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Int. J. Services and Operations Management, Vol. 9, No. 1, 2011
An overview of existing performance measurement frameworks in the context of world class manufacturing performance measurement A.K. Digalwar* and K.S. Sangwan Mechanical Engineering Group, Birla Institute of Technology and Science, Pilani-333031, India E-mail:
[email protected] E-mail:
[email protected] *Corresponding author Abstract: Performance measurement plays a significant role in order to sustain an improved performance. An enterprise’s measurement system strongly affects the behaviour of people, both inside and outside. If organisations are to survive and prosper in information age competition, they must use a measurement system derived from their strategies and capabilities. As enterprises introduce world class manufacturing (WCM) techniques, they need new methods of performance measurement to control and improve their production plants. Recent studies provide a useful framework for performance measurement and strategic alignment. The paper first highlights the imperatives of a performance measurement system for manufacturing excellence then discusses existing performance measurement systems and their limitations in measuring world class manufacturing performance. Finally, the paper suggests that there is a need to develop a new performance measurement system and proposed a framework for world class manufacturing performance measurement. Keywords: world class manufacturing; performance measurement framework; manufacturing excellence; balanced scorecard. Reference to this paper should be made as follows: Digalwar, A.K. and Sangwan, K.S. (2011) ‘An overview of existing performance measurement frameworks in the context of world class manufacturing performance measurement’, Int. J. Services and Operations Management, Vol. 9, No. 1, pp.60–82. Biographical notes: A.K. Digalwar received his PhD from BITS Pilani, India. Presently, he is working as an Assistant Professor in Mechanical Engineering. He has over 12 years of teaching experience at graduate and postgraduate levels. His areas of interest are performance measurement systems, world class manufacturing, total quality management, green manufacturing, knowledge management and manufacturing strategy. He has published many papers in national/international conferences and international journals. He is a Life Member of the Indian Society of Technical Education and a member of Performance Measurement Association, UK. K.S. Sangwan received his BE and ME from Punjab Engineering College, Chandigarh, and PhD from BITS, Pilani. He is presently working as an Assistant Professor in the Mechanical Engineering Group, BITS, Pilani and has over 14 years teaching experience at graduate and postgraduate levels. He has published a monogram on concurrent engineering and many research papers in
Copyright © 2011 Inderscience Enterprises Ltd.
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national and international journals. He is a reviewer of many prestigious national and international journals. His areas of research interest are CMS, green manufacturing, world class manufacturing, TPM, concurrent engineering, operations management, and application of fuzzy mathematics, genetic algorithms, simulated annealing and neural networks in design of manufacturing system. He is a Life Member of the Institution of Engineers (India), Society of Operations Management and Indian Society of Technical Education.
1
Introduction
Turbulent and uncertain marketplaces throughout the world are the result of intense competition, changes in manufacturing management, development in manufacturing technology, environmental changes, rapid advances in information technology, developments in new processes and materials, opening ups of economy, shortening of product lifecycle, the transition of production system to new organisational forms and managerial practices under the pressure of radical changes in competition, marketplaces, technologies and socioeconomics has attracted much research attention. It is becoming increasingly important for manufacturing organisations to articulate world class status and for that they need to give world class performance (Sangwan and Digalwar, 2008). To know the world class performance, measurement is important because ‘if you cannot measure it, you cannot manage it and thus you cannot improve upon’ therefore, performance measurement is a prerequisite to any improvement efforts in enterprises in order to sustain the improved performance and if possible, improve it further (Digalwar and Metri, 2005). An enterprise’s measurement system strongly affects the behaviour of people, both inside and outside. If organisations are to survive and prosper in information age competition, they must use measurement system derived from their strategies and capabilities (Digalwar and Sangwan, 2007; Schiuma, 2009). As enterprises introduce world class manufacturing techniques they need new method of performance measurement to control their production plants. Traditional performance measurement systems are invalid for the measurement of world class manufacturing practices, as they do not supply the business with the required information to compete in their industry. As traditional performance measures are based on management accounting, they are primarily concerned with cost. But in today’s manufacturing environment, cost-based measures are no longer the only basis for decision-making. Enterprises now require performance measures that are based on strategic parameters. Schiuma (2009) pointed out that the analysis of the managerial models and tools developed in the management literature and practice stresses the importance of measurement as a process grounding the identification, classification and qualitative and/or quantitative analysis of the variables and components affecting the business process performances. Starting from the introduction of the scientific management all the frameworks for managing performance, from operations to marketing, from logistic to selling, from human resource management to supply chain management, and so on, have adopted the measurement as an indispensable process for organisational performance management and the organisational strategic governance. Performance measures have become paramount important as they are the prerequisite for continuous improvement of
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any organisation. They are mainly used to compare the performance of different organisations, plants, departments, teams and individuals, and to assess employees (Kennerley and Neely, 2003). For companies to ensure achievement of their goals and objectives performance measures are used to evaluate, control and improved production processes. Many organisations have spent considerable time and resources implementing balanced performance measurement systems (Kaplan and Norton, 1996). The literature in the field of performance measurement emphasises the importance of maintaining relevant measures that continue to reflect the issues of importance to the business and the development of new performance measurement systems is required for success of organisation (Ghalayini and Noble, 1996; De Toni and Tonicha, 2001; Kennerley and Neely, 2003). Recent studies provide useful framework for performance measurement and strategic alignment. The paper first highlights the imperatives of performance measurement systems for manufacturing excellence then discusses existing performance measurement systems and their limitations in measuring world class manufacturing performance. The paper, finally, suggests that there is a need to develop new performance measurement system and proposed a framework for world class manufacturing performance measurement.
