International Accounting and Finance Master Thesis No 2001:12

Performance Measurement in Entrepreneurial Organisations

-An Empirical Study of Swedish Manufacturing Firms

Per Mattila & Mikael Åhlqvist

Graduate Business School School of Economics and Commercial Law Göteborg University ISSN 1403-851x Printed by Elanders Novum AB

Abstract The concept of entrepreneurship has attracted increased interest in recent years - within the field of business as well as in society as a whole. However, our knowledge of how management accounting - including the branch of performance measurement - is used in the entrepreneurial context is practically non-existent. The aim of this study is to enhance our understanding of how systems of performance measurement are designed and used in entrepreneurial organisations. A survey was conducted on the design and use of performance measurement systems in twelve Swedish manufacturing firms, all of which had experienced high organic growth. The findings show that performance measurement systems play a significant role in entrepreneurial organisations. This is reflected in the use of a large number of measures, a frequent reporting of the measures, and a relatively high variety of business aspects measured. In contrast with the normative literature, the different uses of performance measurement are mainly confined to operative and internal areas of business. The performance measurement was also studied in relation to five firm characteristics: entrepreneurial orientation, firm performance, firm size, firm age, and firm ownership. The findings indicate that the variables have, in some aspects, an effect on the performance measurement systems used by the firms. Key Words: performance measurement, performance measurement systems, entrepreneurship, entrepreneurial organisations, manufacturing industry

Acknowledgements First of all we would like to thank our tutor, Christian Ax, who has shown great patience and been a major source of inspiration. Thank you for challenging us and helping us to bring our work to a higher academic level. We would also like to show our gratitude to Johan Hammar who has been a great source of knowledge in the area of entrepreneurship. This thesis would not have been the same without your initial help. We also owe a great deal of gratitude to Seraj Agahi who designed the web questionnaire and provided us with space on a server. Thank you for the help you have given us, you saved us a lot of time. Also many thanks to all the firms, the Managing Directors and Financial Managers that have sacrificed their valuable time for interviews and answered the web questionnaires. Your time and sacrifices have been invaluable to us. Gothenburg, 7 December 2001 Per Mattila & Mikael Åhlqvist

Table of Contents 1 INTRODUCTION ..........................................................................................................1

1.1 BACKGROUND ...........................................................................................................1 1.2 RESEARCH ISSUE AND OBJECTIVES OF THE STUDY ....................................................2 1.3 POTENTIAL CONTRIBUTIONS OF THE STUDY ..............................................................4 1.4 SCOPE AND LIMITATIONS...........................................................................................4 1.5 DEFINITION OF KEY CONCEPTS..................................................................................5

2 METHODOLOGY .........................................................................................................7 2.1 RESEARCH APPROACH ...............................................................................................7 2.2 DATA COLLECTION....................................................................................................8

2.2.1 Literature Review..............................................................................................8 2.2.2 Choice of Data Collection Method ...................................................................8 2.2.3 Choice of Survey Population ..........................................................................11 2.2.4 Choice of Survey Questions ............................................................................11

2.2.4.1 Questions for the Telephone Interviews .....................................................11 2.2.4.2 Questions in the Web Questionnaire ..........................................................12

2.2.5 Test of Survey Questions.................................................................................13 2.2.6 Sample of Studied Firms.................................................................................14 2.2.7 The Selection Criteria.....................................................................................16 2.2.8 Choice of Respondents....................................................................................19 2.2.9 Conduct of the Telephone Survey and Web Survey ........................................20

2.3 MEASURES OF FIRM CHARACTERISTICS...................................................................21 2.4 RESEARCH EVALUATION .........................................................................................22

2.4.1 Validity............................................................................................................22 2.4.2 Reliability........................................................................................................22

3 FRAME OF REFERENCE..........................................................................................24 3.1 ENTREPRENEURSHIP ................................................................................................24 3.2 ORGANISATIONAL ENTREPRENEURSHIP...................................................................25

3.2.1 Entrepreneurial Strategy ................................................................................26 3.2.2 Entrepreneurial Orientation...........................................................................27

3.3 PERFORMANCE MEASUREMENT...............................................................................28 3.3.1 Introduction ....................................................................................................28 3.3.2 Normative Literature on the Design and Use of Performance Measurement 29 3.3.3 Empirical Literature on the Design and Use of Performance Measurement .33

4 THE DESCRIPTIVE STUDY – RESULTS AND ANALYSIS................................37 4.1 THE DESIGN OF PERFORMANCE MEASUREMENT SYSTEMS ......................................37

4.1.1 Categories of Performance Measures and Their Importance ........................37 4.1.2 Performance Measures Used..........................................................................40 4.1.3 The Frequency of Use .....................................................................................41

4.2 THE USE OF PERFORMANCE MEASUREMENT SYSTEMS............................................42 4.2.1 Different Uses of Performance Measurement ................................................42 4.2.2 Measures and Different Uses..........................................................................44 4.2.3 Users of Performance Measurement ..............................................................45 4.2.4 Performance Measures Used by Different Actors ..........................................46

4.3 PERFORMANCE TARGETS .........................................................................................46 4.4 THE USE OF ‘NEW’ MODELS IN MANAGEMENT ACCOUNTING.................................47

5 THE EXPLANATORY STUDY – RESULTS AND ANALYSIS ............................ 49 5.1 ENTREPRENEURIAL ORIENTATION........................................................................... 49

5.1.1 Depiction of the Population............................................................................ 49 5.1.2 Survey Results and Analysis ........................................................................... 50

5.2 FIRM PERFORMANCE ............................................................................................... 51 5.2.1 Depiction of the Population............................................................................ 52 5.2.2 Survey Results and Analysis ........................................................................... 52

5.3 FIRM SIZE ................................................................................................................ 53 5.3.1 Depiction of the Population............................................................................ 54 5.3.2 Survey Results and Analysis ........................................................................... 55

5.4 FIRM AGE ................................................................................................................ 56 5.4.1 Depiction of the Population............................................................................ 56 5.4.2 Survey Results and Analysis ........................................................................... 57

5.5 FIRM OWNERSHIP .................................................................................................... 58 5.5.1 Depiction of the Population............................................................................ 59 5.5.2 Survey Results and Analysis ........................................................................... 59

5.6 SUMMARY OF RESULTS AND ANALYSIS................................................................... 61

6 CONCLUSIONS........................................................................................................... 63 6.1 THE DESCRIPTIVE STUDY ........................................................................................ 63 6.2 THE EXPLANATORY STUDY ..................................................................................... 65 6.3 SUGGESTIONS FOR FUTURE RESEARCH.................................................................... 66

REFERENCES ..................................................................................................................... 68

APPENDIX 1 - SEARCH STRINGS

APPENDIX 2 - TRANSLATION OF QUESTIONS ABOUT PERFORMANCE MEASUREMENT

APPENDIX 3 – TRANSLATION OF THE COVER LETTER IN THE E-MAIL WITH WEB QUESTIONNAIRE

APPENDIX 4 – TRANSLATION OF WEB QUESTIONNAIRE

APPENDIX 5 - THE BRANCHES USED IN THE SAMPLE POPULATION

APPENDIX 6 – THE SIZE OF THE SAMPLE POPULATION

APPENDIX 7 – FREQUENCY OF PERFORMANCE MEASURES

Tables TABLE 2.1. DISTRIBUTION AND NUMBER OF CONDUCTED INTERVIEWS AND ANALYSED FIRMS 16 TABLE 5.1. AVERAGE NUMBER OF MEASURES USED ................................................................50 TABLE 5.2. AVERAGE NUMBER OF MEASURES REPORTED PER PERIOD .....................................51 TABLE 5.3. AVERAGE NUMBER OF MEASURES USED ON EACH LEVEL.......................................51 TABLE 5.4. AVERAGE NUMBER OF MEASURES USED ................................................................52 TABLE 5.5. AVERAGE NUMBER OF MEASURES REPORTED PER PERIOD .....................................53 TABLE 5.6. AVERAGE NUMBER OF MEASURES USED ON EACH LEVEL.......................................53 TABLE 5.7. AVERAGE NUMBER OF MEASURES USED ................................................................55 TABLE 5.8. AVERAGE NUMBER OF MEASURES REPORTED PER PERIOD .....................................55 TABLE 5.9. AVERAGE NUMBER OF MEASURES USED ON EACH LEVEL.......................................56 TABLE 5.10. AVERAGE NUMBER OF MEASURES USED ..............................................................57 TABLE 5.11. AVERAGE NUMBER OF MEASURES REPORTED PER PERIOD ...................................58 TABLE 5.12. AVERAGE NUMBER OF MEASURES USED ON EACH LEVEL.....................................58 TABLE 5.13. AVERAGE NUMBER OF MEASURES USED ..............................................................59 TABLE 5.14. AVERAGE NUMBER OF MEASURES REPORTED PER PERIOD ...................................60 TABLE 5.15. AVERAGE NUMBER OF MEASURES USED ON EACH LEVEL.....................................60 Figures FIGURE 4.1. CATEGORIES OF PERFORMANCE MEASURES AND THEIR IMPORTANCE.................38 FIGURE 4.2. DIFFERENT USES OF PERFORMANCE MEASUREMENT...........................................43 FIGURE 4.3. THE USERS OF PERFORMANCE MEASUREMENT....................................................45 FIGURE 5.1. THE ENTREPRENEURIAL ORIENTATION OF THE FIRMS ...........................................50 FIGURE 5.2. THE PERFORMANCE OF THE FIRMS........................................................................52 FIGURE 5.3. THE SIZE OF THE FIRMS ........................................................................................54 FIGURE 5.4. THE AGE OF THE FIRMS.........................................................................................57 FIGURE 5.5. THE OWNERSHIP STRUCTURE OF THE FIRMS .........................................................59

1 Introduction

1.1 Background Renewal is a presumption for economic development (Johannisson & Lindmark, 1996). The notion of renewal deals with the break-up of old routines and thinking in order to create new ways of acting. Schumpeter (1934) introduced the concept of ‘creative destruction’ to describe the process that consists of both destructive as well as creative activities that lead to economic development. This process of renewal is the very essence of entrepreneurship. By introducing innovations in the form of new products, production processes, and markets, entrepreneurial activities may as a result lead to the creation of new industries and firms (Wiklund, 1998). Entrepreneurship has therefore been described as the fuel for the economy (Cornwall & Perlman, 1990). The concept of entrepreneurship has undoubtedly attracted increased interest in recent years from politicians, business people, and academics. During the past decade, entrepreneurship has been exalted as a necessity for society as a whole, as well as for specific organisations and industries. It appears as if entrepreneurship, as well as entrepreneurs, has an important role to play in today’s society (Czarniawska-Joerges & Wolff, 1991; Spilling, 1998; Landström, 1999). In a time when unemployment rates are high, when market globalisation is increasing and when environmental changes are escalating, the need for entrepreneurship becomes understandable. Politicians struggling with unemployment ask for and try to stimulate increased entrepreneurship - mainly with the aim of increasing the number of start-ups. Businesses, on the other hand, confronted with fierce global competition tend to regard entrepreneurship as a way of staying competitive and alert (Lövstål, 2001). The interest in entrepreneurship has also been reflected in the academic debate (Johannisson & Landström, 1999). Within the field of business, an increasing number of studies have been presented focusing on either the achievement of entrepreneurial processes (Gaddefors, 1996; Hjorth, 1995) or the conditions for entrepreneurship in different contexts, such as education (Johannisson et al., 1997) or in regions (Davidsson, 1996). The interest in studying

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entrepreneurship within existing organisations and not only individuals has, during the past decades, increased (Landström, 1999). Moreover, there have been several attempts to conceptually develop a general theory of entrepreneurship (Bull & Willard, 1993; Bygrave & Hofer, 1991; Gartner, 1988). Although discussed in a number of different settings, there are contexts in which the issue of entrepreneurship has not been addressed. One of these contexts is the field of accounting. As a matter of fact, it seems to exist an avoidance of entrepreneurship in the accounting literature while, at the same time, accounting seems to be avoided in the entrepreneurship literature (Olson et al., 2000). The need to understand the role and function of accounting within organisational processes has, since the 1980s, been stressed by several accounting researchers. For example, Roberts & Scapens (1985) argues that in order to understand how accounting is integrated in different organisational and societal processes, accounting should be studied in the environment in which it functions. Similarly, in a comment on the reinforcement and development of existing research directions, Scapens & Bromwich (2001) argue that there is a need for more research on management accounting for new organisational forms - hereby highlighting the opportunity for studying accounting in a context such as the entrepreneurial.

1.2 Research Issue and Objectives of the Study Since the initial criticisms were levelled at management accounting in the early 1980s, the methods of management accounting have undergone substantial changes (Bromwich & Bhimani, 1994). Within the field of management accounting, the branch of performance measurement1 has been given special attention in this respect. During the past decade, both academics and practitioners have stressed the importance of a well functioning system of performance measurement in order for firms to thrive, or maybe even survive, in an increasingly competitive environment (Brimson, 1991; Euske et al., 1993; Johnson & Kaplan, 1987). Much criticism has been directed at the traditional systems of performance measurement and their sole focus on financial results

1 For a definition of ‘performance measurement’ and other related concepts, see section 1.5

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and inability to consider the strategic aspects of business (e.g., Dixon et al., 1990; Kaplan & Norton, 1996). The debate on the subject comprises a large number of books and articles on how performance measurement should really be designed and used, including several ‘new’ concepts such as Balanced Scorecard, Performance Pyramid, and Value-Based Management (Kaplan & Norton, 1996; McNair et al., 1990). Subsequently, there have been several studies with the purpose of empirically determining whether the new competitive situation has affected the design and use of systems for measuring performance (Kald & Nilsson, 2000). These studies show, for example, that performance measurement has broadened its earlier focus to include non-financial measures (e.g., Bromwich & Bhimani, 1994; Fitzgerald et al., 1992). However, much of the interest has been directed at larger and well-established firms (e.g., Johansson et al., 1997; Kald & Nilsson, 2000; Stivers et al., 1999). As mentioned above, our understanding of how accounting information is used within the entrepreneurial context is practically non-existant (Olson et al., 2000). Hence, no systematic information or mapping is to be found on the role of performance measurement in connection with entrepreneurship. Bearing in mind the previous discussion, the objective of this study is to illustrate the prevailing practice of performance measurement in entrepreneurial organisations2. The aim is to enhance our knowledge and understanding of how systems of performance measurement are designed and used in organisations characterised as entrepreneurial. This is concretised in the following research objectives:

• What systems of performance measurement are used by entrepreneurial organisations?

• Why are these systems used, i.e. for what purposes are the performance

measurement systems used?

2 For a definition of ‘entrepreneurial organisation’, see section 1.6

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• Are there relationships between the design and use of performance measurement systems and firm characteristics such as entrepreneurial orientation, firm performance, firm size, firm age, and firm ownership?

1.3 Potential Contributions of the Study The aim of this study is to provide ‘new’ knowledge of performance measurement in the context of entrepreneurship. Since this is the first study focusing on the design and use of performance measurement systems in entrepreneurial organisations, one major contribution will therefore be the creation of knowledge of management accounting in a ‘new’ organisational context - the entrepreneurial context. Moreover, the findings may be used as input for future research, for example as a basis for developing hypotheses to be tested on, for example, a larger sample of firms, or firms in other industries or organisational contexts.

1.4 Scope and Limitations The study is limited to formal systems of performance measurement - that is, measurements that are extracted continuously according to a pre-determined plan. Consequently, the study of the informal use of performance measurement systems is left outside the scope of this thesis. This limitation is made due to the nature of the research objectives of the study and the following methodological considerations. For example, the complex nature of the informal use of performance measurement could be expected to be hard to capture by the use of telephone interviews, which is the choice of method for data collection in this study. The study is further limited to a single industry - the manufacturing industry. This restriction is mainly due to time limitations, but also with the argument that it makes it possible to avoid an overly heterogeneous population. The importance of working with a population of firms that have similar industry characteristics is stressed by several academics (e.g., Ask & Ax, 1997; Miles & Snow, 1978; Samuelson, 1990). Another motive for studying the manufacturing industry is that there exists a current interest and public concern over the competitive status of manufacturing firms (Zahra et al., 1999).

