrial classification. In the case of this report, the SIC code selected is: 737 which is defined as “computer programming, data processing and computer related services”. This classification should be seen as a working assumption. In order to obtain a more detailed discussion of this classification, the reader is referred to the Web sites developed by the U.S. Census Bureau: http://www.census.gov/epcd/www/naics.html. Basic definitions and descriptions are provided at: http://www.census.gov/epcd/www/drnaics.htm#q1. A full correspondence table between SIC and NAICS codes, and detailed definitions are given at http://www.census.gov/epcd/www/naicstab.htm. Stage 2. Firm-level Data Collection. A global search was conducted across over 20,000 companies in over 40 major economies, including Germany, for those that report financials (balance sheet and income statements) and that are involved in computer programming, data processing and computer related services. It should be noted that the public-domain financials can be either historic or projections. It should also be noted that even historic figures can be modified in the future and often represent “estimates” of performance. Stage 3. Standardization. Once collected, public domain financial figures of firms identified in Stage 2 are standardize into comparable categories (assets, liabilities, and income). Again, these are limited to firms involved in some aspect of computer programming, data processing and computer related services (i.e. are members of the value chain). From there, we eliminate all currency effects by standardizing within each category (creating ratios). In order to maintain comparability over time and across countries, vertical analysis is used. In the case of a firm’s assets, we treat the total assets as equaling 100, irrespective of the value of the local currency. All other assets are then calculated as a percent of total assets. In this way, the structure of the firm’s assets can be easily interpreted and compared with international benchmarks. For liabilities, total liabilities and equity are indexed to equal to 100. For the income statement, total revenue is indexed to equal 100, and all other figures are calculated as a percent of these figures. Stage 4. Filtering. Not all the firms selected in Stage 2 or the ratios calculated in Stage 3 are used for the country, regional or global benchmarks, as a number of companies are purposely dropped from the analysis. This is justified by the “outlier” phenomenon that plagues such analysis. The problem lies in that any given company in the benchmarking pool may be facing some exceptional event or may be organized in an exceptional way so as to make
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Financial Indicators
16
its ratios vastly different from the norm. By including such firms, the global benchmarks can be overly skewed. In many countries, firms are organized into holding groups. These groups nominally have very few employees (e.g. 4 to 25 employees), but have extremely large assets, liabilities, or revenues. As such, the inclusion or exclusion of firms having this form of management can affect the ratios and benchmarks reported. Likewise, some firms have no net sales, no assets, no liabilities, or ratios. Others have ratios that appear implausible for a normal or viable company. In order to not allow these firms to affect the global benchmarks, only those firms with reasonable financials have been chosen. Finally, in some countries, detailed financials are not available or are not comparable to either the company in question or the global norm (e.g. various forms of depreciation). In this case, only those which exist and are comparable are reported. The details, therefore, that comprise a given ratio or set of ratios may not be reported. This may lead to the addition of several ratios, not summing to the whole. Stage 5. Calculation of Global Norms. Once the filtering process has eliminated outliers, a final list of companies included is compiled. Based on this list, the ratios discussed in Stage 3 are calculated for every firm, and then averaged to create country, regional and global benchmarks. The world average is calculated using each country’s population as a weight. Stage 6. Projection of Deviations. The goal of this report is not only to estimate raw ratios or averages, but also to present the difference between Germany and projected global averages for that same ratio. Furthermore, it can be insightful to know the location of each ratio within the distribution of the countries represented in Stage 5. These deviations, in fact, can be seen as projections or likely scenarios for the future. This is often true for two reasons. First, while a company’s financials change from year to year, its ratios are often stable. This is especially true for the country, regional and global benchmarks which represent averages across companies. From a purely Bayesian sense, the difference between the company’s recent ratios and the benchmarks are a reasonable prior for future deviations. This is true, even if the entire industry is hit by an external or exogenous shock, such as an oil crisis or economic slowdown. In other words, we assume that the structure of the variance in the industry’s financials remains stable. Second, many of the data are based on preliminary reports that might be changed in future filings. As forecasts, therefore, the numbers derived from these are also forecasts of past and future performance (with associated uncertainties). The calculation of the difference between a country’s ratios and the global benchmarks is meant to yield roughly approximate forecasts, or "useful measures". Within Europe, the reliability of estimates varies from one country to another for those ratios given in tables that report national averages. This is true because reliable source statistics are not available for all countries in Europe. Countries with the highest reliability, or sample sizes after filtering in Stage 4, include Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Spain, Sweden, Switzerland, and United Kingdom. Others are generally econometrically extrapolated using models that use country characteristics (e.g. income per capita) as independent variables (i.e. countries having similar economic structures are assumed to have similar operating ratios). Again, the forecasts are based on the assumption of relative stability. This assumption has proven extremely robust in previous applications of this methodology (i.e. today’s weather is a good predictor of tomorrow’s weather, but not the weather three years from now). The results reported should be viewed as those for a “proto-typical” firm operating in Germany whose primary activity is computer programming, data processing and computer related services. Stage 7. Projection of Ranks and Percentiles. Based on the calculation of deviations, relative ranks and percentiles are calculated across the firms used in the benchmarks. The percentile estimates the percent of a representative sample of countries in the world having values of the ratio lower than Germany. It is important to note that a percentile being high (or low) does not mean good (or bad) past, present or future financial performance. The reader must draw this conclusion on their own. The estimates provided were created to provide managerial insight, and not a recommendation with respect to particular investments within any country. We graphically report, for each part of the financial statement, the larger structural differences between Germany and the regional and global benchmarks, and provide a summary table of ranks and percentiles. These are estimates for firm which would be involved in computer programming, data processing and computer related services. A deviation from the global norm need not be a bad sign. Rather, it is simply a substantial difference that might merit further attention or perhaps signal a country's relative strength or weakness for the coming fiscal year. www.icongrouponline.com
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Financial Indicators
3.1.2
17
Labor Productivity Gaps in Germany
In the case of labor productivity measures, this report maintains comparability over time and across countries by using a common currency (the US dollar) and relates each measure to a “per employee basis”. Ratios are projected using raw financial statistics and, as ratios, are therefore comparable. Given a country’s human resource ratios, the resulting figures are benchmarked across regional and global averages. The seven stage approach given above is used in a similar manner. We then report, for each part of the financial statement, the larger labor productivity gaps that Germany has vis-à-vis the worldwide average (for computer programming, data processing and computer related services). Again, a gap need not be a bad sign. Rather, it is simply a substantial difference that might merit further attention or signal a firm’s relative incentive to invest locally. All figures are projections, so due caution is required.
3.1.3
Limitations and Extensions
Shim and Siegal (p. 60) stress that “while ratio analysis is an effective tool for assessing a company’s financial condition,” operating Germany or any other country, “its limitations must be recognized.” They find that (p. 59) “no single ratio or group of ratios is adequate for assessing all aspects of a company’s financial condition” operating in a particular country. The authors note the following limitations associated with ratio analyses which apply to the global benchmarking and vertical analysis presented here (p.60): • • • • • • • •
Accounting standards or policies may limit useful comparisons across companies Management accounting practices across companies and countries may not be performed in the same style Ratios are static and do not reveal future trends Ratios do not indicate the quality of the components used to calculate the ratios (i.e. ratios have ambiguous interpretations) Reported ratios may not reflect real values Companies may be highly diversified, limiting the comparability of their ratios to others Industry averages or norms are approximate; finer industry definitions may be required for certain interpretations or comparisons Financial statements and resulting ratios often mean different things to different people depending on their points of view or motivations.
Again, all figures reported here are estimates, so due caution is required. The above caveats, and the fact that statements made in this report are forward-looking, requires that this point be emphasized. A number of intervening factors can have material effect on the ratios and variances forecasted. These include changes in a company's management style, exchange rate volatility, changes in accounting standards, the lack of oversight or comparability in accounting standards, changes in economic conditions, changes in competition, changes in the global economy, changes in source data quality, and similar factors.
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Financial Indicators
3.2 3.2.1
FINANCIAL RETURNS RATIOS
IN
18
GERMANY: ASSET STRUCTURE
Overview
In this chapter we consider the asset structure of companies involved in computer programming, data processing and computer related services operating in Germany benchmarked against global averages. The chapter begins by defining relevant terms. A common-size statement, or vertical analysis of assets is then presented for companies operating in Germany and the average global benchmarks (total assets = 100 percent). For ratios where there are large deviations between Germany and the benchmarks, graphics are provided (sometimes referred to as a financial “gap” analysis). Then the distribution of ratios is presented in the form of ranks and percentiles. Certain key vertical analysis asset ratios are highlighted across countries in the comparison group.
3.2.2
Assets – Definitions of Terms
The following definitions are provided for those less familiar with the asset-side of financial statement analysis. As this chapter deals with the vertical analysis and global benchmarking of assets, only definitions covering certain terms used in this chapter’s tables and graphs are provided here . The glossary below reflects commonly accepted definitions across various countries and official sources. •
Accumulated Depreciation - Buildings. Accumulated depreciation is commonly understood as a contra asset account used to report the accumulation of periodic credits to reflect the use of the estimated service life of a fixed asset. Buildings are fixed assets which represent the acquisition and improvement costs of permanent structures owned or held by the company. Such structures typically include office buildings, storage quarters, or other facilities and also associated items such as loading docks, heating and airconditioning equipment, refrigeration equipment, and all other property permanently attached to or forming an integral part of the structure. However, it generally does not include furniture, fixtures, or other equipment which are not an integral part of the building.
•
Accumulated Depreciation – Property, Plant & Equipment Under Capitalized Leases. Accumulated depreciation of property, plant and equipment under capitalized leases is commonly understood as a contra asset account used to report the accumulation of periodic credits to reflect the use of the estimated service life of property, plant and equipment under capitalized lease obligations.
•
Accumulated Depreciation - Transportation Equipment. Accumulated depreciation of transportation equipment is commonly understood to be contra asset account used to report the accumulation of periodic credits to reflect the use of the estimated service life of transportation equipment.
•
Accumulated Depreciation -Machinery & Equipment. Accumulated depreciation of machinery and equipment is commonly understood to be contra asset account used to report the accumulation of periodic credits to reflect the use of the estimated service life of machinery and equipment.
•
Buildings. Buildings are defined as fixed assets which represent the acquisition and improvement costs of permanent structures owned or held by the company. Such structures include office buildings, storage quarters, or other facilities and also associated items such as loading docks, heating and air-conditioning equipment, refrigeration equipment, and all other property permanently attached to or forming an integral part of the structure. However, it does not include furniture, fixtures, or other equipment which are not an integral part of the building.
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Financial Indicators
19
•
Cash. Cash is typically defined as money on hand, on deposit with chartered bank, or held in the form of eligible securities.
•
Current Assets. Current assets are generally defined to be resources which are available, or can readily be made available, to meet the cost of operations or to pay current liabilities.
•
Deferred Charges. Deferred charges are generally understood to represent the amount which has been paid for services already received by the company but has not been charged to operations.
•
Finished Goods. Finished goods generally comprise the ready-for-sale inventory.
•
Intangible Other Assets. Intangible assets are generally understood to be nonphysical assets such as legal rights (patents and trademarks) recorded at their historical cost then reduced by systematic amortization.
•
Investments in Unconsolidated Subsidiaries. Investments in unconsolidated subsidiaries are typically defined as investments for the purpose of generating revenue in subsidiaries whose financial statements are not combined with the company's.
•
long Term Receivables. Long-term receivables are commonly defined as amounts due within a period exceeding one year from private persons, businesses, agencies, funds, or governmental units which are expected to be collected in the form of moneys, goods, and/or services.
•
Machinery & Equipment. Machinery and equipment is commonly defined as a fixed asset classification which typically includes tangible property (other than land, buildings, and improvements other than buildings) with a life of more than one year. Such assets typically include office equipment, furniture, machine tools, and motor vehicles. Equipment may be attached to a structure for purposes of securing the item, but unless it is permanently attached to an integral part of the building or structure, it will generally be classified as equipment and not buildings. Equipment is generally defined as tangible property other than land, buildings, or improvements other than buildings, which is used in operations. Examples include machinery, tools, trucks, cars, furniture, and furnishings.
•
Prepaid Expenses. Prepaid expenses are typically defined as those supplies and/or services (not inventory) acquired or purchased but not consumed or used at the end of the accounting period.
•
Progress Payments. Progress payments are commonly defined as periodic payments to a supplier, contractor, or subcontractor for work as it is completed as desired, in order to reduce working capital requirements.
•
Property Plant & Equipment Under Capitalized Leases. Property plant & equipment under capitalized leases generally consists of the gross book value (rather than the more commonly-used measures of fixed capital stocks in current or real value), of all commercial buildings, associated land and equipment used therein that are owned by the company and that are either used or operated by the company or leased or rented to others (under capitalized leases).
•
Property Plant and Equipment - Gross. Gross property, plant and equipment generally consists of the gross book value (rather than the more commonly-used measures of fixed capital stocks in current or real value), of all commercial buildings, associated land and equipment used therein that are owned by the company and that are either used or operated by the company or leased or rented to others.
•
Property Plant and Equipment - Net. Net PP&E equals the original cost of property, plant, and equipment (PP&E), less accumulated depreciation, depletion and amortization (DD&A).
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Financial Indicators
20
•
Raw Materials. Raw materials are materials which will be converted by a manufacturer into a finished product.
•
Receivables (Net). Net receivables are defined as the net amount due to the company from private persons, businesses, agencies, funds, or governmental units which is expected to be collected in the form of moneys, goods, and/or services.
•
Rental/Lease Property. Rental or leased property is property necessary to the operation of the company and paid for the use of structures, land, roads, rolling stock and equipment.
•
Short Term Investments. Short-term investments are investments which can be typically liquidated in less than one year.
•
Tangible Other Assets. Other tangible assets are commonly understood to be something substantial or real that is capable of being given an actual or approximate value (market or estimated), not classified elsewhere.
•
Total Assets. Total assets are defined as the financial representation of economic resources, the beneficial interest in which is legally or equitably secured to a particular organization as a result of a past transaction or event.
•
Total Inventories. Total inventories are defined as the total amount of goods on hand.
•
Transportation Equipment. Transportation equipment is equipment used for the transportation of goods for sale.
•
Work in Process. Work in progress includes goods which have been started but are not yet ready for sale.
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Financial Indicators
3.2.3
21
Asset Structure: Outlook
Using the methodology described in the introduction, the following table summarizes asset structure benchmarks for firms involved in computer programming, data processing and computer related services in Germany. To allow comparable benchmarking, a common index of Total Assets = 100 is used. All figures are current-year projections for companies operating in Germany based on latest financial results available. Asset Structure Germany Europe World Avg. _________________________________________________________________________________________________________
Cash & Short Term Investments Cash Short Term Investments Receivables (Net) Total Inventories Raw Materials Work in Process Finished Goods Progress Payments & Other Prepaid Expenses Other Current Assets Current Assets - Total Long Term Receivables Investments in Unconsolidated Subsidiaries Other Investments Property Plant and Equipment - Net Property Plant and Equipment - Gross Buildings Machinery & Equipment Rental/Lease Property Transportation Equipment Other Property Plant & Equipment Property Plant & Equipment Under Capitalized Leases Accumulated Depreciation - Total Accumulated Depreciation - Buildings Accumulated Depreciation -Machinery & Equipment Accumulated Depreciation - Rental/Lease Property Accumulated Depreciation - Transportation Equipment Accumulated Depreciation - Other Prop & Equip Accumulated Depreciation - PP&E Under Capitalized Leases Other Assets Deferred Charges Tangible Other Assets Intangible Other Assets Total Assets
28.70 15.28 15.44 28.15 5.74 1.33 1.36 4.64 0.56 0.82 3.87 67.66 0.77 0.26 0.88 12.75 23.68 6.10 5.82 23.36 8.12 10.51 3.82 11.77 1.55 3.84 21.04 2.66 6.39 6.27 19.55 0.59 0.51 18.37 100.00
18.36 11.91 8.33 32.42 5.30 2.14 1.57 2.70 0.81 1.04 4.81 61.66 1.22 3.92 2.01 18.52 35.27 10.23 20.03 48.06 3.06 6.41 4.44 15.73 2.97 7.55 20.16 0.95 3.84 1.62 11.86 0.79 1.10 10.12 100.00
19.43 9.28 11.78 24.30 6.66 2.22 1.33 2.79 0.89 1.28 3.28 54.42 1.18 4.34 4.13 20.33 36.43 6.92 14.77 10.02 1.58 10.71 3.79 15.09 1.16 4.85 4.57 0.39 4.74 0.41 10.81 0.45 1.08 7.06 100.00
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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Financial Indicators
3.2.4
22
Large Variances: Assets
The following graphics summarize for computer programming, data processing and computer related services the large asset structure gaps between firms operating in Germany and the world average. A gap cannot necessarily be interpreted as a positive or negative reflection on performance. Gaps may signal areas of specialization, market focus, or expertise. More contextual information is required to fully interpret these gaps. The gaps highlighted here are simply those that are large.
Gap: Cash & Short Term Investments 30
28.7
25
19.43
18.36
20 15
9.27
10 5 0 Germ any
Europe
World Average
Gap
Gap: Cash 20 15
15.28 11.91 9.28
10
6
5 0 Germ any
Europe
World Average
Gap
Gap: Current Assets - Total 80
67.66
61.66
60
54.42
40 13.24
20 0 Germ any
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Europe
World Average
Gap
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Financial Indicators
23
Gap: Property Plant and Equipment - Net 25 20 15 10 5 0 -5 -10
18.52
20.33
12.75
-7.58 Germ any
Europe
World Average
Gap
Gap: Property Plant and Equipment - Gross 35.27
40 30
36.43
23.68
20 10 0 -10
-12.75
-20 Germ any
Europe
World Average
Gap
Gap: Machinery & Equipment 25 20 15 10 5 0 -5 -10
20.03 14.77 5.82
Germ any
Europe
World Average
-8.95 Gap
Gap: Rental/Lease Property 48.06
50 40 30
23.36
20
10.02
10
13.34
0 Germ any
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Europe
World Average
Gap
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Financial Indicators
24
Gap: Transportation Equipment 10 8
8.12 6.54
6 3.06
4
1.58
2 0 Germ any
Europe
World Average
Gap
Gap: Accumulated Depreciation - Rental/Lease Property 25
21.04
20
20.16 16.47
15 10
4.57
5 0 Germ any
Europe
World Average
Gap
Gap: Other Assets 20
19.55
15
11.86
10.81
10
8.74
5 0 Germ any
Europe
World Average
Gap
Gap: Intangible Other Assets 20
18.37
15
11.31
10.12
10
7.06
5 0 Germ any
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Europe
World Average
Gap
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Financial Indicators
3.2.5
25
Key Percentiles and Rankings
We now consider the distribution of asset ratios for computer programming, data processing and computer related services using ranks and percentiles. What percent of countries have a value lower or higher than Germany (what is the ratio's rank or percentile)? The table below answers this question with respect to the vertical analysis of asset structure. The ranks and percentiles indicate, from highest to lowest, where a value falls within the distribution of all countries considered in the global benchmark (the number of countries in the benchmark per line item may vary, as indicated in the Rank). Again, a high or low figure does not necessarily indicate good or bad performance. After the summary table below, a few key vertical asset ratios are highlighted in additional tables. Asset Structure
Germany
Rank of Total
Percentile
28.70 15.28 15.44 28.15 5.74 1.33 1.36 4.64 0.56 0.82 3.87 67.66 0.77 0.26 0.88 12.75 23.68 6.10 5.82 23.36 8.12 10.51 3.82 11.77 1.55 3.84 21.04 2.66 6.39 6.27 19.55 0.59 0.51 18.37 100.00
9 of 53 13 of 50 11 of 48 26 of 53 25 of 49 25 of 37 20 of 35 11 of 33 17 of 36 22 of 39 20 of 47 13 of 52 26 of 41 39 of 43 27 of 40 43 of 53 37 of 50 28 of 47 41 of 45 9 of 17 4 of 41 15 of 50 11 of 21 34 of 48 16 of 40 35 of 39 7 of 17 3 of 35 10 of 44 1 of 19 12 of 53 13 of 34 23 of 37 13 of 44
83.02 74.00 77.08 50.94 48.98 32.43 42.86 66.67 52.78 43.59 57.45 75.00 36.59 9.30 32.50 18.87 26.00 40.43 8.89 47.06 90.24 70.00 47.62 29.17 60.00 10.26 58.82 91.43 77.27 94.74 77.36 61.76 37.84 70.45
_________________________________________________________________________________________________________
Cash & Short Term Investments Cash Short Term Investments Receivables (Net) Total Inventories Raw Materials Work in Process Finished Goods Progress Payments & Other Prepaid Expenses Other Current Assets Current Assets - Total Long Term Receivables Investments in Unconsolidated Subsidiaries Other Investments Property Plant and Equipment - Net Property Plant and Equipment - Gross Buildings Machinery & Equipment Rental/Lease Property Transportation Equipment Other Property Plant & Equipment Property Plant & Equipment Under Capitalized Leases Accumulated Depreciation - Total Accumulated Depreciation - Buildings Accumulated Depreciation -Machinery & Equipment Accumulated Depreciation - Rental/Lease Property Accumulated Depreciation - Transportation Equipment Accumulated Depreciation - Other Prop & Equip Accumulated Depreciation - P P & E Under Capitalized Leases Other Assets Deferred Charges Tangible Other Assets Intangible Other Assets Total Assets
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
26
Cash & Short Term Investments Countries
Value (total assets = 100)
Rank
Percentile
49.18 35.01 32.34 31.75 29.89 29.77 29.66 29.43 28.70 28.40 28.31 28.00 27.75 26.29 25.43 25.24 24.20 24.12 22.75 21.40 21.08 20.49 19.51 19.26 19.18 18.42 18.07 17.94 16.95 16.68 16.33 15.89 14.56 12.92 12.51 12.42 12.28 6.96 6.86 6.84 4.84 4.73 3.86 3.75 1.02
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 20 22 23 24 25 26 27 28 29 30 32 33 34 35 36 39 40 41 42 44 45 46 48 49 50 51 53
98.11 96.23 94.34 92.45 90.57 88.68 86.79 84.91 83.02 81.13 79.25 77.36 75.47 73.58 71.70 69.81 67.92 66.04 62.26 58.49 56.60 54.72 52.83 50.94 49.06 47.17 45.28 43.40 39.62 37.74 35.85 33.96 32.08 26.42 24.53 22.64 20.75 16.98 15.09 13.21 9.43 7.55 5.66 3.77 0.00
Region
_________________________________________________________________________________________________________
New Zealand Israel Denmark Sweden Czech Republic Hong Kong Japan Brazil Germany Canada Singapore Chile USA China Norway South Korea Poland Indonesia Russian Federation Greece Finland Australia Italy Malaysia India Netherlands the United Kingdom South Africa Thailand France Switzerland Ireland Belgium Philippines Luxembourg Hungary Austria Portugal Turkey Mexico Spain Peru Pakistan Taiwan Argentina
Oceana the Middle East Europe Europe Europe Asia Asia Latin America Europe North America Asia Latin America North America Asia Europe Asia Europe Asia Europe Europe Europe Oceana Europe Asia Asia Europe Europe Africa Asia Europe Europe Europe Europe Asia Europe Europe Europe Europe the Middle East Latin America Europe Latin America the Middle East Asia Latin America
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
27
Cash & Short Term Investments (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total assets = 100)
Rank
Percentile
50.93 32.34 31.75 29.89 28.70 28.55 28.37 28.36 28.03 27.45 25.43 24.33 24.20 23.22 23.17 22.75 22.69 21.76 21.40 21.08 20.94 20.90 19.83 19.67 19.57 19.51 18.42 18.07 16.68 16.33 15.89 15.23 14.56 12.51 12.42 12.28 12.16 11.86 11.86 11.17 10.62 10.45 6.96 6.66 6.52 5.98 5.81 5.61 4.84 4.55 4.13
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Andorra Denmark Sweden Czech Republic Germany Faroe Islands Latvia Croatia Iceland Monaco Norway Estonia Poland Belarus Slovakia Russian Federation Lithuania Moldova Greece Finland Kazakhstan Bulgaria Malta Vatican City Isle of Man Italy Netherlands the United Kingdom France Switzerland Ireland Liechtenstein Belgium Luxembourg Hungary Austria San Marino Guernsey Jersey Ukraine Gibraltar Georgia Portugal Cyprus Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Spain Slovenia Albania
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
28
Receivables (Net) Countries
Value (total assets = 100)
Rank
Percentile
51.67 45.98 45.01 44.19 43.58 43.49 42.95 40.69 39.67 39.52 38.11 36.90 36.78 35.54 34.44 33.63 32.75 31.84 31.78 31.14 30.90 30.43 29.19 28.59 28.48 28.15 27.94 27.87 27.49 26.64 26.02 25.47 25.23 23.84 21.93 21.49 21.28 19.22 18.71 18.48 17.81 17.03 15.91 13.33 4.97
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 32 34 35 37 38 40 41 43 44 45 46 47 49 51 53
98.11 96.23 94.34 92.45 90.57 88.68 86.79 84.91 83.02 81.13 79.25 77.36 75.47 73.58 71.70 69.81 67.92 66.04 64.15 62.26 60.38 58.49 56.60 54.72 52.83 50.94 49.06 47.17 45.28 43.40 39.62 35.85 33.96 30.19 28.30 24.53 22.64 18.87 16.98 15.09 13.21 11.32 7.55 3.77 0.00
Region
_________________________________________________________________________________________________________
Austria Netherlands Portugal Spain France Hungary Ireland Taiwan Greece Belgium Argentina Italy South Africa Poland Norway Singapore Hong Kong the United Kingdom Thailand India Finland Malaysia Sweden Australia Denmark Germany Turkey Mexico Canada Luxembourg Japan USA Switzerland South Korea China Russian Federation Indonesia Philippines Brazil Israel Chile Czech Republic New Zealand Peru Pakistan
Europe Europe Europe Europe Europe Europe Europe Asia Europe Europe Latin America Europe Africa Europe Europe Asia Asia Europe Asia Asia Europe Asia Europe Oceana Europe Europe the Middle East Latin America North America Europe Asia North America Europe Asia Asia Europe Asia Asia Latin America the Middle East Latin America Europe Oceana Latin America the Middle East
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
29
Receivables (Net) (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total assets = 100)
Rank
Percentile
51.67 51.18 49.90 49.90 45.98 45.01 44.19 43.58 43.49 43.09 42.95 41.49 39.67 39.52 39.11 37.20 37.18 36.90 36.77 36.61 36.28 35.54 34.44 32.61 31.95 31.84 31.41 30.90 30.75 30.69 29.19 28.48 28.15 26.64 26.55 25.73 25.23 24.36 23.68 23.54 22.99 22.84 21.94 21.89 21.49 21.44 17.03 16.47 16.16 16.16 11.63
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Austria San Marino Guernsey Jersey Netherlands Portugal Spain France Hungary Cyprus Ireland Slovenia Greece Belgium Ukraine Vatican City Gibraltar Italy Malta Georgia Isle of Man Poland Norway Monaco Moldova the United Kingdom Faroe Islands Finland Kazakhstan Bulgaria Sweden Denmark Germany Luxembourg Romania Iceland Switzerland Bosnia & Herzegovina Macedonia Liechtenstein Estonia Serbia & Montenegro Belarus Slovakia Russian Federation Lithuania Czech Republic Andorra Latvia Croatia Albania
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
30
Total Inventories Countries
Value (total assets = 100)
Rank
Percentile
34.66 24.37 23.19 12.21 10.75 9.59 9.55 9.42 8.92 8.29 7.77 7.51 7.38 6.76 6.65 6.59 6.53 6.27 5.84 5.74 5.50 5.24 5.13 5.12 5.10 5.05 4.75 4.68 4.67 4.49 4.10 3.97 3.40 2.89 2.46 1.09 1.04 0.79 0.54 0.43 0.16 0.12
1 3 4 5 6 7 8 9 10 12 14 15 16 18 19 20 21 23 24 25 27 28 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49
97.96 93.88 91.84 89.80 87.76 85.71 83.67 81.63 79.59 75.51 71.43 69.39 67.35 63.27 61.22 59.18 57.14 53.06 51.02 48.98 44.90 42.86 38.78 36.73 34.69 32.65 30.61 28.57 26.53 24.49 22.45 20.41 18.37 16.33 14.29 12.24 10.20 8.16 6.12 4.08 2.04 0.00
Region
_________________________________________________________________________________________________________
Peru Brazil Chile South Africa China Hungary Philippines Switzerland Indonesia Norway Greece Spain South Korea Thailand Russian Federation Taiwan Singapore Netherlands Hong Kong Germany Denmark France Malaysia Portugal Sweden Japan Austria Canada Belgium Italy the United Kingdom Poland USA Argentina Australia India Czech Republic Finland Luxembourg Israel Pakistan Ireland
Latin America Latin America Latin America Africa Asia Europe Asia Europe Asia Europe Europe Europe Asia Asia Europe Asia Asia Europe Asia Europe Europe Europe Asia Europe Europe Asia Europe North America Europe Europe Europe Europe North America Latin America Oceana Asia Europe Europe Europe the Middle East the Middle East Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
31
Total Inventories (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total assets = 100)
Rank
Percentile
30.25 9.59 9.42 8.79 8.63 8.29 8.20 8.08 7.77 7.51 7.20 7.11 7.10 7.05 6.79 6.78 6.65 6.64 6.34 6.27 5.74 5.60 5.50 5.24 5.12 5.10 4.90 4.75 4.71 4.67 4.59 4.59 4.52 4.49 4.10 3.97 3.57 3.44 3.43 3.43 1.04 0.99 0.99 0.79 0.54 0.12
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46
97.83 95.65 93.48 91.30 89.13 86.96 84.78 82.61 80.43 78.26 76.09 73.91 71.74 69.57 67.39 65.22 63.04 60.87 58.70 56.52 54.35 52.17 50.00 47.83 45.65 43.48 41.30 39.13 36.96 34.78 32.61 30.43 28.26 26.09 23.91 21.74 19.57 17.39 15.22 13.04 10.87 8.70 6.52 4.35 2.17 0.00
_________________________________________________________________________________________________________
Albania Hungary Switzerland Liechtenstein Ukraine Norway Gibraltar Georgia Greece Spain Malta Estonia Isle of Man Slovenia Belarus Slovakia Russian Federation Lithuania Monaco Netherlands Germany Faroe Islands Denmark France Portugal Sweden Cyprus Austria San Marino Belgium Jersey Guernsey Vatican City Italy the United Kingdom Poland Moldova Kazakhstan Iceland Bulgaria Czech Republic Latvia Croatia Finland Luxembourg Ireland
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
32
Current Assets - Total Countries
Value (total assets = 100)
Rank
Percentile
79.78 75.99 73.83 73.48 73.46 73.17 73.13 72.48 71.98 70.56 69.91 68.27 67.66 67.63 67.57 67.21 66.37 66.26 66.13 65.09 62.87 62.42 61.66 61.54 60.74 60.57 60.27 60.22 59.55 58.74 58.16 57.59 56.54 55.54 55.46 54.42 54.30 53.58 53.44 53.34 49.12 44.65 42.45 42.37
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 35 37 38 39 40 41 42 46 47 48 49
98.08 96.15 94.23 92.31 90.38 88.46 86.54 84.62 82.69 80.77 78.85 76.92 75.00 73.08 71.15 69.23 67.31 65.38 63.46 61.54 59.62 57.69 55.77 53.85 51.92 50.00 48.08 46.15 44.23 42.31 40.38 38.46 36.54 32.69 28.85 26.92 25.00 23.08 21.15 19.23 11.54 9.62 7.69 5.77
Region
_________________________________________________________________________________________________________
Greece Norway Austria Brazil Denmark Hungary Netherlands Hong Kong Singapore Sweden Chile France Germany Finland Japan South Africa Thailand Poland Italy New Zealand Canada USA Switzerland South Korea Taiwan the United Kingdom China Portugal Belgium Malaysia India Spain Indonesia Ireland Russian Federation Israel Australia Turkey Mexico Peru Czech Republic Philippines Argentina Luxembourg
Europe Europe Europe Latin America Europe Europe Europe Asia Asia Europe Latin America Europe Europe Europe Asia Africa Asia Europe Europe Oceana North America North America Europe Asia Asia Europe Asia Europe Europe Asia Asia Europe Asia Europe Europe the Middle East Oceana the Middle East Latin America Latin America Europe Asia Latin America Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
33
Current Assets - Total (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total assets = 100)
Rank
Percentile
79.78 75.99 73.94 73.83 73.46 73.17 73.13 73.13 72.97 71.30 71.30 70.56 69.80 69.50 68.27 67.66 67.63 67.40 66.66 66.26 66.13 65.80 63.06 62.56 61.66 61.59 60.57 60.22 59.58 59.55 59.33 57.65 57.59 57.54 57.33 57.23 56.62 56.50 55.54 55.46 55.33 54.06 50.91 49.12 46.72 46.62 46.60 46.56 45.41 43.80 42.37
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Greece Norway Malta Austria Denmark Hungary Netherlands San Marino Isle of Man Guernsey Jersey Sweden Monaco Faroe Islands France Germany Finland Andorra Vatican City Poland Italy Ukraine Iceland Gibraltar Switzerland Georgia the United Kingdom Portugal Moldova Belgium Estonia Cyprus Spain Liechtenstein Kazakhstan Bulgaria Belarus Slovakia Ireland Russian Federation Lithuania Slovenia Romania Czech Republic Bosnia & Herzegovina Latvia Croatia Albania Macedonia Serbia & Montenegro Luxembourg
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
34
Property Plant and Equipment - Net Countries
Value (total assets = 100)
Rank
Percentile
45.92 45.73 45.60 44.62 35.48 35.35 31.26 31.12 29.84 28.00 26.77 25.19 24.97 23.49 20.94 20.85 20.39 19.89 19.79 19.65 18.69 18.26 18.20 17.67 17.31 16.50 15.70 14.61 14.04 14.01 13.97 13.93 13.86 13.50 12.75 12.59 11.74 11.10 9.73 8.92 7.79 7.49 7.39 6.99 6.34
1 2 3 4 6 7 8 9 10 12 13 17 18 20 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 43 44 45 46 47 48 49 50 51 52 53
98.11 96.23 94.34 92.45 88.68 86.79 84.91 83.02 81.13 77.36 75.47 67.92 66.04 62.26 58.49 56.60 54.72 52.83 50.94 49.06 47.17 45.28 43.40 41.51 39.62 37.74 35.85 33.96 32.08 30.19 28.30 26.42 24.53 22.64 18.87 16.98 15.09 13.21 11.32 9.43 7.55 5.66 3.77 1.89 0.00
Region
_________________________________________________________________________________________________________
Pakistan Turkey Mexico Czech Republic Argentina Peru Indonesia Thailand Philippines Malaysia Taiwan Luxembourg Switzerland Greece Singapore Italy India New Zealand the United Kingdom Hong Kong Japan Hungary Brazil Australia Chile China Norway USA Poland South Africa South Korea Spain Canada Finland Germany Russian Federation Netherlands Belgium Denmark France Ireland Austria Sweden Israel Portugal
the Middle East the Middle East Latin America Europe Latin America Latin America Asia Asia Asia Asia Asia Europe Europe Europe Asia Europe Asia Oceana Europe Asia Asia Europe Latin America Oceana Latin America Asia Europe North America Europe Africa Asia Europe North America Europe Europe Europe Europe Europe Europe Europe Europe Europe Europe the Middle East Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
35
Property Plant and Equipment - Net (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total assets = 100)
Rank
Percentile
44.62 43.45 42.35 42.33 39.87 38.75 37.38 30.86 25.19 24.97 23.49 23.30 21.77 21.48 21.02 20.85 20.59 20.30 19.79 18.84 18.26 16.42 15.70 15.61 15.37 14.75 14.04 13.93 13.50 13.47 13.08 12.86 12.83 12.75 12.62 12.59 12.56 12.15 12.13 11.74 11.10 9.73 8.92 7.79 7.49 7.42 7.39 7.24 7.24 6.34 6.07
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Czech Republic Romania Latvia Croatia Bosnia & Herzegovina Macedonia Serbia & Montenegro Albania Luxembourg Switzerland Greece Liechtenstein Malta Isle of Man Vatican City Italy Andorra Monaco the United Kingdom Faroe Islands Hungary Ukraine Norway Gibraltar Georgia Iceland Poland Spain Finland Estonia Slovenia Belarus Slovakia Germany Moldova Russian Federation Lithuania Kazakhstan Bulgaria Netherlands Belgium Denmark France Ireland Austria San Marino Sweden Guernsey Jersey Portugal Cyprus
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
36
Accumulated Depreciation - Total Countries
Value (total assets = 100)
Rank
Percentile
58.56 36.04 36.01 35.94 34.84 31.96 24.64 21.21 19.88 18.74 18.07 17.83 17.28 17.05 16.96 16.95 16.09 14.89 14.50 13.83 13.43 12.56 12.17 12.08 11.86 11.79 11.77 11.14 10.45 10.00 9.95 9.41 9.31 9.18 7.73 6.94 6.39 5.66 3.84 3.82
1 2 3 4 5 8 10 11 13 14 15 16 17 18 19 20 21 24 26 27 28 29 30 31 32 33 34 35 36 37 38 40 41 42 43 44 45 46 47 48
97.92 95.83 93.75 91.67 89.58 83.33 79.17 77.08 72.92 70.83 68.75 66.67 64.58 62.50 60.42 58.33 56.25 50.00 45.83 43.75 41.67 39.58 37.50 35.42 33.33 31.25 29.17 27.08 25.00 22.92 20.83 16.67 14.58 12.50 10.42 8.33 6.25 4.17 2.08 0.00
Region
_________________________________________________________________________________________________________
Pakistan Turkey Indonesia Mexico Switzerland Czech Republic Philippines Peru Malaysia Thailand Greece Brazil the United Kingdom Japan Chile Netherlands USA India Spain Australia Singapore France Belgium Finland Denmark Canada Germany Italy South Korea Norway Hong Kong Russian Federation Sweden New Zealand Poland South Africa Portugal China Ireland Israel
the Middle East the Middle East Asia Latin America Europe Europe Asia Latin America Asia Asia Europe Latin America Europe Asia Latin America Europe North America Asia Europe Oceana Asia Europe Europe Europe Europe North America Europe Europe Asia Europe Asia Europe Europe Oceana Europe Africa Europe Asia Europe the Middle East
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
37
Accumulated Depreciation - Total (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total assets = 100)
Rank
Percentile
34.84 34.25 32.51 31.96 31.43 30.54 30.34 30.32 29.46 18.51 18.07 17.28 16.95 16.74 16.52 16.25 14.50 13.61 13.02 12.56 12.17 12.08 11.86 11.77 11.23 11.14 10.07 10.00 9.61 9.59 9.54 9.51 9.41 9.39 9.31 7.73 6.95 6.69 6.68 6.39 6.12 3.84
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42
97.62 95.24 92.86 90.48 88.10 85.71 83.33 80.95 78.57 76.19 73.81 71.43 69.05 66.67 64.29 61.90 59.52 57.14 54.76 52.38 50.00 47.62 45.24 42.86 40.48 38.10 35.71 33.33 30.95 28.57 26.19 23.81 21.43 19.05 16.67 14.29 11.90 9.52 7.14 4.76 2.38 0.00
_________________________________________________________________________________________________________
Switzerland Romania Liechtenstein Czech Republic Bosnia & Herzegovina Macedonia Latvia Croatia Serbia & Montenegro Albania Greece the United Kingdom Netherlands Malta Isle of Man Iceland Spain Slovenia Monaco France Belgium Finland Denmark Germany Vatican City Italy Estonia Norway Belarus Slovakia Faroe Islands Andorra Russian Federation Lithuania Sweden Poland Moldova Kazakhstan Bulgaria Portugal Cyprus Ireland
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
38
Intangible Other Assets Countries
Value (total assets = 100)
Rank
Percentile
30.98 25.20 24.49 23.73 21.29 20.92 20.61 20.13 19.88 18.85 18.53 18.50 18.37 18.14 17.80 17.66 14.59 13.40 13.09 11.10 9.62 9.19 9.12 8.45 8.24 7.32 6.47 5.91 5.83 5.19 5.08 4.35 3.76 3.25 3.05 1.48 0.62 0.03 0.03
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 18 19 20 21 22 23 24 25 26 27 28 30 31 32 33 34 35 36 37 38 39 42 43
97.73 95.45 93.18 90.91 88.64 86.36 84.09 81.82 79.55 77.27 75.00 72.73 70.45 68.18 65.91 63.64 59.09 56.82 54.55 52.27 50.00 47.73 45.45 43.18 40.91 38.64 36.36 31.82 29.55 27.27 25.00 22.73 20.45 18.18 15.91 13.64 11.36 4.55 2.27
Region
_________________________________________________________________________________________________________
Luxembourg Belgium Ireland Australia Canada Israel Spain Sweden USA Philippines France the United Kingdom Germany Argentina Austria Finland Norway Netherlands Denmark Italy Switzerland India Portugal Hungary South Africa Poland South Korea Malaysia Russian Federation China Hong Kong Singapore Japan Greece New Zealand Czech Republic Thailand Turkey Mexico
Europe Europe Europe Oceana North America the Middle East Europe Europe North America Asia Europe Europe Europe Latin America Europe Europe Europe Europe Europe Europe Europe Asia Europe Europe Africa Europe Asia Asia Europe Asia Asia Asia Asia Europe Oceana Europe Asia the Middle East Latin America
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
39
Intangible Other Assets (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total assets = 100)
Rank
Percentile
30.98 25.20 24.49 20.61 20.13 20.09 19.35 18.53 18.50 18.37 17.80 17.66 17.63 17.19 17.19 14.59 13.40 13.09 11.19 11.10 9.62 9.12 8.98 8.73 8.45 7.60 7.32 7.22 7.11 6.58 6.34 6.32 6.24 5.96 5.94 5.83 5.82 4.87 4.22 3.25 3.16 3.01 2.97 1.48 1.40 1.40 0.03 0.02 0.02 0.02
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
98.00 96.00 94.00 92.00 90.00 88.00 86.00 84.00 82.00 80.00 78.00 76.00 74.00 72.00 70.00 68.00 66.00 64.00 62.00 60.00 58.00 56.00 54.00 52.00 50.00 48.00 46.00 44.00 42.00 40.00 38.00 36.00 34.00 32.00 30.00 28.00 26.00 24.00 22.00 20.00 18.00 16.00 14.00 12.00 10.00 8.00 6.00 4.00 2.00 0.00
_________________________________________________________________________________________________________
Luxembourg Belgium Ireland Spain Sweden Iceland Slovenia France the United Kingdom Germany Austria Finland San Marino Jersey Guernsey Norway Netherlands Denmark Vatican City Italy Switzerland Portugal Liechtenstein Cyprus Hungary Ukraine Poland Gibraltar Georgia Moldova Kazakhstan Bulgaria Estonia Belarus Slovakia Russian Federation Lithuania Faroe Islands Monaco Greece Andorra Malta Isle of Man Czech Republic Latvia Croatia Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
3.3 3.3.1
FINANCIAL RETURNS RATIOS
IN
40
GERMANY: LIABILITY STRUCTURE
Overview
In this chapter we consider the liability structure of firms operating in Germany benchmarked against global averages. The chapter begins by defining relevant terms. A common-size statement, or vertical analysis of liabilities and shareholder equity is then presented for the proto-typical firm operating in Germany and the average global benchmarks (sometimes referred to as a financial “gap” analysis). The figure reflect firms involved in computer programming, data processing and computer related services in Germany. For ratios where there are large deviations between Germany and the benchmarks, graphics are provided (total liabilities and equity = 100 percent). Then the distribution of ratios is presented in the form of ranks and percentiles. Certain key vertical analysis liability ratios are highlighted.
