Non-financial performance measurement in manufacturing companies

The British Accounting Review 37 (2005) 261–297 www.elsevier.com/locate/bar

Non-financial performance measurement in manufacturing companies Ahmed Abdel-Maksouda, David Dugdaleb,*, Robert Lutherc a

b

Department of Accounting, University of Sharjah, United Arab Emirates Department of Economics, University of Bristol, 8 Woodland Road, Bristol BS8 1TN, UK c Bristol Business School, University of the West of England, Bristol, UK Received 14 January 2004; revised 16 February 2005; accepted 15 March 2005

Abstract The contemporary manufacturing environment is characterised by increased worker responsibility coupled with the measurement and reporting of numerous aspects of performance. At shop-floor level much of this performance measurement and reporting is non-financial. This paper reports on a large scale, empirical investigation of the measurement practices in British factories at the beginning of the 21st century. Descriptive statistics are provided as well as a classification model of shop-floor non-financial measures. In addition, the relationships between operational measures and contingent firm-specific and external variables are identified. Various partial relationships are found, and ‘across the board’ high levels of shop-floor performance measurement are found to be associated with a severely competitive environment, an upward communication corporate ethos, and with the adoption of JIT or TQM/TPM. q 2005 Elsevier Ltd. All rights reserved. Keywords: Operational performance measurement; Non-financial performance measures

1. Introduction Success in global markets requires products of high quality at low cost, and a first-class customer service. Many companies have responded to these challenges by implementing innovative managerial practices such as JIT, investing in advanced manufacturing technologies such as CAD/CAM, and emphasising quality, delivery, innovation and

* Corresponding author. E-mail address: [email protected] (D. Dugdale).

0890-8389/$ - see front matter q 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.bar.2005.03.003

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flexibility in meeting customer needs (Banker et al., 1993). Global competition has been met by new management and production techniques and costs controlled through streamlined business processes (IFAC, 1998). These changes are often supported by employee empowerment with increased worker involvement in the control of all phases of manufacturing, and by management information and decision making being diffused throughout the organisation (Kaplan, 1983; Banker et al., 1993; IFAC, 1998). In a parallel, but related, development it has been suggested that ‘day to day’ control of manufacturing and distribution operations is best handled with non-financial measures. In this paper, cognisant of the enlarged role of workers in contemporary manufacturing environments, we report a detailed, large-scale investigation of the development and application of non-financial measures of performance at the shop-floor level in UK manufacturers. The research is informed by, and builds upon the corporate performance measurement literature. Since our analysis aims to explore possible relationships between performance measures and other organisational characteristics, we follow a broadly interpreted contingency theory approach to the analysis of survey data. The paper comprises seven sections. First, we review the literature on contingency theory, corporate performance measurement and specific contextual variables in manufacturing companies, concluding with an a priori grouping of variables derived from analysis of the literature. In Section 3, we describe the methodology adopted in gathering and analysing data. Section 4 sets out and provides commentary on the descriptive statistics derived from the raw data. Section 5 reports factor analysis of both the dependent (non-financial performance measures) and contingent variables (such as the adoption of advanced technology, degree of competition etc.) This section concludes with a revised summary of variable groupings, now based on factor analysis, and commentary on the comparison with a priori groupings. In Section 6, we analyse the associations between dependent and contingent variables using Kendall’s non-parametric tau test. Our final section draws conclusions from the analyses and relates these to the extant literature. 2. The literature 2.1. Contingency theory Our methodological approach is based on contingency theory, the theoretical perspective that emphasises how contingent factors such as technology and environment affect the design and functioning of organisations. Its central premise is that no universally appropriate organisational structure applies equally to all organisations in all circumstances. Instead, each structure is, or should be, a response to a set of contingencies. The variables most commonly identified in the contingency theory literature are size, environmental uncertainty, production technology, corporate strategy and market environment (Covaleski et al., 1996; Otley, 1995; Mitchell et al., 2000). A company’s management accounting system is a significant element of its organisational structure and the features of an appropriate accounting system will depend upon the specific circumstances that the company faces (Otley, 1980). Accordingly, numerous researchers have attempted to identify important contingencies and assess their impact on the design of management accounting systems. A brief overview of studies that have particular relevance to the themes of this paper is presented below.

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Following Burns and Stalker’s (1961) seminal work, Gordon and Narayanan (1984) examined the relationships between an organisation’s perceived environmental uncertainty (PEU), its structures and its information systems. They found that higher/(lower) PEU is associated with organic/(mechanistic) types of organisational structure, and with higher/(lower) perceived importance attached to information characterised as being external, ex-ante, or non-financial. Chenhall (1997) examined the effect of the interaction between TQM and reliance on manufacturing performance measures (MPM) on organisational performance. His results showed that the association between TQM and performance was stronger where MPM were used as part of managerial evaluation. Similarly, Sim and Killough (1998) investigated whether manufacturing practices such as TQM or JIT achieve higher performance when they are accompanied by particular management accounting systemsin particular performance goals, performance measures and workers’ performancecontingent rewards. They found that performance gains can arise from complementarities between TQM or JIT and performance goals and performance-contingent rewards. Chenhall and Langfield-Smith (1998) examined management techniques, management accounting practices and the performance of organisations with differing strategic priorities. They found that high performance firms with product differentiation strategies were associated with, amongst other things, quality systems, team-based structures and employee-based measures.Thosewitha strongemphasisonlow pricestrategieswerefoundtobeassociatedwith manufacturing system innovation, process improvement, and activity-based techniques. Anderson and Lanen (1999) studied the contingent relationship between external competition and management accounting practices and explored the potentially mediating effects of firms’ competitive strategies. They attributed changes in management accounting practices (planning and control, performance measurement, and cost management) to whether firms adopted ‘defender’ or ‘prospector’ strategies and whether they were domestic or international. Clearly, numerous factors can potentially affect the design of a management accounting system. As part of this tradition, we consider relationships between organisational features (in our case non-financial shop floor measures) and potentially associated contingent influences. Given the lack of knowledge about factory floor non-financial measurement,we are not seeking to test hypotheses based on a priori conceptualisation. Instead, as explained by Hartmann (2000), we adopt the contingency framework as a pragmatic device to explore this specialist field with a view to theoretical development. Also, this study differs from the formal contingency approach in that some of our ‘contingent variables’, such as management accounting practices or innovative managerial practices, would normally be outcomes rather than inputs. 2.2. Corporate performance measurement The measurement and communication of financial performance is central to accounting. For internal (management) accounting, corporate objectives are supported and communicated by detailed plans and budgets. Managerial control then involves measuring actual performance, comparing it to planned performance and taking remedial action to attempt

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to correct, in particular, adverse deviations. Experience with this management style has led to the overarching slogan ‘what you measure is what you get’. A statement by the International Federation of Accountants (IFAC, 1998) portrays the development of management accounting in sequential stages. In Stage I early management accountants concentrated on cost determination and financial control; then, by 1965, in Stage II their role expanded to include provision of information for management planning and control. By 1985, in the third stage, they aimed to reduce resource waste in business processes. In Stages I and II shop floor performance was formally reported through financial outcomes. So, through much of the 20th century, standard cost variances provided the principal monitoring of shop floor activity. Nonfinancial ‘process’ indicators, such as units completed, scrapped or rejected, were seen to fall within the domain of ‘operations’ and were not necessarily integrated into the financially dominated management control systems. But in IFAC’s Stage III, shop floor performance measures of actual processes (rather than their financial consequences) start becoming integrated into the formal monitoring system. Kaplan (1983), Vollman (1989), Drucker (1990), Hall et al. (1991) and Conti (1993) had been influential in arguing that traditional, financially based performance measurement systems were insufficient. Broader measures were needed to assess and promote improvements in competitiveness or the effectiveness of new methods, and various authors (Maskell, 1989a; Bhimani, 1993; Bromwich and Bhimani, 1994; Otley, 1997) indicated that operational control is best achieved by non-financial measures. Surveys of UK manufacturers (CIMA, 1993; Drury et al., 1993; Bhimani, 1993, 1994) revealed growing emphasis on non-financial indicators, focusing particularly on quality issues and marketing activities. Aspects of non-financial performance such as customer satisfaction, employee efficiency and quality levels were thought important by all companies surveyed by CIMA (1993) and the central role of ‘front line’ workers, close to processes and customers, was recognised in providing ideas for improving performance. We reviewed studies particularly concerned with ‘operational’ manufacturing measures (Maskell, 1989a,b; Bhimani, 1993; CIMA, 1993, 1996; Drury et al., 1993; Drury, 1996; Otley, 1997; 1999; Chenhall, 1997; Ittner and Larcker, 1998; Chenhall and Langfield-Smith, 1998) and found some inconsistency in this literature in the categorisation of measures. For example, Drury et al. (1993) classify ‘set-up reduction’ as a non-financial measure of product quality while Drury (1996) classifies it as a measure of on-time delivery. And ‘number of complaints received from customers’ is classified as a measure of product quality by Chenhall and Langfield-Smith (1998) but of customer satisfaction by Drury (1996). Nevertheless, six broadly separate categories of measures: product quality, customer satisfaction, on-time delivery, employee morale, efficiency and utilisation, and product development could be discerned. Each of these evaluation categories comprises both financial and non-financial performance measures and, with the exception of product development, is centrally relevant1 to the shop floor.

1

On the basis of evidence gathered from manufacturers when piloting our questionnaire.