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The study is also limited to small and medium sized firms. Some researchers argue that high growth firms that are growing organically, which is an important factor for identifying entrepreneurial organisations, are most likely found in these classes of size (Davidsson & Wiklund, 2000). Moreover, most studies in management accounting to date have been focused on large firms, and the published work concerning smaller ones has been somewhat sporadic (Mitchell & Reid, 2000). It should further be noted that the focus of the study is on the design and use of performance measurement systems in organisations characterised as entrepreneurial. Consequently, the individual entrepreneur(s) as such is left outside the scope of this study and therefore will not be discussed.

1.5 Definition of Key Concepts Entrepreneurial organisations, entrepreneurial orientation and performance measurement, are essential concepts of this study and need to be clearly defined. It may be helpful to define these concepts at the outset to avoid the risk of confusing the concepts and in order to make the text more easily understandable.

• Entrepreneurial organisation relates to firm actions of innovation, risk taking and proactiveness, which are considered as crucial dimensions of entrepreneurship. In this study the term entrepreneurial organisations is defined as “An entrepreneurial firm is one that engages in product-market innovation, undertakes somewhat risky ventures, and is first to come up with ‘proactive’ innovations, beating competitors to the punch". (Miller, 1983)

• Entrepreneurial orientation (abbreviated EO) is an empirical term that

is operationalised and measured. Entrepreneurial orientation refers to the “Managing Directors’ strategic orientation reflecting the willingness of a firm to engage in entrepreneurial behaviour”. The term is best described as the strategic orientation or outlook of the firm. (Wiklund, 1998) EO is further discussed in chapter 3.2.2.

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• Performance measurement refers to the measurement of performance of an activity or part of a firm, for example operating income, product quality, or customer satisfaction (Ax et al., 2001). Consequently, this study focuses on a wide use of performance measurement, including measurements of both financial and non-financial nature.

• Performance measures are the specific numbers or quantities used to

present concentrated information about firm performance received from the measurement of activities or parts of the firm (Mossberg, 1977).

• Performance measurement systems involve a number of performance

measures used to systematically measure the performance of the firm. The systems are the formal, information based routines and procedures used to maintain or alter patterns in organisational activities (Simons, 1995).

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2 Methodology The creation of knowledge is a process (Johansson Lindfors, 1993) and the method is a tool, a way of solving problems and developing new knowledge (Holme & Solvang, 1997). For the knowledge to be considered as scientific, it has to be created in accordance with methods for scientific work (Ask & Ax, 1997). Consequently, the method is a tool used by the researcher in the process of developing new scientific knowledge. This chapter deals with methodological considerations related to the study. The chapter includes the research approach, the complete data collection method, and research evaluation.

2.1 Research Approach This thesis consists of a descriptive and an explanatory study related to the research objectives presented in the introductory section. The descriptive approach is primarily used when the researcher is interested in describing the characteristics of a specified problem area (Lekvall & Wahlbin, 1993). As the knowledge in the area of performance measurement in entrepreneurial organisations is practically non-existent (Olson et al., 2000), the main objective of this study is to describe the design and use of performance measurement systems in entrepreneurial organisations. The explanatory approach is primarily used when the researcher wants to establish correlations between a number of variables, such as the relationship between a firm’s entrepreneurial orientation and its performance measurement systems (Lekvall & Wahlbin, 1993). The explanatory part of the thesis intends to investigate possible relationships between a number of variables related to firm characteristics and the performance measurement systems used by the firms. The variables used were entrepreneurial orientation, firm performance, firm size, firm age, and firm ownership. In section 2.3 the measures of firm characteristics are discussed. These firm characteristics are defined and operationalised in the explanatory result and analysis chapter (Chapter 6).

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2.2 Data Collection Data collection refers to the way data is collected for the purposes of scientific research (Lekvall & Wahlbin, 1993). This section contains a description of the complete data collection method utilised in the study.

2.2.1 Literature Review

The study started with the collection of secondary data. The literature review, “Accounting and Entrepreneurship – A Review and Discussion of the Scientific Literature in the 80s and 90s” by Olson et al. (2000), was the starting point for the collection of secondary sources. Several other literature reviews in the area of accounting (e.g., Langfield-Smith, 1997; Otley et al., 1995; Shields, 1997) and entrepreneurship (e.g., Landström & Johannisson, 2001; Zahra et al, 1999) were thoroughly studied to further our understanding of the research issue. The secondary sources had to be critically examined as the material may have been gathered to address a different problem in the field of management accounting. Moreover, many secondary sources did not clearly describe features such as: the objective of the studies, the data collection method used, and the analysis and interpretation of the data, which made it difficult to assess their usefulness. This problem has been addressed by triangulating the secondary data by the use of a number of independent sources. These sources were collected from academic journals through database searches (ABI/Inform, General Business File and IDEAL) and from other literature (doctoral theses, licentiate theses, etc.) through searches in LIBRIS and GUNDA at Gothenburg University. The searches were mainly made on entrepreneurship and management accounting/performance measurement and combinations of these. The search strings used can be found in Appendix 1.

2.2.2 Choice of Data Collection Method

There are a number of different data collection methods at hand and when deciding on which method to use in a study a number of various factors have to be considered (Yin, 1994). Each method has its own advantages and disadvantages. Therefore, it is of importance to evaluate the methods’ appropriateness in regard to the research problem and the presumptions in each case (Ask & Ax, 1997). The advantages and disadvantages of the data collection methods were evaluated with regard to the objectives of the study,

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the research issue, the time frame, the availability of data, and the characteristics of the respondents. For this study, surveys such as postal questionnaires, web questionnaires, telephone interviews and site visits were evaluated as these seemed to be viable methodological options. From this evaluation two methods were considered appropriate with regard to the characteristics of the study – namely, telephone interviews and the use of a web questionnaire. The respondents in the study were mainly Managing Directors in small and medium sized firms, which had grown rapidly during the last three years and where their level of knowledge of performance measurement was not known. It is common knowledge that the loss of respondents is high for postal questionnaires (Lekvall & Wahlbin, 1993), and the risk for an even higher loss of respondents was imminent, as these (being mainly Managing Directors of small and medium sized firms) may not understand the meaning of all the questions. Therefore, postal questionnaires were considered inappropriate. It was of great importance that the repondents understood the questions, and potential explanations are best given in a discussion-like situation. As stated above, the studied population consisted of firms that have grown rapidly during the last three years. These firms had to fulfil an extensive number of criteria to qualify for the study as entrepreneurial organisations (see section 2.2.7 ‘The Selection Criteria’). A case study of one or a few objects by the use of site visits would provide a too narrow picture of the design and use of the performance measurement systems in the firms. Another reason for not conducting site visits was the aim to include a ‘larger’ number of firms, and bearing in mind that there are a limited number of rapidly growing firms in Sweden in various geographic locations, the site visit approach would not pass the cost/benefit criteria. Hence, the site visit approach was rejected in favour of the telephone survey method. Surveys are commonly used for research that is based on either a descriptive or explanatory research approach (Lekvall & Wahlbin, 1993) and favours questions such as what, who, where, how many and how much (Yin, 1994). The main advantage of the telephone survey method is that it provides an

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opportunity to explain complex and unstructured issues to the respondents, making sure that they have understood the meaning of the questions. A disadvantage is that it may be time consuming to contact the firms and book the interviews. Other aspects considered for the choice of telephone survey as data collection method as follows:

• There was a need to ‘control’ the interview situation as the study focused on small- and medium sized firms. There were questions about concepts of performance measurement that may not be common knowledge among this group of respondents. Hence, the possibility to explain the meaning of these concepts and questions was of great importance.

• It was possible to follow up on the respondent’s answers and make them

explain what they really meant by their answers.

• The higher frequency of answers as compared to a postal questionnaire.

• Long travel distances and high travel expenses could be minimised. Primary data was also collected through the use of a web questionnaire. This questionnaire contained questions about the firm’s market behaviour/ entrepreneurial orientation, and performance (see Appendix 3). These questions, in total 32, used rating scales of the Likert type where the respondent were asked to rate his/her answers. As mentioned, the sample population consisted of firms that have grown rapidly, which indicated that the respondents might have a lack of available time. Therefore, sending the respondents a questionnaire to answer whenever they had the time shortened the telephone interview. The choice of a web questionnaire was mainly based on the fact that the administration is lower compared to postal questionnaires, and it is also easier and less time consuming for the respondents to answer the questions and send them back. It was also easy to remind the respondents if they had not answered the questions. A disadvantage may be that the respondent’s computer literacy could be low. If the respondents indicated that

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there were problems answering the questions over the Internet, the questionnaire was sent via ordinary mail. In the explanatory part of the thesis, the size and age of the firms were two out of five variables analysed in relation to the firms performance measurement systems. The database ‘Affärsdata’ was used to collect the information on these two variables.

2.2.3 Choice of Survey Population

The survey population consisted of Swedish manufacturing firms in the engineering industry according to Statistics Sweden (SCB), and SNI92, the Swedish standard industry classification. A motive for studying a part of the manufacturing industry is that there is a current interest and public concern over the competitive status of manufacturing firms (Zahra et al., 1999). There was also an opportunity to make comparisons with an earlier study from the UK on small and medium sized firms and their use of performance measurement (Bhimani, 1993, 1994; CIMA, 1993). This industry has also been used as a survey population in a great deal of research in management accounting. Normally, the research has been conducted in several sub-industries of the manufacturing industry (Ask & Ax, 1997; Greve, 1999). By limiting the study to the manufacturing industry, it was possible to avoid an overly heterogeneous population. Moreover, it was of great importance to work with a population of firms that had similar industry characteristics (Ask & Ax, 1997; Miles & Snow, 1978) and were working under similar institutional conditions, as the industry factor could have an affect on the result (Samuelson, 1990). Despite these limitations, it is possible to generalise the results to the manufacturing industry by studying several sub-industries within that industry (Greve, 1999).

2.2.4 Choice of Survey Questions

The study consists of two separate parts of survey questions; namely, the questions discussed during the telephone interviews and the questions in the web questionnaire.

2.2.4.1 Questions for the Telephone Interviews These questions focused on the performance measurement of the firm (see Appendix 2) and the point of departure for the selection of these was the

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objective of the study and available knowledge in the studied area. As the knowledge of performance measurement among the respondents was expected to be of varying degrees, it was considered appropriate to develop a well-structured interview guide with a number of questions with fixed answers. This was also supported by the fact that the respondent group was working under constant time constraints. Hence, they would receive an interview guide, which partly comprised questions with fixed answers. However, the interview guide also consisted of a number of broad-ended questions, which were aimed at encouraging discussion. The questions focused mainly on two areas, the design and the use of performance measurement. The structure of the interview guide and several of the questions was, to some extent, drawn from earlier studies in performance measurement (e.g., Kald & Nilsson, 2000). The questions have been reworked, and the literature mainly used for the reformulation of the questions was Ax et al. (2001). The fact that most of the questions and concepts had been validated in earlier studies, provides a more solid base for the interviews and the overall study.

2.2.4.2 Questions in the Web Questionnaire The web questionnaire (see Appendix 3 and 4) was divided into three sections, treating different types of questions. The first section involved questions about market behaviour and the entrepreneurial orientation of the firm. These questions have been developed, used and validated in earlier studies (e.g., Covin & Slevin, 1989; Miller & Friesen, 1982; Wiklund, 1998). Using rating scales graded 1-7, the respondent rated how the firm acts within its market in each of eight dimensions. The eight dimensions assess a firm’s tendency toward product innovation, proactiveness vis-à-vis competitors, and risk taking. The seven-graded scales were added up to an overall entrepreneurial index for the firm3. The index provides an indication of the entrepreneurial orientation of the firm and is, in this study, used to determine whether the firms could be considered as entrepreneurial or not. Firms ending up on the lower end of the

3 Definition of the calculation; (1) Add the numbers for the eight dimensions from the rating scale 1-7 to a total sum. (2) Divide the sum in (1) with eight (the eight questions). The answer equals the firm’s entrepreneurial orientation.

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scale are considered as non-entrepreneurial. The index is also used to identify firms as more or less entrepreneurial, the higher the score, the more entrepreneurial the firm’s orientation. This is discussed further in the explanatory part of the study (Chapter 6). The questions in section two and three were used to measure the performance (effectiveness) of the firm. The researchers have for a longer period been sceptical to the use of objective indicators for the measurement of a firm’s performance. Therefore, this study measures performance in a subjective way by two questions adapted from Greve (1999), which were originally constructed by Govindarajan (1984). Using rating scales of the Likert-type (graded 1-7) the respondent rated how well the firm had succeeded in each of twelve dimensions: sales growth rate, market share, cash flow, operating profit, profit margin, return on investment, new product development, new market development, personnel development, research and development, level of costs, and political/public affairs. Another twelve rating scales (graded 1-5) were used to measure how important it was for the firm to succeed in each respective dimension. The scores from the five-graded scales were used as weights when the scores from the seven-graded scales were added up to an overall performance index for the firm4. The performance index was used to indicate whether the firm had a higher or lower performance. This is further discussed in the explanatory part of the study (Chapter 6).

2.2.5 Test of Survey Questions

Before the actual interviews were conducted, the survey questions were tested on one firm within the survey population. At the test interview, the relevance of the questions was tested along with the disposition of the interview guide and the web questionnaire, as well as the formulations and the answers from the respondent. This test led to a number of changes in the interview guide and the web questionnaire regarding the choice of questions and formulations. An

4 Definition of the calculation; (1) Add the numbers for the twelve dimensions from the rating scale 1-5 together to a total sum. (2) Each rate on the scale 1-7 is multiplied by each rate on the scale 1-5 resulting in a number for each of the twelve dimensions. (3) Add these twelve numbers together to a total sum. (4) Divide the sum in (3) with the total weight from calculation (1). The answer equals the total performance index for the firm. (J. Greve, personal communication, 7 November 2001)

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experienced researcher at the School of Economics and Commercial Law at Gothenburg University also examined and commented on the questions.

2.2.6 Sample of Studied Firms

In order to gain credibility, it is important that the sample of interviewed firms is representative of the studied population. This could also lead to conclusions representative for the total population. However, it has to be noted that the studied firms rely on specific manufacturing methods and each firm has a managerial culture of their own, making it difficult to generalise across firms. Nevertheless, there exists an opportunity to identify aspects common to many organisations. The sample population consisted of active limited Swedish manufacturing firms in the engineering industry, collected from the Swedish database ‘Affärsdata’. It has to be noted that there is a limitation in the database. For the last financial year (2000) approximately 75-80% of the limited firms had registered their annual reports with the Swedish Patent- and Registration Office (PRV) at the date of the data retrieval (Affärsdata, personal communication, 26 October 2001). A population may be viewed as comprising different groups where elements in each group are similar to each other in some way. In those cases, sampling precision may be gained by treating the different groups separately (Aczel, 1996). This study focuses on the engineering industry, which was defined as seven separate sub-industries using the Swedish Industrial Standard Classification Codes (SNI). These sub-industries are: SNI 28 metal; SNI 29 machinery; SNI 30 office and computing machinery; SNI 31 electrical machinery; SNI 32 radio, television and communication equipment; SNI 33 medical and optical instruments; and SNI 34 transport equipment (see Appendix 5). Similar branch selections have been made in earlier research in the area of management accounting (e.g., Ask & Ax, 1997). The sample population was divided into seven groups based on the different classification codes (SNI). By looking at the total number of active limited firms in each of the seven groups, an approximate distribution of the number of firms to be interviewed was made.