3.3.2
Liabilities and Equity – Definitions of Terms
The following definitions are provided for those less familiar with the liability-side of financial statement analysis. As this chapter deals with the vertical analysis and global benchmarking of liabilities and equity, only definitions covering certain terms used in this chapter’s tables and graphs are provided here . The glossary below reflects commonly accepted definitions across various countries and official sources. •
Accounts Payable. Accounts payable are defined as amounts owed on open account to private persons or organizations for goods or services received.
•
Accrued Payroll. Accrued payroll is defined as the cost of payroll that has been incurred but has not yet been paid. Payroll is typically defined as comprising records detailing the salaries, wages, allowances and deductions for each employee for a specific period of time.
•
Capital Surplus. Capital surplus is commonly defined as an amount of equity which is directly contributed capital in excess of the par value.
•
Capitalized Lease Obligations. A capitalized lease obligation is commonly defined as an ownership arrangement in which the item under lease is typically a long-term asset. Capital leases are generally recorded as assets with liability at the current value of the lease payment.
•
Common Equity. Common equity is defined to equal the company's net worth. It typically comprises capital stock, capital surplus, retained earnings, and, in some cases, net worth reserves. Common equity is the portion of total net worth belonging to the common stockholders. Synonyms which are often used for common equity are “common stock” and “net worth”.
•
Common Stock. Common stock is defined as the securities which represent the company's ownership interest. Common stockholders typically assume greater risk than preferred stockholders; although common stockholders maintain greater control and generally greater dividends and capital appreciation. Common stock can be used interchangeably with the term capital stock when the company has no preferred stock.
•
Current Liabilities - Total. Total current liabilities are defined as the total amount of obligations which would require the use of current assets or other current liabilities to pay.
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Financial Indicators
41
•
Current Portion of Long Term Debt. The current proportion of long term debt is typically defined as debt which is payable in more than one year.
•
Deferred Income. Deferred income is commonly defined as the amount for services rendered that has not yet been received.
•
Deferred Taxes. Deferred taxes are compulsory charges from a previous accounting period which are yet unpaid.
•
Deferred Taxes - Credit. Deferred tax credits are defined as credits against compulsory charges from a previous accounting period which are yet unpaid.
•
Income Taxes Payable. Income taxes payable are understood to mean taxes which are levied by state, federal, and local governments on the company's reported accounting profit. Income taxes payable are those which are due in the current accounting period.
•
Long Term Debt. Long-term debt is defined to be due in a period exceeding one year or one operating cycle, whichever is longer. Long-term debt can have an extended repayment period such as a many-year mortgage on land and buildings, or debt that's intended to be permanent such as bonds issued to investors.
•
Long Term Debt Excluding Capitalized Leases. Long term debt excluding capitalized leases is defined as debt which is typically due in a period exceeding one year or one operating cycle, whichever is longer, less capitalized leases (see Long Term Debt for exceptions). Capital leases are generally recorded as assets with liability at the current value of the lease payment.
•
Minority Interest. Minority interest is the proportional share of the minority ownership's interest (less than 50 percent) in the earnings or losses.
•
Non-Equity Reserves. Non-equity reserves are the amount set aside for losses or liabilities which are certain to arise but cannot be quantified with certainty, and are not part of the firm’s equity.
•
Retained Earnings. proprietary funds.
•
Shareholders Equity. Shareholders equity is commonly defined to be the amount of total equity reserved for common and preferred shareholders.
•
Short Term Debt. Short term debt is generally defined as debt payable within one year.
•
Total Liabilities. Total liabilities are generally defined to include all the claims against a corporation. Liabilities include accounts and wages and salaries payable, dividends declared payable, accrued taxes payable, fixed or long-term liabilities such as mortgage bonds, debentures, and bank loans.
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Retained earnings is an equity account reflecting the accumulated earnings of
©2007 Icon Group International, Inc.
Financial Indicators
3.3.3
42
Liability Structure: Outlook
Using the methodology described in the introduction, the following table summarizes liability and equity structure benchmarks for firms involved in computer programming, data processing and computer related services in Germany. To allow comparable benchmarking, a common index of Total Liabilities & Shareholders Equity = 100 is used. All figures are current-year projections for companies operating in Germany based on latest financial results available. Liability Structure Germany Europe World Avg. _________________________________________________________________________________________________________
Accounts Payable Short Term Debt & Current Portion of Long Term Debt Accrued Payroll Income Taxes Payable Other Current Liabilities Current Liabilities - Total Long Term Debt Long Term Debt Excluding Capitalized Leases Capitalized Lease Obligations Provision For Risks and Charges Deferred Income Deferred Taxes Deferred Taxes - Credit Deferred Taxes - Debit Other Liabilities Total Liabilities Non-Equity Reserves Minority Interest Common Equity Common Stock Capital Surplus Other Appropriated Reserves Unappropriated Reserves Retained Earnings Unrealized Foreign Exchange Gain/Loss Unrealized Gain/Loss on Marketable Securities Treasury Stock Total Liabilities & Shareholders Equity
7.29 6.45 3.38 2.16 12.75 27.98 4.62 3.52 1.13 5.94 1.23 -0.41 1.96 2.05 3.77 38.64 0.02 0.58 60.81 15.64 38.81 2.13 -1.35 12.17 -0.28 0.00 0.82 100.00
12.07 8.31 4.61 2.77 18.22 35.50 8.90 8.66 0.25 2.12 0.95 -0.29 1.20 0.84 2.12 46.42 0.10 1.12 47.67 11.70 20.34 8.82 5.84 9.80 -0.36 -0.06 0.76 100.00
7.46 8.65 1.72 1.92 9.50 26.76 5.97 5.82 0.15 0.97 0.21 -0.30 0.36 0.83 1.60 34.81 0.17 1.45 56.89 20.59 23.44 3.58 11.10 10.82 -0.03 0.17 1.00 100.00
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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©2007 Icon Group International, Inc.
Financial Indicators
3.3.4
43
Large Variances: Liabilities
The following graphics summarize for computer programming, data processing and computer related services the large liability structure gaps between firms operating in Germany and the world average. A gap cannot necessarily be interpreted as a positive or negative reflection on performance. Gaps may signal areas of specialization, market focus, or expertise. More contextual information is required to fully interpret these gaps. The gaps highlighted here are simply those that are large.
Gap: Short Term Debt & Current Portion of Long Term Debt 10 8 6 4 2 0 -2 -4
8.31
8.65
6.45
-2.2 Germ any
Europe
World Average
Gap
Gap: Accrued Payroll 4.61
5 4
3.38
3 1.72
2
1.66
1 0 Germ any
Europe
World Average
Gap
Gap: Other Current Liabilities 18.22
20 15
12.75 9.5
10
3.25
5 0 Germ any
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Europe
World Average
Gap
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Financial Indicators
44
Gap: Long Term Debt Excluding Capitalized Leases 10 8 6 4 2 0 -2 -4
8.66 5.82 3.52
-2.3 Germ any
Europe
World Average
Gap
Gap: Provision For Risks and Charges 6
5.94 4.97
5 4 3
2.12
2
0.97
1 0 Germ any
Europe
World Average
Gap
Gap: Other Liabilities 4
3.77
3
2.17
2.12 1.6
2 1 0 Germ any
Europe
World Average
Gap
Gap: Total Liabilities 46.42
50 40
38.64
34.81
30 20 10
3.83
0 Germ any
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Europe
World Average
Gap
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Financial Indicators
45
Gap: Common Equity 80 60
60.81 47.67
56.89
40 20
3.92
0 Germ any
Europe
World Average
Gap
Gap: Common Stock 25 20
20.59 15.64
15
11.7
10 5 0 -5 Germ any
Europe
-4.95 Gap
World Average
Gap: Capital Surplus 40
38.81
30 20.34
23.44
20
15.37
10 0 Germ any
Europe
World Average
Gap
Gap: Unappropriated Reserves 15
11.1
10 5
5.84 1.35
0 -5 -10 Germ any
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Europe
World Average
-9.75 Gap
©2007 Icon Group International, Inc.
Financial Indicators
3.3.5
46
Key Percentiles and Rankings
We now consider the distribution of liability ratios for computer programming, data processing and computer related services using ranks and percentiles. What percent of countries have a value lower or higher than Germany (what is the ratio's rank or percentile)? The table below answers this question with respect to the vertical analysis of liability The ranks and percentiles indicate, from highest to lowest, where a value falls within the distribution of all countries considered in the global benchmark (the number of countries in the benchmark per line item may vary, as indicated in the Rank). Again, a high or low figure does not necessarily indicate good or bad performance. After the summary table below, a few key vertical liability ratios are highlighted in additional tables. Liability Structure
Germany
Rank of Total
Percentile
7.29 6.45 3.38 2.16 12.75 27.98 4.62 3.52 1.13 5.94 1.23 -0.41 1.96 2.05 3.77 38.64 0.02 0.58 60.81 15.64 38.81 2.13 -1.35 12.17 -0.28 0.00 0.82 100.00
31 of 47 28 of 52 11 of 26 21 of 41 20 of 52 39 of 52 40 of 52 40 of 52 6 of 30 2 of 33 9 of 21 31 of 44 9 of 23 8 of 27 13 of 48 35 of 53 15 of 18 24 of 45 12 of 53 26 of 50 5 of 44 29 of 50 33 of 33 22 of 51 23 of 29 4 of 7 9 of 22
34.04 46.15 57.69 48.78 61.54 25.00 23.08 23.08 80.00 93.94 57.14 29.55 60.87 70.37 72.92 33.96 16.67 46.67 77.36 48.00 88.64 42.00 0.00 56.86 20.69 42.86 59.09
_________________________________________________________________________________________________________
Accounts Payable Short Term Debt & Current Portion of Long Term Debt Accrued Payroll Income Taxes Payable Other Current Liabilities Current Liabilities - Total Long Term Debt Long Term Debt Excluding Capitalized Leases Capitalized Lease Obligations Provision For Risks and Charges Deferred Income Deferred Taxes Deferred Taxes - Credit Deferred Taxes - Debit Other Liabilities Total Liabilities Non-Equity Reserves Minority Interest Common Equity Common Stock Capital Surplus Other Appropriated Reserves Unappropriated Reserves Retained Earnings Unrealized Foreign Exchange Gain/Loss Unrealized Gain/Loss on Marketable Securities Treasury Stock Total Liabilities & Shareholders Equity
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
47
Accounts Payable Countries
Value (total liabilities & equity = 100)
Rank
Percentile
27.71 22.65 17.41 17.10 16.88 16.72 15.62 15.25 14.79 14.45 14.19 13.59 13.22 12.99 12.84 12.80 12.29 11.97 11.96 11.81 11.43 11.32 11.08 10.56 9.61 8.76 7.29 7.05 7.03 6.86 6.60 6.50 6.34 6.08 5.78 5.26 5.02 4.00 2.81 2.48
1 2 3 4 5 6 7 8 9 10 11 12 14 15 16 17 19 20 21 22 24 25 27 28 29 30 31 32 33 34 35 37 38 39 40 41 42 43 44 45
97.87 95.74 93.62 91.49 89.36 87.23 85.11 82.98 80.85 78.72 76.60 74.47 70.21 68.09 65.96 63.83 59.57 57.45 55.32 53.19 48.94 46.81 42.55 40.43 38.30 36.17 34.04 31.91 29.79 27.66 25.53 21.28 19.15 17.02 14.89 12.77 10.64 8.51 6.38 4.26
Region
_________________________________________________________________________________________________________
South Africa Hungary Singapore Poland Switzerland Argentina Philippines Greece Thailand Canada Luxembourg Belgium Japan Ireland Portugal France South Korea the United Kingdom Italy Malaysia Hong Kong Spain Russian Federation Netherlands Australia Denmark Germany Turkey Mexico China India USA Norway Brazil Chile New Zealand Sweden Finland Israel Indonesia
Africa Europe Asia Europe Europe Latin America Asia Europe Asia North America Europe Europe Asia Europe Europe Europe Asia Europe Europe Asia Asia Europe Europe Europe Oceana Europe Europe the Middle East Latin America Asia Asia North America Europe Latin America Latin America Oceana Europe Europe the Middle East Asia
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
48
Accounts Payable (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total liabilities & equity = 100)
Rank
Percentile
22.65 20.37 19.36 19.06 17.10 16.89 16.88 15.75 15.37 15.25 14.80 14.77 14.19 14.13 13.95 13.59 12.99 12.84 12.80 12.29 12.06 11.97 11.96 11.85 11.32 11.31 11.29 11.08 11.05 10.96 10.63 10.56 8.76 7.29 6.70 6.57 6.34 6.15 5.98 5.76 5.45 5.02 4.00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43
97.67 95.35 93.02 90.70 88.37 86.05 83.72 81.40 79.07 76.74 74.42 72.09 69.77 67.44 65.12 62.79 60.47 58.14 55.81 53.49 51.16 48.84 46.51 44.19 41.86 39.53 37.21 34.88 32.56 30.23 27.91 25.58 23.26 20.93 18.60 16.28 13.95 11.63 9.30 6.98 4.65 2.33 0.00
_________________________________________________________________________________________________________
Hungary Ukraine Gibraltar Georgia Poland Monaco Switzerland Liechtenstein Moldova Greece Kazakhstan Bulgaria Luxembourg Malta Isle of Man Belgium Ireland Portugal France Cyprus Vatican City the United Kingdom Italy Estonia Spain Belarus Slovakia Russian Federation Lithuania Faroe Islands Slovenia Netherlands Denmark Germany Romania Iceland Norway Bosnia & Herzegovina Macedonia Serbia & Montenegro Andorra Sweden Finland
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
49
Current Liabilities - Total Countries
Value (total liabilities & equity = 100)
Rank
Percentile
57.84 52.26 49.72 48.30 47.94 47.58 47.44 47.30 47.00 44.19 41.60 40.74 40.51 40.28 39.42 38.42 37.57 36.72 36.62 35.86 34.55 34.10 33.72 33.70 33.37 33.04 31.91 31.27 31.26 30.01 29.94 29.63 29.09 29.00 27.98 27.05 27.01 24.77 24.70 24.34 20.78 18.33 18.28 6.28
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 21 22 24 26 27 28 29 30 31 32 34 35 36 37 38 39 41 42 43 44 46 47 48 49 52
98.08 96.15 94.23 92.31 90.38 88.46 86.54 84.62 82.69 80.77 78.85 76.92 75.00 73.08 71.15 69.23 67.31 63.46 61.54 59.62 57.69 53.85 50.00 48.08 46.15 44.23 42.31 40.38 38.46 34.62 32.69 30.77 28.85 26.92 25.00 21.15 19.23 17.31 15.38 11.54 9.62 7.69 5.77 0.00
Region
_________________________________________________________________________________________________________
Austria Brazil Chile South Africa France Greece Spain Taiwan Portugal Thailand Norway Peru Netherlands the United Kingdom Belgium Hungary Argentina Turkey Mexico Sweden Switzerland Poland Denmark Singapore Italy Japan Luxembourg Hong Kong Australia South Korea Finland Ireland Philippines China Germany Russian Federation USA Czech Republic Canada Malaysia India Israel Indonesia New Zealand
Europe Latin America Latin America Africa Europe Europe Europe Asia Europe Asia Europe Latin America Europe Europe Europe Europe Latin America the Middle East Latin America Europe Europe Europe Europe Asia Europe Asia Europe Asia Oceana Asia Europe Europe Asia Asia Europe Europe North America Europe North America Asia Asia the Middle East Asia Oceana
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
50
Current Liabilities - Total (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total liabilities & equity = 100)
Rank
Percentile
57.84 57.29 55.86 55.86 47.94 47.58 47.44 47.00 44.99 44.54 44.10 43.52 41.60 40.51 40.28 39.42 38.42 35.86 35.56 34.88 34.55 34.55 34.10 33.72 33.64 33.37 32.85 32.68 32.35 32.24 32.01 31.91 31.11 30.66 30.01 29.98 29.94 29.63 29.50 29.45 28.93 27.98 27.62 27.55 27.29 27.05 26.98 24.77 23.52 23.51 6.50
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Austria San Marino Jersey Guernsey France Greece Spain Portugal Cyprus Slovenia Malta Isle of Man Norway Netherlands the United Kingdom Belgium Hungary Sweden Albania Romania Ukraine Switzerland Poland Denmark Vatican City Italy Gibraltar Monaco Georgia Liechtenstein Bosnia & Herzegovina Luxembourg Macedonia Moldova Serbia & Montenegro Faroe Islands Finland Ireland Kazakhstan Bulgaria Estonia Germany Belarus Slovakia Iceland Russian Federation Lithuania Czech Republic Latvia Croatia Andorra
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
51
Long Term Debt Countries
Value (total liabilities & equity = 100)
Rank
Percentile
27.80 21.65 20.84 20.78 18.98 18.57 18.44 15.49 13.92 13.77 13.40 11.36 11.23 10.88 10.35 9.89 9.40 8.85 8.76 8.72 8.53 8.46 8.45 8.10 7.97 7.03 6.96 6.91 6.83 6.62 5.14 5.08 4.64 4.62 3.60 3.40 3.21 3.12 3.12 2.61 2.36 1.11 0.94 0.67
1 2 3 4 7 8 9 10 11 12 13 15 16 17 19 20 21 22 23 24 25 26 27 29 30 31 32 33 34 35 36 37 39 40 41 42 43 44 45 48 49 50 51 52
98.08 96.15 94.23 92.31 86.54 84.62 82.69 80.77 78.85 76.92 75.00 71.15 69.23 67.31 63.46 61.54 59.62 57.69 55.77 53.85 51.92 50.00 48.08 44.23 42.31 40.38 38.46 36.54 34.62 32.69 30.77 28.85 25.00 23.08 21.15 19.23 17.31 15.38 13.46 7.69 5.77 3.85 1.92 0.00
Region
_________________________________________________________________________________________________________
Peru Portugal Turkey Mexico Ireland Poland Pakistan Philippines Spain Argentina Denmark Indonesia Italy Brazil Chile New Zealand South Africa France USA Norway Canada Australia the United Kingdom Finland Luxembourg Belgium Austria Switzerland Japan Netherlands South Korea Sweden Russian Federation Germany Thailand Taiwan Malaysia Hong Kong Greece Israel Singapore China India Hungary
Latin America Europe the Middle East Latin America Europe Europe the Middle East Asia Europe Latin America Europe Asia Europe Latin America Latin America Oceana Africa Europe North America Europe North America Oceana Europe Europe Europe Europe Europe Europe Asia Europe Asia Europe Europe Europe Asia Asia Asia Asia Europe the Middle East Asia Asia Asia Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
52
Long Term Debt (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total liabilities & equity = 100)
Rank
Percentile
24.26 21.65 20.72 19.80 18.98 18.57 18.17 17.66 17.03 16.70 16.07 16.04 13.92 13.40 13.07 11.32 11.23 10.24 8.85 8.85 8.72 8.45 8.10 7.97 7.03 6.96 6.91 6.89 6.72 6.72 6.62 6.44 5.08 4.96 4.73 4.72 4.64 4.62 4.62 3.12 2.99 2.89 2.85 2.28 0.67 0.61 0.58 0.57
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48
97.92 95.83 93.75 91.67 89.58 87.50 85.42 83.33 81.25 79.17 77.08 75.00 72.92 70.83 68.75 66.67 64.58 62.50 60.42 58.33 56.25 54.17 52.08 50.00 47.92 45.83 43.75 41.67 39.58 37.50 35.42 33.33 31.25 29.17 27.08 25.00 22.92 20.83 18.75 16.67 14.58 12.50 10.42 8.33 6.25 4.17 2.08 0.00
_________________________________________________________________________________________________________
Albania Portugal Cyprus Romania Ireland Poland Bosnia & Herzegovina Macedonia Serbia & Montenegro Moldova Kazakhstan Bulgaria Spain Denmark Slovenia Vatican City Italy Andorra France Iceland Norway the United Kingdom Finland Luxembourg Belgium Austria Switzerland San Marino Guernsey Jersey Netherlands Liechtenstein Sweden Estonia Belarus Slovakia Russian Federation Germany Lithuania Greece Faroe Islands Malta Isle of Man Monaco Hungary Ukraine Gibraltar Georgia
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
53
Total Liabilities Countries
Value (total liabilities & equity = 100)
Rank
Percentile
72.50 68.91 66.89 66.88 64.50 63.63 61.75 60.52 60.36 56.68 54.77 52.25 51.97 51.96 51.61 51.48 51.34 50.71 50.57 49.27 48.76 47.65 47.29 47.06 46.11 45.47 44.68 44.41 41.24 39.10 38.64 38.44 38.11 37.41 37.03 34.52 34.13 33.37 30.54 30.43 30.23 30.05 22.30 21.58 17.22
1 2 3 4 5 6 7 8 9 10 12 13 14 15 16 17 18 20 21 22 23 24 25 26 27 28 29 30 32 34 35 37 38 39 40 41 42 44 45 46 47 48 50 52 53
98.11 96.23 94.34 92.45 90.57 88.68 86.79 84.91 83.02 81.13 77.36 75.47 73.58 71.70 69.81 67.92 66.04 62.26 60.38 58.49 56.60 54.72 52.83 50.94 49.06 47.17 45.28 43.40 39.62 35.85 33.96 30.19 28.30 26.42 24.53 22.64 20.75 16.98 15.09 13.21 11.32 9.43 5.66 1.89 0.00
Region
_________________________________________________________________________________________________________
Portugal Peru Spain Brazil Austria Chile France Turkey Mexico South Africa Pakistan Taiwan Belgium the United Kingdom Argentina Italy Poland Thailand Netherlands Greece Luxembourg Denmark Norway Ireland Switzerland Philippines Sweden Japan Australia Hungary Germany USA Finland Singapore South Korea Hong Kong Canada Russian Federation China Indonesia Czech Republic Malaysia Israel India New Zealand
Europe Latin America Europe Latin America Europe Latin America Europe the Middle East Latin America Africa the Middle East Asia Europe Europe Latin America Europe Europe Asia Europe Europe Europe Europe Europe Europe Europe Asia Europe Asia Oceana Europe Europe North America Europe Asia Asia Asia North America Europe Asia Asia Europe Asia the Middle East Asia Oceana
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
54
Total Liabilities (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total liabilities & equity = 100)
Rank
Percentile
72.50 69.40 66.89 64.50 63.89 62.79 62.29 62.29 61.75 60.15 57.50 52.77 51.97 51.96 51.89 51.48 51.34 51.29 50.57 49.47 49.27 48.76 47.65 47.29 47.06 46.16 46.11 45.67 45.07 44.68 44.42 44.34 43.03 39.10 38.83 38.64 38.11 36.27 35.70 35.16 34.07 33.99 33.43 33.37 33.29 33.11 32.91 30.23 28.70 28.69 17.83
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Portugal Cyprus Spain Austria San Marino Slovenia Guernsey Jersey France Albania Romania Bosnia & Herzegovina Belgium the United Kingdom Vatican City Italy Poland Macedonia Netherlands Serbia & Montenegro Greece Luxembourg Denmark Norway Ireland Moldova Switzerland Malta Isle of Man Sweden Kazakhstan Bulgaria Liechtenstein Hungary Iceland Germany Finland Monaco Estonia Ukraine Belarus Slovakia Gibraltar Russian Federation Lithuania Faroe Islands Georgia Czech Republic Latvia Croatia Andorra
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
55
Common Equity Countries
Value (total liabilities & equity = 100)
Rank
Percentile
83.03 77.88 73.83 69.77 69.50 69.41 65.87 64.55 64.05 60.95 60.81 60.73 60.67 59.69 59.57 57.92 55.20 54.99 54.72 54.46 52.84 51.95 51.95 51.04 51.00 48.65 47.84 47.83 47.68 46.41 46.22 45.26 45.23 45.08 40.74 39.48 39.37 37.40 36.63 35.50 33.01 31.72 31.40 31.09 26.19
1 2 3 4 5 6 7 9 10 11 12 13 14 15 16 17 19 20 21 22 23 24 25 26 27 29 30 31 32 33 35 36 37 38 39 41 42 43 45 47 48 49 50 51 52
98.11 96.23 94.34 92.45 90.57 88.68 86.79 83.02 81.13 79.25 77.36 75.47 73.58 71.70 69.81 67.92 64.15 62.26 60.38 58.49 56.60 54.72 52.83 50.94 49.06 45.28 43.40 41.51 39.62 37.74 33.96 32.08 30.19 28.30 26.42 22.64 20.75 18.87 15.09 11.32 9.43 7.55 5.66 3.77 1.89
Region
_________________________________________________________________________________________________________
New Zealand India Israel Czech Republic Indonesia Malaysia Canada Hong Kong China USA Germany South Korea Singapore Hungary Finland Australia Sweden Japan Russian Federation Philippines Ireland Denmark Norway Switzerland Luxembourg Netherlands the United Kingdom Thailand Belgium Greece Taiwan Italy Pakistan Poland South Africa Turkey Mexico France Argentina Austria Brazil Spain Chile Peru Portugal
Oceana Asia the Middle East Europe Asia Asia North America Asia Asia North America Europe Asia Asia Europe Europe Oceana Europe Asia Europe Asia Europe Europe Europe Europe Europe Europe Europe Asia Europe Europe Asia Europe the Middle East Europe Africa the Middle East Latin America Europe Latin America Europe Latin America Europe Latin America Latin America Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
56
Common Equity (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total liabilities & equity = 100)
Rank
Percentile
85.98 69.77 66.22 66.19 61.90 61.58 60.81 59.69 59.57 58.83 58.54 55.87 55.75 55.20 54.72 54.59 53.68 52.84 51.95 51.95 51.04 51.04 51.00 50.25 48.65 47.84 47.68 47.63 46.41 45.63 45.26 45.08 43.01 42.45 40.53 39.00 38.93 37.51 37.40 35.50 35.16 34.42 34.28 34.28 33.45 32.27 31.72 29.78 27.14 26.19 25.07
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Andorra Czech Republic Latvia Croatia Faroe Islands Iceland Germany Hungary Finland Monaco Estonia Belarus Slovakia Sweden Russian Federation Lithuania Ukraine Ireland Denmark Norway Switzerland Gibraltar Luxembourg Georgia Netherlands the United Kingdom Belgium Liechtenstein Greece Vatican City Italy Poland Malta Isle of Man Moldova Kazakhstan Bulgaria Romania France Austria San Marino Bosnia & Herzegovina Jersey Guernsey Macedonia Serbia & Montenegro Spain Slovenia Albania Portugal Cyprus
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
57
Retained Earnings Countries
Value (total liabilities & equity = 100)
Rank
Percentile
29.85 28.00 27.50 22.90 22.66 22.48 20.43 19.99 19.71 18.98 18.96 18.33 17.75 17.55 15.35 15.17 14.62 14.40 13.44 13.04 12.17 11.24 11.17 9.39 9.36 8.61 8.48 8.26 8.20 7.76 7.32 6.61 6.05 5.62 5.61 5.23 4.84 4.04 2.66 1.95 1.54 0.27 0.00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 22 23 24 25 27 29 30 31 32 34 35 36 38 39 40 41 42 45 46 47 48 49 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 56.86 54.90 52.94 50.98 47.06 43.14 41.18 39.22 37.25 33.33 31.37 29.41 25.49 23.53 21.57 19.61 17.65 11.76 9.80 7.84 5.88 3.92 0.00
Region
_________________________________________________________________________________________________________
Israel Norway Hong Kong USA Japan India Canada South Africa the United Kingdom Denmark Switzerland Singapore Finland New Zealand Malaysia Ireland Czech Republic Netherlands Australia Indonesia Germany Spain Belgium Turkey Mexico South Korea Austria Sweden Taiwan Russian Federation Philippines Luxembourg France Argentina Poland Thailand Italy Portugal China Hungary Greece Peru Pakistan
the Middle East Europe Asia North America Asia Asia North America Africa Europe Europe Europe Asia Europe Oceana Asia Europe Europe Europe Oceana Asia Europe Europe Europe the Middle East Latin America Asia Europe Europe Asia Europe Asia Europe Europe Latin America Europe Asia Europe Europe Asia Europe Europe Latin America the Middle East
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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Financial Indicators
58
Retained Earnings (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total liabilities & equity = 100)
Rank
Percentile
28.00 26.37 23.13 19.71 18.98 18.96 18.18 17.78 17.75 17.69 15.17 14.62 14.40 13.88 13.87 12.17 11.24 11.17 10.55 8.92 8.48 8.40 8.30 8.26 8.19 8.19 8.18 7.95 7.92 7.90 7.76 7.74 7.67 6.61 6.05 5.61 5.05 4.88 4.86 4.85 4.84 4.04 3.87 1.95 1.75 1.67 1.64 1.54 1.42 1.41 0.24
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Norway Faroe Islands Iceland the United Kingdom Denmark Switzerland Andorra Monaco Finland Liechtenstein Ireland Czech Republic Netherlands Latvia Croatia Germany Spain Belgium Slovenia Romania Austria San Marino Estonia Sweden Guernsey Jersey Bosnia & Herzegovina Macedonia Belarus Slovakia Russian Federation Lithuania Serbia & Montenegro Luxembourg France Poland Moldova Vatican City Kazakhstan Bulgaria Italy Portugal Cyprus Hungary Ukraine Gibraltar Georgia Greece Malta Isle of Man Albania
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
3.4 3.4.1
FINANCIAL RETURNS RATIOS
IN
59
GERMANY: INCOME STRUCTURE
Overview
In this chapter we consider the income structure of companies operating in Germany benchmarked against global averages. The chapter begins by defining relevant terms. A common-size statement, or vertical analysis of income is then presented for the proto-typical firm involved in computer programming, data processing and computer related services operating in Germany and the average global benchmarks (total revenue = 100 percent). For ratios where there are large deviations between Germany and the benchmarks, graphics are provided. Then the distribution of ratios is presented in the form of ranks and percentiles. Certain key vertical analysis income ratios are highlighted across countries in the comparison group.