2
Classification of literature on performance measures
The performance measures can be broadly classified into three categories – traditional performance measures, non-traditional performance measures and integrated frameworks. The performance measurement literature has had two main phases. The first phase began in the late 1880s and went through the 1980s. In this phase the emphasis was on traditional financial measures such as profit, return on investment, return on sales and productivity. The second phase started in the late 1980s as a result of changes in the world market. Companies began to lose market share to overseas competitors who were able to provide higher quality products with lower costs and more variety. To regain a competitive edge companies not only shifted their strategic priorities from low cost production to quality, flexibility, short lead time and dependable delivery, but also implemented new technologies and philosophies of manufacturing management such as computer integrated manufacturing (CIM), flexible manufacturing systems (FMS), just in time (JIT), optimised production technology (OPT) total quality management (TQM), total productive maintenance (TPM), supply chain management (SCM). The implementation of these changes revealed that traditional performance measures have many limitations such as: •
based on accounting system
•
mainly financial measures
•
intended for middle and top managers
•
neglected at the shop floor
•
lagging metrics
•
had a fixed format
An overview of existing performance measurement frameworks •
intended mainly for monitoring performance
•
not applicable for JIT, TQM, CIM, etc.
•
hinders continuous improvement.
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To overcome the limitations associated with traditional performance measures, researchers developed some non-traditional performance measures, these were basically cost and time based (activity based costing by Johnson, 1988; throughput accounting by Goldratt, 1990) and time based. [Operating profit through time and investment management (OPTIM) by Sullivan (1986), value focused cycle time by Noble and Lahay (1994), the overall equipment effectiveness ratio by Nakajima (1988), manual assembly efficiency by Peterson (2000)]. Examining the current literature of business strategy and performance measurement reveals that cost and time has been proposed as the new strategic metric in the world market. The importance of time can be realised from the following argument: Measuring, controlling and compressing time will increase quality, reduce costs, improve responsiveness to customer orders, enhance delivery, increase productivity, reduce risks since reliance on forecasts is reduced, increase market share and increase profits (Maskell, 1991; Azzone et al., 1991; Bockerstette and Shell, 1993; Hum and Sim, 1996; White, 1996; Digalwar, 2006). Bockerstette and Shell (1993) argued that reducing cycle time reduces costs and improves customer satisfaction, which in turn increases revenue. Azzone et al. (1991) argued that time is a more important metric than cost and quality since it can be used to drive improvements in both of them and it has a common definition throughout the manufacturing system. Quality does not have such a common definition and cost is a lagging metric. Furthermore, cost reduction is not always beneficial. In contrast, time is not a lagging metric and it is always beneficial to reduce time. Moreover, reducing time will decrease costs by eliminating the activities that add no value to products. Quality will also increase since eliminating non value-added activities will decrease the chance of error introduction. Hum and Sim (1996) argued that the variability of time is an important metric that should be used to assess manufacturing system performance. They stated that reducing the variability of an activity through decreasing rate of scrap and rework, reducing machine breakdowns, reducing batch sizes, eliminating material shortage and increasing the accuracy of the bill-of-materials will drive improvements in quality and costs. Time-based performance measurement systems have been developed to help companies control and improve their operations. Stalk (1988) stated that time-based companies should go beyond measures like lead time, on-time delivery and response time to time-based metrics which could be used as diagnostic tools throughout the organisation. They summarised the main time based metrics that companies could use into four different areas – new product development, decision-making, processing and production, and customer service. New product development includes: time from idea to market; rate of new-product introduction; and percentage first competitor to market. Decision-making includes: decision cycle time and time lost waiting for decisions. Processing and production includes: value added as percentage of total elapsed time, uptime yield, inventory turnover and cycle time (per major phase of main sequence. Customer service includes: response time, quoted lead time; percentage deliveries on time; and time from customer’s recognition of need to delivery. Azzone et al. (1991) presented a framework of performance measures for time-based companies. This model
