global best practices statistical yearbook · 2004-11-17 · participation is guaranteed through...

Emanating from the most comprehensive operational competitiveness benchmarking programme ever completed in the automotive

components industry…

Global Best Practices Statistical Yearbook:

2004 Edition

ISBN Number: 0-620-31887-2

Copyright Benchmarking and Manufacturing Analysts (2004)

Global Best Practices Programme – 2004 Statistical Yearbook

Copyright B&M Analysts (2004)

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Foreword

This Best Practices Statistical Yearbook represents the second annual yearbook to emerge from the Global Best Practices Benchmarking Programme. Consistent with the first yearbook, it has been developed over a considerable period of time and with the input of a number of international experts, including Professor John Bessant of Cranfield University, Professor Raphael Kaplinsky of the University of Sussex and Professor Mike Morris of the University of Natal. The operational competitiveness benchmarking tool upon which the yearbook is based is, we believe, the most advanced and rigorous available globally, with the team at Benchmarking and Manufacturing Analysts, led by Dr. Justin Barnes, refining and advancing its content over the last six years – during intensive engagements with multinational and nationally owned automotive component manufacturers across the globe.

We therefore present the second annual best practices yearbook with a great deal of pride, as well as confidence in its ability to add value to the operations of those component manufacturers with the vision to use its data to drive their competitiveness forward. As highlighted in the first yearbook, in the new global operating environment confronting firms, there is simply no place to hide. Excellence is not a “nice to have”; it is essential for survival and future success. This yearbook is intended as a mechanism to support firms in their endeavours to achieve this. However, it should not only direct positive change, but also empower firms with the knowledge that where their performance is strong, this can be recognized with a level of confidence.

This second edition of the yearbook represents a substantial advance on the first edition, with the database expanding from 75 to 84 firms. Our intention is to expand the global reach of the Best Practices Yearbook next year, enabling us to include additional disaggregated datasets and finally to begin analyzing longitudinal trends. We therefore hope that your acquisition of this yearbook leads to your participation in the Global Best Practices Benchmarking Programme for automotive component manufacturers in future years. Participation is guaranteed through the completion of the questionnaire available at www.bmanalysts.com and the payment for this yearbook. Alternatively, contact us at [email protected] for a copy to be emailed to you. Remember, firms who participate in the programme receive a 50% discount on the yearbook price and are guaranteed next Year’s yearbook at the same price as the 2004 book.

Benchmarking and Manufacturing Analysts will be happy to answer any queries firms have regarding any of the data included in the yearbook. Queries can be directed to [email protected]. We sincerely hope that this yearbook is of benefit to you. Any comments pertaining to its content and structure (positive or negative) are welcome and can be directed to the above email address.

The Team at B&M Analysts

Global Best Practices Programme – 2004 Statistical Yearbook


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Disclaimer Whilst every care has been taken to ensure the accuracy and integrity of the data presented in the yearbook, Benchmarking and Manufacturing Analysts takes no responsibility whatsoever for company decisions derived from the data.

Copyright Please note that copyright exists on the yearbook and that no company or individual is permitted to reproduce any portion of this publication by any means without the prior permission of a representative of Benchmarking and Manufacturing Analysts. Failure to adhere to this copyright will result in legal action.

Global Best Practices Programme – 2004 Statistical Yearbook: Content


Yearbook content Foreword…………………………………………………………………...ii Introducing Benchmarking and Manufacturing (B&M) Analysts……………………………………………………..…. iv Introduction………………………………………………………. ………1 Section 1 – Understanding the yearbook………….……..4 Section 2 – Aggregate “Market Driver” performance findings………………………………………….....18 Section 3 – Sub-sector performance findings………..66 Section 4 – Developed economy versus Developing economy firm performance ……………….154 Section 5 – Firm performance based on market focus…………………………………………………………………….…202 Section 6 – Performance findings according to employment size of participating firms…….……….…250 Appendix – One page competitiveness self-assessment

Global Best Practices Programme – 2004 Statistical Yearbook: B&M Analysts

Copyright B&M Analysts

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Introducing Benchmarking and Manufacturing (B&M) Analysts

Founded in 1997, B&M Analysts is the premier benchmarking and manufacturing diagnostics consulting company in Africa. With its head office in Durban, South Africa and subsidiary offices in Port Elizabeth, South Africa and Brighton, United Kingdom, a host of international linkages, as well as world class methodologies and personnel, the company has established an enviable reputation in a number of manufacturing sectors. This is most obvious in the automotive components industry where its client list includes prominent national and multinational companies. As a result of its operational excellence and proven track record over the last seven year, the company has grown substantially. The resources acquired over this period are focused exclusively on servicing the needs of B&M Analysts’ diverse and growing client base. The company's vision statement captures the essence of this focus: “To be a globally recognized benchmarking organization with cutting edge industry development services and superior manufacturing best

practice product commercialization capabilities.” The full ambit of services offered by B&M Analysts is clearly reflective of the company’s world class capabilities in its chosen focus areas: 1. Firm-level operational competitiveness benchmarking and diagnostic

services, including, a. Global comparator benchmarking b. Customer and supplier benchmarking c. Manufacturing excellence assessments