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The aim of the empirical study was to interview fifteen companies in total within the seven groups. It should be noted that this is not a statistical study and the aim was not to reach an acceptable level of statistical inference. Rather, the purpose is to address the research problem and reach a high level of quality on the empirical data with the limited resources at hand. Each of the seven sub-industries in the sample was divided into two sub-groups by the size of the firms. The study focuses on small and medium sized firms using the European Unions quantitative definition. Small firms have 10-49 employees and an annual sale of not more than ECU 7 million5. Medium sized firms have 50-249 employees and not more than ECU 27 million in annual sales. The limitation of the study to small- and medium sized firms was mainly due to the fact that high growth firms that are growing organically, an important factor of entrepreneurship, are most likely found in these classes of size (Davidsson & Wiklund, 2000). The very small firms, or micro firms, with 0-9 employees were excluded from the study due to the fact that there is a notable shift in the formality regarding organisation and customers at around 10 employees, which makes micro firms different from small firms (Storey, 1994). The sample was selected by looking at every tenth firm in each sub-group in the database. The firms had to fulfil a number of criteria to be selected (see section 2.2.7, ‘The Selection Criteria’, below). This procedure was performed until the sample population was considered large enough. The total size of the sample was 84 firms (see Appendix 6). The firms in the sample population were contacted over the telephone and a number of questions were asked to determine whether the firm corresponded to additional selection criterion, on which there was no information available in the database. A great number of firms did not correspond to these criteria and a major part were constrained to do an interview due to lack of time. As a result 17 firms were booked for interviews. Out of these 17 booked interviews, 14 were conducted whereas the other three were cancelled due to the respondent’s lack of time. Twelve of these 14 firms were included in the analysis. The other two firms were excluded since they ended up on the lower end of the entrepreneurial index and, thus,

5 Based on the exchange rate in December 31 2000.

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were not considered to be entrepreneurial. The sample selection and the interview booking also aimed at reaching an even distribution between small- and medium sized firms. For the distribution of interviews see table 2.1.

Branch No. of active limited firms

Total no. of interviews

No. of interviews (10-49)

No. of interviews (50-249)

SNI 28 1695 5 3 2 SNI 29 1117 2 0 2 SNI 30 51 1 1 0 SNI 31 306 2 1 1 SNI 32 128 1 1 0 SNI 33 247 0 0 0 SNI 34 239 1 0 1 Total 3783 12 6 6

TABLE 2.1. DISTRIBUTION AND NUMBER OF CONDUCTED INTERVIEWS AND ANALYSED FIRMS As can be seen from table 2.1, no interviews were conducted with firms in SNI 33, the manufacture of medical, precision and optical instruments, watches and clocks. All firms corresponding to the selection criteria were selected from the database and contacted, but a major part did not pass the additional selection criteria and the rest were not able to participate in the study. As a result no interviews were conducted with firms in SNI 33.

2.2.7 The Selection Criteria

The main objective of the study was to describe how the performance measurement systems of entrepreneurial organisations are designed and used. To be able to do that, the entrepreneurial organisations had to be identified. Growth is sometimes assumed to be synonymous with entrepreneurial behaviour; meaning that firms that grow are entrepreneurial firms (Wiklund, 1998). Several researchers state that growth can be seen as a direct proxy for entrepreneurial behaviour (Davidsson, 1989; Naffziger et al., 1994). Wiklund (1998), in his doctoral thesis, concludes that growing firms are also, in most cases, entrepreneurial firms. Therefore, growth was one of the major criteria when selecting the sample population.

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In 1998 NUTEK6 presented an investigation of Swedish growth firms for the period 1993-1996. To select the firms for the investigation, a number of criteria were used and these criteria have been adapted and utilised in this study. Some of the criteria have been changed to better suit the objectives and problem of the study. The following criteria have been used: • The firm has to be a part of at least one of the selected sub-industries, SNI

28-SNI 34. The firm cannot, however, be a part of any other industry. A firm registered both within for example SNI 28 and SNI 25 was excluded from the study.

• The firm has to be a limited firm and have employed at least ten employees

during the last financial year (2000). • The firm must have managed its operations during all four financial years

(1997-2000) and the revenue must not have fallen below 0.5 million SEK during any of these four financial years.

• Firms experiencing growth due to trade in shares and other financial

instruments were not included. • The last financial year should end between 2000-06 and 2000-12. The

length of the financial year should be a normal calendar year (365 days) and firms that have changed their financial year some time between 1997 and 2000 are excluded to avoid misleading effects on the calculated growth.

• The firm should at least have doubled its revenue during the last four

financial years (1997-2000), meaning a yearly average revenue increase of at least 25%7.

6 NUTEK is The Swedish Business Development Agency. 7The studied firms have during the past four years filed four annual accounts to the proper authorities (Patent- och registreringsverket). This means that the revenue growth has occurred in three periods, 1997 to 1998, 1998 to 1999 and 1999 to 2000. If the firm grow with an average of 25% a year the total increase will be (1 + 0.25) * (1 + 0.25) * (1 + 0.25) –1 = 0.953 meaning 95.3% which is an approximate equivalent of a doubling of the revenue over the three year period.

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Growth is, in this study, operationalised by an average revenue increase of at least 25% a year. According to Hoy et al. (1992), revenue is the best way of operationalising growth and is also a measure that many academics use. It is also argued that revenue is a measure commonly used by practitioners (Barkham et al., 1996; Hoy et al., 1992). Another important reason for using revenue instead of the number of employees is that firms often grow without hiring additional employees in proportion with to the overall growth (NUTEK, 1998). The reason for the choice of an average annual growth of 25% a year over a three-year period is that it is an established definition used in several investigations. It is also considered as a proof of growing power within the firm. (NUTEK, 1998) • The growth of the firm during the period (1997-2000) must have been

organic. That is, the firm cannot have grown through reorganisations, mergers, acquisitions, or through other similar actions.

• The growth must be due to the actions of the firm, such as entering new

markets or offering a new product mix, and not due to changes in the environment/market, such as an overall increase in demand.

As stated earlier, growth can be seen as a direct proxy for entrepreneurial behaviour and, thus, growing firms are to be seen as entrepreneurial firms. However, Wiklund (1998) argues that entrepreneurial behaviour and growth are not completely one and the same. He also suggests that researchers aiming at defining entrepreneurial behaviour should recognise this, and use a multi-item measurement of entrepreneurial behaviour. Therefore, the last question above was asked to determine whether the firms fulfil other criteria indicating entrepreneurial behaviour, such as entering new markets or developing new products. Wiklund’s (1998) study shows that growth and other manifestations of entrepreneurial behaviour accompany each other, meaning that firms that are considered to be entrepreneurial along one dimension also tend to be entrepreneurial along other dimensions. By asking the firms this question, the possibilities for determining whether the firms are entrepreneurial should increase. Furthermore:

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• Firms ending up on the lower end of the entrepreneurial index, based on the questions on market behaviour and the entrepreneurial orientation of the firm in the web questionnaire, were excluded from the study. These firms were considered as having a conservative strategic posture and were characterised by low technological and product innovation, a cautious competitive orientation, and a weak risk-taking propensity by the top management (Covin & Slevin, 1989).

• The Managing Director of the firm should have held his/her position during

at least one year and consider him-/herself as having the knowledge to answer the questions about market behaviour and performance during the last three years (1998-2000). The respondent should also consider him-/herself as having the necessary knowledge to answer the questions about the design and use of performance measurement systems within the firm.

The main part of the criteria outlined above was available in the database, but three additional questions had to be asked at the first contact with the firms. These questions were whether the firm had grown organically, whether the growth of the firm could be due to the actions of the firm and not only changes in the environment/market, and how long the Managing Director of the firm had held his/her position. It was also asked whether he/she considered him-/herself as having the knowledge to answer the questions about market behaviour and performance during the last three years, as well as the questions about the performance measurement in the firm. The firms that fulfilled all the above criteria and felt positively about the study were interviewed.

2.2.8 Choice of Respondents

Apart from selecting the right firms, it was also of great importance to select the right respondents. A number of demands were set to identify the suitable respondents for the telephone interviews, as well as for answering the web questionnaire. The questions about performance measurement asked in the telephone interviews was answered by a respondent who:

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• Has good knowledge about the design and use of the performance measurement systems in their firm.

• Has good knowledge of the firms overall operations. The questions on performance measurement were answered by the Managing Director in seven of the twelve interviews, by the Financial Manager in four interviews, and by the Controller in one of the interviews. The questions in the web questionnaire dealt with the market behaviour/ entrepreneurial orientation and the performance of the firm - areas in which the Managing Director of the firm ought to have the best knowledge. Moreover, the measurement scales in the questions about the market behaviour/entrepreneurial orientation are related to the respondents’ self-perception of the firms’ strategy. The Managing Director is, in most cases, involved in developing these strategic questions within the firm and, as a result, is the most suitable respondent of the web questionnaire. Therefore, the respondent of the web questionnaire should: • Consider him-/herself as having the knowledge to answer the questions

about market behaviour/entrepreneurial orientation and performance during the last three years (1998-2000).

The Managing Director answered the web questionnaire in all cases but one, where the Financial Manager answered the questions. This was acceptable since the Financial Manager claimed he had the same knowledge as the Managing Director regarding these questions.

2.2.9 Conduct of the Telephone Survey and Web Survey

The questions on performance measurement that were discussed during the telephone interviews were sent to the respondents via the ordinary mail at least a week ahead of the interview. This provided the respondents with an opportunity to prepare themselves for the interview. After the first contact was made with the firms and the interviews were booked, a shortcut to the web

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questionnaire with an explaining text was e-mailed to the Managing Director (see Appendix 3 and 4). Each interview took between 25 to 60 minutes and was recorded with the respondent’s permission. The recording was necessary as the amount of information from the interviews was high and it was impossible for the interviewer to make all the necessary notes throughout the interview. The recorded interviews were typed up immediately after the interviews and questions that stemmed from the later interview analysis, were followed up by asking the necessary questions via e-mail or telephone. The web survey was followed up by e-mail reminding the respondent’s that had not answered the web questionnaire.

2.3 Measures of Firm Characteristics The explanatory study intended to investigate the possible relationships between a number of variables and the design and use of performance measurement systems. In the literature, a great number of various variables of firm characteristics exist (Ask & Ax, 1997). The variables chosen in this study were entrepreneurial orientation, firm performance, firm size, firm age, and firm ownership. The objective of the analysis was to investigate whether there were differences between firms in relation to these variables, and if the variables affected the design and use of the performance measurement systems. The variables of firm characteristics can be described as dependent variables, while the performance measurement system is the independent variable. To be efficient, a firm has to adapt its structure to its environment; for example, the larger a firm is, the more developed its performance measurement system. However, different variables of firm characteristics could have an effect on the shaping of the performance measurement system. The variables of firm characteristics are used as a means (proxy variable) for investigating the real area of interest (Ask & Ax, 1997), in this case, the design and use of performance measurement systems. The operationalisation of the measures and other methodological issues related to the explanatory study are further discussed in Chapter 5, ‘The Explanatory Study – Results and Analysis’.

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2.4 Research Evaluation There are various sources of mistakes affecting the quality of the study in terms of validity and reliability. To be able to achieve a high level of credibility for the study and the following conclusions, it is important to demonstrate that it is conducted in such a way that it accurately identifies and describes the studied phenomenon.

2.4.1 Validity

Validity is an expression of how well the adopted measurement instrument measures the issues actually meant to be measured in the study. However, it should be noted that there is no objective way of determining to what extent the measurement instrument is valid or not, meaning that the level of validity has to be determined on a subjective basis. (Lekvall & Wahlbin, 1993) If a number of knowledgeable people study the questions in a questionnaire and determine them to be ‘good’ in relation to the purpose of the questions, it is reasonable to assume that there is a degree of validity (Lekvall & Wahlbin, 1993). In this study, a test interview was conducted with one company within the survey population, and an experienced researcher at the School of Economics and Commercial Law at the Gothenburg University also examined and commented on the questions. Moreover, the questions in the web questionnaire have been used and validated in earlier studies (e.g., Govindarajan, 1984; Greve, 1999). This indicates a high face validity, which is an expression for external validity (Ask & Ax, 1997). Internal validity is the logical relationship between an investigation and the available theory in the studied area (Ask & Ax, 1997). This relationship between existing theory and the empirical study was established by a thorough review of the literature in the area. The theoretical framework established throughout that review was used as the basis for the research questions in the two questionnaires, as well as when analysing the results.

2.4.2 Reliability

Reliability is an expression for a measurement instrument’s capability to withstand random effects. A measurement instrument that generates the same or similar results on multiple occasions has high reliability (Lekvall &

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Wahlbin, 1993). It should be noted that it is practically impossible to make several completely consistent investigations, as there will always be a certain level of random effect in all investigations (Ask & Ax, 1997). The use of clearly defined questions in the telephone survey, as well as in the web questionnaire, increases the probability of replicating this study. Moreover, the research method is clearly defined and described in the thesis, and the reliability is also positively affected by the fact that the questions were tested in a test-interview. In general, it could be concluded that the clearer and more stringent the questions are, and the more standardised the measurement method is, the higher the reliability (Ask & Ax, 1997).

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3 Frame of Reference

The frame of reference for this study consists of two main sections. The first section discusses entrepreneurship, entrepreneurial organisations and other related concepts that are of importance for the study. This is followed by a section on performance measurement, which reviews the situation in both the normative and empirical literature.

3.1 Entrepreneurship There does not exist any unitary definition of the concept of entrepreneurship in the research literature (Bygrave, 1989; Cunningham & Lischeron, 1991; Landström, 1999). In fact, the concept has been used to define a wide range of activities, such as creation, founding, adapting, and managing a venture. Hence, entrepreneurship takes many forms and it is not surprising that a consensus has not been reached on the definition of entrepreneurship (Cunningham & Lischeron, 1991). The research in entrepreneurship has a very long history with its roots in economics but has developed into a multidisciplinary field. As a result, entrepreneurship has been viewed from many different perspectives (Cunningham & Lischeron, 1991; Landström, 1999). Stevenson & Jarillo (1990), in a review of the literature on entrepreneurship, divided the research into three main categories: what happens when entrepreneurs act; why they act; and how they act. The first question concerned economists, such as Joseph Schumpeter (1934), and is focused on the effects of entrepreneurship on economic development. The psychological/sociological approach promoted by behavioural scientists is concerned with the second question why, while the last question how has mainly been developed within the area of ‘management studies’ (ibid). As the interest in entrepreneurship increased among management researchers in the 1970s, the focus of the studies turned from the individual to the process of establishment and growth (Landström, 1999). Olson et al. (2000) states that the existing definitions of entrepreneurship have, to a large extent, argued that entrepreneurship is about exploration and exploitation of opportunities (see also Shane & Venkataraman, 2000).

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Exploration is about the process of discovering and exploring business opportunities and may take place in an existing organisation, as well as outside existing organisations in the form of private exploration projects. Exploration projects are assumed to generate organisational growth and, as a result, growth in the society. However, the exploration does not in-itself generate growth; the exploitation generates growth. Entrepreneurship is about growth whether it is caused by innovation of new products or by increased demand on existing products. It is also possible to find entrepreneurial action in the exploitation of new products, as well as of old products. Consequently, the process of defining entrepreneurship becomes a question of defining exploitation. (ibid) As some researchers shifted their focus from the individual to the process, new alternative definitions of entrepreneurship were established. Bygrave & Hofer (1991) define the entrepreneurial process as “all the functions, activities and actions related to the discovery of opportunities and the creation of organisations for the purpose of exploiting the aforementioned opportunities”. In a more recent definition, Shane & Venkataraman (2000) state that entrepreneurship is about “how opportunities to create future goods and services are discovered, evaluated and exploited”. The classic definition of entrepreneurship by Schumpeter (1934) stresses that entrepreneurship has to do with combining resources in new ways that create disequilibrium in the economic system. This means that entrepreneurial firms are innovative to such an extent that they have an impact on the market (Wiklund, 1998). Stevenson (1984) advocates that pursuit of opportunity is the most important component of entrepreneurship (see also Stevenson & Jarillo, 1990). Wiklund (1998) argue, however, that these two definitions complement each other, and when combined define entrepreneurship as “taking advantage of opportunity by novel combinations of resources in ways which have impact on the market”.