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2.3. Contextual variables in contemporary manufacturing companies Many commentators2 suggest that contingent variables such as managerial and technological factors, organisational structure and environmental factors are important in understanding performance measurement systems. This study, guided by the extant literature, concentrates on the specific techniques and practices relevant to shop-floor operations that reflect the broader, organisation-wide concerns of contingency theorists. Managerial issues are addressed by assessing use of modern techniques such as JIT, TQM etc. and the degree of interest in contemporary management accounting practices such as activity-based costing, economic value added etc. Technological issues are addressed by assessing the degree of use of a range of technologies including, CAD, CAM, CIM etc. Organisational structure is considered via a range of contingent variables that reflect the degree of involvement of shopfloor workers, size of company and so on. External environmental factors are represented in the study through contingent variables that ask respondents to indicate the importance of several dimensions of the competitive environment. 2.3.1. Advanced manufacturing techniques (AMTs) and innovative managerial practices (IMPs) The late 20th century saw the widespread introduction of computer assisted ‘advanced’ manufacturing technologies and managerial techniques such as just-in-time manufacture and total quality management. Both changes relied on increased worker involvement and concomitant revised shop floor performance measurement systems (Clark, 1989; Mather, 1989; Dixon et al., 1990; Kaplan and Norton, 1992). Some traditional accounting measures became redundant (Harries, 1990; Bromwich and Bhimani, 1994) and managers sought different elements of information about activities under their control (Kaplan, 1983; Maskell, 1989a,b; Innes and Mitchell, 1989; Littler and Sweeting, 1989; CIMA, 1993; Drury et al., 1993). Cobb (1993) found that companies adopting IMPs tended to move away from centralised, monthly reporting in mainly financial terms to decentralised, daily or weekly reporting of operational indicators. Other studies reported positive associations between the emphasis placed on AMTs and IMPs and the provision of non-financial measures such as defect rates, on-time delivery, and machine utilisation (Daniel and Reitsperger, 1991; Banker et al., 1993; Abernethy and Lillis, 1995; Perera et al., 1997; Ittner and Larcker, 1998). Banker et al. (1993) surveyed shop-floor employees in 40 US plants and found reporting of manufacturing performance measures for line personnel to be positively related to the implementation of IMPs and AMTs. The nature of manufacturing performance measures appropriate for different elements of AMTs and IMPs has been identified as a useful area for further research (Kaplan, 1993; Ittner and Larcker, 1998; Chenhall and Langfield-Smith, 1998). However, despite evidence permeating the literature of the effect of IMPs and AMTs on performance measures generally, their effect on measures at shop floor level has not yet been examined in depth. 2 Otley, 1980, 1997; Lee, 1987; Drucker, 1990; Daniel and Reitspergers, 1991; Banker et al., 1993; CIMA, 1993; Abernethy and Lillis, 1995; Bruggeman and Slagmulder, 1995; Ittner and Larcker, 1998; Perera et al., 1997; Chenhall and Langfield-Smith, 1998; Jazayeri and Hopper, 1999.

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2.3.2. Management accounting practices There are differing views concerning the role of management accounting in developing wider measures of performance. First, some commentators argue that management accounting is well placed to provide information to develop performance measures (Shank, 1989; Back-Hock, 1992; Nanni et al., 1992; Shields and Young, 1992; Horngren et al., 1994; Chenhall and Langfield-Smith, 1998). Proponents of this view see non-financial measurement as simply an extension of the established role that management accounting has played in evaluating managerial and organisational performance. It is argued that some ‘advanced’ accounting techniques have been promoted to enhance the way in which performance measures assist in the management of change. Examples include balanced scorecard models and performance measurement hierarchies (Kaplan and Norton, 1992; Lynch and Cross, 1992; Nanni et al., 1992; Chenhall and Langfield-Smith, 1998). The alternative view is that the involvement of accountants does not necessarily lead to the design of innovative performance measurement systems (Johnson, 1992; McKinnon and Bruns, 1992). It is argued that there is a tendency for management accountants to bring an overly financial view to the task that may lead to an unbalanced set of performance measures (Vollman, 1989; Eccles, 1991). In addition, management accountants tend to favour performance measures with a product-oriented focus rather than the process-oriented focus that is more helpful in integrating activities with strategies (Nanni et al., 1992; Chenhall and Langfield-Smith, 1998). 2.3.3. Shop-floor involvement A common theme in new manufacturing environments is the empowerment of shop-floor (SF) workers by putting production under their control and encouraging them to solve problems, improvise, become more flexible and interactive (Kaplan, 1983; Banker et al., 1993). Several aspects of SF involvement are incorporated in this research study: SF suggestions, reporting feedback to SF, SF training and remuneration, and finally, size of workforce. It has been suggested (CIMA, 1993) that ideas for improving processes and performance for customers must increasingly come from ‘front-line’ workers who are closest to internal processes and customers. Kaplan and Norton (2001) report the case of an organisation that attempted to validate hypothesised balanced scorecard cause-andeffect relationships by measuring the strength of linkages among measures in their four different perspectives. A correlation was found between an increased number of suggestions and lower rework (an internal business process measure). Commentators such as Banker et al. (1993), Cobb (1993) and Bromwich and Bhimani (1994) argue that change in performance reporting and control systems is needed to match the changing environment. Manufacturing performance feedback helps line personnel to learn and directs effort towards productivity and quality improvements. More traditionally, Maskell (1992) and Cobb (1993) argue that more detailed reporting of shop floor information is needed to enable companies to keep close track of the use of their resources. The Drury et al. (1993) survey of UK manufacturers shows that SF data collection and training is expected to be one of the changes in the management accounting systems in UK

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organisations. They identify two significant management accounting problems in UK firms: obtaining accurate and timely information on-line from the SF level and educating SF staff to interpret more fully the information produced. Training and employee empowerment enables firms to deliver high quality and low cost products and services required for today’s sophisticated markets (Brancato, 1995) Finally, workforce size is also potentially important. The CIMA (1993) survey found that a growing workforce generates control problems and a greater need for explicit performance measurements. 2.3.4. Competitive environment The dynamics of a company’s markets are potentially important in influencing shop floor non-financial performance measures. External influences, especially if they threaten survival, can affect the measurement of performance and even force reassessment of an organisation’s very structure (CIMA, 1993; Drury et al., 1993). Substantial change in the nature and intensity of competition can force firms to identify and measure the non-financial ‘value drivers’ that might lead to success in the new competitive environment and Chenhall and Morris (1986) found a positive association between perceived environmental uncertainty and the demand for broadbased information systems.

Application of IMPs

Application of AMTs

Advanced management accounting practices

SFNFPMs of: Customer satisfaction On-time delivery

Shop-floor involvement

Product quality

Efficiency and utilisation

Employee morale

Competitive environment Industry type

Fig. 1. A literature-based model of shop floor non-financial performance measures (dependent) and contingent (independent) variables.

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2.3.5. Industry type The term ‘manufacturing’ encompasses a wide range of industries that differ in respect of industrial processes, levels of labour and capital intensiveness, modes and intensity of competition and so forth. These industry features inevitably influence the scope and emphasis of various potential non-financial measures of factory performance and consequently our study follows prior research by including industry type as a contextual variable worth investigating. To conclude, we note that a contingency-type approach was advocated by CIMA (1993), (Executive Summary): ‘Performance measures appear to change as the company is influenced by different factors, some to do with innovations in manufacturing technology and factory organisation and others entailing the imposition of particular standards (such as quality levels) by a customer’. Similarly, Drucker (1990) and Otley (1997) suggested that variables such as the extent of AMTs and IMPs are important in understanding performance measurement systems. Our review of the literature leads us to propose, prior to analysis of data collected, the summary model of shop floor nonfinancial performance measurement shown in Fig. 1 below.

3. Methods and data While much has been written about measuring the overall performance of businesses and about the performance of higher-level management, the literature concerned specifically with detailed non-financial performance measures at operational level is limited. Factory visits were, therefore, undertaken in order to sensitise the researchers to shop-floor issues and facilitate judgement as to which business measures were applicable at shop-floor level. On the basis of in-depth interviews at the factories and the literature reviewed above, a questionnaire was compiled. This was then validated and amended by piloting it with 13 academics and 24 practising management accountants. Since our aim was to obtain a comprehensive view of the shop-floor performance measures used in UK manufacturers, a large-scale postal survey was undertaken. Questionnaires relating to 19 shop-floor non-financial performance measures3 (SFNFPMs) were sent to the management accountants4 of 3

Consistent with Fig. 1, the 19 individual measures, derived from the studies listed under Corporate Performance Measurement in Section 2, fell into five groups: product quality (scrap, defects, rework and batches); customer satisfaction (number of complaints received from customers, number of returns and number of warranty claims); on-time delivery (percentage of on-time delivery to customer, on time production, schedule adherence and manufacturing cycle efficiency); employee morale (percentage of staff turnover, percentage of absenteeism, percentage of lateness and employee attitude survey) and efficiency and utilisation (efficiency, activity, capacity utilisation and proportion of over-time worked). 4 The questionnaire was sent to management accountants, financial managers, or managers who are responsible for the management accounting function in the surveyed manufacturing firms. This reflected our interest in traditional and contemporary management accounting techniques. However, because of the wide range of data collected, respondents were encouraged, in covering letters and within the questionnaire itself, to consult with other specialist managers where necessary.

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2242 UK manufacturing firms belonging to 21 different industries (SIC codes 15–36) having more than 200 employees. Respondents were asked to indicate whether the SFNFPMs listed were used and, if they were, their perceived importance. A second part of the questionnaire gathered data on the 37 internal and external contingent (independent) variables. For these independent variables5 respondents were asked to convey the extent of their impact (e.g. for variables relating to the competitive environment) or the extent of their application (e.g. for variables relating to advanced manufacturing technology). The total number of usable responses to the questionnaire was 313 giving an overall percentage of 14.3%. In most cases the questionnaires were completed comprehensively; on individual questions where one or more respondents failed to indicate an answer the analysis was based on those that had responded. A summary of the descriptive statistics calculated from the data is presented, together with a commentary in Section 4. As shown in Fig. 1, and consistent with the literature, we had presumed at the outset that the measures and the independent variables could be grouped under five and six headings, respectively. However, factor analysis revealed differences between the theoretical and empirical groupings of the 19 SFNFPMs. This process, explained in Section 5, re-grouped the 19 non-financial performance measures into five, slightly altered, evaluation categories. Also, again based on the empirical data from the questionnaire survey, the 37 contingent variables were found to group into nine factors, rather than the original six shown in Fig. 1. Tests for possible association between the existence and importance of the 19 nonfinancial performance measures and the 37 contingent variables, relating to the firms’ internal and external environments, are reported and interpreted in Section 6. 4. Summary descriptive statistics 4.1. Non-financial performance measures Management accountants were asked to indicate whether various shop-floor nonfinancial performance measures were applied in their companies and, if they were, the importance attached to them. Importance was signified on a seven-point scale from 1 (no importance) to 7 (critical importance) and the 19 measures are shown in rank order in Table 1. 5 These comprised six IMPs (JIT, TQM, TPM, MRPI/II, ERP, OPT), eight AMTs (FMS2, CAD, CAM, CIM, CNC, CAE, AS/RS, AGVS), seven contemporary management accounting practices (benchmarking, activitybased techniques, balanced scorecard, economic value added, throughput accounting, strategic management accounting, customer profitability analysis). Also eight shop-floor aspects (company’s interest in its SF suggestions, impact of SF suggestions for cost reduction, impact of SF suggestions for quality improvement, percentage of SF receiving feedback, frequency of feedback, average annual SF formal training, average annual basic wages, workforce size), six aspects of competition (quality, innovation, customer service, price, delivery, flexibility). Respondents were also asked whether their market was becoming more competitive and the extent to which changes in competition had affected their companies’ shop-floor performance measurement system.