2. Publication of an annual Global Best Practices Statistical Yearbook 3. Learning network facilitation 4. Manufacturing policy and strategy research 5. Publication of a bi-annual multimedia Manufacturing Excellence Resource

Package For further information on the services rendered by B&M Analysts, as well as its products, please visit www.bmanalysts.com.

Global Best Practices Programme – 2004 Statistical Yearbook: Introduction


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Introduction

Background On the basis of B&M Analysts’ successful coordination of a global ‘best practices’ benchmarking programme for automotive component manufacturers over the last six years and the development of a truly world class operational competitiveness database, we are extremely pleased to present the second annual Global Best Practices Statistical Yearbook for automotive component manufacturers. This yearbook represents the culmination of years of firm-level research into the competitiveness of automotive component manufacturers and as such should prove an invaluable tool to management teams the world over interested in better understanding their competitiveness standing in relation to global standards on a number of key best practice fronts – from inventory control to internal and external quality performance to human resource development and product innovation. By interrogating the data included in this yearbook managers should be able to answer those key questions that they most often struggle with: 1. Are we meeting the demanding and rapidly changing standards of the

global automotive industry? 2. Using an objective operationally-based benchmark, how competitive

are we really? 3. In which areas do we really excel and/or fail and where should we be

focusing our attention to deliver performance standards consistent with that of the leading firms in the industry?

4. And finally, are our measurement systems rigorous enough? In purchasing this yearbook, managers now have the opportunity to participate in firm-level benchmarking exercises that identify the extent to which they are adhering to lean production practices relative to 84 automotive component manufacturers located in Western Europe, South Africa, Eastern Europe, Malaysia, Brazil and Australia. In essence, this yearbook affords each and every manager the opportunity to answer the above questions in an objective manner. Comprising six sections and over 200 pages of firm-level statistical information, the extensive key competitiveness measures explored in this Yearbook are grouped under six market driver indicators: 1. Cost control 2. Quality performance 3. Value chain flexibility/reliability 4. Operational flexibility/reliability 5. Human resource development 6. Product development In addition to the key competitiveness indicators that fall under each of these market drivers, a full statistical overview of financial performance is also presented. Whilst these findings are important in that they offer an indication of comparative firm health, they simply reveal firm-level



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competitiveness and market conditions in previous years, and are a poor indication of present and future competitive capacity. Considering the findings is important, but the other parts of this yearbook represent its core value - the ability to measure oneself against a variety of lean production competitiveness performance standards, so that one can motivate for positive change and the attainment of enhanced performance standards that surpass that of the competition and not only satisfy customers, but genuinely delight them!

Structure of the Yearbook A full explanation of each of the market drivers around which this yearbook is organised is presented in Section 1, as are the formulae underpinning each of the core competitiveness indicators that highlight comparative performance. This section also includes a short essay on the importance of benchmarking (to help those along that are still unsure of its use and application), and an extensive profile of the aggregated database upon which this yearbook is based. Managers who read Section 1 should, at its completion, fully understand both the structure and value of the yearbook, whilst also having detailed knowledge of the composition of the dataset upon which this yearbook is based. Individuals engaging the yearbook for the first time are therefore strongly encouraged to start their engagement here. Only once the market driver benchmarking approach and the composition of the database is fully understood should individuals interrogate the detailed benchmarking data comprising the remainder of the yearbook. Section 2 presents the competitiveness data in an aggregated form. The Global Best Practices Programme dataset is presented in both table and figure formats and is broken down according to percentiles, quartiles, means (averages) and medians. The averages for each of the disaggregated datasets are also presented in this section. The data is disaggregated in terms of four principle categories – market focus, type of economy (developed versus developing), sub-sector and firm-size. The next four sections of the yearbook then focus upon each of the disaggregated datasets. Section 3 focuses on firm-level performance findings in terms of market focus (Original Equipment Manufacturer [OEM], aftermarket and 1st tier component manufacturers), whilst Section 4 considers the sub-sector specific performance findings (interior/exterior trim, metal forming/fabrication, foundry/forge, electronics/harnesses, powertrain parts and glass). Section 5 then focuses on the developed versus developing economy firm findings, and Section 6 disaggregates the data according to firm size (based on employment numbers). In addition to the detailed firm-level competitiveness data presented in the yearbook, financial data capturing sales and employment trajectories, as well as operating profits is also presented. This should give managers at automotive component manufacturers a comprehensive perspective on their present financial and competitiveness performance in the ever more demanding global automotive industry.