3.4.2
Income Statements – Definitions of Terms
The following definitions are provided for those less familiar with the income-side of financial statement analysis. As this chapter deals with the vertical analysis and global benchmarking of income, only definitions covering certain terms used in this chapter’s tables and graphs are provided here . The glossary below reflects commonly accepted definitions across various countries and official sources. •
Amortization. Amortization generally refers to the depreciation, depletion, or charge-off to expense of intangible and tangible assets over a period of time. Amortization is commonly understood to be the taking as an expense (writing off) of the loss of value of an intangible asset such as a copyright, a patent, or a mailing list, in an accounting period.
•
Cost of Goods Sold (excluding depreciation). For retail companies, cost of goods sold is generally defined as the equivalent of starting inventory plus purchases minus ending inventory. In manufacturing, cost of goods sold is defined to equal the starting inventory plus the cost of goods manufactured minus ending inventory. Most pure service firms do not generally have cost of goods sold.
•
Current Domestic Income Tax. Current domestic income taxes are commonly defined as compulsory charges levied by the government where the company is located on current income.
•
Current Foreign Income Tax. Current foreign income taxes are commonly defined as compulsory charges levied by foreign governments on current income.
•
Deferred Domestic Income Tax. Deferred domestic income tax is defined as a compulsory charge from a previous accounting period which is yet unpaid to the government where the company is located on current income.
•
Deferred Foreign Income Tax. Deferred foreign income tax is generally defined as a compulsory charge from a previous accounting period which is yet unpaid to foreign governments on current income.
•
Depletion. Depletion is commonly defined to be included as one of the elements of amortization, and is understood to be the portion of the carrying value (other than the portion associated with tangible assets) prorated in each accounting period for financial reporting purposes.
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Financial Indicators
60
•
Depreciation. Depreciation generally is defined as the expiration in the service life of fixed assets, other than depletable assets, attributable to wear and tear, deterioration, action of the physical elements, inadequacy and obsolescence. Depreciation is commonly defined as the portion of the cost of a fixed asset charged as an expense during a particular period. In accounting for depreciation, the cost of a fixed asset, less any salvage value, is prorated over the estimated service life of such an asset, and each period is charged with a portion of such cost. Through this process, the cost of the asset is ultimately charged off as an expense.
•
Earnings Before Interest and Taxes (EBIT). EBIT is a financial measure defined as revenues less cost of goods sold and selling, general, and administrative expenses. In other words, operating and non-operating profit before the deduction of interest and income taxes.
•
Extraordinary Items. Extraordinary items are defined to include income and expense items associated with events and transactions that possess a high degree of abnormality and are of a type that would not reasonably be expected to recur in the foreseeable future.
•
Gain/Loss Sale of Assets. Gains or losses associated with the sale of assets are defined as increases or decreases in equity (net assets) resulting from the sale of assets.
•
Gross Income. Gross income is commonly defined as all the money, goods, and property received by the company that must be included as taxable income.
•
Income Taxes. Income taxes are defined to include those taxes levied by state, federal, and local governments on the company's reported accounting profit. Income taxes generally include both deferred and paid taxes. They are generally determined after the interest expense has been deducted.
•
Interest Expense on Debt. Interest expenses on debt are those which are spent on current debt and added to the net income so avoid underestimating interest coverage.
•
Minority Interest. Minority interest is the proportional share of the minority ownership's interest (less than 50 percent) in the earnings or losses.
•
Net Income Available to Common. Net income available to common is defined as the net income available to common stockholders.
•
Net Income Before Preferred Dividends. Net income before preferred dividends is generally calculated as the difference between total revenues and total expense prior to the granting of preferred dividends.
•
Net Sales or Revenues. Revenues or net sales are defined as payments made to and received by an entity. May take the form of taxes, user fees, fines, fees for service, and so on.
•
Non-Operating Interest Income. Non-operating interest income is generally understood to be any interest received (e.g., royalty, production payment, net profits interest) that does not involve the operation of the company.
•
Operating Expenses. Operating expenses are generally defined as those incurred in paying for the company’s day-to-day activities.
•
Operating Income. Operating income is generally defined to equal operating revenues less operating expenses. It typically excludes items of other revenue and expense such as equity in earnings of unconsolidated companies, dividends, interest income and expense, income taxes, extraordinary items, and cumulative effect of accounting changes.
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Financial Indicators
61
•
Pretax Equity In Earnings. Pretax equity in earnings is generally defined to equal a company's proportional share (based on ownership) of the gross earnings or losses of an unconsolidated company.
•
Pretax Income. Pretax income is generally defined as income before tax deductions.
•
Selling, General & Administrative Expenses. Selling, general and administrative expenses are expenses independent from cost of sales for the purpose of illustrating the amount of the company's selling and administrative costs. Generally included in this figure are the costs of employees' salaries, commissions, and travel expenses; company payroll and office costs; and advertising and promotion.
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Financial Indicators
3.4.3
62
Income Structure: Outlook
Using the methodology described in the introduction, the following table summarizes income structure benchmarks for firms involved in computer programming, data processing and computer related services in Germany. To allow comparable benchmarking, a common index of Net Sales or Revenues = 100 is used. All figures are current-year projections for companies operating in Germany based on latest financial results available. Income Structure Germany Europe World Avg. _________________________________________________________________________________________________________
Net Sales or Revenues Cost of Goods Sold (Excluding Depreciation) Depreciation, Depletion & Amortization Gross Income Selling, General & Administrative Expenses Other Operating Expenses Operating Expenses - Total Operating Income Extraordinary Credit - Pretax Extraordinary Charge - Pretax Non-Operating Interest Income Pretax Equity In Earnings Other Income/Expense Net Earnings Before Interest and Taxes (EBIT) Interest Expense on Debt Pretax Income Income Taxes Current Domestic Income Tax Current Foreign Income Tax Deferred Domestic Income Tax Deferred Foreign Income Tax Minority Interest Discontinued Operations Net Income Before Extra Items/Prefer Dividends Extraordinary Items & Gain/Loss Sale Of Assets Net Income Before Preferred Dividends Net Income Available to Common
100.00 57.24 6.56 37.36 23.55 92.13 13.33 5.88 0.00 0.82 2.18 -0.22 3.44 11.03 1.05 9.27 3.55 3.47 0.87 0.83 0.09 0.19 -0.49 5.98 0.00 5.98 5.98
100.00 58.13 7.67 29.02 22.47 82.09 3.72 9.85 1.11 2.22 1.80 0.01 1.90 14.04 3.62 10.53 3.67 4.44 0.18 -0.10 -0.03 0.24 -0.01 6.58 0.02 6.60 6.58
100.00 55.68 7.59 29.38 21.19 78.97 2.66 12.16 0.17 0.47 1.79 -0.01 1.49 16.24 3.42 12.89 2.91 1.90 0.20 0.00 0.05 0.36 -0.01 9.64 -0.11 9.53 9.63
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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©2007 Icon Group International, Inc.
Financial Indicators
3.4.4
63
Large Variances: Income
The following graphics summarize for computer programming, data processing and computer related services the large income structure gaps between firms operating in Germany and the world average. A gap cannot necessarily be interpreted as a positive or negative reflection on performance. Gaps may signal areas of specialization, market focus, or expertise. More contextual information is required to fully interpret these gaps. The gaps highlighted here are simply those that are large.
Gap: Gross Income 40
37.36 29.02
30
29.38
20 7.98
10 0 Germ any
Europe
World Average
Gap
Gap: Selling, General & Administrative Expenses 25
23.55
22.47
21.19
20 15 10 2.36
5 0 Germ any
Europe
World Average
Gap
Gap: Other Operating Expenses 100
92.13
82.09
80
78.97
60 40 13.16
20 0 Germ any
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Europe
World Average
Gap
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Financial Indicators
64
Gap: Operating Expenses - Total 15
13.33 10.67
10 3.72
5
2.66
0 Germ any
Europe
World Average
Gap
Gap: Operating Income 15 10
9.85
12.16
5.88
5 0 -5
-6.28
-10 Germ any
Europe
World Average
Gap
Gap: Earnings Before Interest and Taxes (EBIT) 20 15
11.03
14.04
16.24
10 5 0 -5
-5.21
-10 Germ any
Europe
World Average
Gap
Gap: Interest Expense on Debt 4 3 2 1 0 -1 -2 -3
3.62
3.42
1.05
-2.37 Germ any
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Europe
World Average
Gap
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Financial Indicators
65
Gap: Pretax Income 15 10
9.27
10.53
12.89
5 0 -3.62
-5 Germ any
Europe
World Average
Gap
Gap: Net Income Before Extra Items/Prefer Dividends 9.64
10 5.98
6.58
5 0 -3.66
-5 Germ any
Europe
World Average
Gap
Gap: Net Income Before Preferred Dividends 9.53
10 5.98
6.6
5 0 -3.55
-5 Germ any
Europe
World Average
Gap
Gap: Net Income Available to Common 9.63
10 5.98
6.58
5 0 -3.65
-5 Germ any
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Europe
World Average
Gap
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Financial Indicators
3.4.5
66
Key Percentiles and Rankings
We now consider the distribution of income ratios for computer programming, data processing and computer related services using ranks and percentiles. What percent of countries have a value lower or higher than Germany (what is the ratio's rank or percentile)? The table below answers this question with respect to the vertical analysis of income structure. The ranks and percentiles indicate, from highest to lowest, where a value falls within the distribution of all countries considered in the global benchmark (the number of countries in the benchmark per line item may vary, as indicated in the Rank). Again, a high or low figure does not necessarily indicate good or bad performance. After the summary table below, a few key vertical income ratios are highlighted in additional tables. Income Structure
Germany
Rank of Total
Percentile
100.00 57.24 6.56 37.36 23.55 92.13 13.33 5.88 0.00 0.82 2.18 -0.22 3.44 11.03 1.05 9.27 3.55 3.47 0.87 0.83 0.09 0.19 -0.49 5.98 0.00 5.98 5.98
29 of 48 21 of 53 15 of 51 20 of 44 17 of 50 6 of 43 38 of 53 27 of 29 22 of 32 23 of 48 27 of 27 9 of 53 29 of 53 38 of 53 26 of 53 20 of 53 18 of 41 1 of 14 4 of 37 3 of 9 19 of 42 5 of 5 31 of 53 3 of 8 30 of 53 31 of 53
39.58 60.38 70.59 54.55 66.00 86.05 28.30 6.90 31.25 52.08 0.00 83.02 45.28 28.30 50.94 62.26 56.10 92.86 89.19 66.67 54.76 0.00 41.51 62.50 43.40 41.51
_________________________________________________________________________________________________________
Net Sales or Revenues Cost of Goods Sold (Excluding Depreciation) Depreciation, Depletion & Amortization Gross Income Selling, General & Administrative Expenses Other Operating Expenses Operating Expenses - Total Operating Income Extraordinary Credit - Pretax Extraordinary Charge - Pretax Non-Operating Interest Income Pretax Equity In Earnings Other Income/Expense Net Earnings Before Interest and Taxes (EBIT) Interest Expense on Debt Pretax Income Income Taxes Current Domestic Income Tax Current Foreign Income Tax Deferred Domestic Income Tax Deferred Foreign Income Tax Minority Interest Discontinued Operations Net Income Before Extra Items/Prefer Dividends Extraordinary Items & Gain/Loss Sale Of Assets Net Income Before Preferred Dividends Net Income Available to Common
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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Financial Indicators
67
Cost of Goods Sold (Excluding Depreciation) Countries
Value (total revenue = 100)
Rank
Percentile
89.70 87.06 84.48 84.36 83.71 76.96 75.28 72.71 71.43 71.26 71.23 70.16 69.96 69.18 68.01 65.99 65.44 64.52 63.17 62.65 62.51 62.12 61.28 58.79 58.74 58.44 57.73 57.24 55.56 54.04 52.06 51.51 51.02 50.82 50.36 49.81 46.30 44.50 32.98 19.75 3.27
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 23 24 25 26 27 28 29 30 31 33 34 35 36 37 38 40 41 44 47 48
97.92 95.83 93.75 91.67 89.58 87.50 85.42 83.33 81.25 79.17 77.08 75.00 72.92 70.83 68.75 66.67 64.58 62.50 60.42 58.33 56.25 52.08 50.00 47.92 45.83 43.75 41.67 39.58 37.50 35.42 31.25 29.17 27.08 25.00 22.92 20.83 16.67 14.58 8.33 2.08 0.00
Region
_________________________________________________________________________________________________________
Luxembourg Hungary Belgium Czech Republic Sweden France South Africa Brazil Spain Peru India Norway Netherlands Chile South Korea China Japan Malaysia Switzerland Poland Finland Ireland Russian Federation Denmark Singapore the United Kingdom Philippines Germany Argentina Portugal Thailand Australia New Zealand Hong Kong Canada Italy USA Greece Indonesia Israel Pakistan
Europe Europe Europe Europe Europe Europe Africa Latin America Europe Latin America Asia Europe Europe Latin America Asia Asia Asia Asia Europe Europe Europe Europe Europe Europe Asia Europe Asia Europe Latin America Europe Asia Oceana Oceana Asia North America Europe North America Europe Asia the Middle East the Middle East
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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©2007 Icon Group International, Inc.
Financial Indicators
68
Cost of Goods Sold (Excluding Depreciation) (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total revenue = 100)
Rank
Percentile
89.70 87.06 84.48 84.36 83.71 80.08 80.04 78.29 76.96 74.44 73.29 71.43 70.16 69.96 67.06 65.56 63.17 62.65 62.57 62.51 62.43 62.21 62.12 61.28 61.14 58.95 58.79 58.44 57.24 56.96 56.33 54.20 54.11 54.04 52.83 51.73 50.21 49.81 48.73 46.77 44.50 41.24 40.70
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43
97.67 95.35 93.02 90.70 88.37 86.05 83.72 81.40 79.07 76.74 74.42 72.09 69.77 67.44 65.12 62.79 60.47 58.14 55.81 53.49 51.16 48.84 46.51 44.19 41.86 39.53 37.21 34.88 32.56 30.23 27.91 25.58 23.26 20.93 18.60 16.28 13.95 11.63 9.30 6.98 4.65 2.33 0.00
_________________________________________________________________________________________________________
Luxembourg Hungary Belgium Czech Republic Sweden Latvia Croatia Ukraine France Gibraltar Georgia Spain Norway Netherlands Slovenia Estonia Switzerland Poland Belarus Finland Slovakia Albania Ireland Russian Federation Lithuania Liechtenstein Denmark the United Kingdom Germany Monaco Moldova Kazakhstan Bulgaria Portugal Andorra Cyprus Vatican City Italy Faroe Islands Iceland Greece Malta Isle of Man
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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Financial Indicators
69
Selling, General & Administrative Expenses Countries
Value (total revenue = 100)
Rank
Percentile
53.64 53.42 43.41 40.93 40.63 39.13 37.84 36.42 35.17 34.26 33.28 31.91 31.23 29.85 24.47 23.55 21.06 20.22 18.27 17.36 17.34 17.29 17.29 17.14 15.96 15.91 15.46 15.44 14.90 14.71 14.47 14.44 13.97 13.00 12.36 8.10
1 2 3 4 5 6 8 9 10 11 12 13 14 15 19 20 21 22 23 24 25 26 27 28 29 30 32 33 34 36 37 38 39 40 41 44
97.73 95.45 93.18 90.91 88.64 86.36 81.82 79.55 77.27 75.00 72.73 70.45 68.18 65.91 56.82 54.55 52.27 50.00 47.73 45.45 43.18 40.91 38.64 36.36 34.09 31.82 27.27 25.00 22.73 18.18 15.91 13.64 11.36 9.09 6.82 0.00
Region
_________________________________________________________________________________________________________
Israel Denmark Belgium Indonesia Netherlands Italy USA Canada France Thailand Ireland the United Kingdom Australia India Poland Germany Hong Kong Malaysia Japan China Switzerland Singapore Norway South Korea Turkey Mexico Brazil Russian Federation South Africa Chile Greece Peru Argentina Sweden Philippines Luxembourg
the Middle East Europe Europe Asia Europe Europe North America North America Europe Asia Europe Europe Oceana Asia Europe Europe Asia Asia Asia Asia Europe Asia Europe Asia the Middle East Latin America Latin America Europe Africa Latin America Europe Latin America Latin America Europe Asia Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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Financial Indicators
70
Selling, General & Administrative Expenses (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total revenue = 100)
Rank
Percentile
53.42 43.41 40.63 39.45 39.13 38.23 35.17 33.28 31.91 24.47 23.55 22.00 21.17 21.13 20.19 17.34 17.29 16.77 16.52 16.18 15.77 15.73 15.44 15.41 15.16 14.47 13.91 13.52 13.41 13.23 13.04 13.00 12.60 8.10
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34
97.06 94.12 91.18 88.24 85.29 82.35 79.41 76.47 73.53 70.59 67.65 64.71 61.76 58.82 55.88 52.94 50.00 47.06 44.12 41.18 38.24 35.29 32.35 29.41 26.47 23.53 20.59 17.65 14.71 11.76 8.82 5.88 2.94 0.00
_________________________________________________________________________________________________________
Denmark Belgium Netherlands Vatican City Italy Iceland France Ireland the United Kingdom Poland Germany Moldova Kazakhstan Bulgaria Faroe Islands Switzerland Norway Monaco Estonia Liechtenstein Belarus Slovakia Russian Federation Lithuania Romania Greece Bosnia & Herzegovina Macedonia Malta Isle of Man Serbia & Montenegro Sweden Albania Luxembourg
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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Financial Indicators
71
Operating Expenses - Total Countries
Value (total revenue = 100)
Rank
Percentile
23.14 18.15 16.61 13.94 13.33 12.50 12.03 11.95 10.21 9.13 7.33 7.16 5.63 4.89 4.37 3.98 3.56 3.18 3.11 2.28 1.70 1.48 1.25 0.97 0.90 0.76 0.55 0.53 0.51 0.49 0.48 0.46 0.20 0.05 0.04 -0.14 -0.17 -7.51
1 2 3 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 23 25 26 27 28 29 30 31 32 33 35 36 37 38 39 40 41 42 43
97.67 95.35 93.02 88.37 86.05 83.72 81.40 79.07 76.74 74.42 72.09 69.77 67.44 65.12 62.79 60.47 58.14 55.81 53.49 46.51 41.86 39.53 37.21 34.88 32.56 30.23 27.91 25.58 23.26 18.60 16.28 13.95 11.63 9.30 6.98 4.65 2.33 0.00
Region
_________________________________________________________________________________________________________
Finland Australia Philippines Netherlands Germany Spain Switzerland Ireland Norway Portugal Singapore France South Africa Denmark the United Kingdom Sweden India Peru Indonesia Hong Kong Malaysia USA Poland China Italy Belgium South Korea Luxembourg Argentina Russian Federation Brazil Chile Israel Pakistan Japan Canada Greece Czech Republic
Europe Oceana Asia Europe Europe Europe Europe Europe Europe Europe Asia Europe Africa Europe Europe Europe Asia Latin America Asia Asia Asia North America Europe Asia Europe Europe Asia Europe Latin America Europe Latin America Latin America the Middle East the Middle East Asia North America Europe Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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Financial Indicators
72
Operating Expenses - Total (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total revenue = 100)
Rank
Percentile
23.14 13.94 13.33 12.50 12.03 11.95 11.73 11.22 10.21 9.13 8.74 7.16 7.11 4.89 4.37 3.98 2.78 2.19 1.50 1.25 1.13 1.08 1.08 0.91 0.90 0.76 0.53 0.53 0.50 0.50 0.49 0.49 -0.16 -0.16 -0.17 -7.12 -7.13 -7.51
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38
97.37 94.74 92.11 89.47 86.84 84.21 81.58 78.95 76.32 73.68 71.05 68.42 65.79 63.16 60.53 57.89 55.26 52.63 50.00 47.37 44.74 42.11 39.47 36.84 34.21 31.58 28.95 26.32 23.68 21.05 18.42 15.79 13.16 10.53 7.89 5.26 2.63 0.00
_________________________________________________________________________________________________________
Finland Netherlands Germany Spain Switzerland Ireland Slovenia Liechtenstein Norway Portugal Cyprus France Monaco Denmark the United Kingdom Sweden Albania Faroe Islands Iceland Poland Moldova Kazakhstan Bulgaria Vatican City Italy Belgium Luxembourg Estonia Belarus Slovakia Russian Federation Lithuania Isle of Man Malta Greece Croatia Latvia Czech Republic
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
73
Operating Income Countries
Value (total revenue = 100)
Rank
Percentile
44.13 42.82 42.71 22.13 21.70 20.11 18.94 15.51 15.01 14.89 14.41 12.94 12.42 11.66 11.46 11.33 10.30 10.05 9.33 8.23 7.67 7.58 7.42 7.22 7.20 7.06 6.91 6.79 6.72 6.71 6.42 6.34 5.88 5.59 5.48 5.02 4.58 4.55 3.91 3.82 3.49 2.36 0.12 -0.10 -4.06
1 2 3 5 6 7 8 10 11 12 13 14 15 16 17 18 20 21 22 24 25 26 28 29 30 31 32 33 34 35 36 37 38 40 41 43 44 45 47 48 49 50 51 52 53
98.11 96.23 94.34 90.57 88.68 86.79 84.91 81.13 79.25 77.36 75.47 73.58 71.70 69.81 67.92 66.04 62.26 60.38 58.49 54.72 52.83 50.94 47.17 45.28 43.40 41.51 39.62 37.74 35.85 33.96 32.08 30.19 28.30 24.53 22.64 18.87 16.98 15.09 11.32 9.43 7.55 5.66 3.77 1.89 0.00
Region
_________________________________________________________________________________________________________
New Zealand Turkey Mexico Philippines Hong Kong Israel Greece Argentina India Portugal Singapore Australia China Pakistan Indonesia Czech Republic USA Spain Japan South Korea Malaysia the United Kingdom Russian Federation Canada Poland Brazil Denmark Thailand Chile France South Africa Netherlands Germany Italy Peru Belgium Switzerland Sweden Finland Taiwan Ireland Norway Luxembourg Austria Hungary
Oceana the Middle East Latin America Asia Asia the Middle East Europe Latin America Asia Europe Asia Oceana Asia the Middle East Asia Europe North America Europe Asia Asia Asia Europe Europe North America Europe Latin America Europe Asia Latin America Europe Africa Europe Europe Europe Latin America Europe Europe Europe Europe Asia Europe Europe Europe Europe Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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©2007 Icon Group International, Inc.
Financial Indicators
74
Operating Income (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total revenue = 100)
Rank
Percentile
45.70 40.69 37.34 36.29 35.01 20.81 18.94 17.56 17.33 14.89 14.25 13.97 11.33 10.75 10.75 10.41 10.05 9.44 7.94 7.58 7.57 7.56 7.42 7.40 7.20 6.91 6.71 6.47 6.34 6.23 6.22 5.88 5.63 5.59 5.02 4.78 4.58 4.55 4.27 3.91 3.49 2.36 0.12 -0.10 -0.10 -0.10 -0.10 -3.42 -3.47 -3.65 -4.06
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Andorra Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Faroe Islands Greece Malta Isle of Man Portugal Cyprus Monaco Czech Republic Latvia Croatia Iceland Spain Slovenia Estonia the United Kingdom Belarus Slovakia Russian Federation Lithuania Poland Denmark France Moldova Netherlands Kazakhstan Bulgaria Germany Vatican City Italy Belgium Albania Switzerland Sweden Liechtenstein Finland Ireland Norway Luxembourg Guernsey Jersey San Marino Austria Georgia Gibraltar Ukraine Hungary
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
75
Earnings Before Interest and Taxes (EBIT) Countries
Value (total revenue = 100)
Rank
Percentile
56.35 55.88 55.73 42.24 39.12 26.28 23.20 23.02 22.37 20.54 18.11 17.90 17.41 17.26 17.12 16.42 16.16 16.12 14.48 11.97 11.40 11.10 11.03 10.71 9.67 9.37 9.14 9.14 9.09 8.88 8.30 8.19 8.15 8.15 7.93 7.53 7.35 6.46 5.67 5.07 4.88 4.41 1.52 1.24 0.68
1 2 3 5 6 7 8 9 10 11 13 14 15 16 18 19 20 21 24 26 27 28 29 30 31 32 33 34 35 36 38 39 40 41 42 43 44 46 47 48 49 50 51 52 53
98.11 96.23 94.34 90.57 88.68 86.79 84.91 83.02 81.13 79.25 75.47 73.58 71.70 69.81 66.04 64.15 62.26 60.38 54.72 50.94 49.06 47.17 45.28 43.40 41.51 39.62 37.74 35.85 33.96 32.08 28.30 26.42 24.53 22.64 20.75 18.87 16.98 13.21 11.32 9.43 7.55 5.66 3.77 1.89 0.00
Region
_________________________________________________________________________________________________________
New Zealand Turkey Mexico Pakistan Portugal Israel Philippines Hong Kong Greece Thailand India Argentina Czech Republic Brazil Indonesia Chile Australia Singapore China Ireland Denmark Spain Germany USA Malaysia Japan Poland Peru South Korea Italy South Africa Russian Federation the United Kingdom Taiwan France Netherlands Finland Switzerland Canada Sweden Belgium Norway Hungary Luxembourg Austria
Oceana the Middle East Latin America the Middle East Europe the Middle East Asia Asia Europe Asia Asia Latin America Europe Latin America Asia Latin America Oceana Asia Asia Europe Europe Europe Europe North America Asia Asia Europe Latin America Asia Europe Africa Europe Europe Asia Europe Europe Europe Europe North America Europe Europe Europe Europe Europe Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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©2007 Icon Group International, Inc.
Financial Indicators
76
Earnings Before Interest and Taxes (EBIT) (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total revenue = 100)
Rank
Percentile
58.35 53.10 48.73 47.36 45.68 39.12 37.45 22.37 22.07 20.74 20.46 17.41 16.52 16.52 15.63 11.97 11.40 11.10 11.03 10.82 10.42 9.14 8.95 8.88 8.76 8.36 8.35 8.22 8.19 8.17 8.15 7.98 7.93 7.91 7.89 7.53 7.35 6.46 6.02 5.07 4.88 4.41 1.52 1.36 1.30 1.28 1.24 0.68 0.67 0.65 0.65
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Andorra Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Portugal Cyprus Greece Faroe Islands Malta Isle of Man Czech Republic Latvia Croatia Monaco Ireland Denmark Spain Germany Iceland Slovenia Poland Vatican City Italy Estonia Belarus Slovakia Moldova Russian Federation Lithuania the United Kingdom Albania France Kazakhstan Bulgaria Netherlands Finland Switzerland Liechtenstein Sweden Belgium Norway Hungary Ukraine Gibraltar Georgia Luxembourg Austria San Marino Jersey Guernsey
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
77
Pretax Income Countries
Value (total revenue = 100)
Rank
Percentile
55.18 34.67 34.58 25.27 22.35 21.85 20.54 17.89 16.43 16.14 15.60 15.51 15.02 14.14 12.67 12.16 10.64 9.69 9.69 9.27 9.21 8.79 8.52 8.34 8.30 7.13 6.87 6.76 6.60 6.53 5.69 5.62 5.60 5.41 5.24 5.15 4.51 4.21 4.21 3.65 3.47 2.21 1.22 0.54 0.08
1 2 3 5 6 7 8 10 11 12 13 14 15 17 18 20 23 24 25 26 27 28 29 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 51 52 53
98.11 96.23 94.34 90.57 88.68 86.79 84.91 81.13 79.25 77.36 75.47 73.58 71.70 67.92 66.04 62.26 56.60 54.72 52.83 50.94 49.06 47.17 45.28 41.51 39.62 37.74 35.85 33.96 32.08 30.19 28.30 26.42 24.53 22.64 20.75 18.87 16.98 15.09 13.21 11.32 9.43 7.55 3.77 1.89 0.00
Region
_________________________________________________________________________________________________________
New Zealand Turkey Mexico Israel Hong Kong Philippines Greece India Czech Republic Portugal Singapore Indonesia Thailand Australia China Argentina Pakistan USA Spain Germany South Korea Malaysia Denmark Japan Russian Federation the United Kingdom Taiwan France Italy Poland Switzerland Netherlands Finland Brazil South Africa Chile Sweden Ireland Canada Belgium Norway Peru Hungary Luxembourg Austria
Oceana the Middle East Latin America the Middle East Asia Asia Europe Asia Europe Europe Asia Asia Asia Oceana Asia Latin America the Middle East North America Europe Europe Asia Asia Europe Asia Europe Europe Asia Europe Europe Europe Europe Europe Europe Latin America Africa Latin America Europe Europe North America Europe Europe Latin America Europe Europe Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
78
Pretax Income (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total revenue = 100)
Rank
Percentile
57.14 32.94 30.23 29.38 28.34 21.44 20.54 19.03 18.78 16.43 16.14 15.59 15.59 15.45 15.13 9.79 9.69 9.27 9.10 8.87 8.52 8.47 8.45 8.30 8.28 7.13 6.76 6.65 6.60 6.53 5.87 5.69 5.65 5.64 5.62 5.60 5.31 4.51 4.21 3.65 3.47 1.93 1.22 1.09 1.04 1.02 0.54 0.08 0.08 0.08 0.08
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Andorra Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Faroe Islands Greece Malta Isle of Man Czech Republic Portugal Latvia Croatia Cyprus Monaco Iceland Spain Germany Slovenia Estonia Denmark Belarus Slovakia Russian Federation Lithuania the United Kingdom France Vatican City Italy Poland Moldova Switzerland Kazakhstan Bulgaria Netherlands Finland Liechtenstein Sweden Ireland Belgium Norway Albania Hungary Ukraine Gibraltar Georgia Luxembourg Austria San Marino Jersey Guernsey
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
79
Income Taxes Countries
Value (total revenue = 100)
Rank
Percentile
15.37 15.32 14.16 8.12 7.61 6.08 5.71 5.25 4.55 4.13 4.09 3.86 3.85 3.55 3.55 3.38 3.09 2.64 2.54 2.53 2.49 2.45 2.35 2.22 2.12 2.05 2.03 1.99 1.98 1.96 1.93 1.85 1.81 1.74 1.40 1.38 1.33 1.22 0.96 0.86 0.68 0.57 0.30 0.17 -0.22
1 2 4 5 6 7 8 9 12 14 15 16 18 19 20 21 22 24 25 26 27 28 29 30 31 32 33 34 35 36 37 39 40 41 42 43 44 45 46 47 49 50 51 52 53
98.11 96.23 92.45 90.57 88.68 86.79 84.91 83.02 77.36 73.58 71.70 69.81 66.04 64.15 62.26 60.38 58.49 54.72 52.83 50.94 49.06 47.17 45.28 43.40 41.51 39.62 37.74 35.85 33.96 32.08 30.19 26.42 24.53 22.64 20.75 18.87 16.98 15.09 13.21 11.32 7.55 5.66 3.77 1.89 0.00
Region
_________________________________________________________________________________________________________
Turkey Mexico New Zealand Greece Czech Republic Philippines Thailand Portugal Japan Argentina Indonesia Italy Israel Australia Germany USA Denmark Singapore India South Africa France Belgium Malaysia the United Kingdom Hong Kong South Korea Finland Netherlands Poland Sweden Canada Russian Federation Spain China Brazil Switzerland Chile Ireland Peru Taiwan Norway Hungary Pakistan Austria Luxembourg
the Middle East Latin America Oceana Europe Europe Asia Asia Europe Asia Latin America Asia Europe the Middle East Oceana Europe North America Europe Asia Asia Africa Europe Europe Asia Europe Asia Asia Europe Europe Europe Europe North America Europe Europe Asia Latin America Europe Latin America Europe Latin America Asia Europe Europe the Middle East Europe Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
80
Income Taxes (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value (total revenue = 100)
Rank
Percentile
14.67 14.60 13.40 13.02 12.56 8.12 7.61 7.53 7.43 7.22 7.22 5.25 5.03 3.89 3.86 3.55 3.41 3.09 2.56 2.49 2.45 2.22 2.03 2.03 1.99 1.98 1.97 1.96 1.88 1.88 1.85 1.84 1.81 1.78 1.71 1.71 1.70 1.38 1.29 1.22 0.83 0.68 0.57 0.51 0.48 0.48 0.17 0.17 0.16 0.16 -0.22
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Andorra Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Greece Czech Republic Malta Isle of Man Latvia Croatia Portugal Cyprus Vatican City Italy Germany Iceland Denmark Monaco France Belgium the United Kingdom Faroe Islands Finland Netherlands Poland Estonia Sweden Belarus Slovakia Russian Federation Lithuania Spain Moldova Kazakhstan Bulgaria Slovenia Switzerland Liechtenstein Ireland Albania Norway Hungary Ukraine Gibraltar Georgia Austria San Marino Jersey Guernsey Luxembourg
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
3.5 3.5.1
81
FINANCIAL RETURNS IN GERMANY: PROFITABILITY RATIOS Overview
In this chapter we consider additional financial ratios estimated for firms involved in computer programming, data processing and computer related services operating in Germany benchmarked against global averages. The chapter begins by defining relevant terms. Estimates are then presented for the proto-typical firm operating in Germany compared to average global benchmarks. For ratios where there are large deviations between the average firm in Germany and the benchmarks, graphics are provided. Then the distribution of ratios is presented in the form of ranks and percentiles. Certain key ratios are highlighted across countries in the comparison group.