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Table 1 Shop-floor non-financial measures-in ranked order of importance Measures (ranked by mean value on scale of 1–7)

Mean importance for firms using the measure

Median

% of firms using this measure

On-time delivery to customers Number of complaints from customers Number of customer returns Efficiency (standard hours produced/hrs worked) Defects (% of total production) Scrap (% of total production) Absenteeism Number of warranty claims Manufacturing cycle efficiency Activity (std hrs produced/budgeted std hrs) Capacity utilisation (hrs worked/budgeted hrs) Proportion of overtime worked % Schedule adherence % On-time production Rework (% of total production) Employee lateness Staff turnover Employee attitudes Batches (% adjusted)

6.4 6.2 5.9 5.8

7 7 6 6

92 95 91 90

5.8 5.7 5.5 5.5 5.3 5.3

6 6 6 6 6 6

87 90 97 70 62 86

5.3

6

84

5.3 5.2 5.2 5.2 4.9 4.6 4.5 4.1

5 5 6 5 5 5 5 4

92 68 76 84 90 89 63 56

Non-financial performance measures have attained greater theoretical prominence since the promotion of the ‘balanced scorecard’ (Kaplan and Norton, 1992, 1993, 1996) and other related ideas such as the ‘performance prism’ (Neely et al., 2002) and the ‘value chain scoreboard’ (Lev, 2001). Our findings reveal that such measures are now extensively employed in UK manufacturing companies with most of the measures listed used by more than 80% of the responding companies. Where measures are used, they are generally considered to be important. The overwhelming majority of UK manufacturing companies measure delivery timeliness and number of complaints from customers, and respondents perceive these two measures to be critically important. As the third ranked measure also relates to the measurement of customer satisfaction it is clear that most manufacturing companies are very customer focused. While the top three measures relate directly to customers the next four relate to process efficiency and cost control. There are measures of efficiency, defect and scrap levels and absenteeism in most firms and these measures are important. Fewer companies systematically measure warranty claims (another customer oriented metric) or manufacturing cycle efficiency (another efficiency measure) but, for those that do, these measures are also important. There are measures of activity and capacity utilisation in over 80% of responding firms and these are important with over 50% of respondents marking them ‘6’ or ‘7’ on

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the rating scale. The proportion of overtime worked also receives widespread attention. Linking these results with the high importance attached to measures of efficiency and cost control shows that UK manufacturers pay considerable attention to controlling their production costs. Percentage on-time production and percentage schedule adherence are measured in 76% and 68% of responding firms respectively. This indicates that a significant minority of companies does not explicitly quantify manufacturing delivery performance. However, it must be remembered that ‘on-time delivery to customers’ is a critically important metric for many companies, measured by 92% of respondents. It is likely that, especially in companies that produce for stock, on-time delivery of production is not vital, but on-time delivery to customers is. While, as we have seen, measures of customer satisfaction and process efficiency receive considerable attention, less importance is attributed to the ‘employee oriented’ measures of lateness or staff turnover, although both are almost universally measured. Employee attitude surveys are not conducted in a significant minority of responding firms and, where they are undertaken, their importance is, typically, not judged to be so great as are other measures. 4.2. Contingent (‘independent’) variables In this paper, we are interested in the contingent variables for their potential influence on the non-financial performance measures. Descriptive statistics for the contingent variables, therefore, appear in an Appendix rather than in the main text. Nevertheless, this update of the extent to which advanced manufacturing techniques, innovative managerial practices, contemporary management accounting concepts, etc. are currently being applied is interesting in its own right and merits some comment. Of the advanced technologies only computer-aided design is widely employed—by over 80% of manufacturers. Other technologies are employed by less than 60% of respondents although computer aided manufacturing and CNC (computer numerically controlled machines) are used in more than half of responding firms. Materials requirements planning (MRP) systems are employed by 84% of respondents while the ‘Japanese inspired’ TQM, JIT and TPM (total quality management, just-in-time production and total preventive maintenance) are all employed by over 80% of firms. 54% of respondents claimed to use enterprise requirements planning (ERP) systems and a significant minority (37%) claimed to employ the specialised ‘optimised production technology’ (OPT) scheduling software. Thus, most manufacturing companies employ modern production methods based on computer-based production planning and/or the TQM and JIT ‘philosophies’. Although more than 50% of companies make use of customer profitability analysis, performance benchmarking, and strategic management accounting, relatively few companies apply these techniques systematically. Contrary to the impression given by some textbooks, less than 50% of respondents claim to apply activity-based techniques, throughput accounting, the balanced scorecard and economic value added and the proportion applying these systematically ranges from only 12% (activity-based

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techniques) to 16% (throughput accounting). We conclude that systematic take-up of these contemporary management accounting techniques is not yet extensive in UK manufacturing companies although most firms have some experience of them. Most companies both collect and are interested in suggestions from shop-floor workers. However, feedback to workers concerning their performance is selective with only 52% of respondents claiming to provide feedback to over three-quarters of the workforce. Where feedback is provided, it can be frequent with over 40% of respondents claiming to provide feedback on a daily or weekly basis. The survey provides unequivocal evidence that manufacturing companies are concerned about the competitive environment with virtually every company (more than 99%) concerned about their competitive situation. Respondents saw all the competitive dimensions as important with customer service, quality, price and delivery in particular having mean ratings of approximately 6 (where a rating of 7 reflects ‘critical importance’). Furthermore, a majority of companies saw changes in the competitive environment having important influences on their shop-floor performance measurement systems. This finding provides support for the contingency approach we have adopted. 4.3. Summary The descriptive statistics for the non-financial performance measures reveal indisputably widespread interest in non-financial performance measures in UK manufacturing companies. Customer related metrics are widely reported and are perceived to be crucial and a number of measures related to efficiency, utilisation and cost are also widely monitored and considered very important. The widespread integration of NFPMs confirms that much of UK manufacturing accounting has achieved IFAC (1998)’s evolutionary Stage III. The descriptive statistics for the contingent variables reveal almost universal concern with various dimensions of the competitive environment; intuitively, one might expect this to be related to the general concern with non-financial measures related to customer satisfaction. There is widespread application of ‘innovative production procedures’ but more limited application of ‘advanced manufacturing technologies’ (except computer aided design) and ‘contemporary management accounting practices’. The core issue for this paper is an exploration of the degree to which the use of non-financial measures might be related to the contingent variables and we turn to this in the remainder of the paper.

5. Factor analysis The starting point in development of the survey instrument was a listing of the nonfinancial, shop-floor related indicators (measures) that could be drawn from the literature and from factory visits and interviews. These are the 19 dependent variables in the study. A similar approach was adopted in identifying 37 independent variables that specify the internal and external environmental characteristics.

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The first step in exploring this data was to undertake factor analysis on both the dependent and independent variables.6 We had assumed, a priori, that the variables could be grouped as shown in Fig. 1, into five categories of measures and six groups of contingent variables. The grouping of non-financial measures is more than just a matter of convenience—it reflects our understanding of claims in the performance measurement literature; for example, that the dimensions of timeliness, quality and efficiency are important in satisfying customers or that satisfied employees are a necessary, but not sufficient, condition in achieving these. One of our aims was to test the, sometimes implicit, assumptions in the literature concerning the appropriate number of measurement ‘dimensions’ in a shop-floor performance ‘scorecard’. Furthermore, it had been stressed by CIMA (1993) that attention should be directed towards analysis of areas of concern in performance measurement rather than towards the individual measures chosen. Thus, our first reason for undertaking factor analysis was to check the assumptions underpinning our a priori grouping of variables. A second motivation for factor analysis was the usual one of data reduction. Obviously, the number of potential correlations between independent and dependent variables is huge so factor analysis was undertaken in order to make the subsequent analysis more manageable by ‘reducing’ the number of dependent variables (performance measures). These variables have a common measurement scale designed to assess the importance attached to each measure and so data reduction was particularly appropriate. Subsequent statistical analysis was based on aggregate summaries of variables, determined by factor analysis, rather than on the 19 variables of which they are comprised. The use of factors rather than the raw data for the measures also meant that, if respondents had seen some variables as synonymous (for example, scrap and defects) these were combined into a single variable for analysis. Factor analysis was also undertaken on the independent variables and revealed a more refined, and empirically based, grouping of these variables than that assumed a priori in Fig. 1. However, for these variables, measurement scales differed, so data reduction was not so appropriate, and, in addition, we were interested in whether specific technologies and practices impacted decisions concerning shop-floor measures. Factor analysis was not, therefore, used to reduce the number of variables. It was used, however, to group the contingent variables for analysis and discussion, thus providing a convenient structure for Section 6. 5.1. The non-financial performance measures Table 2 summarises the factor analysis of the non-financial performance measures. Five factors emerged from an analysis of the 19 SFNFPMs. These are similar to the a priori grouping of variables and this gives some confidence both in our research methods and in the consistency of respondents’ replies. 6 We initially assumed that causality would be from our presumed ‘independent’ variables to the use and importance of the non-financial performance measures. However, in the light of the results we amended some of our views.

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Table 2 Rotated factor matrix for SFNFPMs SFNFPMs

Factor 1

Scrap (% of production) Defects (% of production) Rework (% of production) Batches (% adjusted) No. of complaints from customers No. returns No. of warranty claims % on-time delivery to customers % on-time production % schedule adherence Manufacturing cycle efficiency Staff turnover Absenteeism Lateness Employee attitude survey Efficiency Activity Capacity utilisation Proportion of overtime worked Eigenvalues % of variance Cumulative %

2

3

4

5

.02 .126 .166 .103 .107

.275 .226 .146 .360 .223

.330 .139 .167 .03 .210

.462 .605 .662 .493 .02

.121 .251 .151 .08 .688

.07 .145 .02

.08 .05 .363

.226 .01 .221

.202 .239 .154

.642 .434 .327

.01 .256 .274

.636 .789 .405

.176 .08 .08

.249 .198 .333

.129 .03 .256

.118 .125 .245 .138 .597 .917 .708 .340

.230 .156 .09 .393 .009 .131 .181 .02

.511 .773 .554 .177 .216 .08 .144 .366

.157 .04 .155 .114 .08 .117 .114 .191

.09 .181 .147 .132 .08 .08 .122 .243

2.157 11.353% 11.353%

1.961 10.319% 21.672%

1.752 9.224% 30.896%

1.730 9.105% 40.001%

1.542 8.117% 48.118%

Extraction method: Alpha factoring. Rotation method: Varimax Kaiser normalisation. The number of factors to be retained was determined by choosing the SPSS system default option; that is to consider all factors with eigenvalues of one or more.