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Yearbook benefits Given its comprehensive dimensions, an analysis of the benchmarking data in the yearbook should be of immeasurable value to both individual managers and companies. As should be clear, not only will managers be in a position to gauge their company’s competitiveness strengths and weaknesses in terms of each of the operational performance measures explored, they will also receive explanations outlining the importance of each of the measures, thus ensuring that the value of the Statistical Yearbook is made explicit. The manner in which companies perform against the averages, as well as the better and poorer performing outliers, will provide a clear indication of whether they are meeting the competitiveness challenges of the new global operating environment, whilst the disaggregated data will provide a clear indication of where firm performance levels should be in relation to those firms that match their profile characteristics in terms of geographical location, firm size, conversion processes and/or market focus.

Queries Importantly, if any individual has a query pertaining to the data included in the Yearbook, they are encouraged to contact B&M Analysts at [email protected]. Your query will be treated in the strictest of confidence and we will respond within 48 hours, thus ensuring that the benefits of the Yearbook are maximized.

Global Best Practices Programme – 2004 Statistical Yearbook: Section 1


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Section 1 – Understanding the 2004 Yearbook To ensure that you fully understand the content of this yearbook we strongly encourage you to start engaging with it here. This section aims to comprehensively outline the yearbook’s 2004 content and comprises four sub-sections. The first explores the importance of benchmarking and the merits of the market driver approach used in the composition of the Global Best Practices Programme - 2004 Statistical Yearbook dataset. It takes the form of a short essay and is important in situating the scientifically valid nature of the yearbook, as well as its intrinsic value to management teams. The second section provides an overview of the market driver benchmarking methodology upon which the entire yearbook is based, as well as the competitiveness measures underpinning each of the six market drivers. Importantly, the formulae attached to each of the competitiveness measures are also presented, thus ensuring a clear understanding of the measures included in Sections 2 through 6. The third sub-section then explores the profile of firms included in the dataset. The size of each population group is made explicit as are the exact characteristics of the sets and sub-sets of firms – from their ownership to their location, quality accreditations, number of customers and suppliers to their operating profiles. This sub-section situates the exact parameters of the dataset and will help make explicit the manner in which a manager reading the yearbook can differentiate their firm’s profile from that of the various categories of firms included in the dataset. The final sub-section outlines the manner in which managers should engage with the statistics presented in the yearbook. Importantly, it outlines the manner in which the data is presented, explores the various statistics used, and provides an example of how the data can be interpreted and used to galvanize management action to effect positive change within companies based in developed and developing economies alike.

1.1. Contextualising the importance of benchmarking in the global automotive components industry

How did the Western automobile industry catch-up with the Japanese? During the 1970s and 1980s, not only did the Japanese automobile industry sweep through global markets, even in the largest market of the USA they accounted for over 30% of sales. Many people predicted that the Japanese firms would completely drive out their American competitors. Yet this did not happen, with the US assemblers rapidly improving their performance standards to those close to (and in certain instances even equal to) the Japanese. The largest European automobile firms responded similarly.



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In the beginning, many of the Western firms thought that the answer to the Japanese challenge was to invest in the most modern technology. Some did so, and burnt their fingers, badly! But they soon came to realise that the Japanese had not beaten them because of their superior technology, but rather due to their ability to produce with a new system, most often called lean production. So, after carefully comparing themselves with the Japanese, and with other automobile firms in their own markets and in Europe, the American producers have been able to restructure their operations, thus putting themselves in a stronger position to withstand further inroads by the Japanese. How did they make this comparison with Japanese practices? In turning around their operations, the Western automobile firms benchmarked themselves against all of their competitors, not just the Japanese. From this, they were able to identify their strengths and weaknesses - both in their performance, and in their practices. At the same time they were able to identify the practices that other firms used to achieve better results. From this benchmarking exercise they were able to take the necessary actions to regain their diminishing competitiveness. Who to benchmark against? Generally, the most useful firms to benchmark against are those operating in a similar sector. This is because certain performance indicators are conversion specific. But in many cases this may not be possible. Alternatively, firms may wish to diversify, so that they would like to see how firms producing related, but not identical products, are faring. And, in some cases, firms even find it useful to compare themselves with firms in other sectors, to see whether anything new can be learnt from their behaviour and performance. What to benchmark? International experience suggests that there are a number of key variables to benchmark, across all industries. These are with respect to business strategy and performance; the organisation of production and inventory control; procedures to assure quality; procedures to ensure continuous improvement and human resource development; the design and development of new products and production processes; and systems of relations with suppliers. But, in addition to these general benchmarks, each industry also has a number of specific parameters, which need to be taken into account, hence the importance of sector specific benchmarking. Who should do this benchmarking? The problem with benchmarking is that although firms are eager to find out how they are performing in relation to other firms, their competitors naturally do not want to let their secrets out. For this reason, it is generally very difficult for individual firms to gain access to their competitors. As a result, for benchmarking to be successful, neutral investigators are required. Neutral investigators collect the relevant data with the participation of the