3.5.2
Ratios – Definitions of Terms
The following definitions are provided for those less familiar with financial ratio analysis. As this chapter deals with the global benchmarking of ratios, only definitions covering certain terms used in this chapter’s tables and graphs are provided here . The glossary below reflects commonly accepted definitions across various countries and official sources. •
Accounts Receivables Days. The number of days' receivable sales generally correlates to the amount of the accounts receivables to the average daily sales on account. Accounts receivables days is often determined by dividing the gross receivables by (net sales/365).
•
Cash Earnings Return On Equity (%). Cash earnings return on equity generally measures the return of revenues to the shareholders. This ratio is generally calculated by dividing (net income before nonrecurring items minus preferred dividends) by the average common equity.
•
Cash Flow. Cash flow is generally defined as being equal to the company's net income plus the charge-off amounts for depreciation, depletion, amortization, extraordinary charges to reserves. These are bookkeeping deductions which are not paid out as cash.
•
Current Ratio. The current ratio is generally defined as a ratio of liquidity measuring the ability of a business to pay its current obligations when due. The current ratio is generally calculated by dividing total current assets by total current liabilities. Managers and lenders often want the current ratio to be 2.00 or greater. This ratio is often seen as an indication of short-term debt-paying ability. The higher the ratio, the more liquid the company.
•
Dividend Payout (% Earnings) - Total Dividends (%). The dividend payout ratio is generally used to measure the amount of current earnings per common share which are paid out in dividends. This ratio is generally determined by dividing dividends per common share by diluted earnings per share.
•
Fixed Charge Coverage Ratio. The fixed charge coverage ratio is generally seen as an indication of the company's ability to cover its fixed charges. This ratio is typically determined by dividing recurring earnings excluding interest expense, tax expense, equity earnings, and minority earnings plus interest from rentals by interest expense including capitalized interest and interest from rentals.
•
Gross Profit Margin (%). The gross profit margin is typically defined to equals the difference, in percent, between net sales revenue and the cost of goods sold.
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Financial Indicators
82
•
Inventories (# of Days) Held. Inventory days held is generally determined by dividing the ending inventory by (the cost of goods held/365). The number of days held results in the average daily cost of goods held.
•
Inventory Turnover (%). Inventory turnover is used as a measure of the balance of inventory. It generally compares the amount of inventory with the total sales for the year. The ratio can reflect both on the quality of the inventory and the efficiency of management. Typically, the higher the turnover rate, the greater the likelihood that profits would be larger and less working capital bound up in inventory.
•
Net Margin (%). The net margin is the ratio of net income dollars generated by each dollar of sales.
•
Operating Profit Margin (%). Operating profit margin percent is the ratio of operating profit to net sales. Operating profit (loss) is income or loss before taxes calculated by the difference between total revenues and total expense disregarding the effects of any extraordinary transactions.
•
Quick Ratio. The quick ratio, also commonly known as the “acid test ratio”, is a refined current ratio and is often seen as a more conservative measure of liquidity. The quick ratio is generally determined by dividing cash and equivalents plus trade receivables by total current liabilities. The ratio shows the degree to which a company's current liabilities can be covered by the most liquid current assets. Financial management texts generally conclude that any value of less than 1 to 1 implies a reciprocal dependency on inventory or other current assets to liquidate short-term debt.
•
Reinvestment Rate - Total (%). The reinvestment rate is typically defined as the rate at which an investor assumes interest payments made on a debt security can be reinvested over the life of that security.
•
Return on Assets (%). Return on assets is generally used to measure a company's ability to use assets to create profit.
•
Return on Equity - Total (%). The return on total equity ratio is often seen to reflect the profitability of the company's operations after income taxes. Return on equity is often considered to be a good measure of the company's profitability. Tax laws and tax loss carryovers can affect the net income and therefore can also affect the return on equity.
•
Return on Invested Capital (%). The ratio of return on invested capital is typically defined as an evaluation of earnings performance without regard to the method of financing. This ratio measures the earnings on investment and is an indication of how well the company utilizes its asset base. Return on investment is a type of return on capital, therefore this ratio can be an indication of the company’s ability to reward investors who provide long-term funds and to attract future investors.
•
Tax Rate (%). The tax rate is typically defined as the average rate of domestic tax owed to government by the company.
•
Working Capital. Net working capital equals the difference between total current assets and total current liabilities. Working capital often reflects a company's ability to expand volume and meet obligations. Since growth is usually one goal, the amount of working capital on this year's balance sheet should be greater than that of the previous year's. This is an efficiency, or turnover, ratio which benchmarks the rate at which current assets less current liabilities are used by the company in making sales. A low ratio can indicate a less profitable use of working capital in making sales. On the other hand, a very high ratio can indicate the company is wasting current assets which could be more efficiently deployed in production and in increasing sales and profits; or that the company my be undercapitalized, and thus vulnerable to liquidity problems in a period of weak business conditions.
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Financial Indicators
3.5.3
83
Ratio Structure: Outlook
Using the methodology described in the introduction, the following table summarizes ratio structure benchmarks for firms involved in computer programming, data processing and computer related services in Germany. All figures are current-year projections for companies operating in Germany based on latest financial results available. Ratios Germany Europe World Avg. _________________________________________________________________________________________________________
Profitability Return on Equity - Total (%) Reinvestment Rate - Total (%) Return on Assets (%) Return on Invested Capital (%) Cash Earnings Return On Equity (%) Cash Flow % Sales Cost Goods Sold / Sales (%) Gross Profit Margin (%) Selling, General & Administrative Expense/Net Sales (%) Research & Development / Net Sales (%) Operating Profit Margin (%) Operating Inc / Total Capital (%) Pretax Margin (%) Tax Rate (%) Net Margin (%) Total Asset Turnover (X) th USD Asset Utilization Inventory Turnover (%) Net Sales % Working Capital Capital Expenditure % Gross Fixed Assets Capital Expenditure % Total Assets Capital Expenditure % Total Sales Accumulated Depreciation % Gross Fixed Assets Leverage Total Debt % Total Capital Long Term Debt % Total Capital Equity % Total Capital Fixed Charge Coverage Ratio Dividend Payout (% Earnings) - Total Dividends Fixed Assets % Common Equity Working Capital % Total Capital Liquidity Quick Ratio Current Ratio Inventories % Total Current Assets Accounts Receivables Days Inventories (# of Days) Held
11.86 7.71 6.59 11.86 26.44 13.22 57.24 37.36 20.53 7.26 5.88 10.80 9.27 42.38 5.98 1.33
14.06 10.18 6.99 10.48 48.71 10.21 58.13 29.02 20.45 4.28 9.85 13.15 10.53 48.33 6.60 1.05
17.24 14.50 11.56 14.69 40.11 17.05 55.68 29.38 18.11 3.27 12.16 16.09 12.89 26.86 9.53 0.87
239.05 64.72 29.24 5.19 6.52 49.67
575.30 2.97 34.52 7.09 10.66 43.89
56.47 6.44 24.58 7.10 11.27 35.46
14.64 7.87 91.29 46.47 8.31 28.42 52.91
23.44 15.18 77.99 44.87 13.21 64.49 39.57
18.53 10.27 80.35 173.48 14.92 50.83 38.37
4.34 4.92 8.85 105.62 35.26
1.99 2.34 8.33 112.98 33.74
2.00 2.38 10.66 81.98 57.17
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
3.5.4
84
Large Variances: Ratios
The following graphics summarize for computer programming, data processing and computer related services the large ratio structure gaps between firms operating in Germany and the world average. A gap cannot necessarily be interpreted as a positive or negative reflection on performance. Gaps may signal areas of specialization, market focus, or expertise. More contextual information is required to fully interpret these gaps. The gaps highlighted here are simply those that are large.
Gap: Cash Earnings Return On Equity (%) 60 40
48.71
40.11
26.44
20 0 -13.67
-20 Germ any
Europe
World Average
Gap
Gap: Tax Rate (%) 50
48.33 42.38
40 26.86
30
15.52
20 10 0 Germ any
Europe
World Average
Gap
Gap: Inventory Turnover (%) 575.3
600 500 400 300
239.05
182.58
200 56.47
100 0 Germ any
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Europe
World Average
Gap
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Financial Indicators
85
Gap: Net Sales % Working Capital 80
64.72
58.28
60 40 20
2.97
6.44
0 Germ any
Europe
World Average
Gap
Gap: Accumulated Depreciation % Gross Fixed Assets 50
49.67
43.89 35.46
40 30 20
14.21
10 0 Germ any
Europe
World Average
Gap
Gap: Equity % Total Capital 100
91.29 77.99
80
80.35
60 40 10.94
20 0 Germ any
Europe
World Average
Gap
Gap: Fixed Charge Coverage Ratio 173.48
200 100
46.47
44.87
0 -100
-127.01
-200 Germ any
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Europe
World Average
Gap
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Financial Indicators
86
Gap: Fixed Assets % Common Equity 80
64.49
60 40
50.83
28.42
20 0 -20
-22.41
-40 Germ any
Europe
World Average
Gap
Gap: Working Capital % Total Capital 60
52.91
50
39.57
40
38.37
30 14.54
20 10 0 Germ any
Europe
World Average
Gap
Gap: Accounts Receivables Days 120
105.62
112.98
100
81.98
80 60 40
23.64
20 0 Germ any
Europe
World Average
Gap
Gap: Inventories (# of Days) Held 57.17
60 40
35.26
33.74
20 0 -20
-21.91
-40 Germ any
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Europe
World Average
Gap
©2007 Icon Group International, Inc.
Financial Indicators
3.5.5
87
Key Percentiles and Rankings
We now consider the distribution of financial ratios for computer programming, data processing and computer related services using ranks and percentiles. What percent of countries have a value lower or higher than Germany (what is the ratio's rank or percentile)? The table below answers this question with respect to financial ratios. The ranks and percentiles indicate, from highest to lowest, where a value falls within the distribution of all countries considered in the global benchmark (the number of countries in the benchmark per line item may vary, as indicated in the Rank). Again, a high or low figure does not necessarily indicate good or bad performance. After the summary table below, a few key financial ratios are highlighted in additional tables. Ratios
Germany
Rank of Total
Percentile
11.86 7.71 6.59 11.86 26.44 13.22 57.24 37.36 20.53 7.26 5.88 10.80 9.27 42.38 5.98 1.33
28 of 53 35 of 53 33 of 53 26 of 53 32 of 53 28 of 53 29 of 48 15 of 51 20 of 44 10 of 25 38 of 53 35 of 53 26 of 53 17 of 52 30 of 53 15 of 53
47.17 33.96 37.74 50.94 39.62 47.17 39.58 70.59 54.55 60.00 28.30 33.96 50.94 67.31 43.40 71.70
239.05 64.72 29.24 5.19 6.52 49.67
8 of 48 1 of 52 9 of 49 29 of 53 27 of 53 14 of 47
83.33 98.08 81.63 45.28 49.06 70.21
14.64 7.87 91.29 46.47 8.31 28.42 52.91
38 of 53 37 of 52 7 of 53 22 of 53 32 of 39 42 of 53 10 of 52
28.30 28.85 86.79 58.49 17.95 20.75 80.77
4.34 4.92 8.85 105.62 35.26
3 of 52 3 of 52 28 of 48 19 of 49 26 of 48
94.23 94.23 41.67 61.22 45.83
_________________________________________________________________________________________________________
Profitability Return on Equity - Total (%) Reinvestment Rate - Total (%) Return on Assets (%) Return on Invested Capital (%) Cash Earnings Return On Equity (%) Cash Flow % Sales Cost Goods Sold / Sales (%) Gross Profit Margin (%) Selling, General & Administrative Expense/Net Sales (%) Research & Development / Net Sales (%) Operating Profit Margin (%) Operating Inc / Total Capital (%) Pretax Margin (%) Tax Rate (%) Net Margin (%) Total Asset Turnover (X) th USD Asset Utilization Inventory Turnover (%) Net Sales % Working Capital Capital Expenditure % Gross Fixed Assets Capital Expenditure % Total Assets Capital Expenditure % Total Sales Accumulated Depreciation % Gross Fixed Assets Leverage Total Debt % Total Capital Long Term Debt % Total Capital Equity % Total Capital Fixed Charge Coverage Ratio Dividend Payout (% Earnings) - Total Dividends Fixed Assets % Common Equity Working Capital % Total Capital Liquidity Quick Ratio Current Ratio Inventories % Total Current Assets Accounts Receivables Days Inventories (# of Days) Held
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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Financial Indicators
88
Gross Profit Margin (%) Countries
Value
Rank
Percentile
Israel Turkey Mexico Indonesia USA New Zealand Hong Kong Canada Italy Portugal Australia Germany the United Kingdom Singapore Ireland Philippines Greece Thailand Poland Switzerland Denmark Japan China Argentina Finland Malaysia Pakistan Netherlands South Korea Norway India Russian Federation Peru Brazil Spain Chile South Africa France Sweden Belgium Czech Republic Hungary Luxembourg
73.96 67.41 67.23 55.33 47.75 44.13 43.53 43.50 42.71 42.59 41.33 37.36 36.34 36.02 35.68 35.35 34.98 34.56 32.92 32.55 32.32 30.70 30.63 29.99 28.69 27.90 27.00 26.15 25.91 24.65 24.00 23.35 23.10 23.00 22.55 21.88 21.76 17.53 10.62 10.35 8.75 8.74 7.79
1 2 3 5 7 8 9 10 11 12 13 15 16 17 18 19 20 21 22 23 24 25 26 28 30 31 32 34 35 36 37 39 40 41 42 43 44 45 47 48 49 50 51
98.04 96.08 94.12 90.20 86.27 84.31 82.35 80.39 78.43 76.47 74.51 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 45.10 41.18 39.22 37.25 33.33 31.37 29.41 27.45 23.53 21.57 19.61 17.65 15.69 13.73 11.76 7.84 5.88 3.92 1.96 0.00
Region
_________________________________________________________________________________________________________
the Middle East the Middle East Latin America Asia North America Oceana Asia North America Europe Europe Oceana Europe Europe Asia Europe Asia Europe Asia Europe Europe Europe Asia Asia Latin America Europe Asia the Middle East Europe Asia Europe Asia Europe Latin America Latin America Europe Latin America Africa Europe Europe Europe Europe Europe Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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©2007 Icon Group International, Inc.
Financial Indicators
89
Gross Profit Margin (%) (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value
Rank
Percentile
Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Iceland Andorra Vatican City Italy Portugal Faroe Islands Cyprus Germany the United Kingdom Ireland Greece Monaco Poland Switzerland Malta Denmark Isle of Man Liechtenstein Moldova Finland Kazakhstan Bulgaria Netherlands Estonia Norway Belarus Slovakia Russian Federation Lithuania Spain Slovenia Albania France Sweden Belgium Czech Republic Hungary Latvia Croatia Ukraine Luxembourg Gibraltar Georgia
64.05 58.78 57.13 55.11 48.23 45.70 43.05 42.71 42.59 41.74 40.77 37.36 36.34 35.68 34.98 34.93 32.92 32.55 32.42 32.32 31.99 30.37 29.60 28.69 28.48 28.43 26.15 24.98 24.65 23.84 23.79 23.35 23.30 22.55 21.17 20.16 17.53 10.62 10.35 8.75 8.74 8.31 8.31 7.86 7.79 7.48 7.36
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
97.87 95.74 93.62 91.49 89.36 87.23 85.11 82.98 80.85 78.72 76.60 74.47 72.34 70.21 68.09 65.96 63.83 61.70 59.57 57.45 55.32 53.19 51.06 48.94 46.81 44.68 42.55 40.43 38.30 36.17 34.04 31.91 29.79 27.66 25.53 23.40 21.28 19.15 17.02 14.89 12.77 10.64 8.51 6.38 4.26 2.13 0.00
_________________________________________________________________________________________________________
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
90
Pretax Margin (%) Countries
Value
Rank
Percentile
New Zealand Turkey Mexico Israel Hong Kong Philippines Greece India Czech Republic Portugal Singapore Indonesia Thailand Australia China Argentina Pakistan USA Spain Germany South Korea Malaysia Denmark Japan Russian Federation the United Kingdom Taiwan France Italy Poland Switzerland Netherlands Finland Brazil South Africa Chile Sweden Ireland Canada Belgium Norway Peru Hungary Luxembourg Austria
55.18 34.67 34.58 25.27 22.35 21.85 20.54 17.89 16.43 16.14 15.60 15.51 15.02 14.14 12.67 12.16 10.64 9.69 9.69 9.27 9.21 8.79 8.52 8.34 8.30 7.13 6.87 6.76 6.60 6.53 5.69 5.62 5.60 5.41 5.24 5.15 4.51 4.21 4.21 3.65 3.47 2.21 1.22 0.54 0.08
1 2 3 5 6 7 8 10 11 12 13 14 15 17 18 20 23 24 25 26 27 28 29 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 51 52 53
98.11 96.23 94.34 90.57 88.68 86.79 84.91 81.13 79.25 77.36 75.47 73.58 71.70 67.92 66.04 62.26 56.60 54.72 52.83 50.94 49.06 47.17 45.28 41.51 39.62 37.74 35.85 33.96 32.08 30.19 28.30 26.42 24.53 22.64 20.75 18.87 16.98 15.09 13.21 11.32 9.43 7.55 3.77 1.89 0.00
Region
_________________________________________________________________________________________________________
Oceana the Middle East Latin America the Middle East Asia Asia Europe Asia Europe Europe Asia Asia Asia Oceana Asia Latin America the Middle East North America Europe Europe Asia Asia Europe Asia Europe Europe Asia Europe Europe Europe Europe Europe Europe Latin America Africa Latin America Europe Europe North America Europe Europe Latin America Europe Europe Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
91
Pretax Margin (%) (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value
Rank
Percentile
Andorra Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Faroe Islands Greece Malta Isle of Man Czech Republic Portugal Latvia Croatia Cyprus Monaco Iceland Spain Germany Slovenia Estonia Denmark Belarus Slovakia Russian Federation Lithuania the United Kingdom France Vatican City Italy Poland Moldova Switzerland Kazakhstan Bulgaria Netherlands Finland Liechtenstein Sweden Ireland Belgium Norway Albania Hungary Ukraine Gibraltar Georgia Luxembourg Austria San Marino Jersey Guernsey
57.14 32.94 30.23 29.38 28.34 21.44 20.54 19.03 18.78 16.43 16.14 15.59 15.59 15.45 15.13 9.79 9.69 9.27 9.10 8.87 8.52 8.47 8.45 8.30 8.28 7.13 6.76 6.65 6.60 6.53 5.87 5.69 5.65 5.64 5.62 5.60 5.31 4.51 4.21 3.65 3.47 1.93 1.22 1.09 1.04 1.02 0.54 0.08 0.08 0.08 0.08
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
92
Quick Ratio Countries
Value
Rank
Percentile
New Zealand Denmark Germany Israel Hong Kong Ireland Japan Indonesia Canada Malaysia South Korea USA Singapore India Philippines Russian Federation Italy Czech Republic Netherlands China Sweden Poland Norway Greece Australia Thailand Finland the United Kingdom Belgium Switzerland Hungary France Portugal Luxembourg South Africa Austria Spain Argentina Taiwan Brazil Turkey Mexico Chile Peru
10.37 4.86 4.34 4.17 3.39 3.22 3.10 3.07 2.99 2.99 2.86 2.76 2.72 2.64 2.61 2.57 2.34 2.23 2.09 1.92 1.92 1.87 1.81 1.81 1.77 1.60 1.59 1.57 1.47 1.47 1.45 1.44 1.29 1.26 1.25 1.11 1.04 1.04 0.94 0.92 0.91 0.91 0.88 0.44
1 2 3 4 5 6 7 8 9 10 12 13 14 15 17 18 19 20 23 24 25 26 27 28 29 30 31 32 33 34 35 36 38 39 40 42 43 44 45 46 47 48 49 51
98.08 96.15 94.23 92.31 90.38 88.46 86.54 84.62 82.69 80.77 76.92 75.00 73.08 71.15 67.31 65.38 63.46 61.54 55.77 53.85 51.92 50.00 48.08 46.15 44.23 42.31 40.38 38.46 36.54 34.62 32.69 30.77 26.92 25.00 23.08 19.23 17.31 15.38 13.46 11.54 9.62 7.69 5.77 1.92
Region
_________________________________________________________________________________________________________
Oceana Europe Europe the Middle East Asia Europe Asia Asia North America Asia Asia North America Asia Asia Asia Europe Europe Europe Europe Asia Europe Europe Europe Europe Oceana Asia Europe Europe Europe Europe Europe Europe Europe Europe Africa Europe Europe Latin America Asia Latin America the Middle East Latin America Latin America Latin America
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
93
Quick Ratio (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value
Rank
Percentile
Andorra Denmark Germany Faroe Islands Ireland Iceland Estonia Monaco Belarus Slovakia Russian Federation Lithuania Vatican City Italy Czech Republic Latvia Croatia Netherlands Sweden Poland Norway Greece Moldova Malta Isle of Man Kazakhstan Bulgaria Finland the United Kingdom Belgium Switzerland Hungary France Liechtenstein Ukraine Portugal Luxembourg Gibraltar Cyprus Georgia Austria San Marino Guernsey Jersey Spain Slovenia Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Albania
10.74 4.86 4.34 3.25 3.22 2.79 2.75 2.64 2.63 2.62 2.57 2.57 2.36 2.34 2.23 2.11 2.11 2.09 1.92 1.87 1.81 1.81 1.68 1.68 1.65 1.62 1.62 1.59 1.57 1.47 1.47 1.45 1.44 1.37 1.31 1.29 1.26 1.24 1.24 1.22 1.11 1.10 1.07 1.07 1.04 0.98 0.86 0.79 0.77 0.74 0.39
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
94
Current Ratio Countries
Value
Rank
Percentile
New Zealand Denmark Germany Israel Hong Kong Indonesia Ireland South Korea Japan Malaysia Canada Switzerland Russian Federation USA India Philippines Singapore Finland Italy China Netherlands Czech Republic Sweden Poland Norway Greece Australia Hungary Thailand the United Kingdom Belgium France South Africa Portugal Turkey Mexico Brazil Luxembourg Chile Peru Taiwan Austria Spain Argentina
10.37 5.08 4.92 4.22 3.65 3.58 3.51 3.47 3.41 3.40 3.38 3.19 3.13 3.08 2.99 2.98 2.96 2.54 2.41 2.41 2.33 2.33 2.15 2.08 2.00 1.99 1.96 1.90 1.85 1.83 1.64 1.61 1.51 1.47 1.46 1.46 1.41 1.37 1.34 1.31 1.28 1.28 1.22 1.13
1 2 3 4 5 6 7 8 9 10 11 13 15 16 17 18 19 21 23 24 25 26 27 28 29 30 31 32 33 34 35 36 38 39 40 41 43 44 46 47 48 49 50 51
98.08 96.15 94.23 92.31 90.38 88.46 86.54 84.62 82.69 80.77 78.85 75.00 71.15 69.23 67.31 65.38 63.46 59.62 55.77 53.85 51.92 50.00 48.08 46.15 44.23 42.31 40.38 38.46 36.54 34.62 32.69 30.77 26.92 25.00 23.08 21.15 17.31 15.38 11.54 9.62 7.69 5.77 3.85 1.92
Region
_________________________________________________________________________________________________________
Oceana Europe Europe the Middle East Asia Asia Europe Asia Asia Asia North America Europe Europe North America Asia Asia Asia Europe Europe Asia Europe Europe Europe Europe Europe Europe Oceana Europe Asia Europe Europe Europe Africa Europe the Middle East Latin America Latin America Europe Latin America Latin America Asia Europe Europe Latin America
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
95
Current Ratio (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value
Rank
Percentile
Andorra Denmark Germany Ireland Faroe Islands Estonia Belarus Switzerland Slovakia Russian Federation Lithuania Iceland Liechtenstein Monaco Finland Vatican City Italy Netherlands Czech Republic Latvia Croatia Sweden Poland Norway Greece Hungary Moldova Malta the United Kingdom Isle of Man Kazakhstan Bulgaria Ukraine Belgium Gibraltar France Georgia Portugal Cyprus Romania Luxembourg Austria Bosnia & Herzegovina San Marino Macedonia Jersey Guernsey Spain Serbia & Montenegro Albania Slovenia
10.74 5.08 4.92 3.51 3.50 3.35 3.20 3.19 3.19 3.13 3.12 3.11 2.98 2.87 2.54 2.43 2.41 2.33 2.33 2.21 2.21 2.15 2.08 2.00 1.99 1.90 1.87 1.84 1.83 1.82 1.80 1.80 1.71 1.64 1.63 1.61 1.60 1.47 1.41 1.39 1.37 1.28 1.27 1.26 1.24 1.23 1.23 1.22 1.19 1.14 1.14
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
96
Inventories % Total Current Assets Countries
Value
Rank
Percentile
Peru Brazil Chile Philippines Switzerland South Africa Indonesia Thailand China South Korea Hungary Spain Russian Federation Norway Taiwan Singapore Greece Hong Kong Malaysia Belgium Germany Netherlands Portugal Denmark Japan France Canada the United Kingdom Argentina Italy Sweden Poland Austria USA Australia Czech Republic India Luxembourg Israel Finland Ireland
64.97 33.17 31.56 19.77 16.33 16.11 16.09 16.07 15.98 13.24 13.11 12.64 11.93 10.99 10.85 10.58 9.68 9.09 9.05 8.99 8.85 8.35 8.00 7.97 7.92 7.68 7.52 7.48 6.82 6.74 6.68 6.37 6.26 5.35 4.93 2.11 1.47 1.36 0.81 0.61 0.05
1 3 4 5 7 8 9 10 11 14 15 16 19 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48
97.92 93.75 91.67 89.58 85.42 83.33 81.25 79.17 77.08 70.83 68.75 66.67 60.42 56.25 54.17 52.08 50.00 47.92 45.83 43.75 41.67 39.58 37.50 35.42 33.33 31.25 29.17 27.08 25.00 22.92 20.83 18.75 16.67 14.58 12.50 10.42 8.33 6.25 4.17 2.08 0.00
Region
_________________________________________________________________________________________________________
Latin America Latin America Latin America Asia Europe Africa Asia Asia Asia Asia Europe Europe Europe Europe Asia Asia Europe Asia Asia Europe Europe Europe Europe Europe Asia Europe North America Europe Latin America Europe Europe Europe Europe North America Oceana Europe Asia Europe the Middle East Europe Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
97
Inventories % Total Current Assets (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value
Rank
Percentile
56.71 16.33 15.24 13.11 12.77 12.64 12.18 12.16 11.93 11.91 11.87 11.79 11.21 11.04 10.99 10.26 9.68 8.99 8.97 8.85 8.85 8.72 8.35 8.00 7.97 7.68 7.66 7.48 6.79 6.74 6.68 6.37 6.26 6.20 6.05 6.05 5.73 5.51 5.50 5.41 2.11 2.00 2.00 1.36 0.61 0.05
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46
97.83 95.65 93.48 91.30 89.13 86.96 84.78 82.61 80.43 78.26 76.09 73.91 71.74 69.57 67.39 65.22 63.04 60.87 58.70 56.52 54.35 52.17 50.00 47.83 45.65 43.48 41.30 39.13 36.96 34.78 32.61 30.43 28.26 26.09 23.91 21.74 19.57 17.39 15.22 13.04 10.87 8.70 6.52 4.35 2.17 0.00
_________________________________________________________________________________________________________
Albania Switzerland Liechtenstein Hungary Estonia Spain Belarus Slovakia Russian Federation Lithuania Slovenia Ukraine Gibraltar Georgia Norway Monaco Greece Belgium Malta Isle of Man Germany Faroe Islands Netherlands Portugal Denmark France Cyprus the United Kingdom Vatican City Italy Sweden Poland Austria San Marino Guernsey Jersey Moldova Kazakhstan Bulgaria Iceland Czech Republic Latvia Croatia Luxembourg Finland Ireland
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
98
Accounts Receivables Days Countries
Value
Rank
Percentile
Thailand Finland Portugal Italy Greece Spain Malaysia Poland Israel Argentina Hong Kong Singapore France New Zealand Hungary Norway Germany South Korea Belgium Netherlands India Russian Federation Czech Republic Ireland Austria China the United Kingdom Philippines Canada Taiwan Denmark USA Sweden Indonesia Australia South Africa Japan Switzerland Peru Luxembourg Brazil Chile
238.82 197.13 196.64 183.90 169.78 163.41 154.47 142.01 129.47 125.41 123.21 119.38 118.07 111.65 110.76 106.09 105.62 104.49 103.53 96.44 95.72 94.16 92.99 91.93 90.81 89.52 85.71 83.73 80.73 79.71 78.40 78.39 77.55 76.03 74.92 73.32 71.30 69.17 63.57 58.41 47.02 44.74
1 3 4 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 41 43 44 45 48 49
97.96 93.88 91.84 87.76 85.71 83.67 81.63 79.59 77.55 75.51 73.47 71.43 69.39 67.35 65.31 63.27 61.22 59.18 57.14 55.10 51.02 48.98 46.94 44.90 42.86 40.82 38.78 36.73 34.69 32.65 30.61 28.57 26.53 24.49 22.45 20.41 16.33 12.24 10.20 8.16 2.04 0.00
Region
_________________________________________________________________________________________________________
Asia Europe Europe Europe Europe Europe Asia Europe the Middle East Latin America Asia Asia Europe Oceana Europe Europe Europe Asia Europe Europe Asia Europe Europe Europe Europe Asia Europe Asia North America Asia Europe North America Europe Asia Oceana Africa Asia Europe Latin America Europe Latin America Latin America
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
99
Accounts Receivables Days (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value
Rank
Percentile
Finland Portugal Cyprus Vatican City Italy Greece Spain Malta Isle of Man Slovenia Poland Moldova Kazakhstan Bulgaria Faroe Islands France Monaco Andorra Hungary Norway Germany Belgium Estonia Ukraine Netherlands Belarus Slovakia Gibraltar Russian Federation Lithuania Georgia Czech Republic Ireland Austria San Marino Latvia Croatia Guernsey Jersey the United Kingdom Iceland Denmark Sweden Switzerland Liechtenstein Luxembourg Albania
197.13 196.64 188.23 185.38 183.90 169.78 163.41 157.36 155.28 153.41 142.01 127.68 122.87 122.65 118.14 118.07 115.76 115.62 110.76 106.09 105.62 103.53 100.73 99.60 96.44 96.14 95.92 94.70 94.16 93.94 93.24 92.99 91.93 90.81 89.95 88.26 88.23 87.70 87.70 85.71 79.19 78.40 77.55 69.17 64.55 58.41 55.49
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
97.87 95.74 93.62 91.49 89.36 87.23 85.11 82.98 80.85 78.72 76.60 74.47 72.34 70.21 68.09 65.96 63.83 61.70 59.57 57.45 55.32 53.19 51.06 48.94 46.81 44.68 42.55 40.43 38.30 36.17 34.04 31.91 29.79 27.66 25.53 23.40 21.28 19.15 17.02 14.89 12.77 10.64 8.51 6.38 4.26 2.13 0.00
_________________________________________________________________________________________________________
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
100
Inventories (# of Days) Held Countries
Value
Rank
Percentile
Indonesia Peru Philippines Hong Kong Canada China Brazil Chile Malaysia South Korea Russian Federation USA Greece Singapore Spain Thailand Italy Netherlands South Africa Israel Germany the United Kingdom Switzerland Hungary Australia Poland Japan Sweden Taiwan Argentina Portugal Belgium France Norway Denmark India Austria Czech Republic Finland Luxembourg Ireland
302.82 226.31 108.44 98.85 80.05 76.67 75.75 72.08 68.93 57.06 51.42 47.13 45.88 44.69 43.99 40.94 39.08 38.63 38.10 36.28 35.26 34.17 33.57 30.88 29.55 28.73 27.98 26.26 24.23 22.59 21.44 20.91 19.83 18.54 15.73 13.01 11.50 9.38 5.42 2.19 0.47
1 3 6 7 9 10 11 12 13 14 16 17 18 19 20 21 22 23 24 25 26 28 29 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48
97.92 93.75 87.50 85.42 81.25 79.17 77.08 75.00 72.92 70.83 66.67 64.58 62.50 60.42 58.33 56.25 54.17 52.08 50.00 47.92 45.83 41.67 39.58 35.42 33.33 31.25 29.17 27.08 25.00 22.92 20.83 18.75 16.67 14.58 12.50 10.42 8.33 6.25 4.17 2.08 0.00
Region
_________________________________________________________________________________________________________
Asia Latin America Asia Asia North America Asia Latin America Latin America Asia Asia Europe North America Europe Asia Europe Asia Europe Europe Africa the Middle East Europe Europe Europe Europe Oceana Europe Asia Europe Asia Latin America Europe Europe Europe Europe Europe Asia Europe Europe Europe Europe Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
101
Inventories (# of Days) Held (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value
Rank
Percentile
Albania Faroe Islands Estonia Belarus Slovakia Russian Federation Lithuania Iceland Greece Spain Monaco Malta Isle of Man Slovenia Vatican City Italy Netherlands Germany the United Kingdom Switzerland Liechtenstein Hungary Poland Ukraine Gibraltar Sweden Georgia Moldova Kazakhstan Bulgaria Portugal Belgium Cyprus France Norway Denmark Austria San Marino Guernsey Jersey Czech Republic Latvia Croatia Finland Luxembourg Ireland
197.55 94.79 55.01 52.50 52.38 51.42 51.30 47.62 45.88 43.99 43.34 42.52 41.97 41.29 39.39 39.08 38.63 35.26 34.17 33.57 31.32 30.88 28.73 27.77 26.40 26.26 25.99 25.83 24.86 24.81 21.44 20.91 20.53 19.83 18.54 15.73 11.50 11.39 11.11 11.11 9.38 8.91 8.90 5.42 2.19 0.47
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46
97.83 95.65 93.48 91.30 89.13 86.96 84.78 82.61 80.43 78.26 76.09 73.91 71.74 69.57 67.39 65.22 63.04 60.87 58.70 56.52 54.35 52.17 50.00 47.83 45.65 43.48 41.30 39.13 36.96 34.78 32.61 30.43 28.26 26.09 23.91 21.74 19.57 17.39 15.22 13.04 10.87 8.70 6.52 4.35 2.17 0.00
_________________________________________________________________________________________________________
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
3.6 3.6.1
102
PRODUCTIVITY IN GERMANY: ASSET-LABOR RATIOS Overview
In this chapter, we consider numerous asset-labor ratios for computer programming, data processing and computer related services in Germany benchmarked against global averages. Productivity and utilization ratios are presented for companies oprating in Germany and the average global benchmarks for computer programming, data processing and computer related services. For ratios where there are large deviations between Germany and the benchmarks, graphics are provided (sometimes referred to as a “gap” analysis). Then the distribution of ratios is presented in the form of ranks and percentiles. Certain asset-labor ratios are highlighted across countries in the comparison group. In the case of asset-labor ratios, this report maintains comparability over time and across countries by using a common currency (the US dollar) and relates each measure to a “per employee basis”. Ratios are projected using raw financial statistics and, as ratios, are therefore comparable. Given a country’s human resource ratios, the resulting figures are benchmarked across regional and global averages. We then report the larger asset-labor ratio gaps for computer programming, data processing and computer related services that Germany has vis-à-vis the worldwide average. Again, a gap need not be a bad sign. Rather, it is simply a substantial difference that might merit further attention or signal a firm’s relative incentive to invest locally. All figures are projections, so due caution is required.
