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Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Performance Measurement in SMEs: Diffusion and Characteristics
  5. Factors Influencing Performance Measurement in SMEs
  6. Main Dimensions of PMS Models
  7. A Comparison of PMS Models
  8. Conclusions and Future Research
  9. References

In recent years, literature has identified the increasing complexity of small and medium-sized enterprises (SMEs) and highlighted their sensitivity to differences in managerial culture and management systems. Research has shown that performance measurement systems (PMSs) could play an important role in supporting managerial development in these companies. In this paper, the literature on performance measurement in manufacturing SMEs is reviewed and the diffusion, characteristics and determinants of performance measurement in SMEs are analysed. Shortcomings in the performance measurement systems are highlighted and the many factors that seem to constrain PMSs in manufacturing SMEs are defined, e.g. lack of financial and human resources, wrong perception of the benefits of PMS implementation, short-term strategic planning. Moreover, using dimensions defined according to the information found in the literature, two PMS models specifically developed for SMEs are compared with generic PMS models. The comparison points out an evolution in PMS models over time; in particular, the models developed in the last 20 years are more horizontal, process-oriented and focus on stakeholder needs. However, it is not clear whether these changes are due to the evolution of the generic models or an attempt to introduce models suited to the needs of SMEs. To clarify this matter and better to understand PMSs in SMEs, further theoretical and empirical studies are necessary. The main issues still requiring investigation are listed in a research agenda at the end of the paper.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Performance Measurement in SMEs: Diffusion and Characteristics
  5. Factors Influencing Performance Measurement in SMEs
  6. Main Dimensions of PMS Models
  7. A Comparison of PMS Models
  8. Conclusions and Future Research
  9. References

Since the mid-1980s, increasing attention has been given to the study of performance measurement systems (PMSs). A PMS is a balanced1 and dynamic2 system that is able to support the decision-making process by gathering, elaborating and analysing information (Neely et al. 2002). Following the criticism of traditional performance models, which focused on financial measures, multidimensional and balanced models were created to support the development of the organization and management of big companies (Sinclair and Zairi 2000).

In recent years, the literature has highlighted the need for changes in managerial culture and rationalization of management systems to support the management of the increasing complexity in manufacturing small and medium-sized enterprises (SMEs) (Bernardi and Biazzo 2003; Marchini 1995; Martins and Salerno 1999). Using the European Commission definition (see Storey 1994, 13), we focus our attention on independent and manufacturing SMEs excluding micro-companies and small enterprises employing fewer than 20 people (see Cagliano et al. 2001). These companies are improving their technical and technological capabilities to meet the market needs, but low formalized managerial practices are still adopted; PMS is particularly important for supporting the managerial development required in these companies to manage increasing complexity. In fact, it has often been said (Bridge et al. 1998; Neubauer and Lank 1998) that the critical factors for the success of these SMEs can mostly be found in the attributes of a model of a company whose success basically depends on the figure of the entrepreneur-owner, who is personally responsible for managing the activities of the company. This model is characterized by: flexibility and an ability to react quickly and adapt to the competitive and changing environment; organizational processes which are not very structured or ‘engineered’; significant concentration of decision-making processes in the entrepreneur-owner; focus on technical aspects and production; and the existence of specialist and tacit knowledge that is essentially technological and evolves through learning processes based on learning by doing (Jennings and Beaver 1997; Marchini 1995; Martins and Salerno 1999).

Small and large firm are fundamentally different from each other in three central aspects: uncertainty, innovation and evolution; literature underlines that the central distinction between large and small firms is the greater external uncertainty of the environment in which the small firm operates, together with the greater internal consistency of its motivations and actions (Storey 1994; Welsh and White 1981). PMSs should support SMEs to manage uncertainty, to innovate their products and services, and to sustain evolution and change processes.

Several important changes that have taken place in recent years have created a favourable context for the implementation of PMSs in manufacturing SMEs (for brevity in the following we refer to SMEs). The four main factors that will be discussed here are: the evolution of the competitive environment and the propensity to grow in dimension (in the sense that they must increase the volume of business because of the geographical expansion of competitive spaces), the evolution of the concept of quality, increased focus on continuous improvement, and significant developments in information technology.

The evolution of the competitive environment and propensity to grow in dimension has led to the need for organizational development in these companies (Boldizzoni and Serio 2003). If a PMS does not focus exclusively on financial aspects, it can play a key role in supporting a rational approach to growing complexity and qualitative improvement in SMEs.

The evolution of the quality concept, its organizational impact (Compagno 1997), the introduction of new ISO 9001:2000 norms and the diffusion of quality awards are increasing the importance of implementing performance measurement in SMEs. When these companies introduce new norms or implement guidelines for quality awards, they often find that their management systems are inadequate. Implementing a PMS could support the decision-making processes in SMEs and help them improve their management processes and strategic control (Barnes et al. 1998; Bhimani 1994; Hudson et al. 2001; Tenhunen et al. 2001).

The increasing importance of continuous improvement has led many researchers to point out that PMSs might actually be needed to support continuous improvement processes (Atkinson and Waterhouse 1997; Barnes et al. 1998; Lynch and Cross 1991; Maskel 1989; Neely et al. 1996, 2000). In addition, SMEs tend to have poor strategic planning and do not fully understand what their critical success factors are (Greatbanks and Boaden 1998). The process of designing a PMS forces a company to do strategic planning, and implementing and using it highlights the gaps between the company's current performance and its objectives. Consequently, the PMS helps the company set future objectives and plan any necessary improvement processes (Tenhunen et al. 2001). As Kaplan and Norton (1996) and Lynch and Cross (1991) write, implementing a PMS favours the creation of learning processes and, therefore, agreement on which processes need to be improved.

Innovation in information technology is increasing the opportunity to create a relationship between a PMS and a company's information system (IS) and to reorganize the internal and external information flows using an integrated approach (Bititci et al. 2000; Neely 1999). These new technologies help to reduce the costs of implementing and using a PMS as well. This is particularly important for SMEs, since they tend to have limited financial resources.