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firms, on the understanding that firm-specific confidential information is not released to anyone without their written permission1. This information is then packaged in a manner that disguises the individual identity of participating firms without weakening the value of the knowledge created. Relevance of benchmarking to the global auto components industry As the global automotive components industry is opened up to international competition the importance of benchmarking becomes strikingly clear. Just as the automobile assemblers in North America have come under significant pressure from the Japanese over the last two decades, so automotive component manufacturers across the globe are presently threatened by the opening of their national economies in line with World Trade Organisation requirements. As it did to the North American automobile assembly industry (and shortly thereafter the European automobile industry as well), benchmarking consequently offers automotive component manufacturers a vital and necessary tool in the improvement process that needs to be established in order to increase competitiveness to required levels – in both domestic and international markets. This is apart from the important fact that benchmarking is considered a necessary condition for the attainment of automotive quality standards such as ISO/TS 16949. B&M Analysts’ benchmarking tool Our benchmarking tool has been created with the specific intention of developing firm-level competitiveness. Whilst it was not specifically designed for a particular sector and has been developed as a general continuous improvement tool to be used across manufacturing enterprises of all sizes, it has been widely used for the benchmarking of automotive component firms - with a significant amount of success over the course of the last five years. This success has been underpinned by the scientific rigour of the tool’s development process and its ongoing refinement in line with changing market requirements2. As highlighted above, international experience suggests that there are numerous key variables to benchmark across all industries. But, in addition to these general benchmarks, each industry also has specific parameters that

1 For example, when B&M Analysts completes a benchmarking exercise at a company, the company is at liberty to impose their own confidentiality agreement on us. Failing this, we have our own standard confidentiality agreement, which can be downloaded at www.bmanalysts.com and which guarantees the confidentiality of all benchmarking information received. 2 Key academics associated with the development of the methodology include Prof. John Bessant of the Cranfield School of Management, Prof. Raphael Kaplinsky of the Institute of Development Studies at the University of Sussex, Prof. Mike Morris of the University of KwaZulu-Natal and Dr. Justin Barnes of B&M Analysts.



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need to be considered. "Like-with-like" benchmarks (i.e. comparative benchmarks between firms competing in the same or similar market segments) are consequently the most useful benchmarks, particularly when the findings are being used to direct management action. For example, if two automotive foundry firms are benchmarked against one another, and the findings highlight that the one firm performs worse than the other in terms of inventory holding and internal and external quality performance then there can be no excuses from that firm's management as to the relevancy of the benchmark findings. Getting management to accept the need for change is made far easier. Unfortunately, most benchmarking internationally takes a broad composite index across either a number of sectors or across one broad sector. Firms then compare themselves with these sets of indices. The problem with this is that firms do not receive sufficient specific information to assist them in directing management action to become more competitive. These tools have limited diagnostic value in laying bare the processes that are leading to a firm's comparative (poor or strong) performance levels.

1.2. The market driver methodology and measurement formulae

The benchmarking data presented in this yearbook is fundamentally different. It is based on what we term a quantitatively based Market Driver benchmarking questionnaire that focuses not on indexed, but rather actual performance levels. The uniqueness of the methodology that we have used extensively across the globe is that it allows the competitiveness variables of a specific firm to be directly benchmarked against broad sectoral standards, as well as a narrower range of firms matching its location profile, its manufacturing sub-sector, its size and its market focus. The "market drivers" against which our tool measures performance are outlined in the table overleaf, as are the performance measures that are intrinsic to understanding how effectively firms are meeting these requirements. In addition, the table outlines the importance of each of the six market drivers. As highlighted the basic quality, cost, delivery and speed elements of any world class manufacturing template are covered, with human resource and new product development elements included as key indicators of future competitive potential.



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Market driver Operational performance measures

Indicative value

1. Cost control 1. Total inventory levels 2. Raw material holding 3. Work in progress (WIP)

levels 4. Finished goods holding

Measuring inventory is a sound proxy for the measurement of cost control at manufacturers. Firms with low inventory are operating just in time (JIT) systems & thus are in control of their costs. Raw material, WIP and finished goods stock are all cost contributors.