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contains three main areas in which time measures should be applied: research and development (R&D), operations, and sales and marketing. Hum and Sim (1996) provided a time-based performance measurement system that is based on the concept of positive and negative value-adding measurements. Improvement efforts have been directed to reduce negative value-adding components and decrease system throughput time. These performance measures are actively using in various large and small and medium enterprises. Various researchers (Maskell, 1991; Azzone et al., 1991; Bockerstette and Shell, 1993; Hum and Sim, 1996; White, 1996; Gunasekaran et al. 1999; Kaplan and Cooper, 1998; Goldratt, 1990; Sullivan, 1986; Noble and Lahay, 1994; Nakajima, 1988; Peterson, 2000) discussed there advantages in their research papers, but the limitations of these cost and time based performance measures are, normally they are concentrated on time and cost and neglected other operational performance measures such as quality, flexibility, delivery etc., without controlling and improving these operational measures companies will not be able to compress time and reduce cost (White, 1996; Ghalayini and Noble, 1996; Digalwar, 2006). To overcome this difficulty, researchers developed some conceptual performance measurement framework, where they have integrated the traditional and non-traditional performance measures. Few such popular frameworks are listed here: •
the Sink and Tuttle (1989) framework
•
the performance measurement matrix (Keegan et al., 1989)
•
the performance measurement questionnaire (Dixon et al., 1990)
•
EFQM business excellence model (EFQM, 1999)
•
the balanced scorecard (Kaplan and Norton, 1992)
•
the performance pyramid (Cross and Lynch, 1989)
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the AMBITE system (McMahon and Brown, 1993)
•
the performance objective-productivity (PO-P) system (Vrat et al., 1998)
•
the TOPP performance model (SINTEF, 1992)
•
the performance prism (Neely et al., 2001).
The next section provides review of these frameworks and discusses there limitations in WCM performance measurement perspective.
3
Review of existing performance measurement frameworks
3.1 Sink and Tuttle framework One of the first approaches to performance measurement was published by Sink and Tuttle (1989). The model claims that the performance of an organisational system is a complex interrelationship between the following seven criteria: 1
Effectiveness, doing the right things, at the right time, with the right quality, etc. Defining the criterion as a ratio, effectiveness can be defined as actual output/expected output.
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2
Efficiency, this is an input and transformation process question, defined as resources expected to be consumed/resources actually consumed.
3
Quality, where quality is an extremely wide concept. To make things more tangible, quality could be measured at six checkpoints: upstream systems, inputs, the transformation value-adding process, outputs, downstream systems and the quality management process.
4
Productivity, this is the traditional ratio of output/input, but it appears as just one of several criteria.
5
Quality of work life, one essential, but often forgotten element contributing to a well performing system.
6
Innovation, a key element in sustaining and improving performance.
7
Profitability or budget ability, the ultimate goal for any organisation.
Sink and Tuttle (1989) urge companies to focus on the following four areas: •
performance improvement planning
•
performance measurement and evaluation
•
performance improvement and control
•
cultural support systems.
A major objection to Sink and Tuttle’s model is the almost total lack of knowledge management, environmental focus. None of the seven criteria are focused on the environment, knowledge management and neither is the underlying system. Figure 1
Performance measurement matrix
Source: Sink and Tuttle (1989)
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3.2 The performance measurement matrix Keegan et al. (1989) presented the performance measurement matrix shown in the Figure 1, the strength of the performance measurement matrix lies in the way it seeks to integrate different classes of business performance-financial and non-financial, internal and external. The matrix is not as well packed and does not make explicit links between the different dimensions of business performance (Kennerley and Neely, 2003).