3.2 Organisational Entrepreneurship As mentioned above, the research in entrepreneurship has historically focused on the entrepreneur but has in the past decades turned from the individual entrepreneur to the processes of organisational growth and establishment

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(Landström, 1999). The early work of Schumpeter (1934) suggests that entrepreneurship could arise from different settings. Individuals who work in organisations have the potential for being as entrepreneurial as those working independently to start their own business. An organisation can create an environment where the members can contribute to the entrepreneurial function. The organisation that is able to create such an environment is an entrepreneurial organisation (Cornwall & Perlman, 1990). The starting point for the research on firm-level entrepreneurial activities is identified as Peterson and Berger’s seminal study in 1972. This was later followed in the 1980s by a number of trends emerging that distinguished between individual entrepreneurship and corporate entrepreneurship (Zahra et al., 1999).

3.2.1 Entrepreneurial Strategy

Miller & Friesen (1982) argue that entrepreneurial organisations try to obtain a competitive advantage by routinely making dramatic innovations and taking challenging risks. The central elements of this ‘entrepreneurial strategy’ are the organisation’s actions regarding innovation, risk taking, and proactiveness (Miller, 1983). One of the most important contributions in this field was made by Miller (1983) with his theory and research instruments for the examination of the key linkages between environmental and strategic variables, and a firm’s entrepreneurial activities. A measurement instrument was created to measure the level of entrepreneurial strategy within an organisation. Miller’s conceptualisation has since become the instrument of choice in examining firm-level entrepreneurship (Zahra et al., 1999). Miller (1983) further concludes that: “An entrepreneurial firm is one that engages in product-market innovation, undertakes somewhat risky ventures, and is first to come up with ‘proactive’ innovations, beating competitors to the punch” (p. 771). The non-entrepreneurial firm, on the other hand, is one that innovates very little, is highly averse to risk, and imitates the moves of the competitors instead of leading the way (ibid). The three dimensions that constitute entrepreneurship - innovation, risk taking, and proactiveness – are the entrepreneurial dimensions of strategy. They appear in Miller & Friesen’s study (1978) as three out of eleven dimensions of the strategy making process, meaning that Miller takes a strategic approach to entrepreneurship (Wiklund, 1998). Moreover,

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Miller’s (1983) definition of the characteristics of entrepreneurial strategy puts the focus on the process of entrepreneurship rather than the individual behind it, the entrepreneur (Wiklund, 1998). However, a closer study of Miller’s measurement instrument shows that it actually measures accomplished activities and present attitudes rather than actual behaviour. The scale measures the strategic orientation and the concept, entrepreneurial orientation, seems to be more correct than entrepreneurial strategy. (ibid)

3.2.2 Entrepreneurial Orientation

The researchers in the field of entrepreneurship have not been consistent in labelling the phenomenon studied (Lövstål, 2001; Zahra et al., 1999). A number of labels have been used, such as entrepreneurship (Miller, 1983), organisational entrepreneurship (Jelinek & Litterer, 1995), corporate entrepreneurship (Dess et al., 1999; Zahra, 1993), intrapreneurship (Carrier, 1996; Kuratko et al., 1990), entrepreneurial posture (Covin & Slevin, 1991), strategic posture (Covin & Slevin, 1988), and entrepreneurial orientation (Dess et al., 1997; Wiklund, 1998). Despite the differences in the labels used, most researchers have utilised Miller & Friesen’s (1982) measure of firm-level entrepreneurship or a modified version of the instrument (Zahra et al., 1999). Throughout these studies, different interpretations of the measurement instrument have been suggested but, in spite of that, it is still a viable instrument for the measurement of important aspects of entrepreneurial strategy (Wiklund, 1998). In his doctoral dissertation, Wiklund (1998) makes a review of the studies that have used Miller’s (1983) measurement instrument and concludes that all questions in the measurement scale related to the respondent’s self-perception of the firm’s strategy. Wiklund (1998) uses the findings from Merz et al. (1994) and Brown (1996) to put his label on the construct of entrepreneurial orientation as: “The CEO’s strategic orientation reflecting the willingness of a firm to engage in entrepreneurial behaviour”. This definition is also utilised in this study and entrepreneurial orientation is the concept that will be used here to characterise the entrepreneurial dimensions of a firm’s strategy. This study further adopts Miller’s original

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conceptualisation of entrepreneurship, including the dimensions of innovation, risk taking, and proactiveness, as in a majority of previous studies (e.g., Covin & Slevin, 1989; Naman & Slevin, 1993; Wiklund, 1998). Since this study deals with entrepreneurship within a business context, or more precisely within established firms, it discusses some of the questions and aspects related to entrepreneurial orientation. Entrepreneurial orientation has been shown to be a good predictor of the outcomes of entrepreneurial behaviour (Covin & Slevin, 1990; Merz et al., 1994). Wiklund (1998) finds that there is a strong link between entrepreneurial orientation and entrepreneurial behaviour. This means that an entrepreneurial strategic orientation also leads to actual entrepreneurial behaviour, for example entering new markets, manufacturing new products and so on. An organisation with an entrepreneurial orientation could, thus, be defined as an entrepreneurial organisation.

3.3 Performance Measurement

3.3.1 Introduction

The system used by management to control the activities of an organisation is commonly referred to as the management control system (e.g., Anthony et al., 2001). A management control system typically comprises several different types of control tools or sub-systems. Whereas some of these control tools could be characterised as ‘soft’, such as corporate culture and type of leadership, there are others that could be described as ‘hard’, such as budgeting and costing (Ax et al., 2001). Samuelsson (1996) classifies the different types of control systems into three main categories: formal control systems, organisational structure, and less formalised control systems. According to Ax et al. (2001), the branch of performance measurement should be considered a ‘hard’ and formal control tool and may therefore be grouped along control tools with similar characteristics, such as budgeting, target costing, and benchmarking. As with the concept of entreprenurship, the literature does not provide any unitary definition of performance measurement. Ax et al. (2001) states that the

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concept of performance measurement derives from the fact that every firm achieves a variety of different performances. Hence, the measurement could be related to just about any activity or part of the firm, such as financial results, product quality, or customer satisfaction (ibid). Mossberg (1977) defines a performance measure8 as a number or any other quantity, which in a concentrated form provides information about a firm’s performance. Performance measures could therefore be of a financial nature (reflecting some sort of financial performance such as return on equity (ROE) and operating income) as well as non-financial nature, such as number of complaints and delivery time (reflecting, for example, quality or customer satisfaction) (Anthony et al., 2001). According to Simons (2000), systems of performance measurement involve a number of performance measures used to systematically measure the performance of the firm. The systems are the formal, information-based routines and procedures used to maintain or alter patterns in organisational activities (ibid). When the terms ‘performance measurement’, ‘performance measures’ and ‘performance measurement system’ are used throughout the thesis, they refer to the above descriptions of the concepts. That is, the concept of ‘performance measurement’ relates to the measurement of performance of an activity or part of a firm; for example, operating income, product quality, or customer satisfaction. ‘Performance measures’, in turn, are the specific numbers or quantities used to present concentrated information received from the measurement of an activity or part of the firm. Lastly, a ‘performance measurement system’ involves a number of performance measures used to systematically measure the performance of the firm. Thus, this study focuses on a wide use of performance measurement, including both financial and non-financial measures.

3.3.2 Normative Literature on the Design and Use of Performance Measurement

Since the initial criticisms were levelled at management accounting and control in the early 1980s, a number of normative models for measuring performance 8 Other terms used in the literature with essentially the same meaning are key ratios/figures/variables and key performance indicators.

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have been developed. The early systems for measuring performance tended to focus solely on financial results. Particularly in the USA, few academics and practitioners questioned this one-sided focus, until the declining competitive strength of American firms was apparent in the beginning of the 1980s (Hayes & Abernathy, 1980; Johnson & Kaplan, 1987). During the following debate, a number of books and articles on how performance measurement should really be designed and used have been published (e.g., Kaplan & Norton, 1996; McNair et al., 1990). An often-voiced criticism of traditional performance measurement systems is their inability to consider the strategic aspects of business (Dixon et al., 1990; Kaplan & Norton, 1996). The sole use of financial measures are said to be incompatible with a production strategy that, for example, emphasises quality and Just-in-Time. A consistency between strategy, actions, and measures is easier to meet with non-financial measures than with financial ones. The reason for this is that non-financial measures are directly relevant to actual operations, so that operating personnel find it easier to put their own work situation in a strategic context (ibid). The strategic role of performance measurement has been stressed by a number of authors. Simons (2000), for example, argues that systems of performance measurement should assist managers in tracking the implementation of business strategy by comparing actual results against strategic goals and objectives. He further argues that performance measurement systems can play a critical role as means of facilitating innovation and to adapt to changing business conditions. McNair et al. (1990) claim that the problems with performance measurement are not primarily due to an overemphasis on financial measures. Rather, the difficulty lies in the translation of non-financial measures into financial ones. In order to solve this problem McNair et al. (1990) developed a conceptual model called the Performance Pyramid. The top of the pyramid represents the firm strategy, which, in turn, is broken down into operational goals for subordinate organisational levels such as business units, departments, and work groups. By illustrating the design of the performance measurement system by a pyramid, the authors argue for the use of mutually consistent goals, and that strategy and operational goals are to be formulated by top management. Lower

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organisational levels are supposed to develop relevant non-financial measures and communicate these upward through the pyramid. The controller function should assist in this task and is also responsible for auditing non-financial measures and for translating these into financial ones. (ibid) Kaplan & Norton (1996) have proposed a system of performance measurement that is said to integrate different types of measures, including both financial and non-financial measures. Their model of the Balanced Scorecard, they argue, links the firm’s long-term strategy with its day-to-day operations by adopting measures for different perspectives of the business. Each perspective is to reflect an important dimension of the firm’s business. The model comprises the following four perspectives: 1. The financial perspective: Reflects the financial return to the

owners. 2. The customer perspective: Reflects how customers view the

business. 3. The business-process Reflects what must be excelled at.

perspective: 4. The innovation and Reflects how the firm is to

learning perspective continue to develop. The four perspectives are said to be equally important in the long run and should therefore be balanced against each other. That is, no one of the perspective should be allowed to dominate over the others. In order not to lose focus, the number of measures should be limited to approximately 15. When choosing the measures, we are to identify those areas that are particularly important for the successful implementation of strategy – the so-called critical success factors. The critical success factors could be related to internal, as well as, external aspects of business, and be of both a financial and non-financial nature. Here, it is important to note that the critical success factors are both strategy- and organisation-specific (see also Anthony et al., 2001). According to Olve et al. (1999), the measures used should include performance targets specifying what needs to be excelled at as well as spurring the organisation to develop. Short-term performance targets should be taken

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monthly, while long-term targets should be taken at least once a year (ibid). Similarly, Anthony et al. (2001) argues for a “continous and frequent review” of the measures by the senior management. However, an often-voiced criticism of the Balanced Scorecard approach is that it does not specify how trade-offs are to be made between the different measures used (Otley, 1999). According to Otley (1999), one means of resolving the potential conflict between the measures used lies in the setting of performance targets. The level of difficulty of attaining the required level essentially defines the relative levels of attention that managers need to pay to them. Thus, Otley (1999) regards target setting as a crucial feature of a well-implemented Balanced Scorecard. Like Kaplan & Norton (1996), Fitzgerald et al. (1996) argue that performance measurement systems should be linked to firm strategy, including financial and non-financial measures, external, as well as internal measures and make trade-offs between the various measures of performance. Their ‘Results and Determinants Framework’ is said to distinguish between the results of actions taken and the drivers of determinants of future performance. This is done in an attempt to address criticism of short-termism of performance measurement (ibid). In a similar way, Anthony et al. (2001) and Kaplan & Norton (1996) make a distinction between ‘outcome’ and ‘driver’ measures. Here, outcome measures indicate the result of a strategy (e.g., increased revenue) and tell management what has happened. By contrast, driver measures, for example cycle time, are leading indicators showing the progress of key areas of business. Outcome measures indicate only the final result, whereas driver measures can be used at a lower level and indicate incremental changes that will ultimately affect the outcome. (ibid) In line with Kaplan & Norton (1996), Anthony et al. (2001) argue that firms must find a balance between external measures, for example customer- and competitor indicators and measures of internal business processes such as manufacturing yields and quality indicators. Too often, they argue, firms sacrifice internal development on behalf of external results, mistakenly believing that good internal measures are sufficient. Anthony et al. (2001) conclude that the most important aspect of the performance measurement

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system is its ability to measure outcomes and drivers in a way that causes the organisation to act in accordance with its strategies. Although the strategic importance of performance measurement systems has been emphasised in the normative literature during the past decade (e.g., Anthony et al., 2001; Dixon et al., 1990; Kaplan & Norton, 1996), the use of performance measurement may also be of operative nature. Ax et al. (2001) propose a number of operative uses of performance measurement, such as to signal deviations from operational plans, to motivate employees, as a means for communication, to facilitate comparisons (benchmarking), and to determine the bonus to be awarded.

3.3.3 Empirical Literature on the Design and Use of Performance Measurement

During the 1990s there have been a number of studies for the purpose of empirically determining whether the new competitive situation has affected the actual design and use of performance measurement systems. A study by Fitzgerald et al. (1992) shows that performance measurement in the UK has broadened its focus to include non-financial measures. It is, however, also concluded that there is need for continued development in such areas as quality, reliability of delivery, and lead times. The situation in the USA appears to resemble that in the UK (Bromwhich & Bhimani, 1994). Japan, on the other hand, has made better progress in terms of developing methods of performance measurement, including the use of both a strategic and operational perspective (ibid). Stivers et al. (1998) studied the use of non-financial performance measures in 102 so-called fortune 500 firms in USA and 151 so-called Post 300 Canadian firms. The study shows that non-financial performance measures related to customer service are viewed as most important by the firms in the sample, while non-financial performance measures related to employee involvement and innovation are generally perceived as less important. Moreover, higher perceptions of the importance of non-financial measures are associated with higher levels of measurements and a higher use of those measures. In addition, higher perceptions of the importance of non-financial performance measures

33

are associated with an increased focus on innovation and technology (ibid). Johansson et al. (1997) surveyed 100 listed Swedish firms on their management control systems. The part of the study focusing on performance measurement shows that measures reflecting cost effectiveness are considered most important. Similarly to the results of Stivers et al. (1998), other significant measures relate to quality, reliability of delivery, and customer satisfaction. Areas viewed as less necessary to monitor are employee satisfaction and development potential. A recent study by Kald & Nilsson (2000) focuses on the design and use of performance measurement in business units belonging to major corporate groups in the Nordic countries. Over 200 business units in the industrial and service sector, with an average of 2100 employees each, were surveyed using a postal questionnaire. The results of the design-section of the study suggest that measures that reflect profitability are a very important element in measuring the performance of the business units. Measures reflecting cost effectiveness, distribution of sales, and profitability also plays a relatively significant role. External relations are fairly frequently measured – including measures reflecting reliability of delivery, market position, and customer satisfaction. In line with the findings of Johansson et al. (1997), the measures least used by the business units reflected employee satisfaction and attitudes, product development, competence, process development, environmental profile, and level of technology. The section on the use of performance measurement shows that relatively great store is set on measures reflecting market position and product development (Kald & Nilsson, 2000). Performance measurement is a highly used means of decision support, both at top-management level and the operating level. Furthermore, performance measurement is used fairly often to facilitate comparisons with other business units, to help in the work of quality enhancement, and to determine the amount of bonuses. The authors conclude that it appears as if the business units do not confine the use of performance measurement to internal aspects of the business. However, in contrast to the findings of Stivers et al. (1998) and Johansson et al. (1997), the quality aspect is not viewed as an important area. Another fairly insignificant area of use is

34

for the purpose of supporting compensation. Since the performance measurement is not very well established at lower organisational levels, Kald & Nilsson (2000) conclude that firm management and their staff developed the measures with the strategic plan as the starting point. The part of the study focusing on the use of different models of performance measurement indicates that the Balanced Scorecard is widely adopted; 23 per cent of the business units have already done so and, in two years, 61 per cent of the units may be using a scorecard. A conclusion drawn from the study is that performance measurement at Nordic firms is generally well developed in terms of use of both financial and non-financial measures, and that there is a strong connection between measures used and different planning routines, such as strategic planning. Moreover, the criticism of traditional management accounting seems to have been taken seriously and has affected the development of performance measurement systems at Nordic firms. (ibid) Hertenstein et al. (2000) conducted an exploratory study of management control issues in new product development (NPD) within different sectors of the manufacturing industry in the USA. The interaction with 75 design managers involved with new product development suggests that NPD is rarely measured and that the link between performance measures and strategy appears weak. Furthermore, the NPD managers are generally dissatisfied with NPD performance measurement. However, the firms that did measure NPD tended to use both financial and non-financial measures. Many of the empirical studies conducted on the design and use of performance measurement have been focusing larger and well-established firms (e.g., Johansson et al., 1997; Kald & Nilsson, 2000; Stivers et al., 1998). However, in a study by Bhimani (1993), 77 small and medium-sized firms in the UK manufacturing industry were surveyed on their performance measurement. The part of the study focusing on the users of the measures shows that the managing director of the firms had a tendency to use slightly more measures than the board. The managing director used an average number of 18 measures, while the average number for the board was 15. The results further indicate that key aspects of financial performance are financial return and working capital (ibid).