2. Quality 5. Customer return rates 6. Internal reject rates 7. Internal scrap rates 8. Internal rework rates 9. Return rates to suppliers

Three quality areas are key: Customer returns, internal defects (rejects, reworks, scrap) and supply quality. Customer returns reveal quality satisfaction, but offer an insufficient indication of internal quality performance. Firms may have poor internal systems, but provide quality products by following stringent checks at the end of processes. Here quality is generated at a cost. Low customer returns need to be supported by low defects and strong supplier quality if firms are to manufacture low cost, quality products.

3. Value chain flexibility/ reliability

10. Customer lead times: From finished goods (domestic & international)

11. Customer lead times: From production (domestic & international)

12. On time and in full delivery to customers

13. Supplier lead times (domestic & international)

14. On time and in full delivery of suppliers

Value chain flexibility/reliability is determined by the speed at which a firm accepts a customer order & consistently converts this to a delivered product. Key value chain variables are the flexibility/reliability of its suppliers, and the flexibility/reliability of the interface with its own customers. Given the complexity of production flexibility & reliability issues, these are dealt with separately as Market Driver 4.

4. Operational flexibility/ reliability

15. Manufacturing throughput times

16. Production time lost to machine/tool changeovers

17. Production time lost to machine/tool breakdowns

18. Predictive/preventative maintenance as a % of total maintenance time

Measuring operational flexibility at firms (and linked to this their operational reliability) is critical. Operational flexibility contributes to the responsiveness of a firm, and also to a large extent to its cost control, quality and delivery reliability. Some of the major firm-level flexibility measures are included under other market drivers (e.g. WIP), but additional key measures also highlight the extent of a company’s operational flexibility and these are focused on here.

5. Human resource development

19. Training expenditure 20. Formal off-line training per

employee category 21. Employee suggestions

received and implemented 22. Labour turnover rates 23. Staff turnover rates 24. Management turnover rates 25. Absenteeism rates

OEM demands are becoming more onerous. Whether firms fail or grasp the opportunities afforded by these demands depends on their resource use, with the most critical of these their human resources. The four dimensions to change are manpower, machines, materials and methods, but it is the first that determines ability to deal with the others. Analysing whether firms are investing in employees, fostering continuous improvement and generating worker commitment is thus critical.

6. Product development

26. R&D expenditure 27. Contribution of new products

to total sales

A success determinant for any firm is its ability to bring new products to market. Component firms are no different, although the new product development process is complex given global lead sourcing arrangements. It is thus important to disaggregate R&D spending (an indication of investment in new product development) from the proportion of sales from new products (an indication of the life cycle of products being manufactured at firms).



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As highlighted in the table above, the market driver methodology gives rise to 27 core measures, which automotive component manufacturers should be using to assess their global competitiveness. It is these indicators that constitute the core focus of this statistical best practice Yearbook. The formulae underpinning each of the measures are outlined below, with the numbers in brackets matching the sequencing of the operational performance measures listed in the market driver table. 1.2.1. Cost control measures (1) Total inventory holding:

Turnover for current year Value of total inventory holding at year end = Stock turns per year, THEN

Operating days per annum

Stock turns per annum = Total inventory days

For (2) Raw Materials, (3) WIP and (4) Finished Goods replace “Value of total inventory holding” with value of Raw Materials, WIP and Finished Goods respectively. The sum of these three inventory types will equal the value of total inventory holding. 1.2.2. Quality performance (5) Customer return rate: Number of units returned by customers in year

Total number of units sold in year x 1,000,000 = Customer Return Rate PPM OR If an extremely wide range of products is manufactured and unit values vary so much that individual returns skew unit customer returns enormously then the following may be used:

Value of units returned by customers in year Value of units sold in year x 1,000,000 = Customer Return Rate PPM

(6) Internal reject rate:

Number of manufactured units rejected through inspections in year

Total units manufactured in year x 100 = Internal Reject Rate (%)

OR if an extremely wide range of products is manufactured and unit values vary so much that individual rejects skew unit reject rates enormously then the following may be used:

Value of manufactured units rejected through inspections in year

Total value of units manufactured in year x 100 = Internal Reject Rate (%)



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(7) Internal scrap rate:

Value of material scrapped during production in year Total value of material purchases in year x 100 = Internal Scrap Rate (%)

(8) Internal rework rate: Number of manufactured units reworked as a result of

defects in year Total number of units manufactured in year

x 100 = Internal Rework Rate (%)

(9) Supplier return rate:

Number of units returned to suppliers in year Total number of units purchased in year x 1,000,000 = Supplier Return Rate PPM

OR if an extremely wide range of products is manufactured and unit values vary so much that individual returns skew unit supplier returns enormously then the following may be used:

Total value of units returned to suppliers in year Total value of units purchased in year x 1,000,000 = Supplier Return Rate PPM

1.2.3. Value chain flexibility/reliability (10) Customer lead time performance – Finished goods: This represents the average time taken from the placement of an order by a customer to the delivery of product (when the product is drawn from finished goods stock). Domestic and international customer performance is separated for our calculations, but the formula remains the same.