The aim of this paper is to investigate the relationship between PMSs and SMEs. First, the process used to carry out the literature review is described, and the results of this review are summarized, giving particular attention to the diffusion and specific characteristics of PMSs in SMEs. Then, several factors that influence performance measurement in SMEs are described, and the main dimensions, or characteristics, of the PMS models after the mid-1980s are summarized. Finally, using these dimensions, these models are compared with explicit reference to firm size.

The information used in this study was gathered using a systematic literature review approach as described in Figure 1 (Sign 2004; Tranfield et al. 2003). The three research questions taken into consideration were:

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Figure 1. Literature review process.

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  • • 
    the diffusion and specific characteristics of performance measurement (PM) in SMEs
  • • 
    the factors influencing PM in SMEs
  • • 
    the main dimensions that characterize contemporary PMS models (i.e. models developed after the mid-1980s –Figure 1).

While the strategy used to identify evidence was the same for all three questions considered, the criteria used to select the evidence were not. Given the limited amount of research specifically on PMSs in SMEs, the first two questions were mainly investigated by making reference to conference proceedings and internal reports. In contrast, since many studies propose PMS models and characteristics, mostly journal papers, which have a more theoretical approach, were used to investigate the third area. In fact, it was not possible to study the effectiveness of these dimensions because very little empirical research has been carried out on this topic.

Performance Measurement in SMEs: Diffusion and Characteristics

  1. Top of page
  2. Abstract
  3. Introduction
  4. Performance Measurement in SMEs: Diffusion and Characteristics
  5. Factors Influencing Performance Measurement in SMEs
  6. Main Dimensions of PMS Models
  7. A Comparison of PMS Models
  8. Conclusions and Future Research
  9. References

Very little empirical and theoretical research has been carried out on PM in SMEs. The countries where a lot of research has been carried out on PM for SMEs are Australia (Barnes et al. 1998), where a specific organization has been created to support the development of PMSs for SMEs (called the Commonwealth Scientific and Industrial Research Organization – CSIRO), Finland (Laitinen 2002; Rantanen and Holtari 2000; Tenhunen et al. 2001), the UK (Bhimani 1994; Bititci et al. 2000; Collis and Jarvis 2002; Jarvis et al. 2000; Neely and Mills 1993), and Denmark (Hvolby and Thorstenson 2000). Although an explicit comparison of these studies is not available in the literature, our analysis showed that there do not appear to be any differences based solely on the country where they were carried out. However, five common characteristics were identified.

  • • 
    The difficulty in involving SMEs in performance measurement projects. Moreover, the companies that do take part in these projects rarely continue on to the last phase because of the lack of time available for non-operational activities and the poor involvement of the entrepreneurs or top managers in the PM project (Tenhunen et al. 2001). There is, however, a significant difference between SMEs that have developed a quality culture and those that have not, because quality activities highlight the inadequacy of current managerial practices and thus have a positive impact on the development of managerial systems (Barnes et al. 1998).
  • • 
    The studies indicate that SMEs either do not use any PM model or they use models incorrectly. Many companies often implement only some parts of a general model, while others modify the models without carefully considering the changes made. In other words, they eliminate some dimensions without first carefully understanding and analysing the characteristics of the model and the company. This approach is incomplete and does not consider the specific needs of SMEs (CIMA 1993; Tenhunen et al. 2001). Moreover, some researchers point out that, even if general models were applied correctly, they would be inadequate for the particular characteristics of SMEs: ‘the small enterprise is different from the big company; you cannot simply look at the needs of SMEs by turning your binoculars upside down and making small what was big’ (Marchini 1995). For example, some authors who have assessed the implementation of the Balanced Scorecard in SMEs conclude that this model is not suitable for SMEs (Hvolby and Thorstenson 2000; McAdam 20003). Finally, very few models have been developed for SMEs, and those that do exist have been developed only in the last few years.
  • • 
    Performance measurement implemented in SMEs rarely has a ‘holistic approach’. The studies by Barnes et al. (1998) and Rantanen and Holtari (2000) highlight the fact that SMEs do not usually implement integrated PMSs, and that they are not aware of the existence of integrated PMS models. Furthermore, since small companies focus on operational and financial performance, balanced models are seldom used. In fact, innovation, human resources, work atmosphere, R&D and training are rarely measured (Addy et al. 1994; Chennell et al. 2000; Hudson et al. 1999; Hvolby and Thorstenson 2000; Tenhunen et al. 2001). The study by Antonelli and Parbonetti (2002) highlights that SMEs still do not perceive the need for balanced models, as proposed by Kaplan and Norton (1996), even if some SMEs do use indicators of customer satisfaction, internal processes and training.
  • • 
    SMEs’ approach to performance measurement is informal, not planned and not based on a predefined model; performance measurement is introduced to solve specific problems and the PMS grows out of this process spontaneously rather than as a result of planning (Barnes et al. 1998). Consequently, performance measurement in SMEs is characterized by a poor alignment between strategy and measures (Addy et al. 1994; Chennell et al. 2000; CIMA 1993; Hudson et al. 1999), with the exception of SMEs with quality management experiences. In SMEs, planning is usually absent or limited only to the operation levels where performance is measured. Consequently, SMEs do not take advantage of the implementation of the PMS to introduce strategic planning. Moreover, performance measures usually focus on past activities. In other words, the aim is to gather information to support the control activities rather than the forecasting and planning processes.
  • • 
    SMEs have limited resources for data analysis. Data are gathered and the processes analysed in an imprecise way, and this unformalized approach increases the ambiguity of the measurement objectives. The information is then presented in the same way: SMEs usually use tables rather than graphs, making it difficult to interpret the information (Antonelli and Parbonetti 2002; Barnes et al. 1998). Only SMEs with quality management experience have started to develop a graphical presentation of the information they gather. The same happens for performance measurement review, which is a process needed to make changes in the PMS according to changes taking place in the internal and external contexts. When PM review is not carried out correctly, the PMS is not being used to achieve strategic objectives. The reason SMEs with a quality culture place more attention on gathering, analysing and presenting data and reviewing indicators is probably that quality programs support improvements in how information is managed (Barnes et al. 1998).