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The production process is also generally closely monitored. However, in line with Hertenstein et al. (2000) measures of innovation are not in widespread use among the studied firms. Bhimani (1993) suggests some future actions to be taken, including more empirical research into how far the popular trend towards non-financial performance measurements actually contributes to companies’ financial success, and to establish to what extent non-financial measures can and should complement financial ones.

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4 The Descriptive Study – Results and Analysis This part of the thesis – ‘The Descriptive Study’ - comprises the empirical findings on the design and use of performance measurement systems in the studied firms. The first section of the chapter deals with the overall structure of the performance measurement systems and the specific measures used by the firms. In the following section, the different uses and users of the performance measurement systems are discussed.

4.1 The Design of Performance Measurement Systems

4.1.1 Categories of Performance Measures and Their Importance

An important aspect of the design of performance measurement concerns the categories of measures used for monitoring performance (Kald & Nilsson, 2000). In light of the normative debate on the design of performance measurement systems (e.g., McNair, 1990; Kaplan & Norton, 1996), it is interesting to study the degree to which these systems reflect different aspects of business in entrepreneurial organisations. Therefore, the survey included 16 different categories of measures - ranging from traditional aspects of business to more recently recognised ones - from which the respondents were to indicate their degree of use on a seven-point Likert scale with ‘not at all’ at the one extreme, and ‘to a large extent’ at the other (see question 1 in Appendix 2). The scores of the firms have been added and a mean for each of the different categories has been calculated (see figure 4.1).

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1.8

1.9

2

2.4

2.7

3.1

3.1

3.5

4.2

4.7

4.8

5

5.1

5.2

5.6

5.8

1 2 3 4 5 6

Market position

Product development and innovation

Flexibility

Environmental aspects

Employee situation

Resource utilisation

Customer relationships

Supplier related measures

Sales

Cost related measures

Other accounting based measures

Cash flow

Quality

Productivity

Profitability

Income

(n =12)

7

FIGURE 4.1. CATEGORIES OF PERFORMANCE MEASURES AND THEIR IMPORTANCE As shown in figure 4.1, the upper half of the categories of performance measures (from ‘profitability’ to ‘sales’) reflects, with two important exceptions, traditional financial measures. That is, when dividing the categories in two halves we find that the most important categories of measures are ‘income’, ‘profitability’, ‘cash flow’, ‘other accounting based measures’, ‘cost related measures’, and ‘sales’. This finding is consistent with other studies on the use of performance measurement (e.g., Johansson et al., 1997; Kald & Nilsson, 2000). However, the internal categories of ‘productivity’ and ‘quality’ are two eye-catching exceptions. Although the importance of measures of quality and productivity have been stressed in other studies (e.g., Kald & Nilsson, 2000), it should be noted that their importance is fully comparable with those of ‘cash flow’ and ‘cost related measures’. This finding is also interesting in light of the high growth experienced by the firms. Although the firms have had years of increasing sales internal aspects such as productivity

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and quality are considered important to keep track of as far as the performance measurement is concerned. Measures that reflect external relations – that is, ‘supplier related measures’ and ‘customer relationships’ – also play a relatively significant role. Although the internal categories of ‘productivity’ and ‘quality’ are emphasised, it is evident that the firms consider more aspects than internal processes; a finding which is consistent with other studies (e.g., Johansson et al., 1997; Kald & Nilsson, 2001). A balance between measures that monitor external relations and internal efficiency has also been called for in the normative literature (e.g., Anthony et al., 2001; Kaplan & Norton, 1996). This is a requirement that seem to have been met by the studied firms. An interesting finding is the low degree of use of measures that reflect ‘market position’. By contrast, Kald & Nilsson (2000) found that measures reflecting market position play a fairly significant role. The importance of keeping track of the firm’s market position is also stressed within the normative literature (e.g., Anthony et al., 2001; Kaplan & Norton, 1996). For example, it is often recommended to measure the market share of the firm (ibid). Our findings show, however, that the significance of such measures is among the lowest. Another interesting finding concerns the degree of use of measures that reflects ‘product development and innovation’ and ‘employee situation’9. Although the studied firms are characterised as entrepreneurial, it appears as if measurement of renewal and innovation play a fairly trivial role. This is contrasted with Kaplan & Norton’s (1996) concept of the Balanced Scorecard, which stresses the importance of such a perspective. However, the study by Hertenstein et al. (2000) indicates that aspects of business related to product development are rarely measured.

9 ‘Employee situation’ consists of two categories. In the interviews two categories of employee measures were used; namely, ‘measures that reflect employee competence and learning’ and ‘measures that reflect employee satisfaction and attitudes’. Since the answers were very similar for these two questions they were put together into one category; ‘measures that reflect employee situation’. The index for this measure was calculated by using the average value from the two previous categories. This value was similar to the values from the previously used categories - meaning that this had a minor effect on the result.

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4.1.2 Performance Measures Used

The debate on what measures are preferable when measuring performance has been immense during the past two decades, including the discussion on the use of financial and non-financial measures (e.g., Hayes & Abernathy, 1980; Johnson & Kaplan, 1987). Empirical studies suggest that the performance measurement practice has broadened its focus to include non-financial measures (Fitzgerald et al., 1992; Bromwich & Bhimani, 1994). However, few studies have investigated the actual use of specific measures. In an attempt to map the use of these measures among entrepreneurial organisations, the survey included a section where the respondents were asked to list their specific measures used (see question 2 in Appendix 2). Each measure has been sorted under the different categories used in figure 4.1. The complete frequency table is provided in Appendix 7. The findings show that the measurement of traditional aspects of business, such as profitability, income and cash flow, includes well-known and quite common measures. Here, ‘return on equity’ (ROE) is the most frequent measure. Other frequent measures are ‘return on assets’ (ROA), ‘return on sales’ (ROS), and ‘return on capital employed’ (ROCE). Income is overly measured by ‘operating profit’ but also by ‘profit margin’. In some cases the operating income is distributed between different entities, such as departments, employees, and produced volume. As concluded in the section on the importance of different categories of measures, the studied firms emphasised quality and productivity in their performance measurement. Accordingly, both quality and productivity include a large number of different measures (see table in Appendix 7). Quality is overly measured by ‘number of complaints’ and ‘number of scrapping’, but also with ‘cost for scrapping’ and ‘cost for corrections’. Similarly, productivity includes a variety of different measures. The most commonly used measure is the calculation of ‘estimated time/actual time’ for a certain activity, such as per project or order. A common technique is to distribute different quantities of used material on, for example, produced volume and man-hours. Measurements related to supplier and customer relationships, includes both measures related

40

to time consumption. As shown in the table in Appendix 7, among supplier related measures, ‘delivery time’ is the most common. However, the ‘number of complaints’ and ‘late deliveries’ are also measured. Among measures related to customer relationships, ‘delivery time’ and the calculation of ‘actual delivery time/agreed delivery time’ are most frequent. In comparison with other non-financial measures, the fairly high frequency of measures reflecting environmental aspects is somewhat surprising. This is, however, partly explained by two facts, namely, (1) that some of the firms were obligated by law to keep track of hazardous waste, and (2) that a couple of firms had to use certain environmentally related measures in order to fulfil the requirements of environmental certifications such as ISO-14001. To conclude, although traditional financial measures are most common, non-financial measures are frequently used by the studied entrepreneurial organisations, including measures reflecting quality, productivity and resource utilisation. Moreover, the firms use a number of external measures reflecting both supplier and customer relationships. The average number of measures used by the firms is 22, of which 14 are financial measures and eight are non-financial measures. The high number of measures used by the firms is contrasted by both the normative and empirical literature on performance measurement (e.g., Bhimani, 1993; Kaplan & Norton, 1996). The firm in the study, which used most measures, had a total number of 35, while the firm with the least measures had ten. Whether these findings are the result of the normative debate on the structure of performance measurement is hard to determine. However, judging from our results on the firm’s acquaintance with and experience from ‘new’ models of performance measurement, it appears as if the debate has not affected the studied firms to any greater extent (see section 4.4).

4.1.3 The Frequency of Use

According to Kaplan & Norton (1996) and Olve et al. (1999), measurements connected with the short-term goals of the firms should be taken relatively often, and reporting on a monthly basis is recommended. On the other hand, measurements linked to long-term goals should be taken “at least once a year”

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(Olve et al., 1999). Anthony et al. (2001) suggests a “continous and frequent review” of the measures by the senior management. In line with the normative literature, most measures are reported on either a weekly- or monthly basis (see question 3 in Appendix 2). Measures reflecting sales and cash flow are mostly reported per week. However, most measures are reported monthly, including measures reflecting income, profitability, and costs. Non-financial measures related to quality, productivity, and supplier and customer relationships are mostly reported on a monthly basis. Few of the firms have measurement reporting on a yearly basis – this holds for both financial as well non-financial measures. It may be concluded that a vast majority of the firms have a frequent reporting routine as far as their system of performance measurement is concerned.

4.2 The Use of Performance Measurement Systems

4.2.1 Different Uses of Performance Measurement

The normative and empirical literature on performance measurement proposes a number of possible uses of both an operative and a strategic nature (e.g., Ax et al., 2001; Kald & Nilsson, 2000). The findings on different uses of performance measurement in entrepreneurial organisations are, however, still non-existent. Drawing on the literature in the field, the survey included a section on the purposes of the performance measurement systems (see question 5 in Appendix 2). A wide range of possible uses were included ranging from traditional uses, such as ‘external reporting’ and ‘to motivate employees’, to more recent uses, such as ‘to identify strategic opportunities’ and ‘to facilitate product development and innovation’. The respondents were to indicate their degree of use of twelve different purposes on a seven-point Likert scale with ‘not at all’ at the one extreme, and ‘to a large extent’ at the other. One open alternative was also provided in the case of not covering all possible uses. As none of the respondents used this option it was removed when the empirical results were put together. The scores of the firms have been added and a mean has been calculated for each of the different uses (see figure 4.2).

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3.1

3.3

3.9

4.3

4.7

4.8

5.1

5.1

5.2

5.3

5.8

2.8

1 2 3 4 5 6 7

To facilitate comparisons with for example other similar firms(benchmarking)

To facilitate product development and the innovationclimate

To determine the bonus to be awarded

To create conditions for identification of strategicopportunities

To provide supporting documentation for external reporting

As a means for communication within the firm

To ensure that strategic goals are achieved

To provide information for decision making

To facilitate quality development

To motivate responsible persons and other employees

To ensure that operative goals are achieved

To signal deviations from plans and expectations

(n = 12)

FIGURE 4.2. DIFFERENT USES OF PERFORMANCE MEASUREMENT Figure 4.2 show that three of the five most emphasised uses of performance measurement could be considered traditional ones; namely, ‘to signal deviations from plans and expectations’, ‘to motivate employees’, and ‘to provide information for decision making’. More recently recognised uses of performance measurement are not particularly emphasised – that is, ‘to identify strategic opportunities’ and ‘to facilitate product development and innovation’ (e.g., Kaplan & Norton, 1996; Simons, 2000). Rather, it appears as if the operative and internal areas of business play a significant role in the use of performance measurement with high ratings for uses such as ‘to ensure that operative goals are met’, ‘to motivate employees’, and ‘to facilitate quality development’. The fact that the uses are biased towards the operative and internal features of business - as compared to innovative and strategic ones – is contrasted by the findings of Kald & Nilsson (2000). In their study of business units belonging to

43

Nordic firms, they conclude that the use of performance measurement is not confined to internal aspects of the business (ibid). Rather, they argue, it appears as if the connection between the measures used and strategic planning is strong, and that performance measurement is used as a means of formulating and implementing strategies. The belief that performance measurement should be designed to implement strategy is also widespread in the normative literature (e.g., Anthony et al., 2001; Kaplan & Norton, 1996; McNair et al., 1990). As shown in figure 4.2, our findings do not suggest any particular emphasis on strategic uses, however. Although the use ‘to ensure that strategic goals are achieved’ is rated relatively high, the respondents considered a number of internally oriented uses of performance measurement more significant. It should further be noted that the two least common uses of performance measurement are ‘for the purpose of comparison with, for example, other firms (benchmarking)’ and ‘to determine the bonus to be awarded’. The importance of these two areas of use has been stressed in the normative literature (e.g., Anthony et al., 2001). As shown in figure 4.2, the firms have not adopted these ideas as far as their system of performance measurement is concerned. The fairly insignificant role of ‘determining the bonus to be awarded’ is also interesting when compared to the high ratings of the use ‘to motivate employees’. Although performance measurement is used as a means of motivating employees, it appears as if the studied firms do not link this use to their compensation system.

4.2.2 Measures and Different Uses

The survey included a question on what measures are used by the firms that reflect their different uses of performance measurement (see question 6 in Appendix 2). However, many of the respondents found it hard to answer this question since the measures, in many cases, were used for several different purposes. Only seven out of the twelve respondents provided answers from which it was possible to draw conclusions. A majority of the respondents use all of their measures ‘as a means for communication’ and ‘to provide information for decision making’. The use ‘to provide supporting documentation for external parties’ is mainly met by financial measures. Not surprisingly, the use ‘to facilitate product development’ involves measures that

44

reflect quality. Lastly, the use ‘to motivate employees’ is mainly linked to non-financial measures reflecting productivity and sales.

4.2.3 Users of Performance Measurement

According to the normative literature, the main users of performance measurement are primarily found at higher firm levels. For example, Kaplan & Norton (1996) states that performance measurement systems should be designed to suit the needs of top management. This viewpoint is also held by Anthony et al. (2001) and McNair et al. (1990). However, the empirical findings on the users of performance measurement are somewhat scarce. Hence, the respondents were asked to indicate the degree of use by five different actors related to the firm (see question 4 in Appendix 2). This was done on a seven-point Likert scale with ‘not at all’ at the one extreme and ‘to a large extent’ at the other. The different scores of the firms have been added and a mean for each of the different actors has been calculated (see figure 4.3).

3.85.2

5.86.36.4

1 2 3 4 5 6 7

By Financiers and LendersOn the Operative Level

By the OwnersBy the Board

By the Management

(n = 12)

FIGURE 4.3. THE USERS OF PERFORMANCE MEASUREMENT Figure 4.3 shows that the least frequent users of performance measurement are financiers and lenders. The main users are the firm management and board, with approximately the same degree of use. The minor difference between the management and the board may perhaps be explained by the fact that the studied entrepreneurial organisations were all small or medium-sized firms, with a managing director in many cases included in the board. The high use of performance measurement by both firm management and board is consistent with the findings of Bhimani (1993), which shows that the average number of measures reported to the management of small and medium-sized firms were only slightly higher than those to the board. The relatively high use of

45

performance measurement at the operative level corresponds to the findings of Kald & Nilsson (2000). This is, however, contrasted by the normative literature, which stress the importance of using measurements at the top-management level (e.g. Kaplan & Norton, 1996; McNair et al., 1990).