There were five a priori groupings and five factors emerged from factor analysis, broadly grouped in the expected manner. Factor 1, labelled efficiency and utilisation, includes measures of efficiency, activity, and capacity utilisation. Factor 2, labelled ontime delivery, includes measures of on-time delivery to customers, % on-time production, % schedule adherence, manufacturing cycle efficiency and employee attitude survey. Factor 3, which we have labelled human resources, includes measures of staff turnover, absenteeism, lateness and % overtime worked. Factor 4, labelled product quality, includes measures of scrap, defects, reworks and batch adjustments. Factor 5, labelled customer satisfaction, includes measures of complaints, returns and warranty claims. The only unexpected finding was the inclusion of employee attitude surveys in a factor mainly focused on delivery performance. It is possible that some of the methods employed in order to achieve on-time deliveries, such as the organisation of production into cells and the use of just-in-time techniques, require a reliable, involved and committed workforce. The inclusion of employee attitude surveys in the ‘on-time delivery’ factor had a consequence for the group of variables that had, a priori, been labelled ‘employee morale’.

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The literature (Bhimani, 1993; Drury, 1996) had led us to expect such a grouping. However, with attitude surveys included elsewhere, the group of measures assembled under Factor 3, relating to human resources, could be interpreted in different ways. Emphasis on measures of turnover, absenteeism, lateness etc. might be seen as evidence of concern for employee morale but, ironically, it might equally be interpreted as desire for a disciplined workforce. These alternative, and opposite, interpretations align neatly with McGregor’s (1960) ‘theory X’ and ‘theory Y’ styles of management for either of which the grouping and title ‘Human resources’ is appropriate. The five-factor construct assumed in developing the performance measures, and implicit in the data, is consistent with other conceptions of a multi-dimensional scorecard. Working with executives in 12 companies over a period of one year, Kaplan and Norton (1992) developed ‘the’ balanced scorecard incorporating four measurement dimensions. Their four-dimensional scorecard followed work with companies ‘at the leading edge of performance measurement’ (p. 71) and can be compared with the five dimensional, large sample survey-based construct derived here. At business-unit level they identified customer, process, financial, and learning and growth dimensions and pointed to ‘time, quality, performance and service, and cost’ (p. 73) as important measures on the customer dimension. Our study specifically excludes financial measures but the five dimensions we show to be important at shop-floor level can be readily mapped onto existing scorecard literature. Concern for measurement of on-time delivery, product quality, customer satisfaction, efficiency and utilisation, link to Kaplan and Norton’s time/quality/service/cost analysis. Our other factor, labelled ‘human resources’ (Factor 3) does not readily map onto the Kaplan and Norton scorecard. However, they recognise the importance of employee measures (satisfaction, retention, productivity) when discussing their learning and growth perspective (Kaplan and Norton, 1996: 129). Other work such as that of Olve and Sjostrand (2002: 15) and the ‘Skandia Navigator’ (Edvinsson and Malone, 1997) give more weight to measurements relating to human capital and this survey provides evidence that the human resource dimension is important—at least at shop-floor level. The putative ‘shop-floor scorecard’ implicit in this survey suggests that higher level organisational scorecards can perhaps be ‘cascaded’ to lower organisational levels but that this should be a loosely coupled process. The number of measurement dimensions might vary at different levels of the organisation as particular measures at high levels become dimensions at lower levels. In view of the factors identified from the empirical data our revised conceptualisation appears in the central rectangle in Fig. 2. The original, a priori, ‘5-factor shopfloor performance scorecard’ is supported and the labels on the factors, now empirically derived, are almost the same as those originally assumed. The exception is ‘employee morale’, now referred to as ‘human resources’. It might be tempting to frame a shopfloor measurement scorecard in terms of enthusiastic employees leading to on-time delivery, quality and efficiency and so to satisfied customers. However, the measures grouped as ‘human resources’ (staff turnover, absenteeism, lateness, proportion of overtime worked) could, equally, indicate concern to reduce and control costs rather than with concern for employee morale.

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Factor 1: Advanced manufacturing technologies

Factor 2: Stockhandling systems

Factor 4: Production scheduling software

Factor 3: Innovative managerial practices SFNFPMs of: Customer satisfaction On-time delivery

Product quality

Efficiency and utilisation

Factor 5: Adoption of contemporary ideas

Factor 7: Upward communication

Human resources

Factor 6: Competitive management practices

Factor 8: Workforce characteristics

Factor 9: Competitive environment

Fig. 2. Revised, evidence-based model of shop-floor non-financial performance measures and contingent variables.

5.2. The contingent variables Factor analysis was also undertaken on the 37 contingent variables in order to provide a more objective grouping of variables than our a priori assumption of six ‘natural’ groups detailed in Footnote 5 in Section 3. 5.2.1. A priori group 1: application of AMTs The original eight variables divided into two groups7 with ‘stock handling systems’ (auto storage and auto guidance systems) separated from ‘advanced manufacturing technologies’ (FMS, CAD, CAM, CIM, CNC, CAE). To the latter group UK SIC industry code was added, presumably because the benefits of the listed technologies are industry sensitive.

7

The rotated factor matrix (equivalent of Table 2) for the contingent variables is not included in this paper on account of its bulk (37 variables and nine factors). The information can be supplied by the authors if required.

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5.2.2. A priori group 2: Application of IMPs Six variables divided into two groups, ‘innovative managerial practices’ (JIT, TQM and TPM) and ‘production scheduling software’ (MRP, ERP and OPT). The variables, % of shop-floor receiving feedback and frequency of feedback, were ‘transferred’ from the a priori ‘shop-floor aspects’ to the first IMP group. These factorings are intuitively sensible, associating OPT with other computer production control systems rather than with its philosophical soul mate, throughput accounting. The inclusion of two shop-floor feedback variables in ‘innovative production management practices’ is further evidence of inter-relationships between certain management practices and technologies and the need for a committed and involved workforce. 5.2.3. A priori group 3: advanced management accounting practices The original seven variables divided into two factors labeled ‘adoption of contemporary ideas’ (benchmarking, ABT, balanced scorecard and EVAR) and ‘competitive management practices’ (throughput accounting, strategic management accounting and customer profitability analysis). The variable, formal shop-floor training was transferred in to the former group from the a priori ‘shop floor aspects’ group. Practitioners do not appear to see modern management accounting techniques as competitors, rather, if there is interest in one; there will tend to be interest in several. Again, a human resource oriented variable, shop-floor training, is added to a group of techniques; in this case perhaps interest in new management accounting techniques leads to increased shop-floor communication. The banal labeling, ‘competitive management practices’, reflects difficulty in describing this factor. All three techniques are heavily analytical in nature but while strategic management accounting and customer profitability analysis imply an outward facing orientation, throughput accounting is internally focused on the identification and management of bottlenecks and the use of financial information in pricing and product mix decisions. 5.2.4. A priori group 4: shop floor involvement Eight variables were rearranged in various directions. Three of them, interest in SF suggestions, impact of SF suggestions on cost, and impact of SF suggestions on quality, are labelled ‘upward communication’ while another two, average shop-floor wages and number of employees, form a factor labelled ‘workforce characteristics’. Two of the remaining three variables, percentage of shop-floor receiving feedback and frequency of providing shop-floor feedback, were included with ‘innovative managerial practices’ while formal training was factored with ‘adoption of contemporary ideas’. 5.2.5. A priori group 5: competitive environment The original grouping of seven ‘competitive’ variables relating to the importance attached to quality, innovation, customer service, price, delivery, flexibility as sources of competitive advantage and the effect of competition on the SFNFPM system was confirmed. 5.2.6. Summary Factor analysis of the contingent (presumed independent) variables reveals more differentiation than was originally assumed, so that the six groups in Fig. 1 proliferate into

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nine factors shown in Fig. 2. Stock-handling systems become a distinct subset of advanced manufacturing technologies. Production scheduling software (MRP, ERP, OPT) is separated from the innovative managerial practices JIT, TQM and TPM. The original group of ‘advanced management accounting practices’ divides into adoption of contemporary ideas (benchmarking, ABT, balanced scorecard, EVAR) and competitive management practices (throughput accounting, strategic management accounting, customer profitability analysis). ‘Shop-floor involvement’ variables divide into ‘upward communication’ (concern with shop-floor suggestions) and ‘workforce characteristics’ (remuneration and number). Some changes, such as the differentiation of stock-handling systems from wider AMT and the division of production related practices (JIT, TQM, TPM) from scheduling and more general software (MRP, ERP, OPT), seem intuitively sensible and useful. However, the division of ‘advanced management accounting practices’ is more difficult to interpret; perhaps interest in one high profile, fashionable technique, such as the balanced scorecard, is concomitant with an interest in other highly publicised techniques. Probably, the most interesting insight relates to the ‘shop-floor involvement’ variables. The original eight variables were not grouped together and our expectation of a generalised interest in HR measures was much too simplistic. Instead, companies adopting JIT/TQM/TPM become interested in providing employee feedback—it seems that successful adoption of JIT etc. requires active cooperation from shop-floor personnel. Companies interested in fashionable ideas (such as ABT) are more likely to provide formal shop-floor training— interest in contemporary thinking may go ‘hand in hand’ with formal shop-floor training to spread this knowledge through the organisation. Three variables included reference to ‘shopfloor suggestions’ were grouped together by factor analysis and this factor was labeled ‘upward communication’. And finally two variables associated with size of the workforce and its remuneration were grouped together; this factor being labeled ‘workforce characteristics’.

6. Associations between independent variables and categories of performance measures In this section, we report correlations derived using Kendall’s tau test, between each separate independent variable (as rows in Tables 3–7) and composites of the factored performance measures (as columns). The discussion is structured according to the factored groupings of the independent variables and significant and highly significant correlations are designated by * and ** respectively. 6.1.1. Contingent Factor 1: advanced manufacturing technologies In comparison with later tables, there are relatively few significant correlations between the AMT variables8 and the performance measures. Interest in FMS, CAD, CNC and CAE 8 ‘Industry type’ had also been grouped by factor analysis with the AMTs in Table 8 but, being a categorical variable, is not amenable to Kendall’s tau test. Chi-square tests were used to investigate associations between ‘industry type’ and the five evaluation categories; they are reported later in this section.