3.3 The performance measurement questionnaire (PMQ) Dixon et al. (1990) developed the PMQ to help managers identify the improvement needs of their organisation, to determine the extent to which the existing performance measures support improvements and to establish an agenda for performance measure improvements. The PMQ consist of four parts. The first part provides general data to be used to classify the respondents. Part two of the PMQ assesses the companies’ competitive priorities and performance measurement system. It consists of items labelled as improvement areas. They are placed in the centre of the questionnaire as shown in Table 1. The respondent is asked to circle a number on each side. The third part of the PMQ is similar to part two except the focus is on performance measures. The final part of the questionnaire asks the respondents to provide performance measures that best evaluate their own performance and any other general comments. The results of the PMQ are evaluated in four ways: alignment, congruence, consensus and confusion. Alignment analysis is conducted to investigate in general terms how well a company’s actions and measures complement its strategy. Congruence analysis is conducted to provide a detailed understanding of how well the measurement system supports an organisation’s actions and strategy. Consensus analysis is carried out by grouping the data by management level or by functional group. This analysis shows the effect of communication. The goal of the confusion analysis is to determine the extent of consensus regarding each improvement area and performance measure. The disadvantage of the PMQ is that it cannot be considered a comprehensive integrated measurement system. Another weakness is that it does not take into account the concept of continuous improvement (Ghalayini and Noble, 1996; De Toni and Tonicha, 2001). Table 1
Section of part two of PMQ
Long run importance of improvement
Improvement areas
None >>>>> great
Effect of current performance measures on improvement Inhibit >>>>> support
1234567
Quality
1234567
1234567
Labour efficiency
1234567
1234567
Machine efficiency
1234567
Source: Dixon et al. (1990)
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3.4 The EFQM business excellence model The European Foundation for Quality Management (EFQM) business excellence model developed in 1992 is shown in Figure 2. It originally emanated from the total quality movement and is heavily focused on continuous improvement. The ‘results’ aspect of the EFQM framework is similar to the balanced scorecard, though the EFQM has the advantage of considering the ‘enablers’ in organisational performance as well. A detailed set of scoring criteria is used to determine how the company identifies processes, shows leadership, sets policy, allocates resources, achieve people and customer satisfaction and has an impact on society. Ahmed (2002) stated that the disadvantage of the EFQM framework is that it does not explicitly link business strategy and operations. Figure 2
The EFQM business excellence model Results
Enablers
People results
People
Leadership
Policy and strategy
Processes
Partnership and resources
Customer results
Key performance results
Society results Innovation and learning
Source: EFQM (1999)
3.5 The balanced scorecard Most of the performance measures described so far is limited to measuring manufacturing operations only and some of them measure customer service. In this competitive environment, there is a need for a performance measurement system that gives a fast and comprehensive view of entire business. Balanced score card developed by Kaplan and Norton (1992) is shown in Figure 3. It is such a measurement system, which includes financial measures that tell the results of actions already taken. And it complements the financial measures with operational measures on customer satisfaction, internal processes and the organisation’s innovation and improvement activities. The balanced scorecard allows the manager to look at the business from four important perspectives: Customer perspective, internal perspective, innovation and learning perspective and financial perspective. It provides answer to four basic questions: •
How do customers see us?
•
What must we excel at?
•
Can we continue to improve and create value?
•
How do we look to shareholders?
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In order to apply the balanced score card to work, companies should articulate goals for time, quality, and performance and service and then translate these goals into specific measures (Kaplan and Norton, 1992). Though the balanced scorecard gives information from four different perspectives, it limits the number of measures to avoid information overload, it also prevents sub-optimisation by forcing senior managers to consider all operational measures at the same time. This enables them to see whether improvement in one area may have been achieved at the expense of another. This is possible because the best objectives can also be achieved. For instance, a company can reduce time to market in two different ways: by improving the management of new product introduction or by releasing only products that are incrementally different from existing product. Figure 3
Balanced score card
Source: Kaplan and Norton (1992)
Balanced scorecard is very popular performance measurement system; more than 40% of the largest businesses in the USA had adopted the balanced scorecard by the end of 2000. Data collected by balanced scorecard collaborative put the figure even higher, shows that over 50% of surveyed firms’ worldwide had adopted the balanced scorecard by the middle of 2002 (Kennerley and Neely, 2003). Even though the balanced scorecard has many limitations according to Gahlayini and Noble (1996), balanced scorecard is primarily designed for the senior managers to provide them with an over all view of performance. It is not intended or not applicable at the factory level. Krause (2003) states that balanced scorecard fail to adequately highlight the contributions that employees and suppliers make to help the company achieve its objectives. It fails to identify the role of community in defining the environment within which the company works. It fails to identify the performance measures to assess stakeholders’ contributions. Krause (2003) also argued that there is no clear provision for very long term measures. It fails to account for the role for motivated employees, which are a critical issue in manufacturing services and other service sectors.