4.2.4 Performance Measures Used by Different Actors

In order to find out what types of measures the different actors tend to use, the survey included a question in which the respondents were asked to relate the different measures used by the firm to their users (see question 4.2 in Appendix 2). Our findings show that the firm’s management uses a variety of measures including both financial and non-financial measures. This is also the case for the firm owners and board. Not surprisingly, financiers and lenders are mainly interested in traditional financial measures, such as cash flow, profitability, income and sales, while at the operative level of the firms tend to focus on measures related to productivity and sales. An interesting finding concerns the use of measures that reflect quality. The main user proved to be the firm management, while at the operative level to a large extent is excluded from the use of these measures. Some of the respondents expressed a need for firm management to evaluate quality measurements before presenting the results to other employees. However, this may partly be explained by the fact that the studied firms are small and medium-sized and, thus, are able to inform their employees in a more informal way.

4.3 Performance Targets There is a widespread normative viewpoint that the use of performance targets is of great importance in the use of performance measurement. For example, Kaplan & Norton (1996) and Olve et al. (1999) argue that the use of performance targets is consistent with the overall strategy of the firm, and spurs the organisation to develop. Moreover, the performance targets should not be confined to a certain type of measure; rather, targets are to be set for all measures used by the firm (Kaplan & Norton, 1996; Olve et al., 1999).

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The results show that most firms (eleven out of twelve) use performance targets for some of their measures (see question 7 in Appendix 2). However, the targets are, with one important exception, mainly set for traditional financial categories of measures, such as income, profitability, cash flow, and sales. The exception is for measures reflecting quality, such as number of complaints and scrapping, which frequently involves target levels. Measures related to aspects such as productivity and supplier and customer relationships, rarely involves any performance targets. It is interesting to note that although productivity is frequently measured (see figure 4.1 above), the measurements rarely involve targets. One possible factor explaining this may be related to the fact that the studied firms have experienced exceptionally high growth. This may have contributed to less effort on measurements of productivity, since the production of the firms has expanded immensely. The target setting process is mainly left to the top-management. However, some of the firms use a ‘bottom-up’ approach, involving ‘blue-collar workers’ as well. The process of setting performance targets tends to include two main considerations namely, the historical performance and macro factors, such as market development. With consideration taken to these factors the target levels were mainly set with a gradual increase over time.

4.4 The Use of ‘New’ Models in Management Accounting In the light of the debate on the structure of performance measurement systems, the survey included a section that investigated the respondent’s acquaintance with and experience from ‘new’ models in management accounting (see question 8 in Appendix 2). The respondents were asked if they had any knowledge of four different models that have been discussed within the field of management accounting during the past decade. They were further asked if the firm had implemented or had plans for implementing any of the models. The four models were: Balanced Scorecard, Value-Based Management, Intellectual Capital, and Results and Determinants Framework. The findings show that none of the firms had implemented any of the models, with one exception. One of the firms had partly implemented the Balanced Scorecard where the areas, quality and delivery seem to be functioning well.

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However, all of the models were unknown to a vast majority of the respondents. Only four out of the twelve respondents were familiar with the concept of Balanced Scorecard, and no more than two respondents had heard of Value-Based Management and Intellectual Capital. This is contrasted by the findings of Kald & Nilsson (2000), which indicated that 27 per cent of the Nordic firms surveyed had implemented a scorecard. The systems of performance measurement used by the studied firms were generally considered sufficient in terms of function and precision. Major changes of the performance measurement systems were considered too time consuming. Nevertheless, eight out of the twelve firms had planned for improvements of their performance measurement system. Some of the respondents felt a need to expand their measurement to include more aspects of business, such as employee health situation, market demand, and environmental aspects. Environmentally related improvements of performance measurement were most frequent. This is partly explained by the requirements of environmental certifications, such as ISO 14001 for which a few of the firms were striving.

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5 The Explanatory Study – Results and Analysis

This chapter intends to investigate possible relationships between a number of variables and the design and use of performance measurement systems. The variables studied in relation to the performance measurement are entrepreneurial orientation, firm performance, firm size, firm age, and firm ownership. The purpose of the explanatory study is to provide possible indications and suggestions on whether these variables have an effect on the design and use of performance measurement systems. The main areas of study are the extent of use of performance measures by the firms, whether the measures tend to be financial or non-financial, how frequent the use is, and the extent of the use of measures by various actors such as the management. The sections for each variable begin with a discussion on the operationalisation of the measures. This is followed by a description of the spread of the studied population. Furthermore, an analysis is conducted on the findings for each variable.

5.1 Entrepreneurial Orientation The study focuses on entrepreneurial organisations. As these organisations could be considered as more or less entrepreneurial, it is interesting to investigate whether the grade of entrepreneurship has any effect on the design and use of performance measurement systems. The measure of entrepreneurial orientation has already been operationalised in the methodology chapter, using the seven-grade scale on eight dimensions reflecting the innovativeness, proactiveness, and risk-taking of the firms. These different scores were added up to an overall entrepreneurial index for the firms, providing an indication of their entrepreneurial orientation.

5.1.1 Depiction of the Population

Below, the spread of the population’s entrepreneurial orientation is illustrated. In the analysis ten firms are studied and, as can be seen, all firms are clustered between 4.5 and 5.9. The two firms with 5.3 in score have been excluded from the analysis in order to separate the firms and create two groups to be analysed.

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Group one (lower EO) consists of the firms with 4.5-5.1 in score and group two (higher EO), 5.4-5.9.

02468

1012

1 2 3 4 5 6 7

Entrepreneurial Orientation

Firm

(n=1

2)

FIGURE 5.1. THE ENTREPRENEURIAL ORIENTATION OF THE FIRMS

5.1.2 Survey Results and Analysis

Table 5.1 indicates that there are no strong relationships between the entrepreneurial orientation and the number of performance measures used. By looking at the relations between financial and non-financial measures10, it is indicated that the firms with a higher EO use non-financial measures to a greater extent than those with a lower EO. At the same time, the firms with a lower EO seem to use financial measures to a greater extent.

Lower EO (n=5)

Higher EO (n=5)

Total no. of measures (average) 24 22Finc. measures (average) 17 13Non-finc. measures (average) 7 9TABLE 5.1. AVERAGE NUMBER OF MEASURES USED Whether there are any relationships between the entrepreneurial orientation and the frequency of use of performance measures is difficult to determine. However, firms with a lower EO seem to report their measures to a greater extent on a daily and weekly basis as compared to the firms with a higher EO

10 In this study financial measures are defined as measures of profitability, income, cash flow, other accounting based measures, cost related measures and sales such as revenue. The non-financial measures are as a result measures that reflect productivity, quality and so on.

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(Table 5.2). On the other hand, the high EO firms seem to report measures on a monthly basis to greater extent. Lower EO (n=5) Daily Weekly Monthly

2nd month Quarterly

Six months Year

Per project

No. of firms 1 5 5 1 3 1 3 1Total (average) 5 6 6 11 7 5 1 15

Higher EO (n=5) Daily Weekly Monthly

2nd month Quarterly

Six months Year

Per project

No. of firms 1 4 4 0 1 0 1 0Total (average) 1 5 19 0 6 0 3 0TABLE 5.2. AVERAGE NUMBER OF MEASURES REPORTED PER PERIOD Table 5.3 indicates that there are no strong relationships between the entrepreneurial orientation and the use of performance measures by management. However, the main difference between the low and high EO firms is that the firms with a lower EO report measures to the financiers and lenders to a greater extent. The firms with a higher EO, on the other hand, seems to report measures to the owners, the board and the management at a more equal level keeping the various actors on a similar level of information. Lower EO (n=5)

Financiers and Lenders Owners Board Management

Operative level

Total average 8 15 13 22 5Higher EO (n=5)

Financiers and Lenders Owners Board Management

Operative level

Total average 0 17 21 21 6TABLE 5.3. AVERAGE NUMBER OF MEASURES USED ON EACH LEVEL

5.2 Firm Performance

Performance is an accepted variable, which is commonly used in research investigating the possible relationships between different variables (e.g., Greve, 1999; Govindarjan, 1984; Covin, et al., 1990). The measure of firm performance has already been operationalised in the methodology using rating scales of the Likert-type, graded 1-7 and 1-5, where the scores were added up to an overall performance index for each firm. This index is used to indicate whether the firm has a higher or lower performance and investigates whether

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higher and lower performance has any effect on the design and use of performance measurement systems.

5.2.1 Depiction of the Population

In figure 5.2, the spread of the population’s performance is illustrated. In the analysis, nine firms are included and, as can be seen, all firms are clustered between 4.1 and 5.6. Three firms are excluded from the analysis to be able to separate the firms and create two groups. The three excluded firms had between 4.9 and 5.0 in scores. Group one of the analysed firms consists of the firms with 4.1-4.7 in score and group two, 5.1-5.6.

02468

1012

1 2 3 4 5 6 7

Performance

Firm

(n=1

2)

FIGURE 5.2. THE PERFORMANCE OF THE FIRMS

5.2.2 Survey Results and Analysis

Table 5.4 indicates a possible relationship between performance and the number of performance measures used, as firms with higher performance seem to use more measures. By studying the relationship between financial and non-financial measures, it is indicated that firms with a higher performance use non-financial measures to a greater extent than firms with a lower performance.

Lower performance(n=5)

Higher performance (n=4)

Total no. of measures (average) 19 26Finc. measures (average) 14 15Non-finc. measures (average) 5 11TABLE 5.4. AVERAGE NUMBER OF MEASURES USED

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Whether there are any relationships between performance and the frequency of use of performance measures is difficult to determine. However, firms with lower performance seem to report their measures to a greater extent on a weekly basis as compared to the firms with a higher performance (Table 5.5). Lower performance (n=5) Daily Weekly Monthly

2nd month Quarterly

Six months Year

Per project

No. of firms 0 4 2 0 2 1 1 1Total 0 8 13 0 11 5 1 13Higher performance (n=4) Daily Weekly Monthly

2nd month Quarterly

Six months Year

Per project

No. of firms 1 4 4 1 1 0 1 0Total 1 2 12 11 6 0 4 0TABLE 5.5. AVERAGE NUMBER OF MEASURES REPORTED PER PERIOD Table 5.6 suggests that the relationship between performance and the use of performance measures by firm management is of a minor nature. However, the management, the board as well as the operative level does seem to use more measures in the firms with higher performance. Lower performance (n=5)

Financiers and Lenders Owners Board Management

Operative level

Total 3 17 15 19 2Higher performance (n=4)

Financiers and Lenders Owners Board Management

Operative level

Total 1 16 21 23 7TABLE 5.6. AVERAGE NUMBER OF MEASURES USED ON EACH LEVEL

5.3 Firm Size

The normative literature on performance measurement is mainly focused on larger firms (Ask & Ax, 1997). The design and use of performance measurement systems in small and medium sized firms is not discussed to any large extent. However, size is a commonly used variable when performing a relational analysis (Ask & Ax, 1997). Firm size is defined as the extent of a

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firm’s operation and is most commonly measured by the number of employees (Kimberly, 1976). The size measure is used as an explanatory variable to divide the studied population into separate categories in order to investigate whether size has any effect on the design and use of the performance measurement systems. The firm’s number of employees in year 2000 is used as a basis for this analysis, and the information on firm size was gathered from the database ‘Affärsdata’.

5.3.1 Depiction of the Population

In figure 5.3, the spread of the population’s size is illustrated. For the analysis, the firms are divided into three groups, where group one consists of the firms with 10-36 employees, group two 45-60 employees and group three 90-125 employees.

02468

1012

0 50 100

No. of Employees

Firm

(n=1

2)

150

FIGURE 5.3. THE SIZE OF THE FIRMS

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5.3.2 Survey Results and Analysis

Table 5.7 indicates that there is no strong relationship between the size and the number of performance measures used.

Group one

(n=5)

Group two

(n=4)

Group three

(n=3) Total no. of measures (average) 24 19 22Finc. measures (average) 16 12 13Non-finc. measures (average) 8 7 9TABLE 5.7. AVERAGE NUMBER OF MEASURES USED It cannot be determined whether there are any relationships between size and the frequency of use of performance measures (Table 5.8). Group one (n=5) Daily Weekly Monthly

2nd month Quarterly

Six months Year

Per project

No. of firms 0 5 3 0 2 1 1 1Total 0 7 16 0 11 5 1 13Group two (n=4) Daily Weekly Monthly

2nd month Quarterly

Six months Year

Per project

No. of firms 1 3 4 1 1 0 1 0Total 5 3 11 11 1 0 1 0Group three (n=3) Daily Weekly Monthly

2nd month Quarterly

Six months Year

Per project

No. of firms 1 3 2 0 1 0 1 0Total 1 6 19 0 6 0 3 0TABLE 5.8. AVERAGE NUMBER OF MEASURES REPORTED PER PERIOD Table 5.9 indicates that the owners, the board, the management as well as the operative level in the two larger groups seem to use more measures as compared to the smallest size group.

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Group one (n=5)

Financiers and Lenders Owners Board Management

Operative level

Total 3 17 15 19 3Group two (n=4)

Financiers and Lenders Owners Board Management

Operative level

Total 1 16 21 23 5Group three (n=3)

Financiers and Lenders Owners Board Management

Operative level

Total 1 16 21 23 5TABLE 5.9. AVERAGE NUMBER OF MEASURES USED ON EACH LEVEL

5.4 Firm Age

Firm age is the fourth variable of the firms’ characteristics utilised in the explanatory study. As firms grow older, it is assumed that they also develop their business and their internal systems. By studying the age variable in relation to performance measurement systems, it is possible to clarify the effects of age differences on these systems. The firm’s registration year is used as a proxy for age and the information was gathered from the database ‘Affärsdata’. This information may be criticised, as the firms may have changed their core business during the period from the registration till the year 2000. That could, of course, have an effect on the performance measurement systems in some ways. However, for the purposes of studying the relationships between age and performance measurement systems, this criticism is considered as having only a minor impact on this study.

5.4.1 Depiction of the Population

In figure 5.4, the spread of the population’s age is illustrated. For the analysis, the firms are divided into three groups where group one consists of the younger firms age 4-10 years, group two consists of mid-aged firms of 15-24 years, and group three is the older firms consisting of only one firm with an age of 38 years.

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02468

1012

0 10 20 30 4

Age (Years)

Firm

(n=1

2)

0

FIGURE 5.4. THE AGE OF THE FIRMS

5.4.2 Survey Results and Analysis

The age variable seems to have a small effect on the number of measures used (Table 5.10).

Group one

(n=6)

Group two

(n=5)

Group three

(n=1) Total no. of measures (average) 20 23 22Finc. measures (average) 13 14 15Non-finc. measures (average) 7 9 7TABLE 5.10. AVERAGE NUMBER OF MEASURES USED Whether there are any relationships between performance and the frequency of use of performance measures is difficult to determine. However, the younger firms appear to report their measures to a greater extent on a weekly basis as compared to the older firms (Table 5.11).

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Group one (n=6) Daily Weekly Monthly

2nd month Quarterly

Six months Year

Per project

No. of firms 0 5 4 1 1 0 2 0Total 0 7 12 11 9 0 1 0Group two (n=5) Daily Weekly Monthly

2nd month Quarterly

Six months Year

Per project

No. of firms 1 5 4 0 2 1 1 1Total 5 3 15 0 6 5 3 13Group three (n=1) Daily Weekly Monthly

2nd month Quarterly

Six months Year

Per project

No. of firms 1 1 1 0 1 0 0 0Total 1 1 15 0 6 0 0 0TABLE 5.11. AVERAGE NUMBER OF MEASURES REPORTED PER PERIOD From studying table 5.10 it is hard to determine whether the age variable has any effect on the number of measures used on each level of the firms. Group one (n=6)

Financiers and Lenders Owners Board Management

Operative level

Total 4 15 15 16 7Group two (n=5)

Financiers and Lenders Owners Board Management

Operative level

Total 4 21 18 23 4Group three (n=1)

Financiers and Lenders Owners Board Management

Operative level

Total 0 2 2 25 7TABLE 5.12. AVERAGE NUMBER OF MEASURES USED ON EACH LEVEL

5.5 Firm Ownership

Ownership could have a direct effect on the firm’s internal structures and systems. This could especially be of importance if the Managing Director is also a major owner of the firm. According to the so-called agency theory, which is based on the perspective of the principal, the agent’s behaviour is guided and controlled by using different means for the purpose of furthering the self-interest of the principal (Jacobsen & Thorsvik, 1998). As a result, the relationship between ownership and the performance measurement systems is studied to determine a possible influence on the design and use of the

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performance measurement systems. This information was gathered during the interviews where the respondents were asked whether the Managing Director owned the firm or if any of the owners were actively involved in the firm.