(11) Customer lead time performance – Production: This represents the average time taken from the placement of an order by a customer to the delivery of the product (when the product has to be manufactured and no finished goods are available). Domestic and international customer performance is separated for our calculations, but the formula remains the same. (12) Customer delivery reliability:

Number of on time and in full deliveries to customers in year

Total number of deliveries to customers in year x 100 = On time and in full deliveries (%)

(13) Supplier lead time performance: This represents the average time taken from the placement of an order with a supplier to their delivery of the product. (14) Supplier delivery reliability:

Number of on time and in full deliveries from suppliers in year

Total number of deliveries from suppliers in year x 100 = On time and in full deliveries (%)



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1.2.4. Operational flexibility/reliability

(15) Average throughput time: The average time taken to manufacture the five major products manufactured by the company from the start of production to the end of production. (16) Production time lost to machine/tool changeovers:

Total production time lost due to machine and tool changeovers in year

Total production time in year x 100 = Machine & tool changeovers as a

% of production time (17) Production time lost to machine/tool breakdowns:

Total production time lost due to machine and tool breakdowns in year

Total production time in year x 100 = Machine & tool breakdowns as a

% of production time

(18) Predictive/preventative maintenance as a % of total maintenance time: The proportion of total maintenance time logged at the firm that is predictive and/or preventative as opposed to breakdown oriented, e.g. if 2,000 maintenance hours are logged in a plant in a given year, with 1,000 of these preventative and/or predictive and 1,000 due to breakdowns, the % performance will be 50%.

1.2.5. Human resource development (19) Training as a % of total remuneration: Include only pure training costs (course related costs) and dedicated training personnel costs, but exclude any skills levy payments, loss of production time, travel and accommodation costs from the calculation. The formula for calculating training expenditure as a % of remuneration rates is:

Total training expenditure at company in year Total remuneration (wages & salaries) in year x 100 = Training expenditure as a % of

remuneration (20) Formal off-line training per employee category: Number of days spent on formal off-line training by employee category, e.g. if production workers received an average of 40 hours formal off-line training in 2002 and worked 8 hours per day, then their formal off-line training would equate to 5 days. (21) Employee suggestions received and implemented: Total number of employee suggestions received

in year Average number of employees in year

= Number of suggestions received per employee

Total number of employee suggestions

implemented in year Average number of employees in year

= Number of suggestions implemented per employee



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(22) Labour turnover rate:

Total number of labourers dismissed/resigned in year Average number of labourers employed in year x 100 = Labour turnover rate (%)

Retrenchments and retirements must be EXCLUDED from this figure. ‘Labourers’ include medium, long-term contract labour but excludes casuals.

For (23) staff and (24) management turnover rates replace “average number of labourers employed in year” with number of staff and managers respectively. (25) Absenteeism rate: Total number of man days lost due to employees not being

at work in year Total number of man days available to company in year

x 100 = Absenteeism rate (%)

Only holiday leave should be EXCLUDED from this figure – absenteeism includes compassionate and sick leave.

1.2.6. Product development

(26) Expenditure on own R&D activities: This includes all costs associated with new product development including R&D staffing and facility costs. (27) Contribution of new products to past year sales: Total value of sales in year from products

released over past 12 months Total value of sales in year

x 100 = Contribution of new products to sales (%)

1.2.7. Financial performance findings

Apart from the competitiveness measures explored in the Yearbook, some attention is also given to the financial performance of firms represented in the database. The measures explored are their sales growth, their profit levels before income tax and finally their employment growth over the last five years. Whilst these findings are interesting to include in any benchmarking exercise in that they offer an indication of firm health (hence their inclusion), they simply reveal firm-level competitiveness performance and market conditions in previous years, and are a poor indication of present and future competitive capacity. Their formulae are listed below:

(28) Sales growth over the last five years: Sales growth over the period 1999 to 2003 indexed in domestic currency. (29) Profit levels before income tax:

Profit before income tax for year Turnover for year x 100 = Profit before income tax (%)

(30) Employment growth over the last five years: Indexed employment growth over the period 1999 to 2003.