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3.6 The performance pyramid (SMART system) The strategic measurement analysis and reporting technique (SMART) system also known as performance pyramid was developed by Cross and Lynch (1989) in Wang Laboratories, Inc. as a result of dissatisfaction with traditional performance measures such as utilisation, efficiency, productivity and other financial variances. The objective was to device a management control system with performance indicators designed to define and sustain success. The SMART system can be represented by a four-level pyramid of objectives and measures as shown in Figure 4 at the top corporate vision or strategy. At this level management assigns a corporate portfolio role to each business unit and allocates resources to support them. At the second level, objective for each business are defined in market and financial terms. At the third level more tangible operating objectives and priorities can be defined for each business operating system in terms of customers’ satisfaction flexibility and productivity are represented by specific operational criteria: quality, delivery, process time and cost. As the foundation of the performance pyramid these operational measures are the keys to achieve higher level results and ensure successful implementation of the company strategy. Weakness of the SMART system is that it does not provide any mechanism to identify key performance indicators for quality, cycle time, cost and delivery. Also, the SMART system does not explicitly integrate the concept of continuous improvement (Ghalayini and Noble, 1996; Bourne et al., 2000). Figure 4
The performance pyramid
Source: Cross and Lynch (1989)
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3.7 The AMBITE system The advanced manufacturing business implementation tool for Europe (AMBITE) is modern performance measurement system (Sahay et al., 2000). The objective of this framework is to develop a technique that senior management can use to assess the impact of strategic decisions made by their enterprise. The framework provides a mean of translating the business plan of the enterprise (i.e., critical success factors) into set performance measures. The performance measures will be directly related to the strategy of the enterprise and will also be process oriented. The AMBITE framework shown in Figure 5 uses a business model to describe a manufacturing enterprise. Each of the five macro-business processes (customer order fulfilment, vendor supply, design coordination, co-engineering and manufacturing) are mapped on to measures of performance (time, cost, quality, flexibility and the environment) This is done for the make-to-stock (MTS), assemble-to-order (ATO), make-to-order (MTO) and engineer-to-order (ETO) manufacturing environment, a typology described by McMahon and Brown (1993). Figure 5
The AMBITE performance framework Marketing production process design
Co-engineering
Design coordination
Manufacturing
Suppliers
Customer
Customer order fulfilment
Vendor supply
Production planning and control
Source: McMahon and Browne (1993)
The AMBITE performance measurement framework need to know its CSFs, it should be difficult to develop a consistent set of performance indicators for that enterprise which are directly related to the CSFs. It is process-oriented and generic framework.
3.8 The PO-P system Using the principles of modern business and system theory, and drawing upon the proven strength of the techniques of multiple attribute decision and goal programming, Vrat et al.
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(1998) proposed a new methodology of productivity measurement termed as PO-P. The PO-P system is a multi-criteria productivity management technique, which lays stress on performance against the objectivated output. One of the primary and most important tasks of a productivity measurement technique is to provide comparative information, i.e., on the rise or decline in productivity along with the identification of opportunities for improvements. Productivity of a system should be an indicator of its efficiency and effectiveness. However, external environment has an impact on productivity which can get altered without any change in the productive efforts of the organisation. PO-P model meets these requirements. The PO-P concept is the system productivity. The outputs are the performance of the system (and its sub-systems). These include the tangible as well as the intangible covering areas, such as goods produced, services rendered, organisational goals and values. Also included are performance objectives such as service to community, contribution to human habitat, participation in social welfare so as to provide a specified satisfaction to all members of society who have a stake in the organisation. The performance so achieved (as output) is the result of acquisition, deployment and efficient use of resources in a rationally acceptable norm. Emphasis is on achievement of goals related to a system within the constraints of the resources available. Identification of sub-systems is a major exercise. Burns and Stalker suggest that a system (or a sub-system) has five basic characteristics: a central objective and measure of performance, environment, resources, components and management. An organisation as a system can have functional sub-systems, such as a production sub-system, a marketing sub-system etc., as well as management sub-systems, such as production control sub-system, management information sub-system, personnel management sub-system etc. These sub-systems may be also embedded in other sub-systems. Identification of key performance areas (KPAs) is another major exercise. Here, two considerations are vital. First, identified KPAs should be those which are associated with the sub-systems effectively. There are bound to be overlaps and some areas would appear to be belonging to more than one sub-system. However, it is the sub-system that controls the development of inputs and has the responsibility of function/objectives that the KPAs should belong to. Second, KPA should have basis and relevance to organisational objectives. As organisational objectives can vary from one organisation to another, so should the importance of each of the KPA vary. Business budgets, planning and product strategies of the sub-system have priority over the operational responsibilities of the KPA. A KPA must subordinate to the sub-system.