Despite the recognized importance of performance measurement in SMEs, there seems to be a significant gap between the theory, which highlights the importance of PMSs in supporting the development of managerial systems, and practice, where there are almost no models and tools that deal with the specific characteristics of SMEs. In the next section, the main factors that influence performance measurement in SMEs are summarized.

Factors Influencing Performance Measurement in SMEs

  1. Top of page
  2. Abstract
  3. Introduction
  4. Performance Measurement in SMEs: Diffusion and Characteristics
  5. Factors Influencing Performance Measurement in SMEs
  6. Main Dimensions of PMS Models
  7. A Comparison of PMS Models
  8. Conclusions and Future Research
  9. References

Many researchers state that the specific characteristics of SMEs can be obstacles to the implementation and use of a PMS. These characteristics are briefly described in the following paragraphs.

  • • 
    Lack of human resources. SMEs have limited human resources. All the staff are involved in the activities of managing daily work, and have no extra time for additional activities, such as implementing a PMS (Barnes et al. 1998; Hudson et al. 2000; Hvolby and Thorstenson 2000; McAdam 2000; Noci 1995; Tenhunen et al. 2001).
  • • 
    Managerial capacity. Technical excellence in products and operational processes is often perceived as the only key critical factor in SMEs. A managerial culture is often lacking in these companies and therefore managerial tools and techniques are perceived as being of little benefit to the company. Very often, employees occupy different positions at the same time, the organizations are flat, and though the entrepreneur is in charge of both operational and managerial functions, he/she usually neglects the managerial activities (Marchini 1995).
  • • 
    Limited capital resources. The impact of the resources needed to implement a PMS is proportionally more onerous in SMEs than in large companies (Barnes et al. 1998; Burns and Dewhurst 1996; Ghobadian and Gallear 1997; Hudson et al. 2000; Hvolby and Thorstenson 2000; Neely and Mills 1993; Noci 1995). Moreover, the absence of affordable software platforms that focus on the specific needs of SMEs further obstructs the introduction of PMSs in these companies (Bititci et al. 2002).
  • • 
    Reactive approach. SMEs are characterized by poor strategic planning and their decision-making processes are not formalized. The lack of explicit strategies and methodologies to support the control process promotes both a short-term orientation and a reactive approach to managing the company's activities (Brouthers et al. 1998; Marchini 1995).
  • • 
    Tacit knowledge and little attention given to the formalization of processes. One of the main barriers to organizational development in SMEs is the lack of a managerial system and formalized management of the processes. Furthermore, since knowledge is mainly tacit and context-specific, the information required to implement and use a PMS is difficult to gather (Jennings and Beaver 1997; Marchini 1995; Martins and Salerno 1999).
  • • 
    Misconception of performance measurement. Bourne (2001) underlines that a PMS can only be effectively implemented and used when the company perceives the benefits of the PMS. SMEs often do not understand the potential advantages of implementing a PMS; these systems are perceived as a cause of bureaucratization and an obstacle to the flexibility of SMEs (Hvolby and Thorstenson 2000; Hussein et al. 1998; McAdam 2000).

The limited resources of SMEs require approaches and models that respond to their specific needs and are efficient and easy to implement. The employees involved in implementing and using PMSs must clearly understand the short- and long-term advantages in order to maintain their enthusiasm and commitment (Hudson et al. 1999). PMSs for SMEs must be dynamic and flexible in order to respond to the needs of these companies, but at the same time they must also be structured to a certain degree in order to favour activity planning (Barnes et al. 1998; Hudson and Smith 2000; Hudson et al. 2001). Though the design of PMSs for SMEs must consider strategy, there must also be a strong focus on operational aspects, since traditionally these are the aspects that are critical for the success of SMEs. Finally, the performance measurement process has to be based on a management information system which keeps in mind the limited financial and human resources of small and medium enterprises.

All these factors underline the differences between SMEs and big companies and the need for a different approach to PM in SMEs. Moreover, these factors could be useful in the study of the dimensions of PMSs for SMEs.

Main Dimensions of PMS Models

  1. Top of page
  2. Abstract
  3. Introduction
  4. Performance Measurement in SMEs: Diffusion and Characteristics
  5. Factors Influencing Performance Measurement in SMEs
  6. Main Dimensions of PMS Models
  7. A Comparison of PMS Models
  8. Conclusions and Future Research
  9. References

The following is an analysis of the main dimensions that characterize contemporary PMS models (mostly introduced after the mid-1980s). Each dimension is first discussed in general terms and then with specific reference to SMEs.

Strategy Alignment

For many years, it has been recognized that performance measurement can influence a company's behaviour and consequently affect the successful implementation of company strategy (Skinner 1971). A PMS must be designed and implemented in accordance with a company's business strategy in order to link the strategy to the objectives of functions, groups of people, and individuals (Bierbusse and Siesfeld 1997; Kaplan and Norton 1996; Nanni et al. 1992; Schneiderman 1999), as well as to operational aspects (Greatbanks and Boaden 1998; Lynch and Cross 1991; Meekings 1995; Neely et al. 2002).

The lack of alignment between performance measurement and business strategy in traditional models has been found to be one of the main obstacles to achieving the expected results from a PMS (Atkinson and Waterhouse 1997; Bourne et al. 2000; Dixon et al. 1990; Goold 1991; Kaplan and Norton 1992, 1996; Keegan et al. 1989; Lynch and Cross 1991; McAdam and Bailie 2002; Neely et al. 1994; Sink 1986). In fact, the models proposed after the mid-1980s, such as the Balanced Scorecard (Kaplan and Norton 1996) and the Performance Pyramid System (Lynch and Cross 1991), stress the alignment between strategy and PMS.4

The alignment between strategy and performance measurement is particularly important in SMEs. These companies lack formalized strategy, and implementing a PMS could promote the definition or formalization of business strategy. The first step in designing PMSs for SMEs should be strategy definition (Cook and Wolverton 1995; Hudson et al. 2000; Tenhunen et al. 2001). Furthermore, the relationship between strategy and operational activities must be made explicit in order to avoid losing the focus on the operational aspects (CIMA 1993).