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©2007 Icon Group International, Inc.
Financial Indicators
3.6.2
103
Asset to Labor: Outlook
The following tables and graphs are prepared using the methodology described at the beginning of this section. All units are in thousands of US dollars per employee. All figures are current-year projections for computer programming, data processing and computer related services in Germany based on latest financial results available. Labor-asset Ratios ($k/employee) Germany Europe World Avg. _________________________________________________________________________________________________________
Cash & Short Term Investments Cash Short Term Investments Receivables (Net) Total Inventories Raw Materials Work in Process Finished Goods Progress Payments & Other Prepaid Expenses Other Current Assets Current Assets - Total Long Term Receivables Investments in Unconsolidated Subsidiaries Other Investments Property Plant and Equipment - Net Property Plant and Equipment - Gross Buildings Machinery & Equipment Rental/Lease Property Transportation Equipment Other Property Plant & Equipment Property Plant & Equipment Under Capitalized Leases Accumulated Depreciation - Total Accumulated Depreciation - Buildings Accumulated Depreciation -Machinery & Equipment Accumulated Depreciation - Rental/Lease Property Accumulated Depreciation - Transportation Equipment Accumulated Depreciation - Other Prop & Equip Accumulated Depreciation - PP&E Under Capitalized Leases Other Assets Deferred Charges Tangible Other Assets Intangible Other Assets Total Assets
67.28 36.34 42.10 101.46 11.35 2.13 3.22 7.20 1.79 1.80 5.91 136.40 1.20 0.31 1.18 45.65 48.24 11.68 7.86 51.71 1.03 18.31 6.92 22.86 2.42 5.03 38.61 0.34 10.45 11.50 32.75 1.86 1.37 29.70 267.10
56.60 43.92 24.85 191.72 12.86 4.83 4.16 7.22 1.51 2.22 22.75 151.09 3.26 25.15 13.85 225.89 355.84 28.27 296.87 1852.11 41.07 30.31 5.81 153.58 5.17 12.19 846.10 1.41 11.11 2.19 33.90 3.02 9.48 17.21 616.54
43.32 20.78 19.42 50.67 14.02 3.35 2.25 3.80 2.84 1.39 13.57 107.54 2.60 24.03 8.65 118.23 235.10 17.43 143.89 242.05 17.20 14.59 2.64 99.39 1.93 4.73 189.77 0.66 3.95 0.51 29.10 0.81 3.09 13.99 302.73
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
3.6.3
104
Asset to Labor: International Gaps
The following graphics summarize for computer programming, data processing and computer related services the large labor-asset gaps between firms operating in Germany and the world average. A gap cannot necessarily be interpreted as a positive or negative reflection on performance. Gaps may signal areas of specialization, market focus, or expertise. More contextual information is required to fully interpret these gaps. The gaps highlighted here are simply those that are large.
Gap: Cash & Short Term Investments ($k/employee) 80
67.28 56.6
60
43.32
40
23.96
20 0 Germ any
Europe
World Average
Gap
Gap: Receivables (Net) ($k/employee) 191.72
200 150 100
101.46 50.67
50
50.79
0 Germ any
Europe
World Average
Gap
Gap: Current Assets - Total ($k/employee) 200 150
136.4
151.09 107.54
100 50
28.86
0 Germ any
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Europe
World Average
Gap
©2007 Icon Group International, Inc.
Financial Indicators
105
Gap: Investments in Unconsolidated Subsidiaries ($k/employee) 25.15
30
24.03
20 10
0.31
0 -10 -20
-23.72
-30 Germ any
Europe
World Average
Gap
Gap: Property Plant and Equipment - Net ($k/employee) 250 200 150 100 50 0 -50 -100
225.89 118.23 45.65
-72.58 Germ any
Europe
World Average
Gap
Gap: Property Plant and Equipment - Gross ($k/employee) 355.84
400 300
235.1
200 100
48.24
0 -100 -200 Germ any
Europe
World Average
-186.86 Gap
Gap: Machinery & Equipment ($k/employee) 296.87
300 200
143.89
100
7.86
0 -100
-136.03
-200 Germ any
www.icongrouponline.com
Europe
World Average
Gap
©2007 Icon Group International, Inc.
Financial Indicators
106
Gap: Rental/Lease Property ($k/employee) 1852.11
2000 1500 1000 500
242.05
51.71
0
-190.34
-500 Germ any
Europe
World Average
Gap
Gap: Accumulated Depreciation - Total ($k/employee) 200
153.58
150
99.39
100 50
22.86
0 -50
-76.53
-100 Germ any
Europe
World Average
Gap
Gap: Accumulated Depreciation - Rental/Lease Property ($k/employee) 1000
846.1
800 600 400
189.77
200
38.61
0 -151.16
-200 Germ any
Europe
World Average
Gap
Gap: Total Assets ($k/employee) 800
616.54
600 400
302.73
267.1
200 0
-35.63
-200 Germ any
www.icongrouponline.com
Europe
World Average
Gap
©2007 Icon Group International, Inc.
Financial Indicators
3.6.4
107
Key Percentiles and Rankings
We now consider the distribution of asset-labor ratios using ranks and percentiles across . What percent of countries have a productivity indicator lower or higher than Germany (what is the indicator's rank or percentile)? The table below answers this question with respect to asset-labor structure. The ranks and percentiles indicate, from highest to lowest, where a value falls within the distribution of all countries considered in the global benchmark (the number of countries in the benchmark per line item may vary, as indicated in the Rank). Again, a high or low figure does not necessarily indicate good or bad performance or productivity. After the summary table below, a few key asset-labor ratios are highlighted in additional tables. Asset Structure ($k/employee)
Germany
Rank of Total
Percentile
67.28 36.34 42.10 101.46 11.35 2.13 3.22 7.20 1.79 1.80 5.91 136.40 1.20 0.31 1.18 45.65 48.24 11.68 7.86 51.71 1.03 18.31 6.92 22.86 2.42 5.03 38.61 0.34 10.45 11.50 32.75 1.86 1.37 29.70 267.10
16 of 53 15 of 50 9 of 48 13 of 53 17 of 49 19 of 37 13 of 35 10 of 33 9 of 36 15 of 39 20 of 47 18 of 52 25 of 41 36 of 43 29 of 40 22 of 53 31 of 50 25 of 47 37 of 45 9 of 17 32 of 41 16 of 50 7 of 21 26 of 48 17 of 40 29 of 39 9 of 17 29 of 35 10 of 44 1 of 19 20 of 53 12 of 34 21 of 37 12 of 44 20 of 53
69.81 70.00 81.25 75.47 65.31 48.65 62.86 69.70 75.00 61.54 57.45 65.38 39.02 16.28 27.50 58.49 38.00 46.81 17.78 47.06 21.95 68.00 66.67 45.83 57.50 25.64 47.06 17.14 77.27 94.74 62.26 64.71 43.24 72.73 62.26
_________________________________________________________________________________________________________
Cash & Short Term Investments Cash Short Term Investments Receivables (Net) Total Inventories Raw Materials Work in Process Finished Goods Progress Payments & Other Prepaid Expenses Other Current Assets Current Assets - Total Long Term Receivables Investments in Unconsolidated Subsidiaries Other Investments Property Plant and Equipment - Net Property Plant and Equipment - Gross Buildings Machinery & Equipment Rental/Lease Property Transportation Equipment Other Property Plant & Equipment Property Plant & Equipment Under Capitalized Leases Accumulated Depreciation - Total Accumulated Depreciation - Buildings Accumulated Depreciation -Machinery & Equipment Accumulated Depreciation - Rental/Lease Property Accumulated Depreciation - Transportation Equipment Accumulated Depreciation - Other Prop & Equip Accumulated Depreciation - P P & E Under Capitalized Leases Other Assets Deferred Charges Tangible Other Assets Intangible Other Assets Total Assets
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
108
Cash & Short Term Investments Countries
Value ($K/employee)
Rank
Percentile
237.80 192.95 167.17 150.64 146.05 145.65 132.33 121.10 104.43 88.19 83.57 83.47 75.89 67.28 62.64 62.51 51.20 39.57 37.67 32.95 29.94 28.43 25.22 24.24 23.05 20.60 19.66 18.96 17.76 17.48 16.71 16.18 16.11 15.60 14.85 13.65 13.17 12.88 11.95 9.84 9.33 8.53 8.51 6.85 1.86
1 2 3 5 6 7 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 30 31 33 34 35 36 37 38 39 41 42 43 45 46 48 49 50 52 53
98.11 96.23 94.34 90.57 88.68 86.79 83.02 81.13 79.25 77.36 75.47 73.58 71.70 69.81 67.92 66.04 64.15 62.26 60.38 58.49 56.60 54.72 52.83 50.94 49.06 47.17 43.40 41.51 37.74 35.85 33.96 32.08 30.19 28.30 26.42 22.64 20.75 18.87 15.09 13.21 9.43 7.55 5.66 1.89 0.00
Region
_________________________________________________________________________________________________________
Israel Denmark South Korea Russian Federation Turkey Mexico Hong Kong Japan Italy New Zealand USA Canada France Germany Greece China Sweden Singapore the United Kingdom Norway Australia Switzerland Czech Republic Thailand Belgium Ireland Pakistan Finland Malaysia Poland Taiwan Hungary Philippines Brazil Chile Indonesia South Africa Netherlands Austria Portugal Peru India Luxembourg Spain Argentina
the Middle East Europe Asia Europe the Middle East Latin America Asia Asia Europe Oceana North America North America Europe Europe Europe Asia Europe Asia Europe Europe Oceana Europe Europe Asia Europe Europe the Middle East Europe Asia Europe Asia Europe Asia Latin America Latin America Asia Africa Europe Europe Europe Latin America Asia Europe Europe Latin America
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
109
Cash & Short Term Investments (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
192.95 161.16 153.81 153.46 150.64 150.29 138.77 127.35 126.90 123.77 119.39 105.27 104.43 91.33 84.43 75.89 67.28 62.64 58.06 57.29 51.20 38.37 37.67 32.95 28.43 26.53 25.22 23.94 23.93 23.05 20.60 18.96 17.48 16.18 15.71 15.12 15.09 14.55 13.83 13.62 12.88 11.95 11.84 11.54 11.54 9.84 9.41 8.51 8.14 6.85 6.44
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Denmark Estonia Belarus Slovakia Russian Federation Lithuania Romania Bosnia & Herzegovina Faroe Islands Macedonia Serbia & Montenegro Vatican City Italy Andorra Iceland France Germany Greece Malta Isle of Man Sweden Monaco the United Kingdom Norway Switzerland Liechtenstein Czech Republic Latvia Croatia Belgium Ireland Finland Poland Hungary Moldova Kazakhstan Bulgaria Ukraine Gibraltar Georgia Netherlands Austria San Marino Guernsey Jersey Portugal Cyprus Luxembourg Albania Spain Slovenia
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
110
Receivables (Net) Countries
Value ($K/employee)
Rank
Percentile
2971.78 335.59 192.56 192.03 181.46 173.99 161.26 135.14 121.77 116.46 101.46 90.98 81.45 81.30 73.52 69.32 68.79 67.26 63.57 61.75 56.67 53.72 53.20 50.78 50.30 50.13 49.51 49.40 44.27 43.21 42.07 41.17 32.64 32.59 31.63 28.53 26.29 23.62 19.04 17.38 12.71 12.69 9.92 9.44 9.00
1 2 3 4 5 7 8 9 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 34 35 37 38 39 40 41 42 44 45 46 47 49 50 51
98.11 96.23 94.34 92.45 90.57 86.79 84.91 83.02 79.25 77.36 75.47 73.58 71.70 69.81 67.92 66.04 64.15 62.26 60.38 58.49 56.60 54.72 52.83 50.94 49.06 47.17 45.28 43.40 41.51 39.62 35.85 33.96 30.19 28.30 26.42 24.53 22.64 20.75 16.98 15.09 13.21 11.32 7.55 5.66 3.77
Region
_________________________________________________________________________________________________________
Portugal Ireland Turkey Mexico Taiwan Denmark Greece South Korea Russian Federation Italy Germany Finland Japan Pakistan Israel Argentina Hong Kong Spain Belgium France Hungary China the United Kingdom Australia Thailand USA Singapore Malaysia Switzerland Canada Austria Norway Poland Sweden Netherlands New Zealand Peru South Africa Luxembourg Czech Republic India Philippines Brazil Chile Indonesia
Europe Europe the Middle East Latin America Asia Europe Europe Asia Europe Europe Europe Europe Asia the Middle East the Middle East Latin America Asia Europe Europe Europe Europe Asia Europe Oceana Asia North America Asia Asia Europe North America Europe Europe Europe Europe Europe Oceana Latin America Africa Europe Europe Asia Asia Latin America Latin America Asia
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
111
Receivables (Net) (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
2971.78 2844.66 335.59 182.95 173.99 167.90 163.17 161.26 157.40 149.46 147.50 130.28 124.34 124.05 121.77 121.49 117.40 116.46 101.46 90.98 67.26 65.97 63.57 63.15 61.75 56.67 53.20 50.96 50.65 48.45 48.01 47.70 44.27 42.07 41.67 41.31 41.17 40.62 40.62 32.64 32.59 31.63 29.54 29.35 28.24 28.19 22.95 19.04 17.38 16.50 16.49
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Portugal Cyprus Ireland Romania Denmark Bosnia & Herzegovina Macedonia Greece Serbia & Montenegro Malta Isle of Man Estonia Belarus Slovakia Russian Federation Lithuania Vatican City Italy Germany Finland Spain Faroe Islands Belgium Slovenia France Hungary the United Kingdom Ukraine Iceland Gibraltar Monaco Georgia Switzerland Austria San Marino Liechtenstein Norway Jersey Guernsey Poland Sweden Netherlands Andorra Moldova Kazakhstan Bulgaria Albania Luxembourg Czech Republic Latvia Croatia
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
112
Total Inventories Countries
Value ($K/employee)
Rank
Percentile
68.36 52.09 46.94 32.32 32.17 29.38 16.02 15.13 12.98 12.92 12.66 12.50 12.30 11.95 11.35 9.93 9.88 9.58 9.13 8.11 7.98 7.93 7.91 6.73 6.09 6.02 5.94 5.50 5.48 5.36 5.26 4.57 4.35 4.12 3.78 3.35 1.83 1.51 1.13 0.83 0.52 0.47
1 2 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 37 39 41 42 44 45 46 47 48 49
97.96 95.92 89.80 87.76 85.71 83.67 81.63 79.59 77.55 75.51 73.47 71.43 69.39 67.35 65.31 61.22 59.18 57.14 55.10 53.06 51.02 48.98 46.94 44.90 42.86 40.82 38.78 36.73 34.69 32.65 30.61 28.57 24.49 20.41 16.33 14.29 10.20 8.16 6.12 4.08 2.04 0.00
Region
_________________________________________________________________________________________________________
Peru South Korea Russian Federation Greece China Taiwan Switzerland Japan Spain Brazil Philippines Hungary Chile Canada Germany Italy Singapore Norway France Belgium Hong Kong Sweden South Africa Portugal Austria USA Netherlands the United Kingdom Denmark Thailand Argentina Australia Indonesia Malaysia Poland Pakistan Finland Ireland Israel Czech Republic Luxembourg India
Latin America Asia Europe Europe Asia Asia Europe Asia Europe Latin America Asia Europe Latin America North America Europe Europe Asia Europe Europe Europe Asia Europe Africa Europe Europe North America Europe Europe Europe Asia Latin America Oceana Asia Asia Europe the Middle East Europe Europe the Middle East Europe Europe Asia
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
113
Total Inventories (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
59.67 50.21 47.93 47.82 46.94 46.83 32.32 29.96 29.56 16.02 14.95 12.98 12.50 12.19 11.35 11.24 10.69 10.52 10.01 9.93 9.58 9.58 9.13 8.11 7.93 7.65 6.73 6.45 6.09 6.08 6.03 5.94 5.88 5.88 5.50 5.48 3.78 3.40 3.27 3.26 1.83 1.51 0.83 0.78 0.78 0.52
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46
97.83 95.65 93.48 91.30 89.13 86.96 84.78 82.61 80.43 78.26 76.09 73.91 71.74 69.57 67.39 65.22 63.04 60.87 58.70 56.52 54.35 52.17 50.00 47.83 45.65 43.48 41.30 39.13 36.96 34.78 32.61 30.43 28.26 26.09 23.91 21.74 19.57 17.39 15.22 13.04 10.87 8.70 6.52 4.35 2.17 0.00
_________________________________________________________________________________________________________
Albania Estonia Belarus Slovakia Russian Federation Lithuania Greece Malta Isle of Man Switzerland Liechtenstein Spain Hungary Slovenia Germany Ukraine Gibraltar Georgia Vatican City Italy Norway Monaco France Belgium Sweden Faroe Islands Portugal Cyprus Austria Iceland San Marino Netherlands Jersey Guernsey the United Kingdom Denmark Poland Moldova Kazakhstan Bulgaria Finland Ireland Czech Republic Latvia Croatia Luxembourg
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
114
Current Assets - Total Countries
Value ($K/employee)
Rank
Percentile
449.65 405.19 369.25 368.25 313.31 270.84 234.10 233.84 207.13 189.82 160.04 156.38 148.20 147.59 143.65 136.40 124.34 116.72 105.21 103.14 101.83 100.50 98.58 96.82 95.34 88.65 88.64 88.18 85.78 77.21 72.34 67.42 66.70 59.99 55.89 52.05 45.08 44.94 44.68 38.96 37.07 29.55 27.43 24.66
1 3 4 5 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 33 34 35 36 37 38 39 42 43 44 45 47 48 49 51
98.08 94.23 92.31 90.38 86.54 84.62 82.69 80.77 78.85 76.92 75.00 73.08 71.15 69.23 67.31 65.38 63.46 61.54 59.62 57.69 55.77 53.85 51.92 50.00 48.08 46.15 44.23 42.31 40.38 36.54 34.62 32.69 30.77 28.85 26.92 25.00 19.23 17.31 15.38 13.46 9.62 7.69 5.77 1.92
Region
_________________________________________________________________________________________________________
South Korea Russian Federation Turkey Mexico Israel Taiwan Italy Greece Japan Hong Kong Denmark China USA France Canada Germany Switzerland New Zealand Peru Finland the United Kingdom Singapore Sweden Belgium Hungary Australia Spain Norway Malaysia Argentina Portugal Ireland Austria Thailand Poland Netherlands Philippines South Africa Czech Republic Brazil Chile Luxembourg Indonesia India
Asia Europe the Middle East Latin America the Middle East Asia Europe Europe Asia Asia Europe Asia North America Europe North America Europe Europe Oceana Latin America Europe Europe Asia Europe Europe Europe Oceana Europe Europe Asia Latin America Europe Europe Europe Asia Europe Europe Asia Africa Europe Latin America Latin America Europe Asia Asia
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
115
Current Assets - Total (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
433.48 413.72 412.77 405.19 404.24 350.84 321.96 312.91 301.84 236.00 234.10 233.84 216.73 213.88 182.02 160.04 149.72 147.59 136.40 124.34 120.87 116.03 103.14 101.83 98.58 97.46 96.82 95.34 91.84 88.64 88.18 85.74 83.22 81.52 80.26 72.34 69.25 67.42 66.70 66.07 64.41 64.41 55.89 52.05 50.25 48.35 48.27 44.68 42.41 42.39 29.55
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Estonia Belarus Slovakia Russian Federation Lithuania Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Vatican City Italy Greece Malta Isle of Man Faroe Islands Denmark Iceland France Germany Switzerland Andorra Liechtenstein Finland the United Kingdom Sweden Monaco Belgium Hungary Albania Spain Norway Ukraine Slovenia Gibraltar Georgia Portugal Cyprus Ireland Austria San Marino Jersey Guernsey Poland Netherlands Moldova Kazakhstan Bulgaria Czech Republic Latvia Croatia Luxembourg
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
116
Property Plant and Equipment - Net Countries
Value ($K/employee)
Rank
Percentile
1679.34 1280.12 1276.63 752.97 621.85 243.70 242.25 140.28 119.37 92.24 87.46 80.58 69.72 64.55 54.07 51.64 47.38 45.65 44.20 44.19 41.27 39.83 38.55 36.33 35.95 35.66 34.79 26.75 26.16 25.88 24.67 23.82 23.79 19.11 17.82 17.64 16.60 11.51 11.23 10.80 10.22 9.65 9.18 7.77 7.51
1 2 3 5 6 7 8 9 10 11 12 13 16 17 18 19 21 22 23 24 25 27 28 29 30 31 32 34 35 36 37 38 39 40 41 42 44 46 47 48 49 50 51 52 53
98.11 96.23 94.34 90.57 88.68 86.79 84.91 83.02 81.13 79.25 77.36 75.47 69.81 67.92 66.04 64.15 60.38 58.49 56.60 54.72 52.83 49.06 47.17 45.28 43.40 41.51 39.62 35.85 33.96 32.08 30.19 28.30 26.42 24.53 22.64 20.75 16.98 13.21 11.32 9.43 7.55 5.66 3.77 1.89 0.00
Region
_________________________________________________________________________________________________________
Italy Turkey Mexico Greece Pakistan Hong Kong Japan France Taiwan Thailand Australia USA Peru Argentina the United Kingdom China Switzerland Germany South Korea Denmark Czech Republic Russian Federation Finland Philippines Singapore New Zealand Ireland Norway Portugal Canada Israel Malaysia Hungary Luxembourg Belgium Indonesia Spain Sweden Poland Netherlands India Brazil Chile South Africa Austria
Europe the Middle East Latin America Europe the Middle East Asia Asia Europe Asia Asia Oceana North America Latin America Latin America Europe Asia Europe Europe Asia Europe Europe Europe Europe Asia Asia Oceana Europe Europe Europe North America the Middle East Asia Europe Europe Europe Asia Europe Europe Europe Europe Asia Latin America Latin America Africa Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
117
Property Plant and Equipment - Net (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
1692.92 1679.34 1216.29 1116.18 1084.79 1046.42 752.97 697.87 688.69 233.68 140.28 81.41 60.86 54.07 47.38 45.65 44.21 44.19 42.61 41.27 40.67 40.58 39.83 39.74 39.17 39.15 38.55 36.93 34.86 34.79 26.75 26.16 25.04 23.79 21.39 20.34 20.03 19.11 17.82 16.60 15.58 11.51 11.23 10.80 10.10 9.72 9.70 7.51 7.44 7.25 7.25
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Vatican City Italy Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Greece Malta Isle of Man Faroe Islands France Iceland Albania the United Kingdom Switzerland Germany Liechtenstein Denmark Estonia Czech Republic Belarus Slovakia Russian Federation Lithuania Latvia Croatia Finland Andorra Monaco Ireland Norway Portugal Cyprus Hungary Ukraine Gibraltar Georgia Luxembourg Belgium Spain Slovenia Sweden Poland Netherlands Moldova Kazakhstan Bulgaria Austria San Marino Jersey Guernsey
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
118
Accumulated Depreciation - Total Countries
Value ($K/employee)
Rank
Percentile
1191.48 1061.43 1058.54 599.21 411.73 158.32 66.34 57.93 46.38 43.16 41.83 41.73 37.79 34.17 33.56 30.24 29.47 25.38 24.26 22.86 21.72 20.41 20.14 20.01 18.36 17.30 16.95 16.46 14.44 14.24 14.19 12.03 11.80 10.55 9.45 8.99 8.87 7.18 5.84 4.47
1 2 3 5 6 7 8 9 10 11 12 13 15 17 18 21 22 23 25 26 27 28 29 30 32 33 34 35 36 38 39 40 41 42 43 44 45 46 47 48
97.92 95.83 93.75 89.58 87.50 85.42 83.33 81.25 79.17 77.08 75.00 72.92 68.75 64.58 62.50 56.25 54.17 52.08 47.92 45.83 43.75 41.67 39.58 37.50 33.33 31.25 29.17 27.08 25.00 20.83 18.75 16.67 14.58 12.50 10.42 8.33 6.25 4.17 2.08 0.00
Region
_________________________________________________________________________________________________________
Pakistan Turkey Mexico Greece Japan Hong Kong Switzerland France Thailand Czech Republic Peru Finland USA Italy South Korea Russian Federation Philippines China the United Kingdom Germany Canada Singapore Belgium Indonesia Malaysia Spain Australia New Zealand Sweden Israel Netherlands Ireland Norway Denmark Brazil Chile Portugal Poland India South Africa
the Middle East the Middle East Latin America Europe Asia Asia Europe Europe Asia Europe Latin America Europe North America Europe Asia Europe Asia Asia Europe Europe North America Asia Europe Asia Asia Europe Oceana Oceana Europe the Middle East Europe Europe Europe Europe Latin America Latin America Europe Europe Asia Africa
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
119
Accumulated Depreciation - Total (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
1008.50 925.50 899.47 867.66 599.21 555.37 548.06 151.81 66.34 61.90 57.93 43.16 41.73 40.97 40.95 38.18 36.52 34.45 34.17 32.36 30.88 30.81 30.24 30.17 24.26 22.86 20.14 19.79 17.30 17.05 16.24 14.44 14.19 12.03 11.80 10.55 8.87 8.49 7.18 6.46 6.21 6.20
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42
97.62 95.24 92.86 90.48 88.10 85.71 83.33 80.95 78.57 76.19 73.81 71.43 69.05 66.67 64.29 61.90 59.52 57.14 54.76 52.38 50.00 47.62 45.24 42.86 40.48 38.10 35.71 33.33 30.95 28.57 26.19 23.81 21.43 19.05 16.67 14.29 11.90 9.52 7.14 4.76 2.38 0.00
_________________________________________________________________________________________________________
Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Greece Malta Isle of Man Faroe Islands Switzerland Liechtenstein France Czech Republic Finland Latvia Croatia Iceland Albania Vatican City Italy Estonia Belarus Slovakia Russian Federation Lithuania the United Kingdom Germany Belgium Monaco Spain Andorra Slovenia Sweden Netherlands Ireland Norway Denmark Portugal Cyprus Poland Moldova Kazakhstan Bulgaria
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
120
Intangible Other Assets Countries
Value ($K/employee)
Rank
Percentile
76.43 64.44 54.03 47.98 43.66 42.26 38.82 38.08 37.01 32.99 29.70 28.25 27.55 26.65 25.44 25.44 23.03 22.87 21.09 19.03 18.81 15.02 14.31 14.17 11.69 11.19 11.01 8.08 7.44 7.32 5.63 5.48 5.43 4.93 3.80 0.90 0.88 0.76 0.76
1 2 3 4 5 6 7 9 10 11 12 13 14 15 16 17 18 19 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41
97.73 95.45 93.18 90.91 88.64 86.36 84.09 79.55 77.27 75.00 72.73 70.45 68.18 65.91 63.64 61.36 59.09 56.82 52.27 50.00 47.73 45.45 43.18 40.91 38.64 36.36 34.09 31.82 29.55 27.27 25.00 22.73 20.45 18.18 15.91 13.64 11.36 9.09 6.82
Region
_________________________________________________________________________________________________________
Canada Israel Belgium USA the United Kingdom South Korea Australia Russian Federation Italy Argentina Germany Ireland France Japan Spain Philippines Hong Kong Sweden Luxembourg China Norway Finland Austria Switzerland Portugal Netherlands Hungary Poland Denmark Singapore Greece New Zealand India Malaysia South Africa Thailand Czech Republic Turkey Mexico
North America the Middle East Europe North America Europe Asia Oceana Europe Europe Latin America Europe Europe Europe Asia Europe Asia Asia Europe Europe Asia Europe Europe Europe Europe Europe Europe Europe Europe Europe Asia Europe Oceana Asia Asia Africa Asia Europe the Middle East Latin America
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
121
Intangible Other Assets (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
54.03 48.47 43.66 40.74 38.89 38.80 38.08 37.99 37.31 37.01 29.70 28.25 27.55 25.44 23.88 22.87 22.09 21.09 18.81 15.02 14.31 14.17 14.17 13.82 13.82 13.23 11.69 11.19 11.19 11.01 9.90 9.41 9.27 8.08 7.44 7.26 7.10 6.99 6.97 5.67 5.63 5.22 5.15 0.88 0.84 0.84 0.72 0.66 0.64 0.62
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
98.00 96.00 94.00 92.00 90.00 88.00 86.00 84.00 82.00 80.00 78.00 76.00 74.00 72.00 70.00 68.00 66.00 64.00 62.00 60.00 58.00 56.00 54.00 52.00 50.00 48.00 46.00 44.00 42.00 40.00 38.00 36.00 34.00 32.00 30.00 28.00 26.00 24.00 22.00 20.00 18.00 16.00 14.00 12.00 10.00 8.00 6.00 4.00 2.00 0.00
_________________________________________________________________________________________________________
Belgium Iceland the United Kingdom Estonia Belarus Slovakia Russian Federation Lithuania Vatican City Italy Germany Ireland France Spain Slovenia Sweden Faroe Islands Luxembourg Norway Finland Austria Switzerland San Marino Guernsey Jersey Liechtenstein Portugal Netherlands Cyprus Hungary Ukraine Gibraltar Georgia Poland Denmark Moldova Monaco Kazakhstan Bulgaria Andorra Greece Malta Isle of Man Czech Republic Latvia Croatia Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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©2007 Icon Group International, Inc.
Financial Indicators
3.7 3.7.1
122
PRODUCTIVITY IN GERMANY: LIABILITY-LABOR RATIOS Overview
In this chapter we consider the liability-labor ratios of companies operating in Germany benchmarked against global averages for computer programming, data processing and computer related services. For ratios where there are large deviations between Germany and the benchmarks, graphics are provided (sometimes referred to as a “gap” analysis). Then the distribution of productivity ratios is presented in the form of ranks and percentiles. Certain key liabilitylabor ratios are highlighted for computer programming, data processing and computer related services across countries in the comparison group. Definitions of liability statement terms are given in Chapter 3. In the case of liability-labor ratios, this report maintains comparability over time and across countries by using a common currency (the US dollar) and relates each measure to a “per employee basis”. Ratios are projected using raw financial statistics and, as ratios, are therefore comparable. Given a country’s human resource ratios, the resulting figures are benchmarked across regional and global averages. I then report the larger liability-labor ratio gaps for computer programming, data processing and computer related services that Germany has vis-à-vis the worldwide average. Again, a gap need not be a bad sign. Rather, it is simply a substantial difference that might merit further attention or signal a firm’s relative incentive to invest locally. All figures are projections, so due caution is required.
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Financial Indicators
3.7.2
123
Liability to Labor: Outlook
The following tables and graphs are prepared using the methodology described at the beginning of this section. All units are in thousands of US dollars per employee. All figures are current-year projections for computer programming, data processing and computer related services in Germany based on latest financial results available. Labor-liability Ratios ($k/employee) Germany Europe World Avg. _________________________________________________________________________________________________________
Accounts Payable Short Term Debt & Current Portion of Long Term Debt Accrued Payroll Income Taxes Payable Other Current Liabilities Current Liabilities - Total Long Term Debt Long Term Debt Excluding Capitalized Leases Capitalized Lease Obligations Provision For Risks and Charges Deferred Income Deferred Taxes Deferred Taxes - Credit Deferred Taxes - Debit Other Liabilities Total Liabilities Non-Equity Reserves Minority Interest Common Equity Common Stock Capital Surplus Other Appropriated Reserves Unappropriated Reserves Retained Earnings Unrealized Foreign Exchange Gain/Loss Unrealized Gain/Loss on Marketable Securities Treasury Stock Total Liabilities & Shareholders Equity
14.51 28.09 3.38 3.88 19.02 43.56 30.65 6.88 24.38 9.70 2.49 1.03 11.75 7.16 22.18 118.03 0.05 0.96 148.15 31.02 100.70 8.87 -3.06 26.90 -0.36 -0.01 1.18 267.10
28.34 160.76 4.30 5.29 48.20 86.35 165.53 163.53 2.03 8.98 3.12 0.60 13.41 3.95 40.18 433.23 0.09 5.47 183.94 62.94 94.91 20.77 11.98 33.84 -0.56 -0.35 3.38 616.54
15.22 61.14 1.80 2.24 27.40 64.32 53.27 52.46 0.83 2.99 1.19 -0.10 3.52 2.65 19.63 175.73 1.89 9.66 116.84 50.88 49.00 8.23 8.63 16.79 -0.07 1.30 2.68 302.73
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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©2007 Icon Group International, Inc.
Financial Indicators
3.7.3
124
Liability and Equity to Labor: International Gaps
The following graphics summarize for computer programming, data processing and computer related services the large labor-liability gaps between firms operating in Germany and the world average. A gap cannot necessarily be interpreted as a positive or negative reflection on performance. Gaps may signal areas of specialization, market focus, or expertise. More contextual information is required to fully interpret these gaps. The gaps highlighted here are simply those that are large.