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Table 3 Correlation between advanced manufacturing technologies and performance measures Extent of use of manufacturing technologies:

Importance of measures of efficiency utilisation

Importance of measures of delivery performance

Importance of measures of human resource

Importance of measures of product quality

Importance of measures of customer satisfaction

FMS CAD CAM CIM CNC CAE

0.047 0.087* 0.078 0.082 0.076 0.089*

0.169** 0.099* 0.077 0.056 0.125** 0.164**

0.077 0.025 0.001 K0.014 0.017 0.008

0.100* 0.043 0.089* 0.078 0.050 0.060

0.120** 0.189** 0.057 K0.007 0.068 0.136**

is likely to be linked with a desire for better deliveries and improved customer satisfaction while there is a noteworthy lack of correlation between interest in AMT and HR issues. 6.1.2. Contingent Factor 2: stock handling systems Similarly, interest in the stock handling technologies is correlated with interest in measures delivery performance and customer satisfaction—but not with measures of efficiency, HR or quality (Table 4). 6.1.3. Contingent Factor 3: innovative managerial practices In contrast, companies employing TQM or TPM extensively are very likely to pay keen attention to all the performance measures. However, JIT seems more focused on delivery and quality performance than the more widely drawn TQM and TPM. The latter, Japanese inspired, philosophies might be seen as surrogates for the ‘intensity of management’ and

Table 4 Correlation between stock handling systems and performance measures Extent of use of stock-handling systems:

Importance of measures of efficiency utilisation

Importance of measures of delivery performance

Importance of measures of human resource

Importance of measures of product quality

Importance of measures of customer satisfaction

Automated storage and retrieval systems Automated guided vehicle systems

0.024

0.172**

0.085

0.072

0.116*

0.028

0.114*

0.091

0.032

0.117*

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Table 5 Correlation between innovative managerial practices and performance measures Extent of use of innovative managerial practices:

Importance of measures of efficiency utilisation

Importance of measures of delivery performance

Importance of measures of human resource

Importance of measures of product quality

Importance of measures of customer satisfaction

JIT TQM TPM % of shop-floor receiving feedback

0.081 0.120** 0.146** 0.116**

0.187** 0.186** 0.263** 0.182**

0.062 0.111** 0.195** 0.112*

0.146** 0.100* 0.151** 0.102*

0.083 0.184** 0.089* 0.116*

interest in them is likely to imply interest in analysis of business performance in general, together with a drive to involve shop-floor personnel through feedback9 (Table 5). 6.1.4. Contingent Factor 4: production scheduling software Emphasis on MRP or ERP computer-based production scheduling software is also highly associated with emphasis on several shop-floor measures, although, in contrast to TQM and TPM, not with HR related measures. Attitudes to MRP and ERP systems are broadly similar (ERP being the ‘updated version’ of MRP) but OPT seems subtly different, more customer–and less efficiency-oriented, with more concern for HR than either of the other systems (Table 6). 6.1.5. Contingent Factor 5: adoption of contemporary ideas Generally, interest in contemporary management accounting ideas is highly significantly correlated with emphasis on the internally oriented measures of efficiency and delivery. There is less evidence of association with interest in measures of quality and customer satisfaction. Perhaps emphasis on traditional (internally focused) management accounting methods leads to interest in newer, contemporary, suggestions and practices. If so it may partially explain the strange result for the balanced scorecard where one would surely expect correlation with HR and quality measures. If the drive for new techniques comes from enthusiastic management accountants, they may be more comfortable associating the balance scorecard with familiar, traditional, measures than with the organisationally ‘more distant’ issues of HR, quality and customer satisfaction (Table 7). 6.1.6. Contingent Factor 6: competitive management practices Similarly, it seems that interest in traditional management accounting measures is associated with interest in competitive management practices. And again, like the 9 Also factorised with this group were responses to a question asking about the frequency of feedback provided to shop-floor workers. However, because respondents were asked to indicate answers on an unequal interval scale specifying daily, weekly, monthly, quarterly, yearly, ad hoc, the coded results are difficult to incorporate.

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Table 6 Correlation between production scheduling software and performance measures Extent of use of production scheduling software:

Importance of measures of efficiency utilisation

Importance of measures of delivery performance

Importance of measures of human resource

Importance of measures of product quality

Importance of measures of customer satisfaction

MRP ERP OPT

0.111** 0.113** 0.108*

0.212** 0.135** 0.223**

0.017 K0.024 0.150*

0.131** 0.093* 0.202**

0.089* 0.055 0.134**

Table 7 Correlation between adoption of contemporary ideas and performance measures Extent of adoption of contemporary ideas:

Importance of measures of efficiency and utilisation

Importance of measures of delivery performance

Importance of measures of human resource

Importance of measures of product quality

Importance of measures of customer satisfaction

Benchmarking Activity-based techniques Balanced scorecard Economic value added Amount of formal shopfloor training

0.091* 0.170**

0.135** 0.168**

0.113* 0.130**

0.059 0.140*

0.104 0.003

0.130**

0.180**

0.087

0.088

0.199*

0.059

0.148**

0.097*

0.094*

0.017

0.119**

0.171**

0.091*

–

0.094*

balanced scorecard, interest in strategic management accounting and customer profitability analysis does not automatically lead to interest in measures of product quality and customer satisfaction (Table 8). 6.1.7. Contingent Factor 7: upward communication This group of variables is very significantly correlated with virtually all the dependent variables.10 It seems that a company that is interested in shop-floor suggestions is likely to be interested in measuring everything. It seems unlikely, to us, that a company is interested in measuring everything because it wishes to monitor the outcome of shop-floor suggestions. Rather, a company that has developed a very comprehensive measuring system will have become interested in the impact that shop-floor knowledge can have on company performance (Table 9). 6.1.8. Contingent Factor 8: workforce characteristics Surprisingly, the size of the workforce is negatively correlated with the importance attributed to measuring issues related to human resources. Perhaps these measures, 10

The only exception being between the impact of shop-floor suggestions on quality and the importance of measuring product quality—and this correlation was still significant.

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Table 8 Correlation between competitive management practices and performance measures Extent of application of contemporary management practices:

Importance of measures of efficiency and utilisation

Importance of measures of delivery performance

Importance of measures of human resource

Importance of measures of product quality

Importance of measures of customer satisfaction

Strategic management accounting Customer profitability analysis Throughput accounting

0.086

0.127**

0.079

0.000

K0.004

0.132**

0.079

0.043

0.040

0.058

0.133**

O.122**

0.140**

0.068

0.040

relating to staff turnover, absenteeism, lateness and % overtime worked, are more important in smaller firms where the absence of individuals is more critical. ‘Annual average shop-floor wages and salaries’ shows significant correlation with interest in efficiency measures and customer satisfaction but not with interest in measures of delivery performance, HR or product quality. The result might simply reflect the need for high productivity from highly paid workers (Table 10). 6.1.9. Contingent Factor 9: competitive environment Virtually every one of the variables in this group is highly significantly correlated with all the dependent variables. Perhaps not surprisingly there is a generally strong correlation between the importance of six aspects of competition and the five measures of shop-floor performance. Respondents who gave high ratings for the importance of various ways of competing are likely to represent companies facing stiff competition, circumstances that induce greater monitoring of performance generally. The implication is that if a company is in a highly competitive environment it is likely to emphasise measurement of all facets of the business since any of these could be a source of competitive advantage (or disadvantage) (Table 11). Table 9 Correlation between upward communication and performance measures Extent of upward communication:

Importance of measures of efficiency utilisation

Importance of measures of delivery performance

Importance of measures of human resource

Importance of measures of product quality

Importance of measures of customer satisfaction

Interest in shop-floor suggestions Impact on cost reduction Impact on quality

0.112**

0.233**

0.188**

0.130**

0.151**

0.144**

0.189**

0.217**

0.123**

0.157**

0.195**

0.195**

0.212**

0.107*

0.150**

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Table 10 Correlation between workforce characteristics and performance measures Workforce characteristic:

Importance of measures of efficiency and utilisation

Number of employees Ave level of shop-floor wages

K0.014 0.126**

Importance of measures of delivery performance 0.006 K0.002

Importance of measures of human resource

K0.115** K0.009

Importance of measures of product quality 0.011 K0.018

Importance of measures of customer satisfaction 0.001 0.098*

Interestingly, the exceptional pair (not significantly correlated) was emphasis on customer service as an aspect of competition, and interest in the measurement of product quality. This rather suggests that businesses often see their aim as either to provide a quality product or to maintain excellent customer service, with some degree of mutual exclusivity. The correlations in the final row show, not surprisingly, that firms in which competition affects shop-floor measures do attribute importance to measuring performance. 6.2. Industry sectors It was not appropriate to use Kendall’s tau to look for associations between companies’ sector (industry type being a nominal variable), and their use of SFNFPMs. Instead a chi-square test was applied. This could only be applied to industries in which more than ten companies were represented, but this nevertheless produced some interesting results. Table 12 lists the six measures where existence and importance differed significantly across the 13 most common industry sectors. Table 11 Correlation between competitive environment and performance measures Competitive environment in relation to:

Importance of measures of efficiency and utilisation

Importance of measures of delivery performance

Importance of measures of human resource

Importance of measures of product quality

Importance of measures of customer satisfaction

Quality Innovation Customer service Price Delivery Flexibility Effect of competition on SFNFPMs

0.214* 0.094* 0.171**

0.231** 0.147** 0.174**

0.214** 0.134** 0.221**

0.139** 0.127** 0.068

0.205** 0.151** 0.207**

0.157** 0.164** 0.131** 0.168**

0.089* 0.174** 0.164** 0.272**

0.142** 0.167** 0.167** 0.205**

0.128** 0.108* 0.152** 0.172**

0.142** 0.166** 0.130** 0.132**

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Table 12 Chi-square results of different industries’ evaluation of the existence and importance of SFNFPMs—(only statistically significant results shown) SFNFPMs

Chi-square value

Activity Staff turnover Scrap—% of total production Batches—% adjusted Number of complaints from customers Number of warranty claims

24.5* 27.9* 23.0* 26.0* 30.0* 39.1*

*Significant at 5%(p 2-tailed ! 0.05). d.fZ12 in all cases.