3.9 TOPP system One example of a more recent performance measurement system is the TOPP system, which was developed by SINTEF (1992) in Norway in partnership with the Norwegian Institute of Technology (NTH), the Norwegian Federation of Engineering Industries (TBL), and 56 participating enterprises. In TOPP, four methodologies were used: •
self-audit (questionnaire)
•
extended audit (experts)
•
self-assessment (continuous improvement, trends)
72 •
A.K. Digalwar and K.S. Sangwan benchmarking (breakthrough).
The TOPP views performance along three dimensions (effectiveness, efficiency and changeability) as illustrated in Figure 6. A main concern in TOPP is the many surrounding factors that influence the productivity and competitiveness of a company. This is illustrated in the stakeholder model, see Figure 6. In the stakeholder model the environment is one of several factors influencing the company. Our experience is, however, that the environment is becoming one of the most important stakeholders in any company. Figure 6
Performance model from TOPP
Efficiency
Adaptability Effectiveness
Source: SINTEF (1992)
The environmental focus of the TOPP system is better than in Sink and Tuttle’s model. In the questions for the self-audit and the extended audit, the environment is a major part. The environmental focus is not, however, truly integrated with the other aspects and areas as a WCM measurement system.
3.10 The performance prism The performance prism, one of the recently developed conceptual frameworks as shown in Figure 7, describes that a performance measurement system (PMS) should be organised around five distinct but linked perspectives of performance (Neely et al., 2001). These five perspectives are: 1
Stakeholder satisfaction – who are the stakeholders and what do they want and need?
2
Strategies – what are the strategies we require to ensure the wants and needs of our stakeholders?
3
Processes – what are the processes we have to put in place in order to allow our strategies to be delivered?
4
Capabilities – what are the capabilities we require to operate our processes?
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Stakeholder contributions – what is wanted and needed from stakeholders to maintain and develop these capabilities?
The performance prism has a much more comprehensive view of different stakeholders (e.g., investors, customers, employees, regulators and suppliers) than other frameworks. Neely et al. (2001) argues that the common belief that performance measures should be strictly derived from strategy is incorrect. It is the wants and needs from stakeholders that first must be considered. Then, the strategies can be formulated. Thus, it is not possible to form a proper strategy before the stakeholders have been clearly identified. Figure 7
Performance prism
Stakeholders satisfaction Investor, customers, intermediaries, employees, regulators, communities suppliers Strategies Corporate, business unit, brands/products/services
Processes Develop products services, general demand, fulfil demand, plan and manage enterprise
Capabilities People, practices, technology Infrastructure Stakeholder contribution Source: Neely et al. (2001)
The strength of this conceptual framework is that it first questions the company’s existing strategy before the process of selecting measures is started. In this way, the framework ensures a strong foundation for the performance measures. The performance prism also considers new stakeholders (such as employees, suppliers, alliance partners or intermediaries) that are usually neglected when forming performance measures. However, much attention has been placed on the process of finding the right strategies for the development of a PMS, but little concentration is given on the process of the actual design of a PMS. In other words, the performance prism extends beyond performance measurement, but tells little about how the performance measure is going to
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be realised. The Neely Group has previously published many useful tools in this area and should, if possible, create a better link between such tools and the performance prism.
4
Limitations of existing performance measurement framework
From the above discussion, it is clear that some of these frameworks (e.g., Sink and Tuttle framework, performance measurement matrix, performance measurement pyramid) are very strict on performance measures to be included in the PMS. Others emphasise that a company should have a unique PMS and guide the measurement practitioners to select and design performance measures. However, all conceptual frameworks have in common that they endorse a particular typology (or arrangement) that the performance measures in the PMS must be structured according to. They have paid little attention in the continuous updating of the performance measures. Table 2 below shows comprehensive limitations of the existing PMS. Table 2 S. no.
Limitations of existing PMS in the context of WCM performance measures Performance measurement frameworks
Major limitations in WCM perspective
1
The Sink and Tuttle framework None of the seven criteria are focused on the environment, knowledge management.
2
The performance measurement matrix
The matrix is not as well packed and does not make explicit links between the different dimensions of business performance.
3
The performance measurement questionnaire
It cannot be considered a comprehensive integrated measurement system. Another weakness is that it does not take into account the concept of continuous improvement.
4
EFQM business excellence model
It does not explicitly link business strategy and operations.
5
The balanced scorecard
It fails to identify the role of community in defining the environment within which the company works. It fails to identify the performance measures to assess stakeholders’ contributions.
6
The performance pyramid
It does not explicitly integrate the concept of continuous improvement.
7
The AMBITE system
It is a process-oriented and generic framework.
8
The PO-P system
Identification of KPAs is a major exercise.
9
The TOPP performance model
It is not directly related to the strategy or customer requirements of the enterprise.