Strategy Development

The reciprocal relationship between PMSs and business strategy is underlined in the literature. Although some authors stress that the design of a PMS should be based on company strategy, others explicitly state that a PMS should also support the definition, development and evolution of business strategy in order to support continuous improvement (Bititci 1997; Bourne et al. 2000; Tonchia 2001). In other words, they argue that a PMS and strategy should be separate but interrelated, i.e. the PMS informs the strategy development process and at the same time reflects the priorities of the adopted strategy. Neely et al. (2002) write that performance measures are designed to help managers establish whether they are on the right track to reach the planned objectives. Dixon et al. (1990) write that integrated performance measurement is ‘the process of acquiring cost and other performance knowledge and employing it operationally at every step in the strategic management cycle’. A PMS is a guide to how to develop and implement strategy, and how to find the method that can be used to improve it continuously.

Changes in the internal and external contexts require changes in strategy and defined objectives. To make these changes, knowledge must be accessible (Feurer and Chaharbaghi 1995) and there have to be mechanisms that can be used to gather information. A PMS allows a company to gather data that quantifies the effectiveness and efficiency of its activities and helps it assess whether its strategy is appropriate and whether it has achieved the objectives of its business strategy (Neely et al. 1995; Suwignjo et al. 2000). Moreover, a PMS can provide information on the effectiveness of actions before their full implementation and support changes in defined objectives (Feurer and Chaharbaghi 1995).

Focus on Stakeholders

In the last 20 years, the attention paid to stakeholders has increased dramatically. Freeman (1984) gave the first definition of stakeholders as the groups of people who can influence or who are influenced by the achievement of a company's objectives. Atkinson and Waterhouse (1997) underline that an organization should know what its stakeholders’ expectations are and strive to achieve the objectives they have defined. Dickinson et al. (1998) describe stakeholders as the ‘final judge’ of organizational performance. Funk (2003) stresses the importance of creating a sustainable organization, which is ‘one whose characteristics and actions are designed to lead to a “desirable future state” for all stakeholders’. However, the needs, wishes and levels of satisfaction of different groups of stakeholders vary, and each company has to monitor these aspects. To achieve this, in recent years some authors have adopted a stakeholder perspective in their PM systems and approaches (Atkinson and Waterhouse 1997; Bititci 1994; Kanji 2002; Neely et al. 2002; Sharman 1995). Some of the more recent performance measurement models focus on stakeholders’ needs rather than business strategy as the starting point in performance measurement system design, such as the Integrated Performance Measurement Reference Model (Bititci et al. 1997) and Performance Prism (Neely et al. 2000).

Even though PMS studies focusing on SMEs have begun to adopt the stakeholder approach, the literature shows that only the SMEs taking part in quality awards gather information about stakeholder satisfaction (Barnes et al. 1998). The approach to assessing stakeholder satisfaction in SMEs must be simple because, as Vinten (2000) writes, small businesses struggling to survive cannot be expected to take into consideration the range of stakeholders that a multinational company has. Thomlison's (1992) specification about primary and secondary stakeholders could be applied to SMEs.5

Balance

The most significant criticism of the traditional PMSs is the fact that they focus on financial measures. In fact, all the models developed after the mid-1980s are more balanced. However, scholars take different approaches to balance: Keegan et al. (1989) write about the balance between internal and external measures; Lynch and Cross (1991) propose balancing measures related to all the different organizational levels; Fitzgerald et al. (1991) pay attention to the results–determinants relationship; and Kaplan and Norton (1992) propose balancing four different perspectives based on both the nature of the measures (financial and non-financial) and the object of the measures (internal and external).

In our study, balanced models (also called multidimensional models) are defined as models that adopt different perspectives of analysis and manage them in a co-ordinated way. The innovations in information technology and systems have made it easier to gather and elaborate large amounts of data at a lower cost. These innovations could potentially support the implementation and use of balanced performance measurement systems. However, the use of innovative software has often brought with it an excessive use of measures that are introduced without a planned design. In this case, the performance measurement reports generated are difficult to use and interpret (Neely et al. 2000).

The issue of balance is particularly important when considering SMEs. These companies are characterized by a focus on operational and financial aspects and often only measure the performance of single aspects such as the different elements of the lead time, delivery precision and quality levels (Hvolby and Thorstenson 2000). Although operational issues are very important in SMEs, these companies need to increase their strategic managerial approach to align decision-making processes to strategic objectives; to do so, a balanced PMS could be an important support tool (Tenhunen et al. 2001).

Dynamic Adaptability

A performance measurement system should include systems for reviewing measures and objectives that make it possible both to adapt the PMS quickly to the changes in the internal and external contexts, and systematically to assess a company's strategy in order to support continuous improvement. Many scholars have studied and defined the dynamic approach (Bititci et al. 2000; Bourne et al. 2000; Dixon et al. 1990; Eccles and Pyburn 1992; Fortuin 1988; Ghalayini and Noble 1996; Ghalayini et al. 1997; Lingle and Schiemann 1996; Lynch and Cross 1991; Maskel 1989; McMann and Nanni 1994; Neely et al. 2000; Wisner and Fawcett 1991). By considering these studies and making reference to Bititci et al. (2000), it is possible to define a dynamic PMS as a system with the following characteristics.

  • • 
    An external and internal monitoring system. A system should continuously monitor the developments and changes in the external and internal environments.
  • • 
    A review system and an internal deployment system. A system should ‘use the information provided by the internal and external monitors and the objectives and priorities set by higher level systems, to decide internal objectives and priorities’; moreover, the system has to ‘deploy the revised objectives and priorities to critical parts of the system: business units, processes and activities using performance measures’ (Bititci et al. 2000).