Full data is not reported but brief comments on how the use and importance varies across the 13 industry sectors are included. 6.2.1. Activity Eighty-eight percent of manufacturers of rubber and plastic products indicated greater than ‘moderate’ importance for this measure. It was also very important in machinery and equipment manufacturers and publishers and reproducers of record media. In contrast, it was not important in manufacturers of food products and of non-metallic mineral products. 6.2.2. Staff turnover The existence and importance of measuring ‘staff turnover’ (but not other human resources measures) differs significantly across industry sectors, perhaps reflecting differences in the difficulty and/or expense of recruiting. Seventy-eight percent of publishers and reproducers of record media reported the measure as of more than moderate importance and there were also high scores from manufacturers of rubber and plastic products. In contrast 36% of motor vehicle manufacturers reported that it was not measured. Elsewhere, we report that measurement of staff turnover is particularly practised in smaller companies and this may account for some of the result, as, for example, motor companies are generally larger than companies that publish and reproduce record media. 6.2.3. Scrap In general, a very high percentage of respondents use and attach high importance to the scrap measure. For instance, all respondents from manufacturers of rubber and plastic products and of basic metal products, 93% from manufacturers of non metallic mineral products and 84% from electric machinery consider it to be of ‘above moderate’ to ‘critical’ importance. Significant difference may arise because, in industries such as chemicals or chemical products, scrap can be re-used and, in others, such as motor vehicles, the emphasis may be on assembly rather than processing. In the former industries scrap may be relatively inexpensive, and in the latter industries it may be low, so less emphasis is placed on it. 6.2.4. Batches—% adjusted A high percentage of respondents in various industries do not apply this measure which captures the proportion of batches requiring adjustment due to problems of quality. More

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than 40% of respondents in manufacturing of food products, pulp, publishing and reproduction of record media, non-metallic mineral, fabricated metal, machinery and equipment, electronic machinery and furniture industries do not use that measure. In many cases production in these industries is not in batches and, in the case of food products, defects generally lead to scrapping rather than adjusting. Three industries do, however, attach importance to monitoring the percentage of batches adjusted: manufacturing of textiles, chemicals and chemical products and basic metal. 6.2.5. Customer complaints The vast majority of companies attach high importance to measuring the number of complaints from customers and customer satisfaction is clearly crucial across all industry sectors. Nevertheless, measurement of customer complaints does differ across industry types. Lower importance is attached to this measure in textile and furniture manufacturers. In these two industries, there is often a less direct relationship between the manufacturer and the ultimate consumer. 6.2.6. Warranty claims The final SFNFPM highlighted by the chi-square test relates to the measurement of the number of warranty claims. Most respondents in manufacturing of electronics, machinery and equipment, rubber and plastic products, furniture, fabricated metal products, and motor vehicles use this measure and attach high importance to it. By contrast, in textiles, chemicals and food products this measure is either not applicable or not generally important. 6.3. Summary of discussion relating to correlation statistics The following discussion is structured according to the overall strength of correlation between independent and dependent variables, so Factors 7 and 9 are considered first. 6.3.1. Factor 9: competitive environment and Factor 7: upward communication Virtually all the possible pairings of both of these variables were highly significantly correlated. It seems that perception of a competitive environment leads to concern with all aspects of competition and, probably logically, with the measurement of all aspects of performance. We speculate that concern with shop-floor feedback may be a consequence of general interest in performance measurement rather than a driver of that interest. 6.3.2. Factor 3: innovative managerial practices, and Factor 4: production scheduling software Interest in contemporary approaches to management and production control are significantly correlated with the use of many performance measures. Companies that turn to the, now well proven, techniques of JIT, TQM and TPM are likely to emphasise performance measurement although those adopting JIT seem to adopt a more focused approach on measures of delivery and quality performance. Similarly, companies adopting contemporary computer production control systems (MRP, ERP and OPT) emphasise most measures of performance although not especially human resource measures.

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6.3.3. Factor 5: adoption of contemporary ideas, and Factor 6: competitive management practices Contemporary management accounting and management techniques, such as activitybased techniques or benchmarking, are more significantly correlated with emphasis on traditional management accounting practice than with emphasis on employee, product or customer measures. Particularly surprising is the lack of correlation between the ‘strategic’ techniques (strategic management accounting and customer profitability analysis) and interest in measures of product quality and customer satisfaction. Similarly, there is no correlation between the application of balanced scorecard and non-financial measures of HR or product quality. We speculate that use of traditional management accounting measures of efficiency and capacity utilisation spawns interest in new non-financial techniques—especially internally oriented ones that have some affinity with traditional techniques. The relative lack of correlation between performance measures of customer satisfaction/product quality with new management accounting practices, such as ABC or throughput accounting, may suggest an inward, manufacturing oriented focus even in those management accountants that are interested in innovative accounting. 6.3.4. Factor 1: advanced manufacturing technologies, and Factor 2: stock handling systems Unexpectedly, the contingent variables that correlate least with interest in non-financial performance measurement are applications of advanced manufacturing (and design) technologies. Computer-aided and computer-integrated manufacturing in particular seems to indicate a technological, rather than a results-oriented, bias in the companies that adopt them. There is limited correlation between other technologies (CAD, CAE, AS/RS etc.) and interest in performance measurement but a fairly consistent picture does emerge suggesting that interest in these technologies might be linked to a desire for better deliveries and improved customer satisfaction. Particularly striking is the lack of association between advanced technologies and concern for HR related measures. Possibly AMT companies, having replaced manual labour, have a relatively low proportion of their costs attributable to staffing and are less concerned about employee related measures. More persuasively, it may be that high AMT companies pay higher wages and need to avoid the ‘theory X ethos’ that is associated with measuring absenteeism, lateness and overtime. 6.3.5. Factor 6 competitive management practices, and Factor 8 workforce characteristics These two factors are similar in that they exhibit strong isolated, rather than general, associations between contingent factors and performance measurement. In Factor 6, we find some evidence of internally facing versus externally facing and shop floor versus wholeorganisation splits of emphasis. One of the most striking results is that HR measures are significantly more important in companies with fewer employees.11 This may indicate that in the present environment companies are more concerned, in HR measurement, with the risk of staff leaving, which would have a greater relative impact on companies with smaller staff 11

Although all companies surveyed have more than 200 employees.

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complements, than they are with the risk of industrial action—which might be expected to be more of an issue in larger companies.

7. Discussion of findings in relation to the literature 7.1. Descriptive statistics Authors (Kaplan, 1983; Hall et al., 1991; Banker et al., 1993; Conti, 1993; Bromwich and Bhimani, 1994) have called repeatedly for broader, non-financial, measures to support investment in new technologies and promote improvements in competitiveness. Consistent with this, a number of research reports (CIMA, 1993; Drury et al., 1993; Bhimani, 1993; 1994) have revealed growing emphasis on non-financial indicators in UK manufacturing companies. This study provides confirmation that UK manufacturers are now reporting a comprehensive range of non-financial performance indicators and several of the suggestions in the literature appear to have been implemented in practice. Specifically, most UK manufacturing companies are extremely customer focused with delivery timeliness, number of customer complaints and customer returns being of preeminent importance. Data on these measures is captured by over 90% of companies. Various efficiency and cost control measures are also measured by approximately 90% of companies and are perceived to be very important. There is also a presumption in the literature that a satisfied and committed workforce should underpin organizational processes that lead to increased customer satisfaction (Brancato, 1995). This would logically lead to an interest in human resource measures. The European Foundation for Quality Management’s ‘EFQM Excellence Model’12 is typical in making such causal presumptions and there is some evidence of such relationships in particular circumstances; for example, Rucci et al. (1998) reported ‘The Employee–Customer–Profit Chain at Sears’. However, Lev (2001: 75) is more equivocal, noting that ‘.the research on human resource expenditures is in its infancy’. Our evidence confirms the need for caution because, although employee-related measures such as statistics on staff turnover, absenteeism, and lateness are widely measured, they attract relatively less managerial attention than customer and productivity related measures. Surveys of employee attitudes are undertaken by only 63% of companies surveyed. 7.2. Factor groupings The ‘scorecard’ literature has suggested a number of possible groupings of performance measures with the most famous being Kaplan and Norton’s (1992, 1993, 1996) four dimensional grouping of financial, customer, process and learning measures. At shop-floor level a review of the literature (CIMA, 1993, 1996; Drury et al., 1993; Otley, 1997, 1999; Chenhall, 1997, etc.) revealed five categories of non-financial performance measures: product quality, customer satisfaction, on-time delivery, employee morale, efficiency 12

The EFQM ‘excellence model’ can be downloaded at www.efqm.org/model.

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and utilization. Our factor analysis confirmed these a priori groupings of variables although, surprisingly, one component—employee attitude surveys—was grouped, not with employee related measures such as absenteeism and employee turnover but with measures relating to delivery performance. This left the group labeled human resource measures in a rather ambivalent position. It could be interpreted as supporting either McGregor’s (1960) ‘theory X’ or his ‘theory Y’ management styles depending on whether managers’ use the data for control and cost reduction or to check whether an ‘employee empowerment’ style was working. This equivocation is reflected in the literature where, for example Banker et al. (1993) studied the degree of reporting non-manufacturing measures to workers but Maskell (1992) and Cobb (1993) argued that detailed reporting was necessary for the (traditional) purpose of keeping track of resources. Factor analysis was also undertaken of the independent variables conventionally expected to influence performance measurement. In line with sources such as Bromwich and Bhimani (1994), where separate chapters deal with the ‘Automated Technologies and Management Innovations’ and ‘Emerging Cost Management Approaches’, these had been grouped into five sets of relevant influences. Factor analysis suggested a more nuanced grouping into nine categories of contingent variables. Some of these, such as the separation of stock-handling systems from the group of advanced manufacturing technologies, seem relatively trivial, while others, such as the grouping of JIT, TQM and TPM separately from MRP, ERP and OPT make intuitive sense. The most interesting realignment of measures was, again, in relation to human resources. Factor analysis showed that shop-floor feedback was associated with innovative managerial practices (JIT, TQM, TPM) and shop-floor training with adoption of contemporary ideas (ABT, balanced scorecard etc.) while interest in shop-floor suggestions (labeled ‘upward communication’) was separated from other, shop floor related, contingent variables. The association of employee feedback with JIT, TQM and TPM confirms that shop-floor involvement is important to the implementation of these innovative manufacturing practices. 7.3. Correlations between SFNFPMs and contingent variables The correlations reported in the paper were designed to explore the associations between the 37 contingent variables and the non-financial performance measures. Many significant associations were revealed, confirming the suggestion in the CIMA (1993) Executive Summary, especially in relation to the variables grouped under ‘competitive environment’ and ‘upward communication’. Perhaps this is not surprising but the extent of interest, measuring virtually every aspect of the business, is noteworthy. A number of writers have drawn attention to the increasingly competitive conditions in manufacturing, especially for manufacturers facing global competition in commodity goods. Authors such as Johnson (1992) and Hope and Hope (1995) have noted the importance of measuring aspects of performance in order to meet these challenges. Our study indicates that, in uncertain competitive conditions, managers do indeed, as proposed in Gordon and Narayanan (1984), adopt a broad range of performance indicators. We speculate that companies in difficult competitive situations measure performance on all the dimensions available to them and, consistent with seeking competitive advantage from any source, also consider suggestions from employees very seriously.