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Location of firms participating in the Global Best Practices Benchmarking Programme (n=84)

76%

24%

Developing economies Developed economies

Disaggregation of firms participating in the Global Best Practices Programme by firm size - Based on number of employees (n=84)

25%

23%

52%

1-150 151-250 251+

1.3. Profile of firms in the database

The total population included in the Global Best Practices Database as of the end of January 2004 is 84 firms. It is important to outline the profile of these firms as this highlights the representivity and biases of the dataset. The population is therefore disaggregated here according to the six profile criteria listed below: 1. Geographical location 2. Market focus 3. Size (by employment) 4. Ownership 5. Automotive sub-sector 6. Operating parameters Geographical location The 84 automotive component manufacturers3 in the total population are based in six economies – Western Europe, Eastern Europe, South Africa, Malaysia, Brazil and Australia. The West European and Australian based firms are categorized as “developed economy” in the database and total 20 or 24% of firms. Of the total population, 64 firms (or 76%) are categorized as “developing economy”, with approximately two-thirds of these firms based in South Africa and the remainder in Eastern Europe, Brazil and Malaysia. The proportion of the database comprised of developed and developing economy firms is presented in the accompanying figure.

Firm size In terms of the total range of the population, the smallest firm employed only 18 people in 2003, whilst the largest firm in the population employed just under 4,500. The range for sales turnover is similarly large with the smallest firm turning over only US$1.6m in 2003 versus the largest firm turning over an impressive US$666.1m. If one disaggregates the total population by employment level, a clear spread is evident. As highlighted in the figure, 25% of the population (i.e. 21 firms) 3 Please note that questionnaires were completed on a firm basis, with this usually inclusive of only one plant. In certain instances a firm is comprised of two or three plants and in these rare instances the data reflects the aggregated performance of the firm rather than simply the individual plants.



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Sub-sector breakdown of firms participating in the Global Best Practices Programme (n=84)

18%

12%

13%

8%

7%

5% 2%

35%

Interior/exterior trim Powertrain parts Metal forming/fabricationElectronics/harnesses Glass Foundries/forgesTyres Paint

employ 150 or less employees, whilst 23% (19 firms) employ 151 to 250 and 52% (44 firms) employ 251 or more. Total employment for the entire population of 84 firms is 36,699, giving an average of 436.9 employees per firm. Automotive sub-sector Given the “wide footprint” of the global automotive components industry, it is unsurprising to note the diverse range of sub-sectors represented in the Global Best Practices database. As highlighted in the figure below, for the purposes of more precise classification, the 84 firms in the population have been disaggregated into seven sub-sectors: Metal forming/fabrication (35% of the population, or 29 firms); interior/ exterior trim (18%, 15 firms); electronics/ harnesses (13%, 11 firms); glass (8%, 7 firms); foundries/forges (7%, 6 firms); and powertrain parts (12%, 10 firms). The remaining 7% of firms in the database are tyre (four firms) and paint manufacturers (two firms). Unfortunately these sub-sectors are not large enough for disaggregation purposes, hence their exclusion from the disaggregated data in this yearbook4. Tyre information is however included in the aggregated figures.

Some of the core products covered under each of these sub-sector headings are outlined below:

Metal forming/fabrication: Axles, prop shafts, roll bars, bull bars, fuel tanks, gear locks, clutches, springs, torsion bars, exhaust systems, exhaust components, catalytic converters, shock absorbers, spare wheel carriers, seat frames Interior/exterior trim: Door panels, parcel trays, arm rests, floor mats, sun visors, headlinings, carpets, bumpers, seats, seat fabric, high density foam, wheel caps Electronics/harnesses: Alarms, wiring harnesses (body, cowling and standard types), immobilisers, central locking mechanisms, electric window regulators Glass: Laminated windscreens, toughened side glass, rear lights and vents Foundries/forges: Cylinder heads, manifolds, raw castings (forged and cast products) Powertrain parts: Radiators, heaters, condensers, evaporators, oil, air and fuel filters, spark plugs

4 The policy at B&M Analysts is to only provide sub-sector data when a minimum of five firms is represented in the dataset.



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Market focus of firms participating in the Global Best Practices programme (n=84)

66%

19%

15%

OEMs Aftermarket Other component firms

Ownership of firms participating in the Global Best Practices Programme (n=84)

60%

40%

Local Multinational

Market focus The majority of the firms in the Global Best Practices Database are focused on supplying Original Equipment Manufacturers (OEMs), although a significant proportion are primarily aftermarket focused (i.e. more than 50% of their sales are directed to the aftermarket) and a small number are principally 2nd tier suppliers to 1st tier automotive component firms. This is captured in the adjacent figure. As revealed, 66% of the population (55 firms) are OEM focused, with 19% (16 firms) aftermarket focused and 15% (13 firms) principally suppliers of components to other component manufacturers.

Ownership Given the rapid globalisation of the automotive industry, it is perhaps unsurprising to note that a substantial number of Multinationals are represented amongst the firms in the Global Best Practices Database, with 40% (34 firms) either fully or majority owned by Multinational Corporations. The balance (60% or 50 firms) is comprised of locally owned firms that are either completely independent operations, parts of national holding companies or majority locally owned firms that have an equity relationship with a Multinational. This is graphically highlighted above.