10
The performance prism
Much attention has been placed on the process of finding the right strategies for the development of a PMS, but little concentration is given on the process of the actual design of a PMS.
Another weakness of these frameworks is that little or no consideration is given for existing PMS that companies may have in place. However, companies rarely want to design PMS from scratch. Usually managers are interested in eliminating any weaknesses
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in their existing system (Neely et al., 1995; Tangen, 2003) rather than developing a new system. From the literature review, it is observed that, all conceptual frameworks have their relative benefits and limitations, with the most common limitation being that little guidance is given for the actual selection and implementation of the performance measures.
5
Need of a new framework for WCM performance measurement
In world class manufacturing the focus is on continuous improvement. Performance measurements should therefore activate continuous improvements. As organisations adopt world class manufacturing they need new method of performance measurement to assess the continuous improvement of the organisation. Traditional performance measurement systems are invalid for the measurement of world class manufacturing practices as they are based on outdated traditional cost management systems, lagging metrics, not related to corporate strategy, inflexible, expensive and contradict continuous improvement. The traditional notion of productivity, which has been considered a good indicator of the performance and progress of an organisation, also has many limitations. The simple forms of productivity are misleading while the aggregate ones are complicated and neglected in practice. In response to the need of new performance measurement, many researchers have argued that the new strategic performance measure based on time and cost should be used to drive improvement. Yet, systems solely based on time-based performance measurement have the limitation of over-emphasising the role of time and not considering the impact of other operational performance measures such as quality, flexibility, delivery etc with respect to time. In order to improve time performance all operational performance measures should be measured, controlled and improved. Finally, various conceptual performance measurement frameworks have been developed. However, they also fail to capture the entire domain of world class manufacturing performance measures. Some researchers made an attempt in that direction by identifying the different set of performance measures. Saraph et al. (1989), Ahire et al. (1996), Black et al. (1996) identified critical factors of quality management – the role of management leadership and quality policy, quality department, training, product/service design, supplier quality management, process management, quality data and reporting, employee relation, customer focus. Quality, cost, delivery reliability, lead time, flexibility and employee relationships are the six factors identified by the Maskell (1991) as the key elements of world class manufacturing commonly used by the world class companies. Flynn et al. (1994) recommended top management support, quality information, process management, product design, work force management, supplier involvement and customer involvement as the key performance measures of WCM. However, the authors suggested manufacturing cost, employee empowerment, flexibility, and speed as additional performance measures of WCM. Kasul and Motwani (1995) identified nine critical factors for word class operations – management commitment, quality, customer service, vendor and material management, advanced technology, facility control, flexibility, price/cost leadership and global competitiveness. However, the identified performance measures were not tested and
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validated. Francisco et al. (2003) proposed the need of measurement of knowledge management activities for an organisation that would like to become a world class organisation. Roy et al. (2000) proposed a framework to develop performance indicators for knowledge management. Wong (2005) identified critical success factors for implementing knowledge management in small and medium enterprises. Seven critical factors for environmental management – top management commitment, total involvement of employees, training, green product/process design, supplier management, measurement and information management – are identified by Wee and Quazi (2005). According to the authors there is a need to focus on environmental issues for improving the performance of organisation. Utzig (1988) has suggested the following list of operating measures for advanced manufacturing – lead time, total value-added versus non-value added time and cost, schedule performance, product quality, engineering change notices, machine hours per part, plant/equipment/tooling reliability, cycle time, broad management/worker involvement, problem support, high value-added design, and forecast accuracy. However, authors such as Hayes et al. (1980) or Schmenner (1991) proposed only productivity as a measure of manufacturing performance. Kennerley and Neely (2003) identified the need for a method that can be used for development of measures that can span diverse industry group. Many other researchers such as Joo et al. (2009), Gebauer et al. (2009), Parveen and Rao (2009), Oberoi et al. (2008), Dangayach and Deshmukh (2008), Anand and Kodali (2009), Kounis and Panagopoulos (2007), Field and Meile (2008), Gunasekaran et al. (1998, 2004), Lockamy III (1998) and Motwani (2001) focus on different aspects and techniques of WCM like supply chain management, TQM, manufacturing strategy, lean manufacturing etc. Independently, no one has developed a framework which integrates all performance measures and which can be used for continuous improvement of the organisations. Also very limited literature is available on the performance measurement of WCM, which is based either on examinations of current best practices or the authors’ personal experience indicates a need to: •
develop and validate a comprehensive set of performance measures and their variables which take into account all the aspects of WCM
•
develop a framework which integrates all performance measures and which can be used for continuous improvement of the organisations rather than just a monitoring and controlling tool.