Gap: Short Term Debt & Current Portion of Long Term Debt ($k/employee) 200
160.76
150 100 50
61.14 28.09
0 -33.05
-50 Germ any
Europe
World Average
Gap
Gap: Current Liabilities - Total ($k/employee) 100 80 60 40 20 0 -20 -40
86.35 64.32 43.56
-20.76 Germ any
Europe
World Average
Gap
Gap: Long Term Debt ($k/employee) 200
165.53
150 100 50
53.27
30.65
0
-22.62
-50 Germ any
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Europe
World Average
Gap
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Financial Indicators
125
Gap: Long Term Debt Excluding Capitalized Leases ($k/employee) 200
163.53
150 100
52.46
50
6.88
0 -45.58 Gap
-50 Germ any
Europe
World Average
Gap: Capitalized Lease Obligations ($k/employee) 25
24.38
23.55
20 15 10 5
2.03
0.83
0 Germ any
Europe
World Average
Gap
Gap: Total Liabilities ($k/employee) 500
433.23
400 300 200
175.73
118.03
100 0
-57.7
-100 Germ any
Europe
World Average
Gap
Gap: Common Equity ($k/employee) 183.94
200 150
148.15 116.84
100 31.31
50 0 Germ any
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Europe
World Average
Gap
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Financial Indicators
126
Gap: Common Stock ($k/employee) 80
62.94
60 40
50.88
31.02
20 0 -20 Germ any
Europe
-19.86 Gap
World Average
Gap: Capital Surplus ($k/employee) 120 100
100.7
94.91
80 49
60
51.7
40 20 0 Germ any
Europe
World Average
Gap
Gap: Unappropriated Reserves ($k/employee) 15
11.98 8.63
10 5
3.06
0 -5
-5.57
-10 Germ any
Europe
World Average
Gap
Gap: Total Liabilities & Shareholders Equity ($k/employee) 800
616.54
600 400
302.73
267.1
200 0
-35.63
-200 Germ any
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Europe
World Average
Gap
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Financial Indicators
3.7.4
127
Key Percentiles and Rankings
We now consider the distribution of liability-labor ratios using ranks and percentiles across . What percent of countries have a value lower or higher than Germany (what is the indicator's rank or percentile)? The table below answers this question with respect to liability-labor ratios. The ranks and percentiles indicate, from highest to lowest, where a value falls within the distribution of all countries considered in the global benchmark (the number of countries in the benchmark per line item may vary, as indicated in the Rank). Again, a high or low figure does not necessarily indicate good or bad performance or productivity. After the summary table below, a few key liabilitylabor ratios are highlighted in additional tables. Liability Structure ($k/employee)
Germany
Rank of Total
Percentile
14.51 28.09 3.38 3.88 19.02 43.56 30.65 6.88 24.38 9.70 2.49 1.03 11.75 7.16 22.18 118.03 0.05 0.96 148.15 31.02 100.70 8.87 -3.06 26.90 -0.36 -0.01 1.18 267.10
28 of 47 22 of 52 14 of 26 16 of 41 25 of 52 32 of 52 17 of 52 37 of 52 2 of 30 10 of 33 12 of 21 10 of 44 5 of 23 10 of 27 12 of 48 21 of 53 14 of 18 25 of 45 20 of 53 29 of 50 12 of 44 26 of 50 33 of 33 22 of 51 20 of 29 4 of 7 12 of 22 20 of 53
40.43 57.69 46.15 60.98 51.92 38.46 67.31 28.85 93.33 69.70 42.86 77.27 78.26 62.96 75.00 60.38 22.22 44.44 62.26 42.00 72.73 48.00 0.00 56.86 31.03 42.86 45.45 62.26
_________________________________________________________________________________________________________
Accounts Payable Short Term Debt & Current Portion of Long Term Debt Accrued Payroll Income Taxes Payable Other Current Liabilities Current Liabilities - Total Long Term Debt Long Term Debt Excluding Capitalized Leases Capitalized Lease Obligations Provision For Risks and Charges Deferred Income Deferred Taxes Deferred Taxes - Credit Deferred Taxes - Debit Other Liabilities Total Liabilities Non-Equity Reserves Minority Interest Common Equity Common Stock Capital Surplus Other Appropriated Reserves Unappropriated Reserves Retained Earnings Unrealized Foreign Exchange Gain/Loss Unrealized Gain/Loss on Marketable Securities Treasury Stock Total Liabilities & Shareholders Equity
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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Financial Indicators
128
Accounts Payable Countries
Value ($K/employee)
Rank
Percentile
79.99 72.08 54.50 48.59 48.46 39.34 30.41 29.76 29.51 26.12 23.91 23.78 22.69 22.08 22.02 20.84 20.83 20.29 19.36 17.97 17.83 17.38 16.89 15.67 14.51 13.53 13.27 12.97 9.57 9.44 9.42 7.83 7.03 6.99 6.76 4.55 3.22 3.07 2.79 1.42
1 3 4 5 6 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 26 27 28 29 30 31 34 35 36 37 38 39 40 41 42 43 44 45
97.87 93.62 91.49 89.36 87.23 82.98 80.85 78.72 76.60 74.47 72.34 70.21 68.09 65.96 63.83 61.70 59.57 57.45 55.32 53.19 51.06 48.94 44.68 42.55 40.43 38.30 36.17 34.04 27.66 25.53 23.40 21.28 19.15 17.02 14.89 12.77 10.64 8.51 6.38 4.26
Region
_________________________________________________________________________________________________________
South Korea Russian Federation Italy Turkey Mexico Japan Argentina Switzerland Hungary Greece Singapore Belgium Canada Malaysia South Africa France Spain Philippines the United Kingdom Australia Portugal China Poland Hong Kong Germany Luxembourg Thailand USA Denmark New Zealand Ireland Israel Norway Netherlands Sweden Finland Brazil Chile India Indonesia
Asia Europe Europe the Middle East Latin America Asia Latin America Europe Europe Europe Asia Europe North America Asia Africa Europe Europe Asia Europe Oceana Europe Asia Europe Asia Europe Europe Asia North America Europe Oceana Europe the Middle East Europe Europe Europe Europe Latin America Latin America Asia Asia
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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©2007 Icon Group International, Inc.
Financial Indicators
129
Accounts Payable (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
77.11 73.60 73.43 72.08 71.91 54.95 54.50 46.17 42.37 41.18 39.72 29.76 29.51 27.77 26.54 26.12 25.23 24.84 24.20 23.89 23.78 23.18 20.84 20.83 19.55 19.36 17.83 17.06 16.89 15.18 15.02 14.61 14.58 14.51 13.53 13.10 9.77 9.57 9.42 7.03 6.99 6.76 4.55
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43
97.67 95.35 93.02 90.70 88.37 86.05 83.72 81.40 79.07 76.74 74.42 72.09 69.77 67.44 65.12 62.79 60.47 58.14 55.81 53.49 51.16 48.84 46.51 44.19 41.86 39.53 37.21 34.88 32.56 30.23 27.91 25.58 23.26 20.93 18.60 16.28 13.95 11.63 9.30 6.98 4.65 2.33 0.00
_________________________________________________________________________________________________________
Estonia Belarus Slovakia Russian Federation Lithuania Vatican City Italy Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Switzerland Hungary Liechtenstein Ukraine Greece Gibraltar Georgia Malta Isle of Man Belgium Monaco France Spain Slovenia the United Kingdom Portugal Cyprus Poland Moldova Faroe Islands Kazakhstan Bulgaria Germany Luxembourg Iceland Andorra Denmark Ireland Norway Netherlands Sweden Finland
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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Financial Indicators
130
Current Liabilities - Total Countries
Value ($K/employee)
Rank
Percentile
256.43 253.01 252.32 231.07 210.91 147.37 110.01 97.29 89.81 80.58 80.51 80.36 72.71 70.33 68.35 67.81 67.78 63.86 61.07 59.36 52.32 51.76 50.07 47.69 47.16 47.08 45.62 43.91 43.56 42.94 36.77 34.19 34.19 30.73 29.80 27.71 27.60 27.32 26.80 26.36 23.86 11.25 9.07 8.27
1 2 3 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 23 24 25 26 27 28 29 30 31 32 33 34 35 36 38 39 41 42 43 44 45 46 48 49 50
98.08 96.15 94.23 88.46 86.54 84.62 82.69 80.77 78.85 76.92 75.00 73.08 71.15 69.23 67.31 65.38 63.46 61.54 59.62 55.77 53.85 51.92 50.00 48.08 46.15 44.23 42.31 40.38 38.46 36.54 34.62 32.69 30.77 26.92 25.00 21.15 19.23 17.31 15.38 13.46 11.54 7.69 5.77 3.85
Region
_________________________________________________________________________________________________________
South Korea Turkey Mexico Russian Federation Taiwan Greece China Italy Japan France Israel Peru Spain Belgium Argentina the United Kingdom Hong Kong Finland USA Switzerland Portugal Austria Hungary Australia Sweden Canada Singapore Malaysia Germany Norway Thailand Denmark Poland South Africa Ireland Brazil Netherlands Philippines Czech Republic Chile Luxembourg New Zealand India Indonesia
Asia the Middle East Latin America Europe Asia Europe Asia Europe Asia Europe the Middle East Latin America Europe Europe Latin America Europe Asia Europe North America Europe Europe Europe Europe Oceana Europe North America Asia Asia Europe Europe Asia Europe Europe Africa Europe Latin America Europe Asia Europe Latin America Europe Oceana Asia Asia
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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©2007 Icon Group International, Inc.
Financial Indicators
131
Current Liabilities - Total (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
247.20 240.39 235.93 235.39 231.07 230.53 220.61 214.40 206.82 147.37 136.59 134.79 98.08 97.29 80.58 72.71 70.33 70.14 68.26 67.81 65.00 63.86 61.70 59.36 55.40 52.32 51.76 51.27 50.09 50.07 49.98 49.98 47.16 45.02 44.24 43.56 42.94 42.81 42.15 34.19 34.19 30.74 29.80 29.58 29.52 27.60 26.80 25.44 25.43 23.86 11.65
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Estonia Romania Belarus Slovakia Russian Federation Lithuania Bosnia & Herzegovina Macedonia Serbia & Montenegro Greece Malta Isle of Man Vatican City Italy France Spain Belgium Albania Slovenia the United Kingdom Faroe Islands Finland Iceland Switzerland Liechtenstein Portugal Austria San Marino Cyprus Hungary Guernsey Jersey Sweden Ukraine Monaco Germany Norway Gibraltar Georgia Denmark Poland Moldova Ireland Kazakhstan Bulgaria Netherlands Czech Republic Latvia Croatia Luxembourg Andorra
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
132
Long Term Debt Countries
Value ($K/employee)
Rank
Percentile
1555.05 849.06 668.91 643.27 641.52 269.94 224.71 118.04 61.14 59.93 54.83 48.57 37.82 35.41 30.65 25.04 19.48 17.73 17.61 17.55 16.01 15.81 15.16 14.48 13.78 11.20 10.85 10.83 8.94 8.18 8.04 7.48 6.32 5.77 5.58 5.54 5.49 4.39 3.81 3.58 3.38 2.30 0.88 0.38
1 2 3 4 5 7 8 9 10 11 12 13 15 16 17 18 19 21 22 23 24 25 26 27 28 31 32 33 35 36 37 38 39 40 41 42 43 45 47 48 49 50 51 52
98.08 96.15 94.23 92.31 90.38 86.54 84.62 82.69 80.77 78.85 76.92 75.00 71.15 69.23 67.31 65.38 63.46 59.62 57.69 55.77 53.85 51.92 50.00 48.08 46.15 40.38 38.46 36.54 32.69 30.77 28.85 26.92 25.00 23.08 21.15 19.23 17.31 13.46 9.62 7.69 5.77 3.85 1.92 0.00
Region
_________________________________________________________________________________________________________
Portugal Denmark Italy Turkey Mexico Ireland Pakistan Japan USA France Peru Greece Australia the United Kingdom Germany Argentina South Korea New Zealand Norway Russian Federation Thailand Poland Taiwan Spain Belgium Finland Switzerland Philippines Austria Canada China Luxembourg Netherlands Brazil South Africa Indonesia Chile Israel Sweden Hong Kong Singapore Malaysia Hungary India
Europe Europe Europe the Middle East Latin America Europe the Middle East Asia North America Europe Latin America Europe Oceana Europe Europe Latin America Asia Oceana Europe Europe Asia Europe Asia Europe Europe Europe Europe Asia Europe North America Asia Europe Europe Latin America Africa Asia Latin America the Middle East Europe Asia Asia Asia Europe Asia
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
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Financial Indicators
133
Long Term Debt (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
1555.05 1488.53 849.06 674.32 668.91 611.20 560.89 545.12 525.84 269.94 61.77 59.93 48.57 47.86 45.02 44.42 35.41 30.65 18.78 18.36 17.92 17.88 17.61 17.55 17.51 15.81 14.48 14.21 13.78 13.68 13.65 13.59 11.20 10.85 10.12 8.94 8.86 8.64 8.64 7.48 6.32 3.81 3.44 3.28 0.88 0.79 0.75 0.74
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48
97.92 95.83 93.75 91.67 89.58 87.50 85.42 83.33 81.25 79.17 77.08 75.00 72.92 70.83 68.75 66.67 64.58 62.50 60.42 58.33 56.25 54.17 52.08 50.00 47.92 45.83 43.75 41.67 39.58 37.50 35.42 33.33 31.25 29.17 27.08 25.00 22.92 20.83 18.75 16.67 14.58 12.50 10.42 8.33 6.25 4.17 2.08 0.00
_________________________________________________________________________________________________________
Portugal Cyprus Denmark Vatican City Italy Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Ireland Iceland France Greece Albania Malta Isle of Man the United Kingdom Germany Estonia Andorra Belarus Slovakia Norway Russian Federation Lithuania Poland Spain Moldova Belgium Kazakhstan Bulgaria Slovenia Finland Switzerland Liechtenstein Austria San Marino Jersey Guernsey Luxembourg Netherlands Sweden Faroe Islands Monaco Hungary Ukraine Gibraltar Georgia
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
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Financial Indicators
134
Total Liabilities Countries
Value ($K/employee)
Rank
Percentile
3388.16 2074.26 1427.76 1423.87 1074.20 659.02 471.27 461.41 342.82 283.29 255.28 233.01 207.99 144.42 135.91 122.90 120.03 118.49 118.03 109.29 95.51 93.87 93.10 87.79 87.32 76.82 76.23 61.37 60.28 58.33 56.40 54.11 50.95 48.48 48.46 39.21 36.74 36.67 36.14 35.46 33.98 33.74 30.88 14.41 9.44
1 2 3 4 6 7 8 9 10 11 13 14 15 16 17 18 19 20 21 22 25 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 49 50 53
98.11 96.23 94.34 92.45 88.68 86.79 84.91 83.02 81.13 79.25 75.47 73.58 71.70 69.81 67.92 66.04 64.15 62.26 60.38 58.49 52.83 49.06 47.17 45.28 43.40 41.51 39.62 37.74 35.85 33.96 32.08 30.19 28.30 26.42 24.53 22.64 20.75 18.87 16.98 15.09 13.21 11.32 7.55 5.66 0.00
Region
_________________________________________________________________________________________________________
Portugal Italy Turkey Mexico Denmark Pakistan Japan Greece Ireland South Korea Russian Federation Taiwan France USA Peru Thailand the United Kingdom China Germany Hong Kong Spain Argentina Belgium Australia Israel Finland Switzerland Norway Austria Canada Sweden Singapore Hungary Poland Malaysia Philippines Luxembourg Netherlands South Africa Brazil Czech Republic Chile New Zealand Indonesia India
Europe Europe the Middle East Latin America Europe the Middle East Asia Europe Europe Asia Europe Asia Europe North America Latin America Asia Europe Asia Europe Asia Europe Latin America Europe Oceana the Middle East Europe Europe Europe Europe North America Europe Asia Europe Europe Asia Asia Europe Europe Africa Latin America Europe Latin America Oceana Asia Asia
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
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Financial Indicators
135
Total Liabilities (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
3388.16 3243.22 2091.04 2074.26 1356.56 1244.91 1209.90 1167.10 1074.20 461.41 427.65 422.02 342.82 273.10 260.65 260.06 255.28 254.69 207.99 145.91 120.03 118.64 118.03 104.80 95.51 93.10 89.66 76.82 76.23 71.13 61.37 60.28 59.71 58.22 58.22 56.40 52.48 50.95 48.48 45.81 43.59 43.56 42.89 41.95 41.87 36.74 36.67 33.98 32.25 32.24 31.98
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Portugal Cyprus Vatican City Italy Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Denmark Greece Malta Isle of Man Ireland Estonia Belarus Slovakia Russian Federation Lithuania France Iceland the United Kingdom Albania Germany Faroe Islands Spain Belgium Slovenia Finland Switzerland Liechtenstein Norway Austria San Marino Jersey Guernsey Sweden Monaco Hungary Poland Ukraine Moldova Gibraltar Georgia Kazakhstan Bulgaria Luxembourg Netherlands Czech Republic Latvia Croatia Andorra
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
136
Common Equity Countries
Value ($K/employee)
Rank
Percentile
565.29 509.32 460.40 459.14 446.53 405.87 367.83 331.46 275.05 271.02 231.33 206.12 191.46 191.23 169.36 161.58 148.89 148.15 145.56 124.17 116.27 112.97 95.62 95.16 87.45 82.94 82.76 82.24 80.45 77.78 70.09 69.00 66.63 61.33 58.13 46.57 38.56 38.10 37.13 37.12 34.14 28.96 22.37 17.50 16.65
1 2 3 4 5 7 8 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 34 35 37 38 40 41 43 44 45 46 48 49 51 52 53
98.11 96.23 94.34 92.45 90.57 86.79 84.91 81.13 79.25 77.36 75.47 73.58 71.70 69.81 67.92 66.04 64.15 62.26 60.38 58.49 56.60 54.72 52.83 50.94 49.06 47.17 45.28 43.40 41.51 39.62 35.85 33.96 30.19 28.30 24.53 22.64 18.87 16.98 15.09 13.21 9.43 7.55 3.77 1.89 0.00
Region
_________________________________________________________________________________________________________
Greece Portugal Turkey Mexico Israel Hong Kong South Korea Russian Federation Denmark Pakistan Italy Taiwan Canada Japan USA Australia New Zealand Germany China France Ireland Switzerland the United Kingdom Singapore Thailand Malaysia Belgium Finland Sweden Hungary Philippines Norway Argentina Peru Czech Republic Spain Netherlands Poland India Indonesia Luxembourg Austria South Africa Brazil Chile
Europe Europe the Middle East Latin America the Middle East Asia Asia Europe Europe the Middle East Europe Asia North America Asia North America Oceana Oceana Europe Asia Europe Europe Europe Europe Asia Asia Asia Europe Europe Europe Europe Asia Europe Latin America Latin America Europe Europe Europe Europe Asia Asia Europe Europe Africa Latin America Latin America
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
137
Common Equity (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
565.29 523.93 517.03 509.32 487.54 437.44 401.44 390.15 389.19 376.35 354.60 338.43 337.66 331.46 330.68 275.05 233.20 231.33 171.09 154.19 148.15 124.17 116.27 112.97 105.42 95.62 92.28 82.76 82.24 80.45 77.78 69.94 69.00 66.50 65.48 58.13 55.17 55.15 53.53 46.57 43.72 38.56 38.10 34.26 34.14 32.97 32.91 28.96 28.68 27.96 27.96
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Greece Malta Isle of Man Portugal Cyprus Romania Bosnia & Herzegovina Macedonia Faroe Islands Serbia & Montenegro Estonia Belarus Slovakia Russian Federation Lithuania Denmark Vatican City Italy Iceland Andorra Germany France Ireland Switzerland Liechtenstein the United Kingdom Monaco Belgium Finland Sweden Hungary Ukraine Norway Gibraltar Georgia Czech Republic Latvia Croatia Albania Spain Slovenia Netherlands Poland Moldova Luxembourg Kazakhstan Bulgaria Austria San Marino Jersey Guernsey
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
138
Retained Earnings Countries
Value ($K/employee)
Rank
Percentile
290.98 240.17 122.69 122.35 75.52 68.22 62.95 57.10 51.44 45.59 43.69 36.55 35.38 31.48 30.05 28.12 27.08 27.03 26.98 26.90 26.49 25.96 22.81 18.97 17.67 15.64 15.12 13.04 11.71 11.24 10.63 10.22 9.99 9.56 8.76 7.60 6.59 6.36 6.30 2.54 1.35 0.54 0.01
1 2 3 4 6 7 8 9 10 11 12 13 14 15 16 17 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 38 40 42 43 44 47 48 49 51
98.04 96.08 94.12 92.16 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 25.49 21.57 17.65 15.69 13.73 7.84 5.88 3.92 0.00
Region
_________________________________________________________________________________________________________
Hong Kong Israel Turkey Mexico Portugal Japan USA Denmark France Canada Switzerland Taiwan Finland New Zealand South Korea the United Kingdom Russian Federation Norway Italy Germany Singapore Ireland Belgium Netherlands Australia Malaysia Spain South Africa Sweden Czech Republic Thailand Argentina Poland Greece Philippines India Austria Indonesia Luxembourg Hungary China Peru Pakistan
Asia the Middle East the Middle East Latin America Europe Asia North America Europe Europe North America Europe Asia Europe Oceana Asia Europe Europe Europe Europe Europe Asia Europe Europe Europe Oceana Asia Europe Africa Europe Europe Asia Latin America Europe Europe Asia Asia Europe Asia Europe Europe Asia Latin America the Middle East
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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Financial Indicators
139
Retained Earnings (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
279.02 116.57 106.98 103.97 100.29 75.52 72.29 63.60 57.10 51.44 43.69 40.77 35.38 32.60 28.97 28.12 27.65 27.58 27.20 27.08 27.03 27.01 26.98 26.90 25.96 25.69 22.81 18.97 15.12 14.20 11.71 11.24 10.67 10.66 9.99 9.56 8.98 8.86 8.74 8.65 8.63 6.59 6.53 6.36 6.36 6.30 2.54 2.29 2.17 2.14 0.47
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Faroe Islands Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Portugal Cyprus Iceland Denmark France Switzerland Liechtenstein Finland Andorra Estonia the United Kingdom Belarus Slovakia Vatican City Russian Federation Norway Lithuania Italy Germany Ireland Monaco Belgium Netherlands Spain Slovenia Sweden Czech Republic Latvia Croatia Poland Greece Moldova Malta Isle of Man Kazakhstan Bulgaria Austria San Marino Guernsey Jersey Luxembourg Hungary Ukraine Gibraltar Georgia Albania
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
3.8 3.8.1
140
PRODUCTIVITY IN GERMANY: INCOME-LABOR RATIOS Overview
In this chapter we consider the income-labor ratios for computer programming, data processing and computer related services in Germany benchmarked against global averages. For ratios where there are large deviations between the average firm operating in Germany and the benchmarks, graphics are provided (sometimes referred to as a “gap” analysis). Then the distribution of ratios is presented in the form of ranks and percentiles. Certain key income-labor ratios are highlighted across countries in the comparison group. In the case of income-labor ratios, this report maintains comparability over time and across countries by using a common currency (the US dollar) and relates each measure to a “per employee basis”. Ratios are projected using raw financial statistics and, as ratios, are therefore comparable. Given a country’s human resource ratios, the resulting figures are benchmarked across regional and global averages. We then report the larger income-labor ratio gaps for computer programming, data processing and computer related services that Germany has vis-à-vis the worldwide average. Again, a gap need not be a bad sign. Rather, it is simply a substantial difference that might merit further attention or signal a firm’s relative incentive to invest locally. All figures are projections, so due caution is required.
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Financial Indicators
3.8.2
141
Income to Labor: Outlook
The following tables and graphs are prepared using the methodology described at the beginning of this section. All units are in thousands of US dollars per employee. All figures are current-year projections for computer programming, data processing and computer related services in Germany based on latest financial results available. Labor-income Ratios ($k/employee) Germany Europe World Avg. _________________________________________________________________________________________________________
Net Sales or Revenues Cost of Goods Sold (Excluding Depreciation) Depreciation, Depletion & Amortization Gross Income Selling, General & Administrative Expenses Other Operating Expenses Operating Expenses - Total Operating Income Extraordinary Credit - Pretax Extraordinary Charge - Pretax Non-Operating Interest Income Pretax Equity In Earnings Other Income/Expense Net Earnings Before Interest and Taxes (EBIT) Interest Expense on Debt Pretax Income Income Taxes Current Domestic Income Tax Current Foreign Income Tax Deferred Domestic Income Tax Deferred Foreign Income Tax Minority Interest Discontinued Operations Net Income Before Extra Items/Prefer Dividends Extraordinary Items & Gain/Loss Sale Of Assets Net Income Before Preferred Dividends Net Income Available to Common
259.53 162.56 17.00 100.79 39.55 241.16 62.42 12.83 0.00 1.81 2.90 -0.68 5.62 23.51 4.16 17.53 7.25 5.78 1.51 2.38 0.12 0.25 -0.60 11.35 0.01 11.36 11.35
286.70 123.57 74.39 90.16 54.94 250.12 9.31 29.31 2.97 4.18 3.39 0.12 4.05 56.08 25.30 31.12 10.41 7.04 0.46 -0.15 -0.06 0.34 -0.01 20.12 0.02 20.14 20.12
166.86 73.37 37.39 57.43 27.51 146.51 3.30 20.94 0.82 0.94 1.96 0.00 1.93 32.89 12.09 21.05 5.46 2.70 0.14 -0.06 0.04 1.07 -0.01 14.59 -0.07 14.51 14.58
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
3.8.3
142
Income to Labor: Gaps
The following graphics summarize for computer programming, data processing and computer related services the large labor-income gaps between firms operating in Germany and the world average. A gap cannot necessarily be interpreted as a positive or negative reflection on performance. Gaps may signal areas of specialization, market focus, or expertise. More contextual information is required to fully interpret these gaps. The gaps highlighted here are simply those that are large.
Gap: Net Sales or Revenues ($k/employee) 300
259.53
286.7
250 200
166.86
150
92.67
100 50 0 Germ any
Europe
World Average
Gap
Gap: Cost of Goods Sold (Excluding Depreciation) ($k/employee) 200
162.56
150
123.57
100
73.37
89.19
50 0 Germ any
Europe
World Average
Gap
Gap: Depreciation, Depletion & Amortization ($k/employee) 74.39
80 60
37.39
40
17
20 0 -20
-20.39
-40 Germ any
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Europe
World Average
Gap
©2007 Icon Group International, Inc.
Financial Indicators
143
Gap: Gross Income ($k/employee) 120 100
100.79
90.16
80
57.43
60
43.36
40 20 0 Germ any
Europe
World Average
Gap
Gap: Selling, General & Administrative Expenses ($k/employee) 54.94
60 50 40
39.55 27.51
30 20
12.04
10 0 Germ any
Europe
World Average
Gap
Gap: Other Operating Expenses ($k/employee) 300 250
241.16
250.12
200
146.51
150
94.65
100 50 0 Germ any
Europe
World Average
Gap
Gap: Operating Expenses - Total ($k/employee) 80
62.42
59.12
60 40 20
9.31
3.3
0 Germ any
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Europe
World Average
Gap
©2007 Icon Group International, Inc.
Financial Indicators
144
Gap: Operating Income ($k/employee) 29.31
30
20.94 20
12.83
10 0 -8.11
-10 Germ any
Europe
World Average
Gap
Gap: Other Income/Expense Net ($k/employee) 6
5.62
5
4.05
4 3
3.69 1.93
2 1 0 Germ any
Europe
World Average
Gap
Gap: Earnings Before Interest and Taxes (EBIT) ($k/employee) 56.08
60 40
32.89 23.51
20 0
-9.38
-20 Germ any
Europe
World Average
Gap
Gap: Interest Expense on Debt ($k/employee) 30
25.3
20 10
12.09 4.16
0 -7.93
-10 Germ any
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Europe
World Average
Gap
©2007 Icon Group International, Inc.
Financial Indicators
3.8.4
145
Key Percentiles and Rankings
We now consider the distribution of income-labor ratios using ranks and percentiles across . What percent of countries have a value lower or higher than Germany (what is the ratio's rank or percentile)? The table below answers this question with respect to income-labor ratios. The ranks and percentiles indicate, from highest to lowest, where a value falls within the distribution of all countries considered in the global benchmark (the number of countries in the benchmark per line item may vary, as indicated in the Rank). Again, a high or low figure does not necessarily indicate good or bad performance or productivity. After the summary table below, a few key income-labor ratios are highlighted in additional tables. Income Structure ($k/employee)
Germany
Rank of Total
Percentile
259.53 162.56 17.00 100.79 39.55 241.16 62.42 12.83 0.00 1.81 2.90 -0.68 5.62 23.51 4.16 17.53 7.25 5.78 1.51 2.38 0.12 0.25 -0.60 11.35 0.01 11.36 11.35
17 of 53 11 of 48 13 of 53 13 of 51 18 of 44 13 of 50 1 of 43 26 of 53 27 of 29 20 of 32 17 of 48 26 of 27 11 of 53 22 of 53 23 of 53 24 of 53 12 of 53 15 of 41 3 of 14 1 of 37 3 of 9 16 of 42 5 of 5 24 of 53 3 of 8 23 of 53 24 of 53
67.92 77.08 75.47 74.51 59.09 74.00 97.67 50.94 6.90 37.50 64.58 3.70 79.25 58.49 56.60 54.72 77.36 63.41 78.57 97.30 66.67 61.90 0.00 54.72 62.50 56.60 54.72
_________________________________________________________________________________________________________
Net Sales or Revenues Cost of Goods Sold (Excluding Depreciation) Depreciation, Depletion & Amortization Gross Income Selling, General & Administrative Expenses Other Operating Expenses Operating Expenses - Total Operating Income Extraordinary Credit - Pretax Extraordinary Charge - Pretax Non-Operating Interest Income Pretax Equity In Earnings Other Income/Expense Net Earnings Before Interest and Taxes (EBIT) Interest Expense on Debt Pretax Income Income Taxes Current Domestic Income Tax Current Foreign Income Tax Deferred Domestic Income Tax Deferred Foreign Income Tax Minority Interest Discontinued Operations Net Income Before Extra Items/Prefer Dividends Extraordinary Items & Gain/Loss Sale Of Assets Net Income Before Preferred Dividends Net Income Available to Common
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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©2007 Icon Group International, Inc.
Financial Indicators
146
Cost of Goods Sold (Excluding Depreciation) Countries
Value ($K/employee)
Rank
Percentile
333.99 300.97 277.10 226.57 218.63 207.39 191.60 175.10 170.92 162.56 131.29 123.34 122.60 120.25 115.22 112.21 110.62 105.23 101.62 96.96 95.65 93.20 89.75 89.66 89.37 86.64 83.56 81.12 64.46 54.96 52.30 51.68 50.06 42.32 39.30 33.76 31.36 29.23 24.90 20.58 18.51
1 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 43 45 46
97.92 93.75 91.67 89.58 87.50 85.42 83.33 81.25 79.17 77.08 75.00 72.92 70.83 68.75 66.67 64.58 62.50 60.42 58.33 56.25 54.17 52.08 47.92 45.83 43.75 41.67 39.58 37.50 35.42 33.33 31.25 29.17 27.08 25.00 22.92 20.83 18.75 16.67 10.42 6.25 4.17
Region
_________________________________________________________________________________________________________
South Korea Russian Federation Switzerland Japan Ireland France Belgium Denmark Hungary Germany the United Kingdom Peru Luxembourg USA Canada Sweden Australia South Africa Hong Kong Italy Argentina Greece Norway Netherlands Singapore Spain Portugal China Finland Brazil Chile Poland Malaysia Czech Republic New Zealand Thailand India Pakistan Philippines Israel Indonesia
Asia Europe Europe Asia Europe Europe Europe Europe Europe Europe Europe Latin America Europe North America North America Europe Oceana Africa Asia Europe Latin America Europe Europe Europe Asia Europe Europe Asia Europe Latin America Latin America Europe Asia Europe Oceana Asia Asia the Middle East Asia the Middle East Asia
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
147
Cost of Goods Sold (Excluding Depreciation) (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
321.98 307.30 306.60 300.97 300.26 277.10 258.57 218.63 207.39 191.60 175.10 170.92 162.56 153.70 146.14 143.88 131.29 122.60 121.49 112.21 107.67 97.75 97.44 96.96 93.20 89.75 89.66 86.66 86.64 86.38 85.25 83.56 81.34 79.99 64.46 51.68 46.47 44.72 44.64 42.32 40.70 40.16 40.15
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43
97.67 95.35 93.02 90.70 88.37 86.05 83.72 81.40 79.07 76.74 74.42 72.09 69.77 67.44 65.12 62.79 60.47 58.14 55.81 53.49 51.16 48.84 46.51 44.19 41.86 39.53 37.21 34.88 32.56 30.23 27.91 25.58 23.26 20.93 18.60 16.28 13.95 11.63 9.30 6.98 4.65 2.33 0.00
_________________________________________________________________________________________________________
Estonia Belarus Slovakia Russian Federation Lithuania Switzerland Liechtenstein Ireland France Belgium Denmark Hungary Germany Ukraine Gibraltar Georgia the United Kingdom Luxembourg Iceland Sweden Albania Vatican City Faroe Islands Italy Greece Norway Netherlands Monaco Spain Malta Isle of Man Portugal Slovenia Cyprus Finland Poland Moldova Kazakhstan Bulgaria Czech Republic Andorra Latvia Croatia
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
148
Selling, General & Administrative Expenses Countries
Value ($K/employee)
Rank
Percentile
132.01 131.65 118.50 105.94 99.59 98.95 80.81 79.79 68.68 67.64 60.64 56.49 55.54 50.91 44.11 39.55 38.31 32.97 32.25 26.71 24.99 24.75 24.04 23.13 21.54 19.77 19.01 18.54 18.47 18.29 15.02 12.59 11.68 11.12 11.07 3.74
1 2 4 5 6 7 8 9 10 11 12 13 14 16 17 18 19 20 21 22 23 24 25 26 27 28 30 32 34 35 37 39 40 41 42 43
97.73 95.45 90.91 88.64 86.36 84.09 81.82 79.55 77.27 75.00 72.73 70.45 68.18 63.64 61.36 59.09 56.82 54.55 52.27 50.00 47.73 45.45 43.18 40.91 38.64 36.36 31.82 27.27 22.73 20.45 15.91 11.36 9.09 6.82 4.55 2.27
Region
_________________________________________________________________________________________________________
Turkey Mexico Italy Denmark Israel Belgium France USA Canada Ireland Japan South Korea the United Kingdom Russian Federation Australia Germany Netherlands Switzerland Hong Kong Greece Peru Singapore Argentina Thailand Poland Indonesia South Africa China Sweden Norway India Malaysia Brazil Chile Luxembourg Philippines
the Middle East Latin America Europe Europe the Middle East Europe Europe North America North America Europe Asia Asia Europe Europe Oceana Europe Europe Europe Asia Europe Latin America Asia Latin America Asia Europe Asia Africa Asia Europe Europe Asia Asia Latin America Latin America Europe Asia
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
149
Selling, General & Administrative Expenses (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
125.43 119.46 118.50 115.11 111.87 107.91 105.94 98.95 80.81 80.60 67.64 55.54 54.46 51.98 51.86 50.91 50.79 39.55 38.31 32.97 30.93 30.76 26.71 24.76 24.43 24.00 21.81 21.54 19.37 18.64 18.61 18.47 18.29 11.07
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34
97.06 94.12 91.18 88.24 85.29 82.35 79.41 76.47 73.53 70.59 67.65 64.71 61.76 58.82 55.88 52.94 50.00 47.06 44.12 41.18 38.24 35.29 32.35 29.41 26.47 23.53 20.59 17.65 14.71 11.76 8.82 5.88 2.94 0.00
_________________________________________________________________________________________________________
Romania Vatican City Italy Bosnia & Herzegovina Macedonia Serbia & Montenegro Denmark Belgium France Iceland Ireland the United Kingdom Estonia Belarus Slovakia Russian Federation Lithuania Germany Netherlands Switzerland Faroe Islands Liechtenstein Greece Malta Isle of Man Monaco Albania Poland Moldova Kazakhstan Bulgaria Sweden Norway Luxembourg
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
150
Operating Expenses - Total Countries
Value ($K/employee)
Rank
Percentile
62.42 61.09 36.19 31.82 31.41 22.12 21.56 18.20 15.50 12.30 10.01 7.97 7.61 6.65 6.04 5.50 4.85 4.29 3.15 2.88 2.59 2.33 2.24 1.41 1.18 1.18 1.14 0.88 0.72 0.71 0.47 0.36 0.35 0.20 0.12 -0.16 -0.27 -5.19
1 2 3 4 5 6 7 8 9 10 11 13 14 15 16 17 18 19 21 22 23 25 26 27 29 30 31 33 34 35 36 37 38 39 40 41 42 43
97.67 95.35 93.02 90.70 88.37 86.05 83.72 81.40 79.07 76.74 74.42 69.77 67.44 65.12 62.79 60.47 58.14 55.81 51.16 48.84 46.51 41.86 39.53 37.21 32.56 30.23 27.91 23.26 20.93 18.60 16.28 13.95 11.63 9.30 6.98 4.65 2.33 0.00
Region
_________________________________________________________________________________________________________
Germany France Switzerland Australia Finland Portugal Ireland Spain Norway Netherlands Philippines Hong Kong the United Kingdom Singapore Sweden Peru Denmark South Africa USA Malaysia South Korea Russian Federation Italy Indonesia Poland Belgium India Argentina Luxembourg China Pakistan Brazil Chile Israel Japan Greece Canada Czech Republic
Europe Europe Europe Oceana Europe Europe Europe Europe Europe Europe Asia Asia Europe Asia Europe Latin America Europe Africa North America Asia Asia Europe Europe Asia Europe Europe Asia Latin America Europe Asia the Middle East Latin America Latin America the Middle East Asia Europe North America Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
151
Operating Expenses - Total (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
62.42 61.09 36.19 33.77 31.41 22.12 21.56 21.18 18.20 17.08 15.50 12.30 7.64 7.61 6.45 6.04 4.85 4.80 3.18 2.50 2.38 2.38 2.33 2.33 2.26 2.24 1.18 1.18 1.07 1.03 1.02 0.72 -0.14 -0.15 -0.16 -4.92 -4.92 -5.19
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38
97.37 94.74 92.11 89.47 86.84 84.21 81.58 78.95 76.32 73.68 71.05 68.42 65.79 63.16 60.53 57.89 55.26 52.63 50.00 47.37 44.74 42.11 39.47 36.84 34.21 31.58 28.95 26.32 23.68 21.05 18.42 15.79 13.16 10.53 7.89 5.26 2.63 0.00
_________________________________________________________________________________________________________
Germany France Switzerland Liechtenstein Finland Portugal Ireland Cyprus Spain Slovenia Norway Netherlands Faroe Islands the United Kingdom Monaco Sweden Denmark Albania Iceland Estonia Belarus Slovakia Russian Federation Lithuania Vatican City Italy Poland Belgium Moldova Kazakhstan Bulgaria Luxembourg Isle of Man Malta Greece Croatia Latvia Czech Republic
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
152
Operating Income Countries
Value ($K/employee)
Rank
Percentile
194.13 193.60 77.80 68.12 63.89 62.57 57.84 49.47 34.00 32.15 26.70 26.06 22.69 22.63 21.33 21.15 20.62 20.45 17.43 17.27 16.06 14.66 13.64 12.83 11.78 10.89 10.43 9.48 8.31 7.96 7.91 7.55 7.35 7.11 6.14 6.08 5.44 5.34 5.12 5.08 4.93 3.46 0.13 -0.14 -7.97
1 2 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 21 22 23 24 25 26 27 28 29 31 32 33 34 35 36 37 40 41 43 44 45 46 47 50 51 52 53
98.11 96.23 92.45 90.57 88.68 86.79 84.91 83.02 81.13 79.25 77.36 75.47 73.58 71.70 69.81 67.92 64.15 62.26 60.38 58.49 56.60 54.72 52.83 50.94 49.06 47.17 45.28 41.51 39.62 37.74 35.85 33.96 32.08 30.19 24.53 22.64 18.87 16.98 15.09 13.21 11.32 5.66 3.77 1.89 0.00
Region
_________________________________________________________________________________________________________
Turkey Mexico Hong Kong France Greece Israel Portugal Pakistan New Zealand Japan Argentina USA South Korea Taiwan Australia Denmark China Russian Federation Singapore Spain Ireland Canada the United Kingdom Germany Philippines Belgium Switzerland Peru Czech Republic Sweden Italy Thailand Netherlands Poland India Malaysia South Africa Brazil Indonesia Chile Finland Norway Austria Luxembourg Hungary
the Middle East Latin America Asia Europe Europe the Middle East Europe the Middle East Oceana Asia Latin America North America Asia Asia Oceana Europe Asia Europe Asia Europe Europe North America Europe Europe Asia Europe Europe Latin America Europe Europe Europe Asia Europe Europe Asia Asia Africa Latin America Asia Latin America Europe Europe Europe Europe Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
153
Operating Income (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
184.45 169.27 164.51 158.69 74.61 68.12 63.89 59.22 58.44 57.84 55.37 35.20 26.33 21.88 21.15 20.88 20.83 20.45 20.40 17.27 16.90 16.22 16.06 13.64 12.83 10.89 10.43 9.73 8.31 8.28 7.98 7.96 7.91 7.88 7.88 7.35 7.11 6.40 6.16 6.14 4.93 3.46 0.13 0.13 0.13 0.13 -0.14 -6.71 -6.81 -7.17 -7.97
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Faroe Islands France Greece Malta Isle of Man Portugal Cyprus Andorra Iceland Estonia Denmark Belarus Slovakia Russian Federation Lithuania Spain Monaco Slovenia Ireland the United Kingdom Germany Belgium Switzerland Liechtenstein Czech Republic Albania Vatican City Sweden Italy Latvia Croatia Netherlands Poland Moldova Kazakhstan Bulgaria Finland Norway Austria San Marino Jersey Guernsey Luxembourg Georgia Gibraltar Ukraine Hungary
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
154
Earnings Before Interest and Taxes (EBIT) Countries
Value ($K/employee)
Rank
Percentile
372.02 371.01 193.10 116.63 108.87 94.41 80.61 77.04 76.77 70.26 69.13 48.23 43.41 31.77 30.81 30.50 28.65 27.17 24.49 23.51 22.00 19.55 18.71 18.21 15.81 15.38 13.41 13.05 12.41 12.35 12.04 10.12 9.31 8.93 8.87 8.74 8.59 7.94 7.86 7.41 6.63 5.99 2.98 1.28 1.10
1 2 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 21 22 23 24 25 26 27 29 31 32 33 34 35 38 39 40 41 42 43 44 45 47 48 49 51 52 53
98.11 96.23 92.45 90.57 88.68 86.79 84.91 83.02 81.13 79.25 77.36 75.47 73.58 71.70 69.81 67.92 66.04 64.15 60.38 58.49 56.60 54.72 52.83 50.94 49.06 45.28 41.51 39.62 37.74 35.85 33.96 28.30 26.42 24.53 22.64 20.75 18.87 16.98 15.09 11.32 9.43 7.55 3.77 1.89 0.00
Region
_________________________________________________________________________________________________________
Turkey Mexico Portugal Denmark Pakistan Italy Hong Kong Israel France Ireland Greece Taiwan New Zealand Japan Argentina Australia USA South Korea Russian Federation Germany China Singapore Thailand Spain Peru the United Kingdom Switzerland Brazil Chile Philippines Czech Republic Belgium Finland Canada Netherlands Poland Sweden Indonesia Malaysia India South Africa Norway Hungary Austria Luxembourg
the Middle East Latin America Europe Europe the Middle East Europe Asia the Middle East Europe Europe Europe Asia Oceana Asia Latin America Oceana North America Asia Europe Europe Asia Asia Asia Europe Latin America Europe Europe Latin America Latin America Asia Europe Europe Europe North America Europe Europe Europe Asia Asia Asia Africa Europe Europe Europe Europe
_________________________________________________________________________________________________________
Source: Philip M. Parker, Professor, INSEAD, copyright 2004
www.icongrouponline.com
©2007 Icon Group International, Inc.