Operating profile The operating profile of the firms represented in the Global Best Practices Programme database is presented in the table below. As revealed, the firms operated for an average 245.36 days in 2003, with the average shift configuration being 2.03 shifts per day of 8.24 hours duration. In addition, the firms exported an average of 20.06% of their sales, whilst importing 40.25% of their total purchases. Finally, an average level of unionization amongst the firms was 58.78% in 2003. Operating profile of firms (n=84)

Operating element Average performance in 2003 Operating days per annum 245.36 days Shifts per day 2.03 shifts Hours worked per shift 8.24 hours Exporting levels (as % of sales) 20.06% Importing levels (as % of total purchases) 40.25% Unionisation of workforce 58.78%



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Explanation of statistics used: Average (mean): This refers to the mid-point of the database calculated byadding each of the company performance findings together and then dividingthe total by the number of firms in the database Median: This refers to the mid-point of the database calculated by looking ateach of the company performance findings in the database and choosing thenumber that sits exactly in the middle of the performance spread Percentiles: Like the median, this is also based on performance spread in thedatabase. The focus is not, however, on the mid-point, but on unit values atspecific intervals, e.g. the 90th percentile refers to the unit value separating thetop 10% of performers in the database and the rest. Similarly, the 30%percentile is the point marking the performance of the bottom 30% of firms. Quartiles: This works in the same way as percentiles, except thedisaggregation point is different. The upper quartile refers to the pointseparating the top 25% of performers from the rest, whilst the lower quartilerefers to the point separating the bottom 25% of performers from the rest.

Summary As revealed in this sub-section, the population group represented in the Global Best Practices Programme database is far from homogeneous, with this evident in terms of all the profile areas explored. There is clear variance in terms of geographical location, firm size and ownership, as well as in terms of sub-sector of operation and market orientation. The diversity of the total population is however simply reflective of the general diversity of the global automotive components industry. Whilst the detailed statistical findings presented later in this yearbook are we believe an invaluable indication of performance standards evident in the automotive components industry, they do need to be understood with the variance and average operating profile of the total population in mind. This is the main reason for the disaggregation of the findings in Section 3 through 6.

1.4. Reading the statistics presented in Sections 2 through 6

The data presented in the following sections of this Yearbook are analysed in terms of their spread, with the aggregated performance data analysed by percentile, quartile, median and mean (average). By presenting the data in this manner firm representatives reading this yearbook will be able to clearly ascertain where in the spectrum of best practice performance their particular company lies.

Using total stock holding as an example. The average (mean) performance level for the dataset is 38.76 operating days, with the median sitting at 33.5 operating days. These mid-point indicators illustrate at what point your company needs to be performing to be considered an “average performer”. If your performance is well ahead of this, at say 22 days, then you will be



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intrigued to find out where you stand in relation to the top performing firms in the dataset. In this example, you would be sitting at somewhere between the 70th and 80th percentile, meaning your performance is ahead of about 75% of the firms in the database. Whilst this suggests strong performance, to be a true leader, you would need to perform at 11.94 days, which is the 90th percentile mark, i.e. the level at which you would be ahead of the performance of 90% of the firms in the database. The purpose of the Yearbook is to identify what the level is and to give you a target against which you can drive management action. Using a negative example, you may discover that your total inventory holding is 77 operating days, thus placing you in the bottom 10% of firms. What then? Well, the data will give you a clear reference point against which you can motivate for change and more importantly provide your management team and/or colleagues with improvement targets to move to the 20th (57.48 days) and 30th (45.34 days) percentile over a given period of time. There may of course be mitigating factors for particularly weak or strong performance against the overall database averages. For example, internal scrap rates are generally much higher in a glass manufacturing plant than in a metal forming/fabrication plant. There is therefore a need to analyse your performance in relation to not only overall performance levels (Section 2), but also in relation to those firms in your sub-sector (Section 3), that are located in the same type of economy as yourself (Section 4), share your market focus (Section 5) and that match your firm-size (Section 6). For these disaggregated categorizations the statistical interrogation of data is less extensive due to the smaller population sizes. The key measures explored are 10th and 90th percentiles, upper and lower quartiles and finally mean and medians. By interrogating your performance in relation to the aggregated statistics, as well as the disaggregated data, your comparative competitiveness in relation to the measure should be unequivocal. You will know exactly where you stand and what the performance targets are if you are to elevate yourself to the next level. By aggregating your individual performance in relation to each of the core competitiveness measures explored in the yearbook you should find yourself in a position whereby you can evaluate your competitiveness at a market driver level, i.e. whether your company strength lies in cost control, quality performance, or value chain or operational flexibility, etc. An insightful one-page competitiveness self-assessment sheet is attached as an appendix to the yearbook to enable you to do this, so please make use of it.

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