Although the literature has highlighted the importance of dynamic PMS, most companies use static models (Bititci et al. 1999). This is mostly a result of the lack of:

  • • 
    an ability to distinguish measures that are useful for the control aspect from the measures that support improvement
  • • 
    an understanding of the causal relationship between strategic objectives, processes and activities
  • • 
    external monitoring, which is rarely carried out in SMEs even though they have to be flexible and able to react quickly to changes in the competitive context
  • • 
    the ability of the management to relate systematically the changes in the external and internal environments to changes in their PMSs
  • • 
    frameworks and platforms developed specifically for the needs of SMEs.

Process Orientation

Process management is becoming a part of the language and actions of many organizations. It is defined as an approach based on the organization of a company as a whole set of interconnected activities which aim to map, improve and align organizational processes (Benner and Tushman 2003). The importance of process management is underlined by both quality awards and the new edition of ISO 9001:2000 (Garvin 1998; Ittner and Larcker 1998), which recognizes process management as particularly useful in meeting stakeholder expectations and promoting the integration of the different company functions.

Different studies provide evidence that the performance of business processes has to be monitored, because it has a direct impact on stakeholder satisfaction. However, there are many operational difficulties in introducing the process management approach in companies. Though some organizations have started to re-engineer their processes by moving from vertical structures to horizontal structures that focus on internal business processes, the organization of most companies is still based on functional units (Beretta 2002). A study by Bititci et al. (1999) shows that few companies define and manage business processes. Consequently, PMSs based on a process approach are difficult to implement. Turner and Bititci (1999) highlight that the failure to deliver consistent output to the stakeholders is caused by the lack of co-ordination between functions. Organizations should re-evaluate their performance measurement systems and replace functional performance measures with process-related measures. Adopting process-oriented performance measurement could facilitate business process modelling, show the inadequacy of functional organizations (Beretta 2002) and promote the use of performance measurement as an important support in the decision-making process. Process performance is one of the main factors affecting the reliability of business processes; Turner and Bititci (1999) defined a reliable business process as ‘a process that will continue to provide a high level of stakeholder satisfaction over time’. According to these authors, applying reliability engineering, process thinking and active monitoring concepts to business processes can help systematically identify key performance measures in order to monitor business actively throughout the company. These authors also propose an active monitoring technique for improving and maintaining the reliability of business processes.

The increased importance of process management is influencing PMS models as well (De Toni and Tonchia 1996). Some PMS models introduce the process-oriented dimension (Kaplan and Norton 1992) and others use processes as one of the main starting points in designing PMSs (Bititci et al. 1997).

The increased attention to process management is also highly relevant to SMEs. PMSs based on business processes can provide information that allows companies to be more proactive in meeting stakeholders’ requirements. Since SMEs are small, by their very nature they have more visible end-to-end business processes, which make process orientation a simpler and less political issue. The two PMS models for SMEs considered in this study are based on business processes.

Depth and Breadth

The depth of a PMS is the level of detail to which performance measures and indicators are applied. The breadth of a PMS relates to the scope of the activities included in PMS. An in-depth model helps to define aims and to focus on how to implement and use the PMS from an operational and practical point of view. Tenhunen et al. (2001) write that an in-depth model could help SMEs to concentrate on just a few objectives and develop a more focused PMS over a short period of time using limited resources. However, according to other scholars, the focus must first be placed on the breadth of a model before focusing on a specific objective and developing an in-depth PMS. A broad model includes all the company's activities (managerial, operational and support) and provides a ‘holistic’ assessment of the company's performance. Lynch and Cross (1991) write that it is impossible to improve just one measurement of a company's performance without somehow impacting on other areas of performance. This is because of the inter-relationships between individual measures. This is similar to what Neely et al. (2000) write: ‘a PMS should give a synthetic and general description of company performance and provide comprehensiveness’. Moreover, according to Lynch and Cross (1991), since the performance measurement has to create a base for the management system, the company must consider more than just a few areas in its improvement effort.

A big company needs in-depth systems that ‘go down’ to the level of the single operational department (Lynch and Cross 1991). Models such as the Balanced Scorecard and the Performance Pyramid support in-depth measurement processes, but these models are difficult to implement in SMEs. Dickinson et al. (1998) and McAdam (2000) claim that SMEs should use PMSs that focus on breadth, not depth. By doing this, SMEs could develop a simple model and an integrated approach to corporate governance.

Causal Relationships

Many scholars have written about the causal relationship between results and their determinants in performance measurement: Lynch and Cross (1991) have developed a tool to find the causality link; Fitzgerald et al. (1991) call their model ‘Results and determinants’ to highlight that the results have to be interpreted as a function of specific determinants; Kaplan and Norton (1996) underline that identifying a causal relationship between performance indicators and objectives supports strategy review and learning. Since performance measurement is supposed to support planning and control (Ballantine and Brignall 1994), a PMS should measure not only the results, but also their determinants and quantify the ‘causal relationship’ between results and determinants in order to help monitor past actions and the improvement process (Bititci et al. 2000; Neely et al. 2000). However, since the causal relationships between determinants and results are very complex, and thus difficult to analyse, further research on this issue is still necessary (Neely 1999).

Performance is affected by a large number of multidimensional factors characterized by dynamic behaviour. Many factors are involved in a PMS, and it is very difficult to quantify their actual effects on performance. Suwignjo et al. (2000) have analysed different techniques to analyse the relationship between results and determinants, such as cognitive maps, cause and effect diagrams, tree diagrams and analytic hierarchy processes. Using these techniques, the authors have developed a specific model, called the Quantitative Model for Performance Measurement Systems (QMPMS), that helps identify the factors that affect performance and the relationships that exist between them. The effects of these factors on performance are expressed in quantitative terms. Though the model is easy to understand and implement, it is difficult to define the relationships between some of the factors and their determinants.

Understanding the relationships between results and determinants makes it possible to have periodic feedback on the measures used, performance results (Hynes 1998) and incremental changes (Appiah-Adu and Singh 1998). This would be very useful for improving the processes in SMEs, where incremental changes are often preferred over radical changes.