Financial Indicators
155
Earnings Before Interest and Taxes (EBIT) (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
353.47 324.38 315.25 304.10 193.10 184.84 116.63 95.18 94.41 77.29 76.77 70.26 69.13 64.07 63.23 44.95 28.95 26.20 25.00 24.95 24.49 24.43 23.51 18.96 18.21 17.09 15.38 13.80 13.41 12.52 12.04 11.43 11.43 10.12 9.31 8.87 8.74 8.59 7.86 7.56 7.55 5.99 2.98 2.68 2.55 2.51 1.28 1.27 1.24 1.24 1.10
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Portugal Cyprus Denmark Vatican City Italy Faroe Islands France Ireland Greece Malta Isle of Man Andorra Iceland Estonia Belarus Slovakia Russian Federation Lithuania Germany Monaco Spain Slovenia the United Kingdom Albania Switzerland Liechtenstein Czech Republic Latvia Croatia Belgium Finland Netherlands Poland Sweden Moldova Kazakhstan Bulgaria Norway Hungary Ukraine Gibraltar Georgia Austria San Marino Guernsey Jersey Luxembourg
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Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
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Pretax Income Countries
Value ($K/employee)
Rank
Percentile
188.49 187.98 79.83 76.03 70.35 62.51 55.50 51.51 42.51 40.67 28.95 26.97 25.74 25.55 25.44 24.37 24.30 20.94 20.60 18.86 18.74 17.53 16.26 13.66 11.72 11.60 11.57 11.37 8.08 7.77 7.30 7.26 7.23 7.22 6.65 6.57 6.38 4.38 4.38 4.09 3.89 3.82 2.39 0.28 0.21
1 2 4 5 6 7 8 9 10 11 12 13 14 15 16 18 19 20 21 22 23 24 25 26 27 28 29 31 34 35 36 37 38 39 41 42 43 45 46 47 48 49 51 52 53
98.11 96.23 92.45 90.57 88.68 86.79 84.91 83.02 81.13 79.25 77.36 75.47 73.58 71.70 69.81 66.04 64.15 62.26 60.38 58.49 56.60 54.72 52.83 50.94 49.06 47.17 45.28 41.51 35.85 33.96 32.08 30.19 28.30 26.42 22.64 20.75 18.87 15.09 13.21 11.32 9.43 7.55 3.77 1.89 0.00
Region
_________________________________________________________________________________________________________
Turkey Mexico Hong Kong Israel Portugal France Greece Pakistan New Zealand Taiwan Japan South Korea Italy Australia Denmark USA Russian Federation Argentina Ireland Singapore China Germany Spain Thailand Switzerland Philippines the United Kingdom Czech Republic Belgium Sweden India Finland Malaysia Indonesia Netherlands Canada Poland South Africa Norway Brazil Chile Peru Hungary Luxembourg Austria
the Middle East Latin America Asia the Middle East Europe Europe Europe the Middle East Oceana Asia Asia Asia Europe Oceana Europe North America Europe Latin America Europe Asia Asia Europe Europe Asia Europe Asia Europe Europe Europe Europe Asia Europe Asia Asia Europe North America Europe Africa Europe Latin America Latin America Latin America Europe Europe Europe
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Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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Financial Indicators
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Pretax Income (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
179.09 164.35 159.73 154.08 76.55 70.35 67.34 62.51 55.50 51.44 50.76 44.02 26.00 25.94 25.74 25.44 24.81 24.75 24.62 24.30 24.24 20.60 18.29 17.53 16.26 15.26 11.72 11.57 11.37 10.94 10.79 10.78 8.08 7.77 7.26 6.65 6.38 5.73 5.52 5.51 4.38 3.33 2.39 2.15 2.04 2.01 0.28 0.21 0.21 0.20 0.20
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
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Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Faroe Islands Portugal Cyprus France Greece Malta Isle of Man Andorra Estonia Vatican City Italy Denmark Belarus Slovakia Iceland Russian Federation Lithuania Ireland Monaco Germany Spain Slovenia Switzerland the United Kingdom Czech Republic Liechtenstein Latvia Croatia Belgium Sweden Finland Netherlands Poland Moldova Kazakhstan Bulgaria Norway Albania Hungary Ukraine Gibraltar Georgia Luxembourg Austria San Marino Jersey Guernsey
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Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
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Income Taxes Countries
Value ($K/employee)
Rank
Percentile
65.80 65.63 37.02 13.61 13.00 11.94 11.69 10.91 8.58 7.69 7.25 7.11 6.65 6.37 6.00 5.74 5.23 5.22 5.15 5.12 4.84 4.80 3.91 3.66 3.63 3.57 3.56 3.45 3.35 2.82 2.69 2.67 2.32 2.17 1.97 1.94 1.94 1.65 1.16 1.11 1.06 1.02 1.01 0.34 -0.30
1 2 4 5 6 7 8 9 10 11 12 13 14 15 17 18 19 20 21 22 23 24 26 28 29 30 31 32 33 35 36 37 38 39 40 41 42 44 47 48 49 50 51 52 53
98.11 96.23 92.45 90.57 88.68 86.79 84.91 83.02 81.13 79.25 77.36 75.47 73.58 71.70 67.92 66.04 64.15 62.26 60.38 58.49 56.60 54.72 50.94 47.17 45.28 43.40 41.51 39.62 37.74 33.96 32.08 30.19 28.30 26.42 24.53 22.64 20.75 16.98 11.32 9.43 7.55 5.66 3.77 1.89 0.00
Region
_________________________________________________________________________________________________________
Turkey Mexico Greece Japan Portugal Italy Israel New Zealand Hong Kong USA Germany Argentina South Korea Denmark Russian Federation Australia Ireland Czech Republic Belgium Taiwan France Thailand the United Kingdom Spain Philippines Sweden Switzerland Canada Singapore Finland Pakistan China Netherlands Poland Malaysia Indonesia South Africa Peru India Hungary Brazil Norway Chile Austria Luxembourg
the Middle East Latin America Europe Asia Europe Europe the Middle East Oceana Asia North America Europe Latin America Asia Europe Europe Oceana Europe Europe Europe Asia Europe Asia Europe Europe Asia Europe Europe North America Asia Europe the Middle East Asia Europe Europe Asia Asia Africa Latin America Asia Europe Latin America Europe Latin America Europe Europe
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Source: Philip M. Parker, Professor, INSEAD, copyright 2004
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Income Taxes (Computer Programming, Data Processing and Computer Related Services) Countries in Europe
Value ($K/employee)
Rank
Percentile
62.52 57.38 55.76 53.79 37.02 34.31 33.86 13.00 12.44 12.04 11.94 11.30 8.22 7.77 7.25 6.41 6.37 6.12 6.11 6.00 5.98 5.23 5.22 5.15 4.95 4.95 4.84 3.91 3.66 3.57 3.56 3.44 3.32 3.25 2.82 2.32 2.17 1.95 1.87 1.87 1.44 1.11 1.02 1.00 0.95 0.93 0.34 0.33 0.33 0.33 -0.30
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51
98.04 96.08 94.12 92.16 90.20 88.24 86.27 84.31 82.35 80.39 78.43 76.47 74.51 72.55 70.59 68.63 66.67 64.71 62.75 60.78 58.82 56.86 54.90 52.94 50.98 49.02 47.06 45.10 43.14 41.18 39.22 37.25 35.29 33.33 31.37 29.41 27.45 25.49 23.53 21.57 19.61 17.65 15.69 13.73 11.76 9.80 7.84 5.88 3.92 1.96 0.00
_________________________________________________________________________________________________________
Romania Bosnia & Herzegovina Macedonia Serbia & Montenegro Greece Malta Isle of Man Portugal Cyprus Vatican City Italy Andorra Faroe Islands Iceland Germany Estonia Denmark Belarus Slovakia Russian Federation Lithuania Ireland Czech Republic Belgium Latvia Croatia France the United Kingdom Spain Sweden Switzerland Slovenia Liechtenstein Monaco Finland Netherlands Poland Moldova Kazakhstan Bulgaria Albania Hungary Norway Ukraine Gibraltar Georgia Austria San Marino Guernsey Jersey Luxembourg
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Source: Philip M. Parker, Professor, INSEAD, copyright 2004 www.icongrouponline.com
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4 4.1
MACRO-ACCESSIBILITY IN GERMANY EXECUTIVE SUMMARY
The German economy is the world's third largest, and accounts for about one-third of the European Union's GDP. Germany is the United States' largest European trading partner and fifth largest global partner. Germany practices a "social market" economy that largely follows free-market principles but with a considerable degree of government regulation and generous social welfare protection. The German market, America's largest export market in Europe, has numerous attractive sectors, and remains an important component of any comprehensive European export strategy. For U.S. exporters, Germany holds a market advantage that few countries can match. More world-class trade events are held in Germany than any other location in Europe, and quite possibly in the world. As one example, CeBIT (computers and telecom) the world's largest trade event, draws over 750,000 visitors and 7,000 exhibitors annually, with significant participation from the Asia, Latin America, and Africa. Similar caliber events in many industrial sectors make Germany an international marketing crossroad, permitting U.S. exporters to cover German, European as well as global prospects in one location. A summary of major German trade events supported by the Commercial Service is noted in Section 13 of this document. U.S. investors at the same time can count on high levels of productivity, a highly skilled labor force, quality engineering, first-class infrastructure, and a location in the heart of Europe. However, as for any international location, investment considerations should be conducted with professional assistance and based on thorough analysis. Germans appreciate innovation and high technology, particularly in the consumer goods sectors. New solutions in the multi-media, high- tech and service areas that will help more Germans join the Internet generation offer great potential. U.S. products that offer cutting-edge technology such as computer software, electronic components, health care and medical devices, synthetic materials and automotive technology are especially highly regarded. Price will not always be the determining factor for the German buyer, especially for inputs in the intermediate stages of production, where the manufacturer cares deeply about his own product and service reputation. In approaching the German market, exporters should recognize that the market is as decentralized and diverse as the United States. Bavarian and Rhineland tastes, for example, differ markedly. An American company seeking sales in Germany is strongly advised to take into account such regional differences. Generally speaking, U.S. exporters who seek to support clients from a single European location, or directly from the United States are at a disadvantage given German and other European competitors who have the advantage of proximity. However, unique products, high quality products and service, or the right price may offset such factors. With the exception of the EU Common Agricultural Policy, Germany presents few formal barriers to U.S. trade or investment interests. Germany's regulations and bureaucratic procedures, however, can prove a baffling maze, blunting the enthusiasm of U.S. exporters and investors. While not discriminatory, government regulation is often complex and may offer a degree of protection to already-established local suppliers. Safety or environmental standards, not inherently discriminatory but sometimes zealously applied, can complicate access to the market for U.S. products. American companies interested in exporting to Germany should conduct thorough market research as well as identify relevant standards and obtain timely testing and certification. For U.S. exporters looking to market across the European Union, satisfying German standards may prove to be beneficial given that EU-wide standards are frequently based on German practice. Further information on Germany can be found at the U.S. Commercial Service Germany website http://www.buyusa.de/en. Information on other European markets can be found on the "Showcase Europe" homepage: http://www.buyusa.gov/europe. This is a comprehensive source for market research and business counseling information designed for U.S. exporters interested in the European marketplace.
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ECONOMIC FUNDAMENTALS AND DYNAMICS
Germany's strong post-war economic growth has afforded its citizens one of the highest standards of living in the world. At the same time, Germany supports one of the most comprehensive and generous social safety nets in the industrialized world. The German "social market" economy is based largely on free market principles, but critical labor, wage and regulatory decisions are the result of a consensus between government, business and labor. While the system has served Germany well and remains relatively popular, the German economy today faces serious issues including persistent slow growth, persistently high unemployment, high outstanding government debt, an increasing share of government revenues going for debt service payments, high tax rates, continued high net transfer payments to eastern Germany, high unit labor costs, and growing social security and non-wage labor costs. These problems and the resulting concerns over Germany's attractiveness as an investment site have underscored the need for changes in the government's economic, fiscal and social policy course, towards budget consolidation and structural reforms.
4.2.1
Social Security Reforms
The rapid aging of the German population will put enormous financial pressure on the public pay-as-you-go social security system. Absent major reform, an imminent sharp decline in the ratio of active workers to retirees will force the current system to raise employee and employer contributions or reduce benefits. Already the government has to fund from general tax revenues obligations for former East Germans who reached retirement age without ever contributing to the West German social security system. The government has therefore enacted pension reforms that contain limits to benefits from the public system. However, additional reform measures are needed to cut costs and keep the pension system sustainable.
4.2.2
Labor Market
The performance of the German labor market during the 1990s, measured by the level and growth of job creation and unemployment, was weaker than in most other comparable countries. The difficult situation in Eastern Germany was a major, but not the only, reason for this situation. in addition to lower-than-average workforce participation and levels of employment, the German labor market suffers from numerous structural problems. For example, the portion of long-term unemployed (i.e., over one year) is high, while the employment rate for low-skilled workers is low. Unemployment is particularly high among women, low-skilled and older workers, who are often "pushed" from the primary labor market into the social welfare system. Also, the relatively low level of flexibility in the German labor market is an important factor in Germany's employment picture. There are, of course, other significant factors, including macroeconomic issues. Comparatively strong protection against dismissals, coupled with strict regulation of fixed-term and temporary employment contracts protects a company's core work force, but hampers the transparency of the employment system and leads to segmentation of the labor market. This development has mainly affected young people and women, and increases the risk of long-term unemployment. in addition, factors such as limited acceptance of older workers, as well as "structural mismatches" in the supply and demand of skilled workers also contribute to Germany's persistently high unemployment. The ineffectiveness of Germany's various labor market support programs (too much emphasis on providing for the unemployed and too little emphasis on incentives for work) was another factor contributing to unemployment. While Germany's high non-wage labor costs have a clearly negative impact on employment, the effects of Germany's system of wage determination of multi-company, industry-wide contracts on the labor market are less clear. in order to adapt to the challenges of globalization, many of these contracts have been revised in recent years. They include not only highly flexible working time arrangements in nearly all industry sectors (including so-called corridor solutions in the chemical industry, for example, where workers may work longer or shorter hours than the regular
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37.5-hour workweek without additional costs for the employers), but also have introduced escape clauses for ailing companies (i.e., the metal industry in East Germany), lower entrance pay scales, and performance-based annual bonuses. The Master Agreement for the metal industry in Baden-Wuerttemberg, for example, gives 384 possibilities to deviate from the normal 35-hour week. The new BMW plant in Leipzig has a highly sophisticated working time regime, under which workers can work on Saturdays, longer hours, or consecutive shifts, etc. This means, in essence, the BMW plant can operate about 150 hours a week. Moreover, coverage under a collective agreement has been declining in recent years. in all of Germany, multicompany, industry-wide contracts cover about 43.4 percent of all firms; 5.3 percent are covered by a company-level agreement; and 51.3 percent are not covered at all. An East-West comparison shows that 66.6 percent of the firms in the East are not covered by a collective agreement vs. 47.5 percent of the companies in the West. Differentiated by workers covered by a collective agreement, the ratio of covered/uncovered workers is 73.6 vs. 26.4 percent for all of Germany. Again, the coverage is higher in the West than in the East (75.8 vs. 63.2 percent). Despite high unemployment, serious labor shortages exist in many high-skilled fields.
4.3
POLITICAL RISKS
Despite disagreements over the issue of Iraq, U.S.-German relations are deep and broad ranging, with strong ties in almost every level of the relationship. German-American political, economic, and security relationships have historically been based on close consultation and coordination at the most senior levels. There are positive indications that these relationships will continue to improve in the wake of differing approaches to Iraq. High-level visits regularly take place, and the United States and the FRG cooperate actively on a wide range of international issues. U.S. Government officials enjoy good access to policy- and decision-makers, and are able to raise issues directly affecting U.S. businesses in Germany. Maintaining economic growth and fostering the continued development of eastern Germany are economic priorities for the German government that also have political implications. The states of the former German Democratic Republic (East Germany) contain millions of voters, and the government is continuing its ongoing efforts to bring them up to the economic standards of western Germany as quickly as possible. Accordingly, a high priority is placed on financing eastern development, implying the likelihood of a flow of major project opportunities for years to come. In addition, Germany's political leadership also wants to promote Germany's competitiveness and various proposals are being considered to modernize the country's economic infrastructure. Since unification on October 3, 1990, Germany has placed special emphasis on improving its relations with its directly neighboring states as well as strengthening transatlantic relations. Recognizing that political stability is nurtured by economic prosperity, Germany has been one of the major sources of assistance to Central European and CIS states. Germany is a member of the European Union.
4.3.1
Basic Government Structure
Under the German Constitution, known as the Basic Law, the Federal Republic of German (FRG) is a parliamentary democracy with a bicameral legislature, an independent judiciary and executive power exercised by a Prime Minister whose title is Chancellor. The lower house of Parliament, the Bundestag, consists of deputies elected for a 4-year term. Members are elected through a mixture of a direct vote for constituency candidates and a second vote for party lists. The federal and state electoral laws stipulate that parties must receive at least five percent of the national vote (or at least three directly elected seats in federal elections) in order to be entitled to full proportional representation in the federal and state parliaments. One must be 18-years old to vote in Germany. www.icongrouponline.com
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The Federal President, whose duties as Chief of State are largely ceremonial, may be elected to two five-year terms. Executive power is exercised by the Chancellor who is elected by and responsible to the Bundestag. The Chancellor cannot be removed from office during a four-year term unless the Bundestag has agreed on a successor. The upper house, the Bundesrat, comprising 69 members, is composed of delegations from the 16 state governments. Each state has between three and six votes, depending on its population. The role of the Bundesrat is limited, but it can veto or engage in revision of legislation passed in the Bundestag when the proposed legislation would impose or affect the responsibilities of the states. Among these are matters relating to tax reform, law enforcement and the courts, culture and education, the environment, and social assistance.
4.4
MARKETING STRATEGIES
U.S. companies intending to export to Germany must take into account the commercial context. To a far greater degree than its European neighbors, Germany's population and industry are decentralized and evenly distributed. Major cities and businesses dot the countryside in a landscape that features no single business center. Often U.S. companies seem to seek to cover Europe from a single European base, or even through periodic visits from the United States. The German commercial customer at the same time expects to be able to pick up the telephone, talk to his or her dealer, and have replacement parts or service work immediately available. U.S. exporters should avoid appointing distributors with impossibly large geographic areas, without firm commitments regarding parts inventories or service capabilities, and without agreements on dealer mark-ups. Success in the German market, as elsewhere around the world, requires long-term commitment to market development and sales back-up, especially if U.S. companies are to overcome the geographic handicap with respect to European competitors. Germans at times perceive U.S. suppliers as being quick to defer processing an export order in favor of a subsequent domestic order, or to bypass a successful distributor to deal directly with his customer. Some German entrepreneurs with selective experience with U.S. companies are skeptical about their longterm commitment and after-sales support. U.S. firms entering Germany today are generally aware of the factors that make for a successful export relationship and are ready to establish a credible support network. However, U.S. firms should be ready to address any lingering doubts from prospective German clients/partners.
4.4.1
Services
Services are playing an increasingly important role for Germany's economy. in many studies and reports, the United States has been portrayed as a good example of a service-oriented economy, and many experts believe that a focus on these sectors will provide Germany with an opportunity to significantly reduce unemployment. Despite a still existing reluctance among the workforce, which is traditionally oriented towards manufacturing and industrial processes, growth potential for and the importance of the service sector is considerable. In many areas, the German government follows EU stipulations opening up service markets, such as telecommunications, postal services, the rail system or energy, which may offer potential for U.S., competition. Other sectors, such as the water industry or road haulage may appear to be in general open to competition, but do not at a first glance lend themselves easily to U.S. involvement. Currently, the German telecommunications and IT industries are facing adverse conditions. Due to the overall global downturn in this industry as well as the continued dominance of Deutsche Telekom AG (which itself has seen its share prices decline to an all-time low), many companies that have entered the market enthusiastically have unfortunately closed their doors.
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Even under better economic conditions, the situation of the services industry leaves room for improvement. U.S. companies considering entering the German services market should be aware that the still comparatively high tax rates despite modest cuts and complicated tax laws may constitute an obstacle to investors, although deductions, allowances and write-offs help to move effective tax rates to more internationally competitive levels.
4.4.2
Trade Fairs
No business visitor or company wishing to export to Germany can fail to note that trade fairs play a crucial role in marketing in this country, a role perhaps unique in the world. This is not too surprising when one considers that the trade fair movement was born in Germany in the Middle Ages and that, even today, a major portion of the truly world-class vertical fairs take place within Germany's borders, attracting buyers from around the world. During any given year, one or more major trade fairs will be staged in Germany for almost any product or service. Trade fairs thrive in Germany because they are occasions on which business is actively done, rather than serving simply as public relations venues. U.S. exhibitors at German fairs should bring their order books and be prepared to sell. While U.S. exhibitors and even visitors can often conclude transactions, all attendees can use the great German fairs to conduct market research, see what their worldwide competition is doing, and test pricing strategies. The German fairs should not be thought of as strictly venues for doing business in Germany. The major shows attract buyers from throughout the world, allowing U.S. exhibitors do business here with buyers from Europe, Asia, Africa, Latin America and even with other U.S. companies. The promotion of U.S. participation at German trade fairs is an essential part of "Showcase Europe", a field-driven initiative that is designed to pay tribute to the ongoing integration of a single Europe. "Showcase Europe" concentrates on the following sectors of strategic interest: •
Aerospace
•
Energy
•
Medical Equipment, including Drugs and Pharmaceuticals
•
Telecommunications and Information Technologies
•
Environmental Technologies and Equipment
•
Franchising
•
Travel and Tourism
At selected fairs, for example, U.S. Embassy staff offers U.S. companies a wide range of programs matching their interests with potential German business partners as well as with visitors from other European countries. "Showcase Europe" also focuses on advocacy on behalf of U.S. business interests and concentrates on further opening the markets in the above listed sectors to U.S. companies, including official U.S. government advocacy on behalf of American firms bidding on German procurement projects.
4.4.3
Advertising Options
In addition to exhibiting at a German trade fair, in most cases a strong factor in a broad-based marketing program. Regulation of advertising in Germany is a mix between basic rules and voluntary guidelines developed by the major industry associations. Legal rules were established at the beginning of the 20th century by the "Law Against Unfair Competition". Although it has been modified over time, this law continues to be valid today. in essence, this law allows competitors to bring suit if advertising "violates good manners".
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Many advertising practices that are common in the United States, such as offering premiums, are not allowed in Germany. Any planned advertising campaigns should be discussed with a potential business partner or an advertising agency in Germany. Following is the address of the German Association of Advertising Agencies: Gesamtverband Kommunikationsagenturen e.V. (German Association of Advertising Agencies) Friedensstr. 11 60311 Frankfurt a.M. Telephone: [49][69] 2560080 Telefax: [49][69] 236883 http://www.gwa.de/ There are numerous technical or specialized periodicals that deal with all aspects of technology and doing business in Germany. in addition, Germany has a well-developed array of newspapers and magazines, which offer the opportunity to gather information and advertise products and services.
4.4.4
Associations
Nearly all facets of doing business in Germany have a relevant industry or trade association and can often serve as a suitable point of contact when trying to establish a partnership.
4.4.5
Public Procurement
Selling to German government entities is not always an easy process. However, although there has been a delay in implementing all facets of the EU Utility Directive, in general, German government procurement is nondiscriminatory and ostensibly complies with the GATT Agreement on Government Procurement (the Procurement Code) and the European Community's procurement directives. That said, it is a major challenge to compete head-tohead with major German or other EU suppliers who have established long-term ties with purchasing entities.
4.4.6
Marketing to the New Federal States
While market conditions in the new and old federal states of the reunited Germany continue to converge impressively, U.S. exporters and potential investors should, nonetheless, be aware that the new federal states of eastern Germany still present, in certain respects, distinctive commercial opportunities and challenges. For instance, while promotion and investment assistance provided by the German Federal Government usually covers the entire territory of Germany, some programs and terms are more favorable in the new federal states as part of the government-led effort to transform these states of the former East Germany to a market economy. Additionally, at both the federal and state level there are investment grants, special depreciation and credit programs, and regional promotions, which apply specifically to the new federal states. One regional promotion initiative of particular interest to U.S. firms interested in market opportunities in the new federal states is the Industrial Investment Council of the New German States (IIC). Through extensive market research, the IIC has identified the distinctive commercial conditions which set eastern Germany apart as a favorable commercial destination for major U.S. investors as well as for U.S. exporters. Among some of the distinctive conditions which IIC's market research is highlighting for the new federal states are: wage and labor flexibility across
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the board; local flexibility in accommodating major infrastructure projects; technical, workforce, and niche R&D capabilities along with transportation logistics and distribution advantages; etc.
B2C 68 percent of Germans with Internet access realized at least one business transaction via the Internet. Favorite purchases are airline tickets, electronic devices, computer equipment, books, music CDs and DVDs. Primarily larger firms such as Amazon, Otto, Quelle, Tchibo, Conrad, and Ebay have increased their online sales. Retailers without "physical" retail stores or those lacking brand recognition sometimes encounter difficulties when trying to win the trust of German customers. Besides trust, price and product diversity are the most important competitive factors. Selling groceries over the Internet, for example, has not proven to be successful: Tough price competition and small margins do not leave retailers with enough capital to invest in alternative distribution channels.
B2B Almost all German small- and medium-sized businesses have Internet access. Online transactions are growing and Customer and Partner Relationship Management are becoming increasingly important; public marketplaces, however, are losing attraction. Most e-commerce strategies focus on a quick return on investment. The major channel for B2B transactions remains the traditional Electronic Data Interchange. For the future, experts believe that high-quality brand-name articles and automotive products will be increasingly sold via the net. Major users of B2B solutions are the automotive, retail, energy, and pharmaceutical/ chemical production industries.
Financial Services Germans are heavy users of banking and financial sites and increasingly trust online banking services. Most German banks offer online services.
E-Government Germany offers a good number of e-government services but there is considerable scope for improvement. The central German government online procurement website e-Vergabe was launched in 2002 (www.evergabe.bund.de).
4.5
IMPORT AND EXPORT REGULATION RISKS
Germany's regulations and bureaucratic procedures can be a difficult hurdle for companies wishing to enter the market, requiring close attention by U.S. exporters. Complex safety standards, not normally discriminatory but sometimes zealously applied, complicate access to the market for many U.S. products. U.S. suppliers are well advised to do their homework thoroughly and make sure they know precisely which standards apply to their product, and that they obtain timely testing and certification. The European Union's (EU) attempts to harmonize the various product safety requirements and related standards for industrial products of its member states, which most manufacturers believe has generally helped open 15 member state markets, did not get entirely rid of voluntary national requirements, a fact which complicates the issue. Theoretically, during a transition period national requirements must be met. (After the transition period, the Europewide "CE" mark supersedes all other compliance certificates, provided the products in question are covered by an EU-directive.) The EU's efforts to harmonize standards through the "New Approach" certification-facilitating directives (and separately developed European standards) are incomplete as far as sectors covered. in some cases, U.S. firms, e.g., in the automotive or pharmaceutical sectors, have to worry about complying with the specific requirements of all applicable "Old Approach" product-specific EU technical legislation. German buyers may require additional performance or quality marks, which are not necessarily legally required, but greatly enhance a product's chances to be marketed. Both EU requirements and the standards for a German quality or performance mark will, in many cases, require a product to be modified. Even if the product does not require www.icongrouponline.com
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modification, it will require testing and certification before it can be marketed. Important marks are the "Gepruefte Sicherheit" (GS) mark for mechanical products, and the "Verband Deutscher Elektrotechniker" (VDE) mark for electrical components. It should be emphasized that neither the "GS" license nor the "VDE" license are mandatory for products sold in Germany. The only exception is for products for use in certain work place applications, where either of these marks is required to meet insurance eligibility requirements. The German organization that compiles the standards laying down the requirements for a "GS" mark is the "Deutscher Industrie Normenausschuss - DIN" (German Standards Institute). One of the organizations responsible for testing (in order to obtain the GS and VDE marks) is the "Technischer Ueberwachungsverein e.V. - TUV," (Technical Inspection Association). Although the "VDE" license deals with electrical products, instead of mechanical products, the same process of certification can be followed. A company can obtain "VDE" literature from the VDE publisher (VDE Verlag, GmbH), or directly from the VDE association. The process for "VDE" certification is the same as that of the "GS" mark. TUVs are private companies set up by various German states to inspect and test products for compliance with German safety standards. Individual TUVs have also been authorized by the German Government to test products for compliance with EU legislation, and many have established representative offices in the United States. Firms interested in certification should contact a U.S.-based test laboratory or a Conformity Assessment Body (see: http://ts.nist.gov/ts/htdocs/210/gsig/emc-cabs-mar02.pdf).
4.5.1
Self-Certification
For certain products, self-certification by manufacturers (through a Manufacturer's Declaration of Conformity) is sufficient. Further information is available from the contacts listed at the end of this chapter (see also www.buyusa.gov/europeanunion).
Effect of EU Harmonization on the "GS" and "VDE" Marks The effect of EU harmonization on the "GS" and "VDE" mark is difficult to analyze. It is estimated that about 75 percent of all American products sold in the EU must have the "CE" mark once all directives have been passed and all transition periods have expired. For products subject to CE marking "CE" mark is mandatory; the mark allows the product to be marketed in all the EU member states. National certificates such as the "GS" and the "VDE" marks, may not be legally required, but enhance marketing chances. German consumers look for these marks in much the same way as Americans look for the "UL" mark. Currently, over 20 of the 22 EU directives have been adopted: •
Low-voltage/electrical safety,
•
Toys,
•
Simple pressure vessels,
•
Construction products,
•
Electro-magnetic compatibility,
•
Gas appliances,
•
Personal protective equipment,
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Machinery,
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Medical devices,
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Non-automatic weighing machines,
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Type approval of telecommunications terminal equipment,
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Medical devices,
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Hot water boilers,
•
Lifts and recreational crafts.