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A major stimulus for increasing interest in non-financial measures has been the perception that traditional cost accounting was inadequate in the ‘new manufacturing environment’. There has been a generally held view (Kaplan, 1983; Drucker, 1990; Vollman, 1989; Hall et al., 1991; Conti, 1993) that the introduction of advanced technologies and innovative practices needs to be supported by appropriate non-financial measures. This study generally supports the notion that ‘advanced’ manufacturers should use a variety of non-financial performance measures but reveals the situation to be less straightforward than the literature suggests. Innes and Mitchell (1989: 17–18); Littler and Sweeting (1989: 31–32) reported the selective use of non-financial performance measures in ‘advanced technology’ companies. Our study shows that, while the use of non-financial measures may be associated with advanced technologies, this does not seem to be a key driver in the spread of such measures. Companies adopting advanced manufacturing technologies are still likely to adopt measures very selectively, typically with emphasis on delivery performance and customer satisfaction, not efficiency, quality or human resource measures. More likely to drive general interest in non-financial measures is the adoption of TQM and/or TPM. Chenhall (1997: 188) summarized the consensus view in relation to TQM with performance measures expected to include: ‘.customer satisfaction. on-time delivery, responsiveness to customer needs and various aspects of the value chain’. This widely drawn list of possible performance measures is supported by our findings of strong correlations between both TQM and TPM and all categories of non-financial performance measures. JIT was grouped with these innovative methods but, here, we reveal emphasis on delivery and quality measures rather than the wider range of measures associated with TQM and TPM. This is consistent with Cobb’s (1993: 51–54) report of increased use of mainly production data such as orders/shipments, cycle times, defect rates, and schedule adherence in JIT companies. It seems to us that TQM and TPM may be associated with a general intensity of management rather than the more production-targeted JIT approach. We conclude that where there is interest in production management companies are likely to take considerable interest in a wide range of non-financial measures. Companies that have taken more interest in production technology are likely to be more selective in their choice of non-financial measures. Some of the most difficult results to interpret relate to the adoption of contemporary ideas in management accounting and management. We did find associations between adoption of modern techniques and non-financial measures but they are not as we expected. Particularly surprising, given the emphasis in Kaplan and Norton (1992, 1993, 1996) on a range of scorecard measures, was the lack of association between adoption of the balanced scorecard and the importance of human resource quality measures. In general, we conclude that, if there is causality in these associations, it is likely to relate to the introduction, by management accountants familiar with traditional measures, of new ideas. In other words, companies that already have a comprehensive set of traditional measures may have a propensity to experiment with contemporary suggestions. This would lend some support to the sceptical views of authors13 who argue that there is 13

Such as Johnson (1992), Vollman (1989), Eccles (1991) and McKinnon and Bruns (1992).

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a tendency for management accountants to bring an overly financial view to the task that may lead to an unbalanced set of performance measures. Our results concerning human resource measures, from both the factor analyses and the correlation tests, are worth noting. We find that HR related measures do not fall neatly into a single category. It seems that some activities are important in certain circumstances. In particular, feedback to shop floor employees is associated with modern production management techniques TQM, TPM and JIT and employee training is associated with interest in contemporary techniques such as ABC and the balanced scorecard. In general, there is relatively low importance attached to HR measures and relatively few significant associations between them and the contingent variables. 7.4. Contribution of the study and avenues for further research Overall, this study makes three central contributions to the performance management literature. First, it provides a review of the extent of non-financial performance measurement in UK manufacturers. Second, factor analysis has provided groupings of measures and contingent variables, confirming the groups of measures typically mentioned in the literature and providing a more sophisticated analysis of contingent variables than is usual. Third, analysis of associations between dependent and contingent variables extends the literature, revealing that advanced, typically computer assisted, technologies such as CAD, CAM and CIM are not a key driver of non-financial performance measurement but that competitive environments and the adoption of Japanese inspired production methods such as JIT, TQM and TPM are likely to be associated with considerable interest in NFPMs. The study was designed to investigate empirically the state of shop floor performance measurement in UK manufacturing and to explore relationships between the use of shop floor related measures and a range of potential contingent variables. Further research could build on the idea of a shop floor performance ‘scorecard’ that we have proposed. There is potential for more empirical work that employs our methodology of a large sample survey and statistical techniques to validate general organisation-wide scorecards rather than basing such models on case studies and anecdotal, intuitive or normative methods. Another potential research avenue would be to focus on extending the contingency literature; testing the sophisticated relationships between the contingent and dependent variables highlighted in this study by employing multivariate statistical techniques. This paper provides a basis for these possible avenues of future research by identifying key variables, identifying groupings and correlations and suggesting the likely direction of causality between some variables.

Appendix. Descriptive statistics: attributes of UK manufacturing companies (March 2001) This appendix summarises information relating to the contingent variables that, in a sense, describe the technologies and practices used by UK manufacturing companies at the turn of the century. This information was needed in order to relate the ‘scorecard variables’ to contingent variables but was not the main focus of the study. Nevertheless, the information is interesting in its own right and it is presented here as a resource for other

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researchers specifically interested in these and related issues. The data is based on a postal survey of 2242 UK manufacturing firms having more than 200 employees. There were 313 useable responses, a response rate of 14.3% after allowing for companies that could not be reached or were inappropriate. A.1. Level of application of advanced manufacturing technologies (AMTs) Table A1 shows that computer aided design (CAD) is widely applied in UK manufacturing firms. Other computer-aided technologies are employed by about half the responding companies and those companies that employ them usually use them extensively. The levels of application of the other AMTs are low. A.2. Application of innovative management practices (IMPs) Table A1 Distribution of respondents by the evaluation of the level of application of AMTs AMTs (ranked by mean value on scale of 1–7)

Mean

% firms applying this practice

Computer aided design Computer aided manufacturing Computer numerical control Computer aided engineering Computer integrated manufacturing Flexible manufacturing systems Automated storage and retrieval system Automated guided vehicles systems

4.49 3.22 2.99 2.51 2.50 2.36 1.84 1.42

80.8 56.5 51.8 44.7 48.2 46.6 31.3 15.0

1, not at all; 4, moderately, and 7, sextensively.

Table A2 Distribution of respondents’ level of application of IMPs IMPs (ranked by mean value on scale of 1–7)

Mean

% firms applying this practice

MRPI/II Total quality management (TQM) Just-in-time production (JIT) Total preventive maintenance (TPM) Enterprise requirement planning (ERP) Optimised production technology (OPT)

4.60 4.10 3.85 3.71 2.86 1.93

84 87 81 81 54 37

1, not at all; 4, moderately, and 7, extensively.

‘Material requirements planning’ (MRPI/II), ‘total quality management’, ‘just-in-time production’ and ‘total preventive maintenance’ are now employed in most UK manufacturing companies. However, the application of, especially just-in-time production

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and total preventive maintenance, is usually partial rather than extensive. ERP systems and the specialist OPT production scheduling package have only limited application. A.3. Application of contemporary management accounting practices Respondents were asked to indicate whether seven contemporary management accounting practices were (1) not applied, (2) partially applied or (3) systematically applied in their organisations. Table A3 Distribution of responses concerning contemporary management accounting practices Management accounting practice (ranked by mean on a scale of 1–3)

Mean

Customer profitability analysis Benchmarking of performance Strategic management accounting Activity-based techniques Throughput accounting Balanced scorecard Economic value added

1.85 1.84 1.78 1.62 1.60 1.56 1.52

Percentage of respondents 1

2

3

36.4 28.1 39.0 50.2 56.5 58.8 62.0

41.9 59.4 43.8 37.7 27.5 26.5 24.0

21.7 12.5 17.3 12.1 16.0 14.7 14.1

1, not applied; 2, partially applied; 3, systematically applied.

‘Customer profitability analysis’, ‘benchmarking of performance’, and ‘strategic management accounting’ are widely applied in UK manufacturing firms. Over 60% of responding firms apply these techniques either partially or systematically. Activity-based techniques are not extensively applied according to this survey although perhaps 50% of companies have some experience with them. Take-up of throughput accounting, balanced scorecard and economic value added is certainly not extensive and more than 50% of respondents were prepared to admit that they do not use these techniques. A.4. Level of shop-floor staff involvement Respondents were asked to evaluate the level of five aspects of shop-floor (SF) staff involvement in their companies. In the first three questions, respondents were asked to indicate their interest in shop-floor suggestions on a seven–point Likert scale, from 1 (not at all), through 4 (moderately), up to 7 (extensively). Table A4 Distribution of respondents’ level of application of IMPs IMPs (ranked by mean value on scale of 1–7)

Mean

% firms applying this practice

Interest in SF suggestions Impact on quality improvement Impact on cost reduction

4.97 4.60 4.32

100 97.8 97.4

1, not at all; 4, moderately; and 7, extensively.

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Most companies collect suggestions from the shop-floor and, generally, there is a moderate (or higher) degree of interest in these. Respondents were also asked about the percentage of SF staff routinely receiving feedback of performance and the frequency of providing feedback of performance statistics to SF staff Table A5 Distribution of responses concerning the proportion of shop-floor staff that receive feedback % of respondents

% of SF receiving feedback

0–25%

26–50%

51–75%

76–100%

17.7

12.9

17.0

52.4

Just over 50% of respondents claimed that feedback is given to more than 75% of shopfloor employees. However, the remaining respondents admitted that feedback is given to 75% or less of their employees. Some 30% of respondents provide feedback to less than half of their shop-floor employees. Table A6 reveals that UK manufacturing firms tend to provide feedback to employees on a weekly or monthly basis. Relatively few firms provide daily feedback although a significant minority provide feedback on a quarterly or ad hoc basis. Table A6 Distribution of responses concerning the frequency of providing feedback to shop floor staff % of respondents Frequency of providing feedback

Daily

Weekly

Monthly

Quarterly

Yearly

On an ad hoc basis

12.6

29.7

36.5

8.4

1.9

11.0

A.5. Level of development of skills and training for shop floor staff Respondents were asked to indicate the average days per year that shop floor workers receive formal training and the average annual basic shop floor wages in their companies. Table A7 Distribution of respondents by average formal training for shop floor % of respondents

Average formal training

1–2 days

3–5 days

6–10 days

11–29 days

30–50 days

23.7

43.2

25.0

5.8

2.3

All the respondents claim to invest some time in training shop-floor employees although almost a quarter admit that this may be of only 1–2 days duration per year. Most

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companies (68%) claim to spend between 3 and 10 days per year training employees while less than 10% of respondents claim to spend longer than this. Table A8 Distribution of respondents by average annual shop floor wages £’000s

8–10

10–13

13–16

16–19

19–30

20–40

Ave Annual wages for shop floor (% of companies)

6.5

27.0

30.6

23.1

12.4

0.3

Most respondents pay shop-floor employees between £13,000 and £16,000 per annum and the distribution is reasonably symmetrical about this mode although, not surprisingly, some companies pay significantly more than the average. A.6. Level of monitoring of competitive environment Respondents were asked to indicate the importance of six aspects of competition. Table A9 shows that UK manufacturers take customer satisfaction very seriously. Virtually all the respondents regard all the competitive dimensions as very important and many respondents see customer service, quality, price and delivery as critically important. Respondents were also asked to indicate the extent to which changes in their competitive environment have affected their companies’ shop-floor performance measurement system. Table A9 Distribution of responses to question about the importance of competition on various characteristics Dimensions of competition (ranked by mean value on scale of 1–7)

Mean

% of firms giving the issue some degree of importance

Customer service Quality Price Delivery Flexibility Innovation

6.16 6.12 6.10 5.97 5.27 4.87

99.7 100.0 99.4 100.0 99.0 97.8

1, no importance; 4, moderate importance; and 7, critical importance.