Clarity and Simplicity

The clarity and simplicity of a PMS are of crucial importance for its successful implementation and use. Many scholars state that clarity and simplicity should be the main characteristics of a PMS (Bierbusse and Siesfeld 1997; Eccles 1991; Globerson 1985; Neely et al. 1996, 2000; Maskel 1989; Schneiderman 1999). Clarity and simplicity are not easy to assess, because these characteristics have a subjective component. The literature review highlights the following components as characterizing a clear and simple PMS.

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    Clear definition and communication of the fixed objectives. The company has to define and transmit the objectives it aims to achieve using the adopted measures (Globerson 1985; Maskel 1989; Neely et al. 1996, 2000).
  • • 
    Careful selection of the measures to be used. One of the main problems with PMSs is that often there is too much data, much of which is easy to gather but not useful (Neely 1998). Bierbusse and Siesfeld (1997) write that the excess of data actually makes the PMS less effective; according to Dickinson et al. (1998) the set of measures is big enough when all the stakeholder needs are assessed without useless indicators. Ewing and Lundahl (1996) set a limit of 25 strategic indicators for each manager, and believe that if this limit is exceeded, the PMS is difficult to manage and demotivates those who use it.
  • • 
    Clear definition of measures. The measures have to be defined using objective criteria that make the meaning of each one clear (Globerson 1985; Neely et al. 2000; Schneiderman 1999).
  • • 
    Clear definition of how to gather and elaborate data. The aim in this case is to avoid elements that could reduce the quality of the data gathered (Globerson 1985; Neely et al. 2000). As Neely et al. (2002) write, there are many factors that could influence the quality of the data during the process of defining and implementing the PMS. A clear definition of how information is to be gathered and elaborated improves the quality of the data.
  • • 
    Use of relative instead of absolute measures. Relative data are easier to read and understand than absolute data (Globerson 1985; Neely et al. 2002).
  • • 
    Definition of how the processed information has to be presented. Information has to be communicated using a predefined format supporting the understanding of the data (Globerson 1985; Neely et al. 2002).

According to the literature, SMEs need a simple PMS that can give the management focused, clear and useful information (Hussein et al. 1998; Laitinen 1996, 2002). In fact, SMEs lack the resources needed to implement complex models and do not actually need complex models (Cook and Wolverton 1995; Hussein et al. 1998; Hvolby and Thorstenson 2000; Laitinen 1996; McAdam 2000; Tenhunen et al. 2001; Yeb-Yun 1999). The number of measures used should be limited. Furthermore, particular attention should be paid to the specific requirements of a given SME and the usability of the PMS (Barnes et al. 1998; Tenhunen et al. 2001). Nonetheless, the need to make a PMS simple and easy to use should not compromise the completeness of a system as would be the case if only single measures were used or if PMS models developed for big companies were merely simplified for SMEs by reducing the number of measures without maintaining the holistic vision of the original architecture (McAdam 2000).

A Comparison of PMS Models

  1. Top of page
  2. Abstract
  3. Introduction
  4. Performance Measurement in SMEs: Diffusion and Characteristics
  5. Factors Influencing Performance Measurement in SMEs
  6. Main Dimensions of PMS Models
  7. A Comparison of PMS Models
  8. Conclusions and Future Research
  9. References

Eight PMS models developed after the mid-1980s were compared. The traditional models, such as the activity-based costing which Bourne et al. (2000) defined as models based on accounting systems and financial information, were not included in this comparison because many research studies stress the inadequacy of these models for current managerial needs.

The models were compared using the eight dimensions discussed above (strategy alignment, strategy development, focus on stakeholders, balance, process orientation, depth, breadth, dynamic adaptability, causal relationships, and clarity and simplicity). They were also compared according to the three typologies defined by De Toni and Tonchia (2001) (vertical, balanced and horizontal).

Vertical architectures are defined as models that are strictly hierarchical (or strictly vertical), characterized by cost and non-cost performances on different levels of aggregation, till they ultimately become economic-financial (Berliner and Brimson 1988; Lockamy and Cox 1994; Partovi 1994; Rangone 1996); the first hierarchical model was that of Gold (1955), which connects productivity and ROI.

Balanced architectures are models that are balanced scorecard or tableaux de bord, where several separate performances are considered independently; these performances correspond to diverse perspectives (financial, internal business processes, customers, learning/growth) of analyses, that, however, substantially remain separate and whose links are defined only in a general way (Maskell 1991; Kaplan and Norton 1992, 1996); their model has been integrated with some vertical linkages, from the operational measures up to the financial ones (Brown 1996).

Horizontal architectures (by process) are models which are focused on the value chain and consider the internal relationship of customer/supplier (Moseng and Bredrup 1993; Sink and Tuttle 1989).

This latter comparison made it possible to summarize the results based on the eight dimensions defined in this study (see Table 1).

Table 1.  Comparison of eight PMS models Thumbnail image of

The models considered are six of the most popular generic models, i.e. those which make no reference to company size, developed in the last 15 years, and two PMS models created specifically for SMEs. The main characteristics of these models are summarized below.