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For products where there is not yet a EU directive, national standards, even if they are voluntary, should be adhered to in order to ensure marketability of a product.
Who Has The Authority to Affix the "CE" Mark? For many products, the mark may be affixed by the manufacturer, based on his or her own testing to verify that the product meets EU requirements. However, EU legislation may require that an independent third party be involved in product assessment.
Who Is Qualified to Be an Independent Third Party? The EU accredits so-called "notified bodies", i.e. testing or certification agencies, in addition to TUV, there are other notified bodies in Germany. The complete list is at http://europa.eu.int/comm/enterprise/newapproach/legislation/nb/notified-bodies.htm.
Contact Information for EU "CE" Standards Certification and Standards U.S. Mission to the EU (USEU) Ms. Suzanne R. Sene, Standards Attache Ms. Sylvia Mohr, Standards Specialist Commercial Services 27 Blvd. du Regent B-1000 Brussels, Belgium Telephone: [32] [2] 508 2746 Telefax: [32] [2] 513 1228 Office of European Union and Regional Affairs Mr. Robert Straetz Room H-3036 International Trade Administration U.S. Department of Commerce Washington, D.C. 20230 Telephone: (202) 482-4496 Telefax: (202) 482-2155
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U.S. Contacts for Foreign Standards Information National Center for Foreign Standards Information Ms. Carmina Londono National Institute of Standards and Technology TRF Room A163 Gaithersburg, MD 20899 Telephone: (301) 975-4040 Telefax: (301) 975-2128 American National Standards Institute 1819 L Street NW Washington D.C. 20036 Telephone: (202) 293 8020 Telefax: (202) 293 9287
4.5.2
Value Added Tax/Turnover Tax
In common usage, value-added tax (VAT) and turnover tax are regarded as being identical. All imports and deliveries of goods to or in Germany are subject to VAT, as are services deemed to have been rendered within the country. The tax liability rests on the German business providing service or products or on the importer or buyer of goods or services from abroad. The tax levied on the business is invoiced to customers, who may deduct it from their own liability. The ultimate burden is therefore on the final consumer, who, not being a business, does not file VAT claims and therefore has no rights of deduction. The basic VAT rate is 16 percent. A reduced rate of 7 percent is levied on certain specified items, such as food, books and other publications. The full amount of the VAT should be listed separately on invoices. For invoices up to EUR 100 (USD 100) it is sufficient to indicate only the percentage of the tax rate. Invoices amounting to higher sums must list the payable tax separately. in order to fulfill turnover tax liabilities, all revenues must be listed separately on a pre-payment form of the local tax office. It is important, however, to collect and present all invoices as originals in order to deduct the VAT charged from one's own tax liability or to get reimbursed by the German Ministry of Finance.
4.5.3
VAT Applicable to Online Sales
The European Union's (EU) fifteen member states have reached unanimous agreement on new rules that are set to change the way that Value Added Tax (VAT) is applied to sales of digital products and services over the Internet. The current system allows U.S.-based suppliers to sell things like down-loadable software to EU final consumers without charging VAT; the proposed changes would require charging VAT. Since July 1, 2003, U.S.-based companies selling and delivering services on line to EU customers have to register for VAT purposes with one Member State. They must collect the tax on all sales at the rate applicable in the consumer's country, submit quarterly VAT returns, and remit all VAT revenues to the Member State of registration.
4.5.4
Custom Regulations/Tariffs
Information on customs regulations and tariffs is available from German customs offices, and can differ considerably depending on the products.
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INVESTMENT CLIMATE Openness to Foreign Investment
The German government and industry actively encourage foreign investment in Germany, and German law provides national treatment. Under German law, foreign-owned companies registered in the FRG as a GmbH (limited liability company) or an AG (joint stock company) are treated no differently from German companies. There are no special nationality requirements on directors or shareholders, nor do investors need to register investment intent with any government entity. Foreign companies also generally endure the same or similar investment problems as do domestic firms, such as high marginal income tax rates, inflexible labor laws, and burdensome regulations. The 1956 U.S.-FRG Treaty of Friendship, Commerce and Navigation affords U.S. investors national treatment and provides for the free movement of capital between the U.S. and Germany. Germany subscribes to the OECD Committee on Investment and Multinational Enterprises' (CIME) National Treatment Instrument and the OECD Code on Capital Movements and Invisible Transactions (CMIT). While Germany's foreign economic law contains a provision permitting restrictions on private direct investment flows in either direction for reasons of foreign policy, foreign exchange, or national security, no such restrictions have been imposed. in such a case, the federal government would first consult with the Bundesbank and the governments of the federal states. Industrial policy considerations and lobbying by business interests have, however, occasionally delayed decision-making on investment in certain areas. There is no broad authority to screen or block foreign direct investment.
4.6.2
Conversion and Transfer Policies
As a result of European Economic and Monetary Union (EMU), the Deutsche Mark (DM) was phased out on January 1, 2002 and replaced by the Euro, which is a freely traded currency with no restrictions on transfer or conversion, and which is now the unit of currency in Germany and eleven other EU countries within the monetary union. There is no difficulty in obtaining foreign exchange. There are also no restrictions on inflows and outflows of funds for remittances of profits or other purposes.
4.6.3
Expropriation and Compensation
German law provides that private property be expropriated for public purposes only, in a non-discriminatory manner, and in accordance with established principles of international law. There is due process and transparency of purpose, and investors and lenders to expropriated entities receive prompt, adequate, and effective compensation.
4.6.4
Dispute Settlement
Investment disputes concerning American or other foreign investors and Germany are rare, but come up from time to time. Germany is a member of the International Center for the Settlement of Investment Disputes (ICSID), as well as a member of the New York Convention of 1958 on the Recognition and Enforcement of Foreign Arbitral Awards. German courts are fully available for foreign investors in the event of investment disputes. The government does not interfere in the court system and accepts binding arbitration. For more information on Germany's law on arbitration, reformed in 1997, see www.internationaladr.com/tc121htm.
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Performance Requirements and Incentives
There are about 3,000 incentive programs for investors in Germany. These programs exist on various levels: EU, federal and state (Land) level. Classifying the various programs by target area helps to clarify them for investors. Target areas include the promotion of investment, research and development, human resource development and the promotion of the European market. Grants, incentive programs, guarantees and loans are available towards this purpose. Cash Grants under the Joint Agreement for the Improvement of Regional Economic Structures (Gemeinschaftsaufgabe GA) - improving the structure of regional economies and the economy as a whole is the main objective of the German federal and state governments. The distribution of these subsidies is generally subject to approval by the European Union. Cash grants approved and paid to investors under the Joint Agreement program from 1999 - 2001 totaled EUR 8.6 billion. A comprehensive package of federal and state investment incentives is available to domestic and foreign investors. Germany is in compliance with its WTO TRIMS notification. The government has placed particular emphasis on investment promotion in the New States of former East Germany and offered a large number of incentives to this end. Ongoing efforts to reduce government budget deficits and EU efforts to reduce state aid to industry are putting pressure on these programs. The incentives currently available include: For the eastern German states and eastern Berlin: •
Tax Incentives: Investment allowances, special depreciation allowance
•
Investment Grants: Improvement of Regional Economic Structures Program, grants for research and development, consulting fee and training costs, export, marketing and fair participation assistance
•
Credit Programs: Loans with below-market interest rates from the Bank for Reconstruction (KfW) and its offshoot the Mittelstandsbank, the European Recovery Program (ERP), EU programs and loan guarantee and credit programs.
Programs for all of Germany: •
Tax Incentives: Special depreciation allowance, capital reserve allowance.
•
Investment Grants: Improvement of Regional Economic Structures Program, grants for research and development, consulting fees and training costs.
•
Credit Programs: Loans with below-market interest rates from the Equalization Funds Bank, Reconstruction Funds Bank, the European Recovery Program, European Union programs, loan guarantee programs and other programs for small technology firms and environmental demonstration projects.
U.S. and other foreign firms may also participate in government and/or subsidized research and development programs, provided that: •
The company is legally established in Germany;
•
The activity is a long-term operation with significant R&D capacities;
•
The project engages in sponsored research that is entirely performed in Germany;
•
The firm can exploit intellectual property rights independent from a parent company;
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The Federal Ministry of Education, Science, Research and Technology (BMBF) may exploit intellectual property rights from funded research;
•
Any licensing of technology outside of the EU requires the written approval of BMBF;
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Preference is given to locating manufacturing facilities in Germany for any production resulting from the research (this criterion can be modified on a case-by-case basis.)
American business representatives generally indicate that these formal requirements and the administration of the programs by German authorities do not constitute barriers for access to this R&D funding. Foreign investors can obtain more information on investment conditions and incentives from: Federal Commissioner for Foreign Investment in Germany Markgrafenstr. 34 10117 Berlin, Germany Telephone: [49][30] 206-570 Telefax: [49][30] 206-571-11 E-mail:
[email protected] Internet: www.foreign-direct-investment.de; www.invest-in-germany.de Federal Commissioner for Foreign Investment in Germany 1325 Avenue of the Americas, 28th floor New York, NY 10019 Telephone: (646) 557-1905 Telefax: (646) 557-2006 E-mail:
[email protected] Industrial Investment Council LLC Charlottenstrasse 57 10117 Berlin Telephone: [49][30] 2094-5660 Telefax: [49][30] 2094-5666 E-mail:
[email protected] Internet: www.iic.de
4.6.6
Right to Private Ownership and Establishment
Foreign and domestic entities have the right to establish and own business enterprises, engage in all forms of remunerative activity, and to acquire and dispose of interests in business enterprises. The privatization of state-owned utilities has promoted competition and led to falling prices in some sectors. Following deregulation of the telecommunications sector in 1998, scores of foreign and domestic companies have invested vast sums in that sector. Since then, former state monopolist Deutsche Telekom (DT) has lost more than one third of the long-distance market to competitors, but maintains a 95 percent lock on the "local loop" and 94 percent of DSL broadband connections. The government passed legislation in September 2002 to allow call-by-call and carrier pre-selection in the local loop. Call-by-call was introduced in April 2003, and carrier pre-selection started in July 2003. Foreign investors complain about the lack of competition in local telephony (the state owns 43% of DT), which many observers explained in terms of the government's interest in not further harming DT's share price. Some competition also came to the electricity markets in April 1998, and foreign firms have invested in it, though with great difficulty, owing to the high fees to access incumbents' networks. Natural gas liberalization formally came in August 2000, but competitors have had enormous difficulty gaining access to the incumbents' networks because of cumbersome negotiated access agreements and difficulties in enforcing Cartel Office rulings in a timely manner. Talks on a new negotiated access agreement in the gas sector collapsed in May 2003, and the government decided in
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principle to install a regulator for gas and electricity. in 2004, the positive effects of energy liberalization largely dissipated, as new entrants exited the market and prices began to creep up. In other sectors, Lufthansa Airlines has also been privatized, but the EU requirement that EU airlines remain majority-owned by EU entities limits the amount of foreign investment. The government also partially privatized Deutsche Post (DP) in November 2000, but the government extended the DP monopoly in letter delivery until 2007. The Cartel Office, which enjoys an excellent international reputation, as well as other regulatory agencies address problems and settle complaints brought forward by foreign market entrants and bidders.
4.6.7
Intellectual Property Risks
The German Government adheres to a policy of national treatment, which considers property owned by foreigners as fully protected under German law. There is almost no discrimination against foreign investment and foreign acquisition, ownership, control or disposal of property or equity interests, with airline ownership being an exception. in Germany, the concept of mortgages is subject to a recognized and reliable security. Secured interests in property, both chattel and real, are recognized and enforced. Intellectual property is well protected in Germany. Germany is a member of the World Intellectual Property Organization (WIPO). Germany is also a party to the major international intellectual property protection agreements: the Bern Convention for the Protection of Literary and Artistic Works, the Paris Convention for the Protection of Industrial Property, the Universal Copyright Convention, the Geneva Phonograms Convention, the Patent Cooperation Treaty, the Brussels Satellite Convention, and the Treaty of Rome on Neighboring Rights. U.S. citizens and firms are generally entitled to national treatment in Germany with only a few exceptions. The federal government's commitment under the intellectual property rights portion (TRIPS) of the GATT Uruguay Round has further reduced concerns about the level of software piracy. National treatment is also granted to foreign copyright holders, including remuneration for private recordings. Under the TRIPS agreement, the federal government also grants legal protection for practicing U.S. artists against the commercial distribution of unauthorized live recordings in Germany. Foreign and German rights holders have criticized several exceptions to copyright protections in the new Copyright Act, which passed the Parliament in July 2003.
4.6.8
Transparency of Regulatory System
Germany has transparent and effective laws and policies to promote competition, including anti-trust laws. Restrictions to stores holding sales and store opening hours, which had been questioned by some business for actually limiting competition, have been eliminated or relaxed. The German economy is highly regulated, with authority dispersed over the federal, state, and local levels. Many investors consider bureaucracy excessive, which has prompted most state governments to establish investment promotion offices and investment banks to expedite the process. New rules have simplified bureaucratic requirements, but industry must sometimes contend with officials' relative inexperience with deregulation and lingering pro-regulation attitudes. Taxation of American firms within the FRG is governed by the 1989 "Convention for the Avoidance of Double Taxation with Respect to Taxes on Income." It has been in effect since 1989 (and since January 1, 1991 for the area that comprised the former German Democratic Republic.) With respect to income taxes, both countries agree to grant credit to their respective federal income taxes for taxes paid on profits by enterprises located in each other's territory. The German system is more complex, but there are more similarities than differences between the German and American business tax systems.
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American companies can, with effort, generally obtain the resident and spouse work permit visas they need to do business in Germany, but the relevant laws are quite broad and considerable administrative discretion is exercised in their application. A number of U.S. states have not yet concluded reciprocal recognition of driver's licenses agreements with the German government. Licenses from those states are not usable in Germany.
4.6.9
Capital Market Risks
Germany has a modern financial market sector but is often considered "over-banked" as evidenced by on-going consolidation and low profit margins. Over the last few years, the banking system has suffered from losses and high costs, giving rise to some concerns. On the other hand, in the framework of the IMF's assessment of the German financial sector in Spring 2003, so-called stress tests found that the system is robust. in order to improve their situation, particularly the large private banks launched massive cost cutting programs. Consolidation of the sector is continuing mainly through mergers in the public banking sector. Credit is available at market-determined rates to both domestic and foreign investors and a variety of credit instruments are available. Legal, regulatory and accounting systems are generally transparent and consistent with international banking norms. Germany has implemented a series of laws to improve its securities trading system, including insider-trading laws and the Fourth Financial Market Promotion Law in 2003. in 2002, a corporate governance code was adopted, which, while voluntary, requires listed companies to "comply or explain" why the code or parts thereof have not been followed. The code is intended to increase transparency and improve management response to shareholder concerns. in addition, the Finance and Justice Ministries have announced a 10 Point Plan to improve investor protection, including by strengthening provisions regarding (a) the liability of boards of directors for false or misleading statements; and (b) oversight of auditing operations.
4.6.10
Political Violence
Political acts of violence against either foreign or domestic business enterprises are extremely rare. Isolated cases of violence directed at certain ethnic minorities and asylum seekers have not affected U.S. investments or investors.
4.6.11
Corruption
Among the industrialized nations, Germany ranks in the middle of the field, according to Transparency International's corruption indices. The construction sector and public contracting in conjunction with undue political party influence represent particular areas of continued concern. Strict anti-corruption laws apply to domestic economic activity. U.S. firms have not identified corruption as an impediment to investment. The German government has sought to reduce domestic and foreign corruption. For example, Germany in February 1999 ratified the 1998 OECD Anti-Bribery Convention, thereby criminalizing bribery of foreign public officials by German citizens and firms abroad. Tax reform legislation that became law in March 1999 ended the tax write-off of bribes in Germany and abroad. Germany has increased penalties for bribery of German officials, for corrupt practices between companies, and for price-fixing by companies competing for public contracts. It has also strengthened anti-corruption provisions applying to support extended by the official export credit agency and tightened the rules for public tenders. Most state governments have contact points for whistle blowing and
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provisions for rotating personnel in areas prone to corruption. Government officials are forbidden from accepting gifts linked to their jobs.
4.6.12
Bilateral Investment Agreements
Germany has treaties in force with 119 countries and territories. Of these, eight are covered by treaties with predecessor states (Czechoslovak SFR, Soviet Union, Yugoslavia [SFRY]). These are: Albania, Algeria, Antigua and Barbuda, Argentina, Armenia, Azerbaijan, Bangladesh, Barbados, Belarus, Benin, Bolivia, Bosnia and Herzegovina*, Bulgaria, Burundi, Cambodia, Cameroon, Cape Verde, Central African Republic, Chad, Chile, China, Congo (Republic), Congo (Democratic Republic), Costa Rica, Croatia, Cuba, Czech Republic*, Dominica, Ecuador, Egypt, El Salvador, Estonia, Gabon, Georgia, Ghana, Greece, Guinea, Guyana, Haiti, Honduras, Hong Kong, Hungary, India, Indonesia, Iran, Ivory Coast, Jamaica, Jordan, Kazakhstan, Kenya, Republic of Korea, Kuwait, Kyrgyzstan*, Laos, Latvia, Lebanon, Lesotho, Liberia, Lithuania, Macedonia, Madagascar, Malaysia, Mali, Malta, Mauritania, Mauritius, Mexico, Moldova*, Mongolia, Morocco, Namibia, Nepal, Nicaragua, Niger, Oman, Pakistan, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia*, Rwanda, Saudi Arabia, Senegal, Sierra Leone, Singapore, Slovak Republic*, Slovenia, Somalia, South Africa, Sri Lanka, St. Lucia, St. Vincent and the Grenadines, Serbia and Montenegro*, Sudan, Swaziland, Syria, Tajikistan*, Tanzania, Thailand, Togo, Tunisia, Turkey, Turkmenistan, Uganda, Ukraine, United Arab Emirates, Uruguay, Uzbekistan, Venezuela, Vietnam, Yemen (Arab. Rep.), Zambia, and Zimbabwe. (Note: Asterisk denotes treaty in force with predecessor state.)
4.6.13
OPIC and Other Investment Insurance
OPIC programs were available for the New States of eastern Germany following reunification for several years during the early 1990s, but were suspended following the extraordinary achievements in the economic and political transition.
4.6.14
Labor
The German labor force is generally highly skilled, well educated, disciplined, and very productive. However, the labor market is characterized by various structural problems, German wages and fringe benefits are among the highest in the world, and, partly as a result, unemployment is high (9.7 %, according to national calculation methods, 8.2% by OECD standards). Although sector-wide labor agreements can set wages at high levels in some industries, there are possibilities for company-level agreements, which can significantly attenuate these high levels. Meanwhile, generous unemployment benefits reduce the incentive to take those lower paying jobs that are available. Legislation designed to protect workers can limit the ability of employers to adapt to changing market conditions. The country's system of combined on-the-job and academic training for apprentices produces many of the skills employers need. While widely supported in Germany, there are criticisms of the dual training system. Employers object to its "rigidities" - in principle, protective rules such as restrictions on night work. Another criticism is that the system is too inflexible with regard to occupational categories and training standards; re-training skilled workers for new skills is also extremely difficult. The labor unions complain that employers do not establish enough training slots and do not hire enough of the trainees after their training is completed. The problem of too few slots was documented again in 2003.
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Despite overall high unemployment, a serious labor shortage has appeared in some high-tech sectors, prompting business calls for easier visa procedures for qualified foreign guest workers, especially in the information technology field. The government has responded with a program to attract more foreign IT specialists.
Unionized Labor Unionized labor (28-30 % percent of the labor force) is organized in eight unions largely grouped by industry or service sector. These unions are affiliates of the German Trade Union Federation (DGB). Unions' right to strike and the employers' right to lockout are protected in the German constitution. Court rulings over the years have limited management recourse to lockouts, however. Labor has traditionally been able to agree with management with relatively few work stoppages. Works councils are bodies consisting of worker and management representatives which workers in companies with five or more permanent workers or more can choose to elect. The rights of the works council cover the right to be informed, consulted, and to participate in company decisions. Works councils often help labor and management settle problems before they become disputes and disrupt work. A reform in the law governing the works councils enacted in 2001 accelerated the procedures to establish works councils and strengthened their consultation and participation rights. "Co-determination" laws give the workforce in medium-sized or large companies (stock corporations, limited liability companies, partnerships limited by shares, co-operatives or mutual insurance companies) significant voting representation on the firms' supervisory boards. This codetermination in the supervisory board extends to all company activities.
4.6.15
Free Trade Zone Options
There are two free ports in Germany, one in the Hamburg harbor and the other in Duisburg. These duty-free ports also permit value-added processing and manufacturing, albeit under certain requirements, and both are open to both domestic and foreign entities.
4.7
TRADE AND PROJECT FINANCING
Germany has a basically non-discriminatory, well-developed financial services infrastructure. Germany's universal banking system allows the country's more than 38,000 bank offices not only to take deposits and make loans to customers, but also to trade in securities. The traditional German system of cross-shareholding among banks and industry, as well as a high rate of bank borrowing relative to equity financing, have allowed German banks to exert substantial influence on industry in the past. Germany's tax reform, however, eliminated the capital gains tax on holdings sold by one corporation to another as of January 2002. Private banks control 28 percent of the market, while publicly owned savings banks and Landesbanken controlled by state and local governments account for 36 percent of banks' volume of business, and cooperative banks make up the balance. All three types of banks offer essentially the same, full range of services to their customers. An array of specialist banks finance homeowner mortgages, provide guarantees to small and medium-sized businesses, finance projects in disadvantaged regions in Germany and guarantee exports to developing countries. Practices regarding finance, availability of capital and schedules of payment are comparable to those that prevail in the United States. There are no restrictions or barriers on the movement of capital, foreign exchange earnings or dividends. Virtually all major U.S. banks are represented in the German market principally, but not exclusively, in www.icongrouponline.com
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the city of Frankfurt am Main, Germany's main financial center. A large number of German banks, including some of the partially state-owned regional banks, similarly maintain subsidiaries, branches and/or representative offices in the United States. Germany's largest private banks are Deutsche Bank, HVB, Commerzbank, and Dresdner Bank.
4.8
TRAVEL RISKS
Neither Germany's legal system nor its fully developed infrastructure present any obstacles for traveling to the country. Travel by plane, train or car meets international standards, but prices exceed U.S. standards. The number of in-country flights has been picking up and the train stations that dot the country provide sufficient access to nearly all cities. Nevertheless, cars are the most popular means of transport and Germany's famous highway system is extensive. The condition of roads in eastern Germany may still not reach western German standards, but they are not barriers to traveling. Geographic distances are relatively short, when compared to the United States, but as Germany is much more densely populated than its European neighbors, it may take a little longer to travel the same distance in the FRG than it may take in France or Scandinavia. The industrial and commercial centers in the Rhine-Main (Frankfurt) and Rhine-Ruhr areas are densely populated and heavily industrialized, and business travelers are well advised to plan on early departures to reach their destination on time. Train and air travel are also efficient means of travel, with timely and comprehensive connections between all major and many minor cities throughout both eastern and western Germany. There is sufficient hotel space in most major cities, unless there happens to be a major trade fair or a similar event in a particular city. Business class amenities and services can be found in all major cities, including those in the eastern states. Visas are not required for U.S. passport holders on business (and leisure) travel spending fewer than 90 days in Germany. For longer stays, travelers are encouraged to apply to the German Embassy or German Consulates in advance of travel. Since October 1, 2003, Germans must have a machine-readable passport in order to travel to the U.S. without a visa. in order to avoid the inconvenience and expense of applying in person for a U.S. visa, please advise your German business partners who travel to the U.S. that all travelers, including infants and children, will need to have individual, machine-readable "Europapass"-style passports. Holders of green-cover non-readable German passports and children's travel documents (Kinderausweise) are no longer eligible for visa-free travel. Please advise your German business partners to make advance preparations in order not to delay their business travel to the United States. Further information on the Visa Waiver Program requirements can be found at the Department of State's Visa Services Web site, http://travel.state.gov/vwp.html. Travel Guides for Business Representatives are available for sale by the Superintendent of Documents. U.S. Government Printing Office, Washington, D.C. 20402; Phone: (202) 512-1800; Fax: (202) 512-2250. Business travelers to Germany seeking appointments with U.S. Mission officials should contact the commercial sections of the Embassy or the Consulates General in advance.
4.8.1
Country Data
•
Population: 83 million (2000), including 17.2 million in eastern Germany and 7.4 million foreigners (d).
•
Religion: 34% Protestant, 33% Catholic.
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•
Government: Constitutional, parliamentary confederation; Head of State: Johannes Rau, President; Head of Government, Gerhard Schroeder, Chancellor
•
Language: German
4.9
KEY CONTACTS
Federal Ministry of Economics Bundesministerium fuer Wirtschaft & Technologie Mr. Wolfgang Hantke, America Desk Officer Scharnhorststrasse 34-37 10115 Berlin, Germany Telephone: [49][30] 2014-7578 and 01888-615-7578 Telefax: [49][30] 2014-5479 and 01888-615-5479 E-mail:
[email protected] www.bmwi.de Bundesministerium fuer Wirtschaft & Technologie Dr. Bernard Veltrup, Head of Division - New States Scharnhorststrasse 34-37 10115 Berlin, Germany Telephone: [49][30] 2014-6260 Telefax: [49][30] 2014-5364 E-mail:
[email protected] www.bmwi.de Federal Bureau for Foreign Trade Information Bundesagentur fuer Aussenwirtschaft Ms. Zimniok, North American Desk Officer Agrippastrasse 87-93 50676 Koeln, Germany Telephone: [49][221] 20 57-249 Telefax: [49][221] 20 57-212 www.bfai.de Federal Ministry of Finance Bundesministerium fuer Finanzen Wilhelmstrasse 97 10117 Berlin, Germany Telephone: [49][30] 2242-0 Telefax: [49][30] 2242-3260 www.bundesfinanzministerium.de
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Trade Associations and Chambers of Commerce
Bundesverband der Deutschen Industrie e.V. (BDI) (Federation of German Industries) Breite Strasse 29 10178 Berlin, Germany Telephone: [49][30] 2028-0 www.bdi-online.de Deutscher Industrie und Handelskammertag (DIHK) (Federation of German Chambers of Industry and Commerce) Breite Strasse 29 10178 Berlin, Germany Telephone: [49][30] 203 08-0 Telefax: [49][30] 203 08-1000 E-mail:
[email protected] www.diht.de Bundesverband des Deutschen Gross- und Aussenhandels e.V. (BGA) (Federation of German Wholesale and Foreign Trade) Am Weidendamm 1 A 10117 Berlin, Germany Telephone: [49][30] 5900 995-0 Telefax: [49][30] 5900 995-19 www.bga.de Zentralverband Elektrotechnik- und Eletronikindustrie e.V. (ZVEI) (German Electrical and Electronic Manufacturers Association) Stresemannallee 19 60596 Frankfurt/Main, Germany Telephone: [49][69] 6302-0 Telefax: [49][69] 6302-317 E-mail:
[email protected] www.zvei.de Verband Deutscher Maschinen- und Anlagenbau e.V. (VDMA) (German Association of Machinery and Plant Manufacturers) Lyoner Strasse 18 60528 Frankfurt/Main, Germany Telephone: [49][69] 6603-0 Telefax: [49][69] 6603-1511 E-mail:
[email protected] www.vdma.de
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Bundesverband Informationswirtschaft, Telekommunikation und Neue Medien e.V. (BITKOM) (Federal Association for IT, Telecommunications and New Media Companies) Albrechtstraße 10 10117 Berlin Postfach 640144 10047 Berlin Telephone: [49][30] 2 75 76-0 Telefax: [49][30] 2 75 76-4 00 E-mail:
[email protected] Centralvereinigung Deutscher Handelsvertreter- und Handelsmakler-Verbaende (CDH) (General Association of Commercial Agents and Brokers) Am Weidendamm 1a 10117 Berlin, Germany Telephone: [49][30] 72625-600 Telefax: [49][30] 72625-699 E-mail:
[email protected] www.cdh.de American Chamber of Commerce Rossmarkt 12 60311 Frankfurt am Main Telephone: [49][69] 92 91 04 - 0 Telefax: [49][69] 92 91 04 - 11 E-mail:
[email protected] www.amcham.de
4.9.2
Market Research Firms
It would exceed the scope of this guide to list even only the major market research or consultant companies. Most of these firms belong to one or both of the following associations and can be contacted through these. Bundesverband Deutscher Unternehmensberater e.V. (BDU) (Federal Association of German Consultants) Mr. Christoph Weyrather Zitelmannstr. 22 53113 Bonn, Germany Telephone: [49][228] 9161-0 Telefax: [49][228] 9161-26 E-mail:
[email protected] www.bdu.de Arbeitskreis Deutscher Markt- und Sozialforschungsinstitute e.V. (ADM) (Federation of German Market and Social Research Institutes) Dr. Klaus L. Wuebbenhorst, Member of the Board Langer Weg 18 60489 Frankfurt/Main, Germany Telephone: [49][69] 97843136 Telefax: [49][69] 97843137 E-mail:
[email protected] www.adm-ev.de
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181
Commercial Banks
There are numerous domestic and foreign banks represented in Germany; among the largest German and American institutions are: Deutsche Bank AG Taunusanlage 12 60325 Frankfurt am Main, Germany Telephone: [49] [69] 91 000 Telefax: [49] [69] 910-34227 E-mail:
[email protected] www.deutsche-bank.de Dresdner Bank AG Juergen-Ponto-Platz 1 60301 Frankfurt am Main, Germany Telephone: [49] [69] 263-0 Telefax: [49] [69] 263-4004 www.dresdner-bank.com Westdeutsche Landesbank Herzogstrasse 15 40217 Dusseldorf, Germany Telephone: [49] [211] 826-01 Telefax: [49] [211] 826-6119 www.westlb.de Commerzbank AG Neue Mainzer Strasse 32-36 60311 Frankfurt am Main, Germany Telephone: [49] [69] 1362-0 Telefax: [49] [69] 136-41665 E-mail:
[email protected] www.commerzbank.com Citibank AG Reutterweg16 60323 Frankfurt am Main, Germany Telephone: [49] [69] 1366-0 Telefax: [49] [69] 1366-1113 www.citibank.com JP Morgan GmbH Boersenstr. 2-4 60313 Frankfurt am Main, Germany Telephone: [49] [69] 7124-0 Telefax: [49] [69] 7124-1306 www.jpmorgan.com
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Goldman-Sachs & CO OHG Messeturm Friedrich-Ebert-Anlage 49 60308 Frankfurt am Main, Germany Telephone: [49] [69] 7532-0 Telefax: [49] [69] 7532-2800 www.gs.com Merrill Lynch Bank AG Neue Mainzer Strasse 52 60311 Frankfurt am Main, Germany Telephone: [49] [69] 5899-0 Telefax: [49] [69] 5899-4000 www.ml.com
4.9.4
Other Contacts
The U.S. Agricultural Trade Office in Hamburg closed in September 2002. All marketing inquiries for food and agricultural products should be directed to the Agricultural Affairs Office in Berlin. Office of Agricultural Affairs Clayallee 170 10117 Berlin, Germany Telephone: [49][30] 8305-1158 Telefax: [49][40] 8431-1935 E-mail:
[email protected] www.usembassy.de/ato
4.9.5
Contacts in Washington D.C.
U.S. Department of Commerce International Trade Administration Ms. Kelly Parsons Desk Officer for Germany Room 3513 Washington, DC 20230 Telephone: (202) 482-2177 Telefax: (202) 482-4098 E-mail:
[email protected] www.ita.doc.gov USDA - Foreign Agricultural Service Ag Export Services Division 1400 Independence Ave, SW Washington, DC 20250-1052 Telephone: (202) 720-6343 Telefax: (202) 690-4374 http://www.fas.usda.gov/
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U.S. Department of State Germany Desk EUR/AGS/Room 4228 Washington, DC 20520 Telephone: (202) 647-2005 Telefax: (202) 647-5117 www.state.gov U.S. Department of the Treasury Ms. Carol Carnes Germany Desk Officer 3107 NY Ave Washington D.C. 20220 Telephone: (202) 622-1235 Telefax: (202) 622-0134 www.ustreas.gov Office of the U.S. Trade Representative Office of Europe and the Mediterranean Executive Office of the President 600 17th Street NW Washington, DC 20508 Telephone: (202) 395-3320 Telefax: (202) 395-3974 www.ustr.gov
4.9.6
U.S.-Based Multipliers
Embassy of the Federal Republic of Germany 4645 Reservoir Road, N.W. Washington, D.C. 20007-1998 Telephone: (202) 298-4000 (switchboard) Telefax: (2020 298-4249 www.germany-info.org CMA - German Agricultural Marketing Board North American Office 1800 Diagonal Road, Suite 210 Alexandria, Virginia 22314 Telephone: (703) 739-8900 Telefax: (703) 739-8910 E-mail:
[email protected] www.cmnorthamerica.org German American Chamber of Commerce Inc. (Headquarters) 12 East 49th Street 24th floor New York, NY 10017 Telephone: (212) 974-8830 Telefax: (212) 974-8867 E-mail:
[email protected] www.gaccny.com
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German Representative for Industry and Trade Mr. Robert Bergmann 1627 I Street, NW Suite 550 Washington DC 20006 Telephone: (202) 659-4777 Telefax: (202) 659-4779 E-mail:
[email protected] www.rgit-usa.com
4.9.7
Useful Web Sites
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http://www.buyusa.de/en - U.S. Commercial Service Germany
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www.buyusa.com - U.S. Commercial Service trade matchmaking portal
•
www.agbc.de - American-German Business Club
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www.amcham.de - American Chamber of Commerce in Germany
•
http://www.useu.be/agri/ - the office of Agricultural Affairs at the U.S. Mission to the European Union has a very comprehensive website on EU food laws, import requirements, and duties and quotas.
•
www.fas.usda.gov - The Foreign Agricultural Service website has trade and production statistics, exporter assistance information, marketing information, trade policy news and links to the attaché reports.
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5 5.1
DISCLAIMERS, WARRANTEES, AND USER AGREEMENT PROVISIONS DISCLAIMERS & SAFE HARBOR
Summary Disclaimer. This publication ("Report") does not constitute legal, valuation, tax, or financial consulting advice. Nor is it a statement on the performance, management capability or future potential (good or bad) of the company(ies), industry(ies), product(s), region(s), city(ies) or country(ies) discussed. It is offered as an information service to clients, associates, and academicians. Those interested in specific guidance for legal, strategic, and/or financial or accounting matters should seek competent professional assistance from their own advisors. Information was furnished to Icon Group International, Inc. ("Icon Group"), and its subsidiaries, by its internal researchers and/or extracted from public filings, or sources available within the public domain, including other information providers (e.g. EDGAR filings, national organizations and international organizations). 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objectives, financial situation or particular needs of any particular person or legal entity. With respect to any specific company, city, country, region, or industry that might be discussed in this report, investors should obtain individual financial advice based on their own particular circumstances before making an investment decision on the basis of the information in this report. Investing in either U.S. or non-U.S. securities or markets entails inherent risks. In addition, exchange rate movements may have an effect on the reliability of the estimates provided in this report. Icon Group is not a registered Investment Adviser or a Broker/Dealer.
5.2
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END
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