5.5.1 Depiction of the Population

The ownership of the twelve firms is divided into three groups: the Managing Director also is an owner of the firm (7 firms); the owner is in some way ‘actively’ involved in the firm (2 firms); and where there is no active owner involved in the firm (3 firms). Managing Director Owner

Owner involved in firm

No owner involved in firm

7 2 3 FIGURE 5.5. THE OWNERSHIP STRUCTURE OF THE FIRMS

5.5.2 Survey Results and Analysis

The results in table 5.13 indicate that there is a weak relationship between ownership and the number of performance measures used. However, the result suggests that the firms where the owners are not actively involved use non-financial measures to a greater extent.

Managing Director Owner (n=7)

Owner involved in firm (n=2)

No owner involved in firm (n=3)

Total no. of measures (average) 22 19 23 Finc. measures (average) 14 14 13 Non-finc. measures (average) 8 5 10 TABLE 5.13. AVERAGE NUMBER OF MEASURES USED Whether there are any relationships between ownership and the frequency of use of performance measures is difficult to determine as the firms with the Managing Director as owner and the firms with no active owner have similar results (Table 5.14).

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MD owner (n=7) Daily Weekly Monthly

2nd month Quarterly

Six months Year

Per project

No. of firms 1 7 5 0 3 1 1 1Total 5 6 15 0 7 5 1 13Owner involved (n=2) Daily Weekly Monthly

2nd month Quarterly

Six months Year

Per project

No. of firms 1 1 2 0 1 0 0 0Total 1 1 14 0 6 0 0 0Owner not involved (n=3) Daily Weekly Monthly

2nd month Quarterly

Six months Year

Per project

No. of firms 0 3 2 1 0 0 2 0Total 0 6 16 11 0 0 2 0TABLE 5.14. AVERAGE NUMBER OF MEASURES REPORTED PER PERIOD Table 5.15 indicates that there is a relationship between the use of performance measures by management and ownership. The management of the firm seem to use more measures in firms where the Managing Director also is an owner. Moreover, in firms where the owner is actively involved, the management tends to use more measures as compared to firms where the owners are not involved in the firms operations. MD owner (n=6)

Financiers and Lenders Owners Board Management

Operative level

Total 6 19 17 22 7Owner involved (n=5)

Financiers and Lenders Owners Board Management

Operative level

Total 1 8 20 20 4Owner not involved (n=1)

Financiers and Lenders Owners Board Management

Operative level

Total 1 15 14 16 2TABLE 5.15. AVERAGE NUMBER OF MEASURES USED ON EACH LEVEL

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5.6 Summary of Results and Analysis In this section the analysis is briefly summarised and discussed. The relationship between entrepreneurial orientation and the number of performance measures seems weak. However, it is indicated that firms with a lower EO use financial measures to a greater extent, they report their measures more often on a daily and weekly basis, and they seemed to report measures to the financiers and lenders to a greater extent than the firms with a higher EO. The study of the firms with a higher EO did, on the other hand, indicate that these firms use non-financial measures to a greater extent, they report the main part of their measures on a monthly basis and they also seem to report their measures to the owners the board and the managers on a more equal level leaving these actors on a similar information level. The study indicates a possible relationship between performance and the number of measures used in the firms. Moreover, the firms with higher performance appear to use more measures. They also seemed to use non-financial measures to a greater extent than the firms with lower performance. It is also indicated that the management, the board and the operative level in the higher performing firms use more performance measures. Whether there is any relationship between performance and the frequency of reporting of performance measures is difficult to determine. However, the firms with lower performance seem to report their measures to a greater extent on a weekly basis. The size variable did not seem have any great effect on the performance measurement systems. However, the owners, the board, the management, as well as the operative level in the larger firms, seem to use more measures than the smaller firms. As with the size variable, the age variable did not appear to have any greater effect on the performance measurement systems. However, the younger firms did seem to report their measures to a greater extent on a weekly basis as compared to the older firms. The analysis of the ownership variable indicated that it has a weak relationship with the number of performance measures used in the firms. This was also the

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case for the reporting frequency. However, it seems as if the firms where the owners are not actively involved use non-financial measures to a greater extent compared to the other firms. Moreover, there seems to exist a relationship between ownership and the use of performance measurement by management. It was indicated that the management use more measures in firms where the Managing Director is also an owner. The same was indicated for firms where the owner is actively involved in the firm’s activities.

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6 Conclusions Considering the research objectives of the study, there are some conclusions to be drawn on the design and use of performance measurement systems in entrepreneurial organisations. This chapter provides a summary of the most important findings – including conclusions on the descriptive and the explanatory part of the study. Finally, some suggestions for future research are discussed.

6.1 The Descriptive Study Drawing on the results of the descriptive part of the study it is possible to present an overall pattern of the design and use of performance measurement systems in the studied entrepreneurial organisations.

• The entrepreneurial organisations tend to use performance measurement extensively, including the use of a large number of measures reflecting both financial and non-financial aspects of business. The average number of measures used by the firms is 22, of which 14 are financial measures and eight are non-financial measures. The high number of measures used by the firms is contrasted by both the normative and empirical literature on performance measurement (e.g., Bhimani, 1993; Kaplan & Norton, 1996). Furthermore, the measures are overly reported on a monthly basis, except for measures of sales, which tend to be reported weekly.

• Although traditional financial measurements are emphasised, non-

financial aspects of business are frequently measured by the firms, including measures reflecting quality, productivity, and resource utilisation. Measurements of quality and productivity are viewed as more significant than, for example, cash flow and sales. Externally related measurements, such as supplier and customer relationships, are also viewed as significant. In contrast with the normative literature (e.g., Anthony et al. 2001; Kaplan & Norton, 1996), aspects such as market position and product development are considered fairly insignificant by the studied firms.

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• The main users of performance measurement are the firm management and the board, with approximately the same degree of use. The operative level of the firms is also a frequent user of performance measurement. The least frequent users of performance measurement are financiers and lenders.

• The findings on the use of performance measurement indicate an

emphasis on traditional uses, such as to signal deviations from plans and expectations, to motivate employees, and to provide information for decision making. More recently recognised uses of performance measurement are not particularly emphasised; for example, to identify strategic opportunities and to facilitate product development and innovation (e.g., Kaplan & Norton, 1996; Simons, 2000). Furthermore, it appears as if operative and internal areas of business play a significant role in the use of performance measurement - with high ratings for uses such as to ensure that operative goals are met, to motivate employees, and to facilitate quality development.

• Neither the design nor the use of performance measurement in the

entrepreneurial organisations is particularly related to long-term strategic planning. This finding is contrasted by the normative literature, which stresses the importance of a strategic use of performance measurement (e.g., Anthony et al., 2001; Kaplan & Norton, 1996; Simons, 2000).

• None of the firms have fully implemented any ‘new’ models in

management accounting. Moreover, all of the models proposed were unknown to a vast majority of the respondents. Only four out of the twelve respondents were familiar with the concept of Balanced Scorecard.

To conclude, from the findings of the descriptive study it is evident that performance measurement systems play a significant role in entrepreneurial organisations. This is reflected by three main observations: 1) the large number of measures used by the firms; 2) the frequent reporting of the measures; and 3) the relatively high variety of business aspects measured. Regarding the

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different uses of performance measurement in the entrepreneurial organisations, it appears as if they are very much confined to operative and internal areas of business – including traditional uses such as to ensure that operative goals are achieved and to motivate employees. This finding is, to some extent, in contrast with the normative literature, which stresses long-term strategic and innovative use of performance measurement systems (e.g., Kaplan & Norton, 1996; Simons, 2000).

6.2 The Explanatory Study The results from the explanatory study enable conclusions to be drawn regarding the effect of the different variables on the performance measurement systems in the entrepreneurial organisations.

• The firms with the higher entrepreneurial orientation seem to be using non-financial measures to a greater extent. They reported their measures to firm managagement, the board, and the owners at a more equal level - leaving these actors at a similar information level. Firms with a lower entrepreneurial orientation, on the other hand, used financial measures to a greater extent, reported their measures more often (on a daily and weekly basis), and seemed to report measures to financiers and lenders to a greater extent than the firms with a higher EO.

• A possible relationship between firm performance and the number of

measures used in the firms is implied. It appears as if the firms with a higher performance use more measures, they also seem to use non-financial measures to a greater extent when compared to the firms with lower performance. The firm management, the board and the operative level in the higher performing firms seem to be using more performance measures. The lower performing firms seem to report their measures to a greater extent on a weekly basis.

• The size of the firms does not seem to have any great effect on the design

and use of performance measurement systems. Although the management, the board, the owners as well as the operative level in the

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larger firms appear to use more measures as compared to the smaller firms.

• The age of the firms does not appear to affect the performance

measurement systems. However, the younger firms seem to report their measures to a greater extent on a weekly basis, as compared to the older firms.

• The ownership of the firm seems to have a weak relationship with the

number of performance measures used in the firms as well as for the reporting frequency. Nevertheless, it appears to exist a relationship between the ownership and the use of performance measurement by management. It is indicated that the management uses more measures in firms where the owner, or one of the owners, are the Managing Director. This also seems to be the case for firms where the owner was actively involved in the operations.

From the findings of the explanatory study, it can be concluded that some of the variables effects the performance measurement systems used by the firms. For example, firms with a higher entreprenurial orientation tends to use non-financial measures to a greater extent, and firms with a higher performance tends to use a larger number of measures. However, the indications are fairly weak and should be interpreted with care.

6.3 Suggestions for Future Research The reader may have noted some possibilities for future research throughout the previous chapters. This section contains some explicit suggestions for future research that we hope will encourage others to conduct studies in order to advance our knowledge in entrepreneurship and accounting. In this study, twelve firms were included. This is a fairly small sample and it could be beneficial to make a study of the manufacturing industry using a larger sample of firms. By doing this, the results and tendencies could be more reliable. Furthermore, the possibilities for firms to use the findings in practice for improving their businesses would be improved. There are also opportunities

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to use the model for identifying entrepreneurial organisations developed in this study (see chapter 2 ‘Methodology’) and study other aspects of management accounting within this context. Possible areas for study are, for example, costing or budgeting. Moreover, it could be of interest to study firms considered as ´non-entrepreneurial`and compare the performance measurement systems of these to the entrepreneurial firms. Since this study focused on the manufacturing industry it is possible that the measurement of certain business aspects, such as quality and productivity, are more connected to this particular industry. There are obvious opportunities and it would be of great interest to extend this research into other industries, such as services and trade. These studies could be integrated and compared in order to study the differences of the design and use of performance measurement in entrepreneurial organisations between the industries. The focus of the study has further been on the formal performance measurement systems. The informal performance measurement may also be interesting to study. This would, however, be more of an in depth study focusing on one or a few firms. Moreover, opportunities to extend the explanatory study of various firm characteristics and their effect on the performance measurement systems exist. It may be of interest to study these issues in more depth as this study indicated possible relations between the variables and the performance measurement systems used by the firms. It should, however, be noted that entrepreneurial organisations are a population of firms that is difficult to study. This is, to a great extent, due to the lack of resources, mainly time, for the respondents and their firms. The fact that the studied firms all had experienced a tremendous organic growth during the past few years meant that the managing directors generally had a huge workload. Due to this, a number of potential firms had to be excluded from the study. This should be kept in mind when performing this type of research in the future.

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Appendix 1 - Search Strings

• Entrepreneurship • Corporate entrepreneurship • Entrepreneurial organisation • Organisational entrepreneurship • Entrepreneurial orientation • Strategy and entrepreneurship • Entrepreneurial strategies • Strategic entrepreneurship.

• Management accounting • Management control • Performance measurement

• Entrepreneurship and accounting • Entrepreneurship and management accounting • Entrepreneurship and management control • Entrepreneurship and performance measurement • Management accounting in small- and medium sized firms • Management accounting in small- and medium sized companies • Management accounting in small- and medium sized businesses • Performance measurement in small- and medium sized firms • Performance measurement in small- and medium sized companies • Performance measurement in small- and medium sized businesses • Management accounting in small businesses • Performance measurement in small businesses

Appendix 2 - Translation of Questions About Performance Measurement

31 October 2001 Gothenburg

Dear Sir/Madam, With reference to our telephone conversation about the study in performance measurement in your firm, the questions to be discussed in the upcoming telephone interview are attached. We would be very grateful if you prepare for the interview by looking up the information you may need to be able to answer our questions. The following questions are, in comparison to the questions you answer in the web questionnaire, focused on your performance measurement. Many of the questions are answered by choosing a number on a scale. In some questions we ask you to specify the measures you use (questions 2, 3 and 6). Please note that by measures we mean both financial and non-financial measures. It is not necessary for the measures to reflect monetary quantities. The measures may be absolute accounting figures but also percentages reflecting for example quality, reliability of deliver, etc. Moreover, some of the questions could be characterised as objects for discussion where we want to create a picture over a specific issue and do not expect a simple answer (questions 2.3, 7.2 and 8). To save time and facilitate the interview, we would be grateful if you prepare yourself for the interview as far as possible. Your answers are confidential and the name of your firm will not be mentioned in the thesis. We are very grateful for your time and cooperation and you will, of course, receive a copy of the finished thesis by e-mail. Kind regards, Per Mattila and Mikael Åhlqvist

The Design of Performance Measurement 1 Structure of Performance Measurement To what extent are the categories of measures listed below used by the firm to measure performance on a scale of 1 to 7?

1 2 3 4 5 6 7 1.1

1.2

1.3

Measures that reflect profitability. Not at all � � � � � � � To a large extent

Measures that reflect income. Not at all � � � � � � � To a large extent

Measures that reflect cash flow.

Not at all � � � � � � � To a large extent 1.4 Other accounting based measures, (for example solidity, liquidity and debt/equity ratio).

Not at all � � � � � � � To a large extent 1.5 Cost related measures. Not at all � � � � � � � To a large extent 1.6 Measures that reflect resource utilisation (non-monetary resources).

Not at all � � � � � � � To a large extent 1.7 Measures that reflect productivity.

Not at all � � � � � � � To a large extent 1.8 Measures that reflect the distribution of sales (for example per product or per customer).

Not at all � � � � � � � To a large extent 1.9 Measures that reflect market position.

Not at all � � � � � � � To a large extent 1.10 Measures that reflect customer relationships.

Not at all � � � � � � � To a large extent 1.11 Measures that reflect supplier related measures.

Not at all � � � � � � � To a large extent

1.12 Measures that reflect flexibility. Not at all � � � � � � � To a large extent

1.13 Measures that reflect quality. Not at all � � � � � � � To a large extent 1.14 Measures that reflect employee competence and learning.

Not at all � � � � � � � To a large extent 1.15 Measures that reflect employee satisfaction and attitudes.

Not at all � � � � � � � To a large extent 1.16 Measures that reflect product development and innovation.

Not at all � � � � � � � To a large extent 1.17 Measures that reflect environmental aspects.

Not at all � � � � � � � To a large extent 2 Performance Measures (NB! Read all three questions before you answer any of them) 2.1 What specific measures does your firm use for performance measurement? (In this

question we want you to list all your measures that are a part of a formal system, that is, measures that are extracted continuously according to a pre-determined plan).

2.2 Which category/categories do you consider that each measure belongs to? (In this

question we want to know what measures you use to measure for example profitability, quality etc. To facilitate the interview please, list your measures under each category in question 1 beforehand).

2.3 Do you have any measures/key ratios that do not fit into any of the above categories? If

yes, what are they? What do these reflect and to what extent are these used?

The Uses of Performance Measurement 3 The Reporting of Performance Measures 3.1 How often is each measure reported/extracted? (To facilitate the interview please list

your measures after each alternative below).