  • • 
    Performance Measurement Matrix (Keegan et al. 1989). This model helps a company define its strategic objectives and translate these objectives into performance measures using a hierarchical and integrated approach. A two-by-two matrix combines cost and non-cost perspectives with external and internal perspectives. It is a balanced model, and it is cited in the literature for its simplicity and flexibility. However, this simplicity is sometimes criticized, because it does not consider some perspectives and relationships that are made explicit in other models such as the Balanced Scorecard (Neely et al. 1995, 2000).
  • • 
    Performance Pyramid System (Lynch and Cross 1991). This model is a pyramid built on four levels, showing the links between corporate strategy, strategic business units and operations. The strategic objectives (on the top level) are translated from the company vision using a top-down process. The model is balanced: it measures stakeholder satisfaction (e.g. customer satisfaction, quality, delivery) and operational activity (e.g. productivity, lead time, etc.). This model supports both the definition of the relationship between the different indicators and the management process.
  • • 
    Performance Measurement System for Service Industries (Fitzgerald et al. 1991), also called the Results and Determinants Framework because of its particular attention to the relationship between results and determinants. In particular, this model focuses on six dimensions divided into results (competitiveness, financial performance) and determinants of these results (quality of service, flexibility, resource utilization and innovation). It underlines the importance of carefully defining the performance indicators needed to achieve the performance objective. This model introduces a close link between PMS, strategy and competitiveness. It was developed only for service companies. The authors divided these companies into three types: professional services, service shops and mass service. Each type has specific characteristics that influence how performance is measured (performance variability, intangibility, production and contextual supply, etc.).
  • • 
    Balanced Scorecard (Kaplan and Norton 1992, 1996). This is the most popular model both in the literature and in practice. It aims to provide management with balanced measures based on four perspectives. The first one is the Financial Perspective, i.e. the company's ability to make profits (e.g. return on capital, cash flow, profitability). The second one is the Customer Perspective, which is evaluated using direct and indirect measures. Direct measures involve surveying customers and gathering their opinions regarding topics such as company image, customer perception or product/service customer satisfaction. When indirect measures are used, the customers are analysed but not directly involved in the analysis process (e.g. market share, customer retention). The third perspective is the Internal Process Perspective, i.e. the lead measures are linked to the organizational business processes, which are defined by the key processes the company must excel in to achieve a competitive advantage (e.g. all the processes from product development to the sales service supplied to customer). The last perspective is the Innovation and Learning Perspective, i.e. the company's ability to develop continuous improvement and add value using continuous learning. Each of these perspectives is linked to different types of organizational objectives, measures and activities supporting improvement.
  • • 
    Integrated Performance Measurement System (Bititci et al. 1997). The authors defined the Integrated Performance Measurement System (IPMS) as ‘the information system which enables the performance management process6 to function effectively and efficiently’. The model underlines two main facets of the performance measurement system: Integrity, which is the ‘ability of the performance measurement system to promote the integration of various areas of business’; and Deployment, which ‘refers to deployment of business objectives and policies throughout four levels where the higher level becomes a stakeholder of the lower level’ (Bititci et al. 1997). This model is based on four levels (Corporate, Business Units, Business Processes and Activities) and at each of these levels five key factors are considered (Stakeholders, Control Criteria, External Measures, Improvement Objectives and Internal Measures). Business Units, Business Processes and Activities are classified according to their complexity and the uncertainty of the business environment. This classification makes it possible to define the most appropriate type of performance measures, which are classified in internal, external, capability and learning measures.
  • • 
    Performance Prism (Neely et al. 2002). This is a three-dimensional model which aims to measure the performance of the whole organization. A prism graphically represents the architecture of the model, and each face of the prism corresponds to a specific area of analysis: stakeholder satisfaction (i.e. who are the key stakeholders and what do they want and need?), strategies (i.e. what strategies do we have to put in place to satisfy the wants and needs of our key stakeholders?), processes (i.e. what critical processes do we need if we are to execute our strategies?), capabilities (i.e. what capabilities do we need to operate and enhance our processes?) and stakeholder contribution (i.e. what contributions do we require from our stakeholders if we are to maintain and develop our capabilities?).
  • • 
    Organizational Performance Measurement (OPM) (Chennell et al. 2000). This model was developed specifically for SMEs and is based on three principles: Alignment, i.e. the selected performance measures support the alignment between people's actions and company strategy; Process thinking, i.e. the measurement system makes reference to the process monitoring, control and improvement systems; and Practicability, i.e. at any level in the company there is a consistent process for identifying measures that should be considered and for ensuring the quality and suitability of data. The framework is based on two key management constructs, namely Zone of management and Open systems theory. The first construct describes three zones of management (strategic, tactical and operational) with different authority, responsibility and accountability. The second one focuses on the company's environment, using stakeholder satisfaction analysis. In this model, the most important indicator is stakeholder satisfaction.
  • • 
    Integrated Performance Measurement for Small Firms (Laitinen 1996, 2002). The authors define this model as ‘a hybrid accounting system connecting the traditional view and the activity-based costing together in a causal chain’. The model was specifically designed to be used in SMEs. It is based on seven main dimensions of measures, classified as two external dimensions (financial performance and competitiveness) and five internal dimensions (costs, production factors, activities, products and revenues) connected by a causal chain. The internal dimensions are used to monitor the whole production process, and the external dimensions are used to monitor the company's position in its competitive context.

The main dimensions of the models described above are summarized in Table 1. Reading from left to right, first the six generic models are considered from oldest to most recent, followed by the two models designed for SMEs.

A comparison of the eight models (see Table 1) shows clear differences between the first four generic models, i.e. those that do not consider the company's size and are prevalently vertical (Performance Measurement Matrix, Performance Pyramid System, Result and Determinants Framework, Balanced Scorecard), and the last four models, i.e. those characterized by a horizontal structure (IPMS, Performance Prism, Organizational Performance Measurement and Integrated Performance Measurement for Small firms). This observation can be interpreted in two ways: first, that there is a difference between models for big companies and models for SMEs; secondly, that there has been an evolution in the models over time, where there has been a progressive change from bureaucratic/vertical systems to reactive/horizontal systems.

Most of the models analysed are characterized by strategy alignment and favour strategy improvement. However, the presence of these two characteristics decreases moving from left (generic and older models) to right (SMEs and recent models) (see Table 1). Strategy alignment and strategy improvement characterize the models developed in the 1990s (left of Table 1), which were developed in response to the criticism that the traditional models had no links with strategy. For example, the Balanced Scorecard by Kaplan and Norton (1996) was introduced as a model supporting ‘translating strategy into action’ and the Performance Pyramid System by Lynch and Cross (1991) supports the link between top-level strategy and low-level objectives. Over the years, though the strategy alignment dimension is no longer the starting point in the development of models, it is still important. The increasing attention given to PM in SMEs is leading to an adaptation of these two strategy dimensions to the needs of SMEs. In fact, these companies need to include the characteristics in their PMSs, while continuing to focus on the most critical aspect for SMEs, i.e. operational aspects.