Table A10 Distribution of responses concerning the impact of changes in competitive environment on company’s shop-floor performance measurement system % of respondents

Effect of competitive environment on company’s SFPM system

1

2

3

4

5

6

7

5.9

11.2

10.4

14.0

25.4

23.5

9.4

1, not significant up to 7, very significant.

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295

Most of the respondents perceived a significant inter-relationship between changes in the competitive environment and the shop-floor performance measurement system. Over 70% felt that changes in the competitive environment had at least a moderately significant impact on the performance measurement system. (The correlations between contingent and dependent variables provide emphatic support for this perception. Those companies that perceive themselves to be in very competitive environments take great interest in their performance measurement systems.)

References Abernethy, M.A., Lillis, A.M., 1995. The impact of manufacturing flexibility on management control system design. Accounting, Organizations and Society 20 (4), 241–258. Anderson, S., Lanen, W., 1999. Economic transition, strategy and the evolution of management accounting practices: the case of India. Accounting, Organizations and Society 24, 379–412. Back-Hock, A., 1992. Towards strategic accounting in product management: Implementing a holistic approach to a date and methods base for managerial accounting. European Journal of Operations Research 61, 98–105. Banker, R.D., Potter, G., Schroeder, R.G., 1993. Reporting manufacturing performance measures to workers: an empirical study. Journal of Management Accounting Research, Fall, 33–53. Bhimani, A., 1993. Performance measures in UK manufacturing companies: the state of play. Management Accounting, 20–23. Bhimani, A., 1994. Monitoring performance measures in UK manufacturing companies. Management Accounting, 34–36. Brancato, C.K., 1995. New Corporate Performance Measures, Research Report No. 1118-95-RR, The Conference Board, Inc., USA. Bromwich, M., Bhimani, A., 1994. Management accounting: pathways to progress. Chartered Institute of Management Accountants, London. Bruggeman, W., Slagmulder, R., 1995. The impact of technological change on management accounting. Management Accounting Research 6, 241–252. Burns, T., Stalker, G., 1961. The management of innovation. Tavistock, London. Chenhall, R.H., 1997. Reliance on manufacturing performance measures, total quality management and organisational performance. Management Accounting Research 8, 187–206. Chenhall, R.H., Langfield-Smith, K., 1998. Adoption and benefits of management accounting practices: an Australian study. Management Accounting Research 9, 1–19. Chenhall, R.H., Morris, D., 1986. The impact of structure, environment, and interdependence on the perceived usefulness of management accounting systems. The Accounting Review LX1 (1), 16–35. CIMA, 1993. Performance Measurement in the Manufacturing Sector. Chartered Institute of Management Accountants, London. CIMA, 1996. Management accounting official terminology. Chartered Institute of Management Accountants, London. Cobb, I., 1993. JIT and the Management Accountant: A Study of Current UK Practice. CIMA, London. Covaleski, M., Dirsmith, M., Samuel, S., 1996. Managerial accounting research: the contributions of organizational and sociological theories. Journal of Management Accounting Research8, 1–35. Clark, K.B., 1989. High performance product development in the world auto industry, Paper Presented at the International Forum on Technology Management, La Hulpe, Belgium. Conti, T., 1993. Building Quality: A Guide to Management. Chapman and Hall, London. Daniel, S.J., Reitsperger, W.D., 1991. Management control systems for JIT: an empirical comparison of Japan and the US. Journal of International Business Studies 22 (4), 603–617. Dixon, J. Robb, Nanni, Alfred J., Vollmann, Thomas E., 1990. The New Performance Challenge: Measuring Operations for World-Class Competition, Dow Jones-Irwin, Homewood, IL.

296

A. Abdel-Maksoud et al. / The British Accounting Review 37 (2005) 261–297

Drucker, P.E., 1990. The emerging theory of manufacturing. Harvard Business Review, 94–102. Drury, C., 1996. Management and Cost Accounting, fourth ed. International Thomas Business Press, London. Drury, C., Braund, S., Osborne, P., Tayles, M., 1993. A survey of management accounting practices in UK manufacturing companies. The Charted Association of Certified Accountants, Certified Research Report 32, 1–83. Eccles, R.G., 1991. The performance measurement manifesto. Harvard Business Review, 131–137. Edvinsson, L., Malone, N.S., 1997. Intellectual Capital. HarperCollins Publishers, New York. Gordon, L.A., Narayanan, V.K., 1984. Management accounting systems, perceived environment uncertainty and organization structure: an empirical investigation. Accounting Organizations and Society 9 (1), 33–47. Hall, R.W., Johnson, H.T., Turley, P.B., 1991. Measuring Up: Changing Pathways to Manufacturing Excellence, I11, Homewood, Business One Irwin. Harries, E., 1990. The impact of JIT production on product costing information systems. Production and Inventory Management Journal. Hartmann, F.G.H., 2000. The appropriateness of RAPM: towards the further development of theory. Accounting, Organizations and Society 25, 451–482. Hope, T., Hope, J., 1995. Transforming the Bottom Line. Nicholas Brealey Publishing Limited, London. Horngren, C., Foster G., Datar, S., 1994. Cost Accounting: A Managerial Emphasis. Prentice Hall, Englewood Cliffs, NJ. IFAC, 1998. International Management Accounting Practice Statement: Management Accounting Concepts, International Federation of Accountants, New York. Innes, J., Mitchell, F., 1989. Management Accounting: The Challenge of Technological Innovation 2. Chartered Institute of Management Accountants, London. Ittner, C., Larcker, D.F., 1998. Innovations in performance measurement: trends and research implications. Journal of Management Accounting Research 10, 205–238. Jazayeri, M., Hopper, T., 1999. Management accounting within world class manufacturing. Management Accounting Research 10 (3), 263–302. Johnson, H.T., 1992. Relevance Regained, from Top-down Control to Bottom-up Empowerment. The Free Press, New York. Kaplan, R.S., 1983. Measuring performance: a new challenge for managerial accounting research. The Accounting Review 18 (4), 686–705. Kaplan, R.S., 1993. Research opportunities in management accounting. Journal of Management Accounting Research 5, 1–14. Kaplan, R.S., Norton, D.P., 1992. The balanced scorecard: measures that drive performance. Harvard Business Review, 71–79. Kaplan, R.S., Norton, D.P., 1993. Putting the balanced scorecard to work. Harvard Business Review, 134–147. Kaplan, R.S., Norton, D.P., 1996. The Balanced Scorecard: Translating Strategy into Action. Harvard Business School Press, Boston, USA. Kaplan, R.S., Norton, D.P., 2001. The Strategy-focused Organization. Harvard Business School Press, Boston, USA. Lee, John Y., 1987. Managerial Accounting Changes for the 1990s. Addison-Wesley Publishing Company, USA. Lev, B., 2001. Intangibles: Management, Measurement, and Reporting. Brookings Institution Press, Washington, DC. Littler, D.A., Sweeting, R.C., 1989. Management Accounting: The Challenge of Technological Innovation 3. Chartered Institute of Management Accountants, London. Lynch, R.L., Cross, K.F., 1992. Measure Up-Yardsticks for Continuous Improvement. Basil Blackwell, Cambridge, MA. Mitchell, F., Reid, G., Smith, J., 2000. Information System Development in the Small Firm. CIMA Publishing. Maskell, B., 1989a. Performance measurement for world class manufacturing: Pt 1. Management Accounting, 32–33. Maskell, B., 1989b. Performance measurement for world class manufacturing-3. Management Accounting (UK), 48–50. Maskell, B.H., 1992. Performance measurement for world class manufacturing. Corporate Controller, 44–48. Mather, H., 1989. Competitive Manufacturing. Prentice Hall Business and Professional Division, Eagle Cliffs.

A. Abdel-Maksoud et al. / The British Accounting Review 37 (2005) 261–297

297

McGregor, D., 1960. The Human Side of Enterprise. McGraw Hill, NY, USA. McKinnon, S.M., Bruns, W.J., 1992. Management information and accounting information: what do managers want. Advances in Management Accounting 1, 55–80. Nanni Jr., A.J., Dixon, J.R., Vollman, T.E., 1992. Integrated performance measurement: management accounting to support the new manufacturing realities. Journal of Management Accounting Research 4, 1–19. Neely, A., Adams, C., Kennerley, M., 2002. The performance prism: the scorecard for measuring and managing business success. London, Prentice Hall. Olve, N., Sjostrand, A., 2002. The balanced scorecord. Capstone Publishing, Oxford. Otley, D., 1980. The contingency theory of management accounting: achievement and progress. Accounting, Organizations and Society 5 (4), 413–428. Otley, D., 1995. Management control, organisational design and accounting information systems. In: Ashton, D., Hopper, T., Scapens, R. (Eds.), Issues in Management Accounting. Otley, D., 1997. Better performance management. Management Accounting, 44. Otley, D., 1999. Performance management: a framework for management control systems research. Management Accounting Research 10, 363–382. Perera, S., Harrison, G., Poole, M., 1997. Customer-focused manufacturing strategy and the use of operationsbased non-financial performance measures: a research note. Accounting, Organizations and Society 22 (6), 557–572. Shank, J., 1989. Strategic management accounting: new wine, or just new bottles. Journal of Management Accounting Research 1, 47–65. Shields, M.D., Young, S.M., 1992. Effective long-term reduction: a strategic perspective. Journal of Cost Management, Spring, 16–30. Sim, K., Killough, L., 1998. The performance effects of complementarities between manufacturing practices and management accounting systems. Journal of Management Accounting Research 10, 325–346. Rucci, A.J., Kirn, S.P., Quinn, R.T., 1988. The employee–customer-profit chain at Sears. Harvard Business Review. Vollman, T., 1989. Changing manufacturing performance measurements, Service Organizations. American Accounting Association, Sarasota, FL.