Once a week Once a month Once every quarter Once every six months Once a year Other ………….......

4 The Users of Performance Measures 4.1 To what extent are performance measures used on the following levels within or with

connection to the firm on a scale of 1 to 7?

1 2 3 4 5 6 7 (1) By financiers and lenders. Not at all � � � � � � � To a large extent (2) By the owners. Not at all � � � � � � � To a large extent (3) By the board Not at all � � � � � � � To a large extent (4) By the Management Not at all � � � � � � � To a large extent (5) On the operative level Not at all � � � � � � � To a large extent 4.2 Who are the users of each measure? NB! The measures could have more than one user.

5 The Purpose of Performance Measurement To what extent is the performance measurement used by your firm for the following purposes on a scale of 1 to 7? 1 2 3 4 5 6 7 5.1 To ensure that goals are achieved.

Strategic goals Not at all � � � � � � � To a large extent Operative goals Not at all � � � � � � � To a large extent

5.2 To create conditions for identification of strategic opportunities.

Not at all � � � � � � � To a large extent 5.3 To signal deviations from plans and expectations.

Not at all � � � � � � � To a large extent 5.4 To provide information for decision making; for example, for decisions concerning

resource allocation. Not at all � � � � � � � To a large extent

5.5 As a means for communication within the firm.

Not at all � � � � � � � To a large extent 5.6 To provide supporting documentation for external reporting.

Not at all � � � � � � � To a large extent 5.7 To facilitate quality development.

Not at all � � � � � � � To a large extent 5.8 To facilitate comparisons with for example other similar firms (benchmarking).

Not at all � � � � � � � To a large extent 5.9

5.10

To motivate responsible persons and other employees. Not at all � � � � � � � To a large extent

To determine the bonus to be awarded.

Not at all � � � � � � � To a large extent

5.11 To facilitate product development and the innovation climate within the firm. Not at all � � � � � � � To a large extent 5.12 Do you use performance measurement for other purposes than those mentioned above?

If yes, for what purposes and to what extent? Not at all � � � � � � � To a large extent

6 Measures Used for the Above Purposes 6.1 What measures are used for the above purposes? (To facilitate the interview, please

prepare by listing your measures under each purpose in question 5). 7 The Performance Targets of the Measures Used 7.1 Do you set any performance targets for your measures? If yes for what measure/s? 7.2 How do you go about setting these target levels? 8 The Usage of Performance Measurement Systems 8.1 Do you have any knowledge about the following management accounting systems?

Have knowledge of Yes No

(1) Balanced Scorecard � � Yes No If yes, (a) Have implemented � �

(b) Intend to implement � � If no, why not? If yes, why?

Have knowledge of Yes No

(2) Value Based Management (VBM) � � Yes No for example EVA and MVA If yes, (a) Have implemented � �

(b) Intend to implement � � If no, why not? If yes, why?

Have knowledge of Yes No

(3) Intellectual Capital � � Yes No If yes, (a) Have implemented � �

(b) Intend to implement � � If no, why not?

If yes, why?

Have knowledge of Yes No

(4) Results and Determinants � � Yes No Framework If yes, (a) Have implemented � �

(b) Intend to implement � � If no, why not? If yes, why? 8.2 Have you implemented or do you intend to implement any other management

accounting system not mentioned above? 8.3 Do you plan any changes in your performance measurement?

If yes, what changes and why? 9 Ownership 9.1 Is the Managing Director also an owner of the firm? 9.2 Do any of the owners work within the firm? If yes, what position do the

owner/owners have?

Appendix 3 – Translation of the Cover Letter in the E-mail with Web Questionnaire

Dear Sir/Madam, With reference to our telephone conversation about the study in performance measurement in your firm, the shortcut to the web questionnaire containing 32 simple questions is attached below. The questions are about your firm’s market behaviour and performance. The questions are answered by marking your choice of position on a scale in each question. When you have answered all the questions, press the send button and the answers will be sent to us. It is very important that you answer all the questions, as we are going to use your answers to calculate an index and group the interviewed firms using that index. Your answers are confidential and your firms name will not be mentioned in the thesis. We are very grateful for your involvement in our study and you will, of course, receive a copy of the finished thesis by e-mail. If you have any questions or run into any problems with the web questionnaire or any other part of the study please do not hesitate to contact us or ask us at the telephone interview. The questions regarding performance measurement that will be discussed in the telephone interview will be sent to you via ordinary mail. Click on the shortcut below to answer the web questionnaire. http://w3.informatik.gu.se/~s00agahi/eo/questionnaire.html Kind regards Per Mattila and Mikael Åhlqvist

Appendix 4 – Translation of Web Questionnaire

Entrepreneurship and Performance Dear Sir/Madam, As explained during our conversation over the telephone, we are two students doing our Master’s thesis in Accounting and Finance. The thesis is about management control and, specifically, performance measurement - the use of performance measures and its design in companies that have experienced high growth during the past three years (1998-2000). The growth is measured in terms of revenue growth. We intend to describe the design of performance measurement (what it looks like, what types of measures are used) and a description of the use of the performance measurement and its purpose. You and the other selected firms fulfil a number of hard criteria indicating that your firm is “entrepreneurial”. The working name of the thesis is “Performance Measurement in Entrepreneurial Organisations”. The questions are divided into three sections; Section 1 – Questions about market behaviour; Section 2 – Questions about the firm’s performance in relation to competitors; and section 3 – Questions about success factors. Please answer all the questions in the three sections. Your answers are very important for our study. Your answers are confidential. All your answers are anonymous. Thank you for your cooperation!

Section 1 – Questions About Market Behaviour In this section we ask questions about how your firm acts within its branch/market. Every question contains two questions about how a firm or a manager views different situations. Please mark the number indicating your opinion concerning your firm. Alternative 4 indicates that both statements are equally valid. NB! Mark one number on each line. Answer all the questions. Also remember to identify your firm in the box below. Company:____________________________ 1. Owing to the nature of the environment: Its best to explore it 1 2 3 4 5 6 7 Bold wide-ranging acts are gradually via timid, � � � � � � � viewed as useful and incremental behaviour common practice. 2. Our firm: Has a strong proclivity to 1 2 3 4 5 6 7 Has a strong proclivity low risk project (with � � � � � � � for high risk projects normal and certain rates (with chances of very return). high returns). 3. In our firm: There is a strong tendency to 1 2 3 4 5 6 7 We always try to be follow competitors in � � � � � � � ahead of competitors in introducing new things and product novelty or speed ideas. of innovation and usually

succeed. 4. Our firm is characterised by the fact that: We favour the tried and true. 1 2 3 4 5 6 7 We are growth, inno-

� � � � � � � vation and development oriented.

5. The products or services we market: Are based on ideas 1 2 3 4 5 6 7 Are largely developed in- developed by others. � � � � � � � house. 6. In our firm: There is a strong emphasis on 1 2 3 4 5 6 7 There is a very strong the marketing of the true and � � � � � � � emphasis on R&D, tried products or services. technological leadership

and innovation. 7. During the past three (3) years (1998-2000) our firm has marketed, excluding

mere minor variations: No new lines of products 1 2 3 4 5 6 7 A very large number of or services. � � � � � � � new products or services. 8. During the past three (3) years (1998-2000) our firm has marketed, excluding

mere minor variations: Changes in product lines 1 2 3 4 5 6 7 Changes in product lines have been of a minor nature � � � � � � � have been dramatic (e.g., (e.g., putting in a bookmark from mechanical to with the book). electric calculators).

Section 2 – Questions About the Firm’s Performance in Relation to Competitors Make a judgement of how successful your firm has been during the past three (3) years (1998-2000) in comparison to other companies in the branch in each of the categories below. Please mark the number indicating your firm’s performance. Should this period for some reason not provide a fair picture of the situation you are still asked to answer all questions. NB! Mark only one number on each line. Please answer all the questions. a) Sales growth rate

1 2 3 4 5 6 7 Well below average � � � � � � � Well above average

b) Market share

1 2 3 4 5 6 7 Well below average � � � � � � � Well above average

c) Cash flow

1 2 3 4 5 6 7 Well below average � � � � � � � Well above average

d) Operating profit

1 2 3 4 5 6 7 Well below average � � � � � � � Well above average

e) Profit margin

1 2 3 4 5 6 7 Well below average � � � � � � � Well above average

f) Return on investment

1 2 3 4 5 6 7 Well below average � � � � � � � Well above average

g) New product development

1 2 3 4 5 6 7 Well below average � � � � � � � Well above average

h) New market development

1 2 3 4 5 6 7 Well below average � � � � � � � Well above average

i) Personnel development 1 2 3 4 5 6 7

Well below average � � � � � � � Well above average j) Research and development

1 2 3 4 5 6 7 Well below average � � � � � � � Well above average

k) Level of costs

1 2 3 4 5 6 7 Well below average � � � � � � � Well above average

l) Political/public affaires

1 2 3 4 5 6 7 Well below average � � � � � � � Well above average

Section 3. Questions About the Importance of Success in Various Dimensions How important is it for your firm as a whole to be successful in the factors below? Please mark the number indicating the importance of each factor. NB! Mark only one number on each line. Answer all the questions. a) Sales growth rate

1 2 3 4 5 Of little importance � � � � � Extremely important

b) Market share

1 2 3 4 5 Of little importance � � � � � Extremely important

c) Cash flow

1 2 3 4 5 Of little importance � � � � � Extremely important

d) Operating profit

1 2 3 4 5 Of little importance � � � � � Extremely important

e) Profit margin 1 2 3 4 5

Of little importance � � � � � Extremely important f) Return on investment

1 2 3 4 5 Of little importance � � � � � Extremely important

g) New product development

1 2 3 4 5 Of little importance � � � � � Extremely important

h) New market development

1 2 3 4 5 Of little importance � � � � � Extremely important

i) Personnel development

1 2 3 4 5 Of little importance � � � � � Extremely important

j) Research & development

1 2 3 4 5 Of little importance � � � � � Extremely important

k) Level of costs

1 2 3 4 5 Of little importance � � � � � Extremely important

l) Political/public affairs

1 2 3 4 5 Of little importance � � � � � Extremely important

Thank you for your cooperation! Kind Regards Per Mattila and Mikael Åhlqvist

Appendix 5 - The Branches Used in the Sample Population

Industry Code

Industry

SNI 28 Manufacture of fabricated metal products, except machinery and equipment SNI 29 Manufacture of machinery and equipment n.e.c. SNI 30 Manufacture of office, accounting and computing machinery SNI 31 Manufacture of electrical machinery and apparatus n.e.c. SNI 32 Manufacture of radio, television and communication equipment and apparatus SNI 33 Manufacture of medical, precision and optical instruments, watches and clocksSNI 34 Manufacture of motor vehicles, trailers and semi-trailers

Appendix 6 – The Size of the Sample Population

Branch No. of active

limited firms Total size of sample

Size of sample (10-49)

Size of sample (50-249)

SNI 28 1695 21 10 11 SNI 29 1117 18 9 9 SNI 30 51 5 4 1 SNI 31 306 10 6 4 SNI 32 128 11 6 5 SNI 33 247 11 8 3 SNI 34 239 8 4 4 Total 3783 84 47 37

Appendix 7 – Frequency of Performance Measures

n=12 Profitability # Cost related measures #

Return on equity (Pre-tax) 6 Salary (indirect and direct) 4 Return on capital employed (Pre-tax) 4 Direct salary/invoicing 1 Return on sales (Pre-tax) 3 Salary/manhour 1 Return on assets (Pre-tax) 3 Salary per manhour/work hours 1 Earnings per share 1 Average salary level 1 Total no. of measures 17 Paid absence 1 Vacation pay 1 Income # Employee overheads/revenue 1 Operating income 7 Direct material 2 Operating income/department 1 Direct material/invoiced volume 1 Operating income/employee 1 Direct material/produced volume 1 Operating income/produced volume 1 Direct costs/produced volume 1 Operating income/invoiced volume 1 Cost/invoiced hour 1 Net income 5 Cost/production hours 1 Net income/project 1 Manufacturing overhead 1 Profit margin (Operating income+financial costs/capital employed) 5 Overheads 1 Contribution Margin 1 2 Cost of product development 1 Contribution Margin 2 1 Cost of repairs 1 Contribution Margin 2/product 1 Cost of product defects 1 Contribution Margin 2/customer 1 Cost of corrections 1 Total no. of measures 27 Cost of complaints 2 Cost of scrapping 2 Cash flow # Cost of incorrect deliveries 1 Operating cash flow 4 Cost of goods sold 1 Liquid funds Inventory cost 1 Cash 8 Lease cost 1 Cheque account 8 Depreciation cost 1 Giro 1 Cost of taxes 1 Accounts payable 8 Total cost/project 1

Accounts receivable 8 Employer's contribution for national social security purposes 1

Accounts receivable ledger 1 Total no. of measures 36 Average accounts receivable 1 Total no. of measures 39

Other accounting based measures # Resource utilisation # Equity/assets ratio 9 Inventory turnover rate 4 Debt/equity ratio 2 Inventory volume 1 Quick ratio 2 Invoiced hours/production hours 1 Retention ratio (Investment/revenue) 2 No. of planned work hours 1 Equity/share 1 No. of invoiced hours 1 Asset turnover rate 1 Material usage 1 VAT 1 Total no. of measures 9 Total no. of measures 18 Productivity # Sales # Estimated time/actual time 3 Revenue 7 Kilo/manhour 1 Revenue/customer 4 Units/manhour 1 Revenue/order 2 Meter/manhour 1 Revenue/project 1 Kilo/product 1 Revenue/ongoing project 1 Units/product 1 Revenue/product 1 Meter/product 1 Revenue/salesman 1 No. of production hours 1 Revenue/invoiced hour 1 No. of strokes/machine hour 1 Revenue/work hour 1 Contribution margin/employee costs 1 Revenue/offer 1 Utilisation ratio/working day 1 Revenue/offer compared to actual revenue/offer 1 Manufacturing time/unit 1 Revenue/revenue previous week 1 No. of production start-ups 1 No. of orders 4 Value added/direct salary 1 No. of offers 1 Value added/total salary 1 Invoicing 3 Consumption of material 1 No. of delivered products 2 Machine time 1 Invoiced sales/product 1 No. of repairs 1 No. of sales visits/time unit 1 No. of projects 1 Spare part sale/customer 1 TAK11 1 No. of delivered products /targeted no 1 Total no. of measures 22 No. of units sold/product 1 Total no. of measures 37

11 The TAK measure consists of three parts; 1) Availability = Planned time – stop time/ planned time; 2) Plant efficiency = manufacture time * produced no. of units/ available production time; 3) Quality = produced no. of units – no. of scrapping/ produced no. of units.

Market position # Employee situation #

Market position in comparison to competitors by looking at the annual reports 1

No. and kind of tasks the employees can perform 1

Net income of competitors 1 Education hours/employee 1 Total no. of measures 2 Education hours/production hours 1 Level of education 1 Customer relationships # No. of employees 1 Delivery time 4 Overtime 1 Actual delivery time/agreed delivery time 3 No. of risk moments in production 1 Customer satisfaction (measured by questions with scale) 2

Risk of injuries per employee and moment 1

No. of faulty products delivered 1 Total no. of measures 8 Revenue/customer 1 Total no. of measures 11 Product development and innovation # Cost of product development 1 Supplier related measures # Total no. of measures 1 Delivery time 4 No. of complaints 1 Environmental aspects # No. of late deliveries 1 Quantity of scrap 3 No. of faulty products 1 Quantity of hazardous material 1 Price from supplier 1 Quantity of waste 1 Total no. of measures 8 Total no. of measures 5 Flexibility #

No. and kind of tasks the employees can perform 2 Total no. of measures 2 Total no. of measures # Average no. of measures 22 Quality # Average no. of financial measures 14 No. of complaints 8 Average no. of non-financial measures 8 No. of scrapping 4 Cost of scrapping 2

PPM (produced faulty units/million produced units) 2 No. of quality deviations in production 2 Cost of complaints 2 Correction costs 1 No. of reworked units 1 Cost of scrapping/revenue 1 Total no. of measures 23