The decrease in the attention to strategic alignment seems to be accompanied by an increase in the focus on stakeholders in the more recent models. This does not mean that the importance of strategic alignment is decreasing, but that stakeholder orientation is becoming more critical. In fact, PMS has to ensure that stakeholders needs, strategy and organization remain aligned to maximize the stakeholders’ satisfaction.

All the models analysed are balanced. This dimension is particularly important, and it is explicitly underlined to differentiate these models from more traditional models, which only focus on financial aspects. As mentioned above, the balanced approach is one of the main dimensions of recent models, and it aims to show an integrated snapshot of the whole organization.

The use of process-oriented performance measurement is increasing, particularly in the most recent models (including the models for SMEs). This is probably an answer to the need to integrate the organization and to the increasing importance of business processes to satisfy stakeholder requirements.

Most of the models compared are characterized by breadth. Models focusing on only one function, like the traditional architectures, were not considered in this study. In fact, as mentioned above, models developed in recent years aim to give a holistic view of the organization supported by integrated PMSs. Except for the Performance Measurement Matrix, in which it is ‘so simple to neglect important measures’ (Neely et al. 1995), all the other generic models emphasize breadth and depth to answer the need to have complete and detailed information. These models are often difficult to manage, sometimes not very clear and not responsive to changes in the internal and external contexts. The two models for SMEs place less emphasis on depth and breadth dimensions, probably as a result of the need for an easier approach to performance measurement.

Finally, clarity and simplicity characterize the most recent models (including the models for SMEs), probably in response to criticism of the fact that earlier models are considered to be complex and difficult models.

Conclusions and Future Research

  1. Top of page
  2. Abstract
  3. Introduction
  4. Performance Measurement in SMEs: Diffusion and Characteristics
  5. Factors Influencing Performance Measurement in SMEs
  6. Main Dimensions of PMS Models
  7. A Comparison of PMS Models
  8. Conclusions and Future Research
  9. References

Using a literature review, this study described the characteristics of performance measurement in SMEs and the main factors influencing performance measurement in these companies. Our research showed that, even though the literature highlights the importance of using PMS in SMEs, very few companies carry out performance management. There was found to be a significant gap between theory and practice: the theory underlines the importance of PMS in SMEs in supporting the development of managerial systems, but little research focusing on performance measurement in SMEs is available. The study revealed that there are basically two main obstacles to introducing PM in SMEs: ‘exogenous’ barriers, e.g. the lack of financial and human resources, and ‘endogenous’ barriers, e.g. short-term strategic planning and the perception of PMSs as bureaucratic systems that cause rigidity. Moreover, our analysis of the models developed in the last 20 years highlights the small number of PMS models developed specifically for SMEs. Of the many models that have been developed in the last 20 years, only two focus exclusively on SMEs (Chennell et al. 2000; Laitinen 1996, 2002). Though the comparison carried out reveals an evolution in the models from the mid-1980s to more recent models, which include the two for SMEs, it is not clear whether these innovations are due to the evolution of the generic models or to an attempt to introduce models suited to the needs of SMEs.

The literature claims that there is a need to carry out further research on PMSs in both large companies and SMEs. Many models for large companies have been proposed, but little empirical research has been carried out to assess their effectiveness. In order better to understand performance measurement in general, the following research questions will have to be answered using empirical studies.

  • • 
    Are the dimensions analysed the only main ones that characterize effective generic performance measurement models or do other dimensions need to be considered?
  • • 
    What is the relationship between the different characteristics of PMS models and what factors can influence the role played by these characteristics?

Studying the literature on PMSs for SMEs, we found that very few theoretical and empirical studies have been carried out. Studies focusing on the following research questions would be of interest.

  • • 
    Given the differences between small and large companies underlined in the literature, how do these differences influence performance measurement? Which are the main characteristics of performance measurement models suitable for SMEs? Are the available models suitable for SMEs? Is the development of new models necessary? What are the main differences between performance measurement in SMEs and in large companies? Does the difference between performance measurement in large and small companies focus mainly on the characteristics of the models or the implementation process?
  • • 
    Does size really matter? There is an argument that, because things (such as delays, customer complaints, breakdowns) in SMEs are more visible, people get to know and hear about these without the need for a formalized performance measurement system. How can we assess whether an informal PM already exists in SMEs and, if it does, whether or not it is adequate? This argument is particularly valid if we take the view that a PMS is an information system (Bititci et al. 1997), and the need for a formal information system is not justified because the requisite information is already available (see Ashby's (1956) laws of requisite variety).
  • • 
    Given the three stages that literature defines as characteristic of the implementation of a performance measurement system (design, implement and use: Bourne et al. 2000), what are the key contingency factors that influence the design, implementation and use of PMS in SMEs? What are the relationships between the contingency factors of PMSs and the performance measurement practices in small and medium companies?
  • • 
    The literature provides evidence that SMEs rarely use a PMS as it has been defined in this study. What are the main reasons that prevent the use of PMSs in the decision-making process in SMEs? What are the main forces that could promote and hinder performance measurement in SMEs? What kind of information do entrepreneurs or top managers use in the decision-making processes in SMEs?
  • • 
    This study has shown that models are moving from a vertical approach to a horizontal one. Is this a general trend in PMS approaches, or is it a specific characteristic of PMS models for SMEs?

To answer most of these research questions, additional academic and empirical research are necessary. Performance measurement has been studied using different perspectives that could be summarized in two main research streams; management control systems (MCS) and performance measurement systems (PMS). MCS research studies performance measurement using an accounting management approach; PMS research adopts an operational management point of view. It would be useful to integrate the research on PM in SMEs with an in-depth review of the literature on MCS. Studies based on a mixed approach that overlaps MCS and PMS literature would be necessary to give complete answers to the research questions listed above.

Finally, empirical research must be carried out to find empirical explanations of the theoretical findings and explore issues that are not studied in the literature.

Notes

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  2. Abstract
  3. Introduction
  4. Performance Measurement in SMEs: Diffusion and Characteristics
  5. Factors Influencing Performance Measurement in SMEs
  6. Main Dimensions of PMS Models
  7. A Comparison of PMS Models
  8. Conclusions and Future Research
  9. References
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