6
Proposed performance measurement framework for WCM
Using a thorough synthesis of the world class manufacturing literature, sixteen performance measures – top management commitment, knowledge management, employee training, innovation and technology, employee empowerment, environmental health and safety, supplier management, production planning and control, quality, flexibility, speed, cost, customer involvement, customer satisfaction, customer services and company growth – of world class manufacturing and their 89 variables have been developed. Using the data obtained from a survey of manufacturing industries in India, the identified performance measures were subjected to appropriate statistical tests to establish reliability and validity (for detail please see Digalwar and Sangwan, 2007).
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Finally a five-stage framework of performance measures is proposed for the assessment of world class manufacturing as shown in Figure 5. The five stages of the proposed performance measurement framework are: top management commitment (Stage 1), learning and growth (Stage 2), internal processes (Stage 3), customer (Stage 4), and financial (Stage 5). All performance measures are arranged in these five stages. Stage 1 Top management commitment is at the base of the framework. A cultural (attitude) change is essential for the implementation of most of the aspects of WCM. Without the support of top management in term of resource allocation, continuous monitoring of the progress, and the change management, the cultural change is impossible. Stage 2 Top management commitment to the employee learning and growth is critical for the successful implementation of world class manufacturing. For an organisation to be world class, its employees need to be empowered for which training is essential. These days, with the availability of vast knowledge, employees should be trained in techniques of harnessing this knowledge to develop innovative products quickly to the satisfaction of discerning customer. Stage 3 Empowered cross functional teams are a necessity for the early utilisation of relevant knowledge to take quick and effective decisions in a single trade-off space for the continuous improvement of internal processes viz. cost, quality, flexibility, environmental, health and safety, speed, supplier management, and for production planning and control. Willing participation of an employee in various cross functional teams is possible only if an employee is empowered, satisfied, trained and knowledgeable with the proper attitude. Internal process stage identifies the strengths and weaknesses of internal operations and resources of the company. It reflects the capacity of a firm to respond to customer needs and requirements in a cost and time-effective way. Stages 4 and 5 The ability of an organisation to deliver customised quality goods and services quickly for the satisfaction of customer is dependent upon the internal processes of the organisation. In today’s competitive business environment, customer satisfaction is vital for an organisation to stay in business, grow and makes profit. Managers/decision-makers can use this framework to measure the performance of world class manufacturing. This framework can also be used to assess the current stages, determine the performance measurements, assign responsibilities and resources, and monitor the progress to the implementation of the world class manufacturing in an organisation. When used periodically, the proposed framework of world class manufacturing performance measures will enable decision-makers to evaluate the perception of world class manufacturing in their organisation. In addition, the periodic use of the performance measures framework will help in the monitoring process in identifying those areas where improvement should be made, and in prioritising world class manufacturing efforts. Specification and measurement of the performance measures permit managers to obtain a better understanding of world class manufacturing practices and allow researchers to proceed with the task of developing and testing theories of world class manufacturing.
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Figure 8
Proposed performance measurement framework for WCM Company growth
Stage 5
Customer satisfaction
Stage 4
Customer service
Cost
Speed
Flexibility
Environmental health and safety
Quality
Production planning and control
Employee empowerment
Knowledge management
Employee training
Innovation and technology
TOP MANAGEMENT COMMITMENT
6
Supplier management
Stage 3
Stage 2
Customer involvement
Stage 1
Conclusions
Traditional performance measures have many limitations that make them less applicable in today’s competitive environment. Traditional notion of productivity which has been considered a good indicator of the performance and progress of an organisation also has many limitations. As a result of the limitations of the traditional performance measures researchers have argued that time is the new strategic performance measures that should be used to drive improvement. Yet, system solely based on time based performance measurement have the limitation of over-emphasising the role of time and not considering the impact of other operational performance measures with respect to time. To overcome the limitations associated with previous performance measurement systems, various integrated performance measurement systems have been developed. However, they also suffer from a variety of limitations. Thus, there is still a need for the development of new performance measurement system for today’s manufacturing environment. The proposed framework of world class manufacturing performance measures will enable decision-makers to evaluate the perception of world class manufacturing in their
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organisation. In addition, the periodic use of the performance measures framework will help in the monitoring process in identifying those areas where improvement should be made, and in prioritising world class manufacturing efforts. Specification and measurement of the performance measures permit managers to obtain a better understanding of world class manufacturing practices and allow researchers to proceed with the task of developing and testing theories of world class manufacturing.
Acknowledgements We would like to acknowledge the reviewers for their constructive and helpful comments.
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