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Performance measurement system in SMEs:
diffusion, characteristics and models
Patrizia Garengo
Department of Industrial Engineering and Management
University of Padua, Padua, Italy
Stefano Biazzo
Department of Industrial Engineering and Management
University of Padua, Padua, Italy
Umit S. Bititci
Centre for Strategic Manufacturing
DMEM, University of Strathclyde, Glasgow, UK
Abstract
In recent years, literature has highlighted the SMEs’ need of managerial culture and rational
management systems able to support the management of increasing environment complexity.
Research underlines that performance measurement system (PMS) could play an important
role to support managerial development in these companies. This paper reviews the literature
on performance measurement in SMEs. Diffusion, characteristics and determinants of
performance measurement in SMEs are analysed. Using predefined dimensions, two PMS
models for small and medium companies are compared with generic PMS models. The
comparison underlines an evolution of the more recent models.
Introduction
Since the mid-1980s many scholars and practitioners have begun to study Performance
Measurement System (PMS), defined as a balanced and dynamic system that is able to
support the decision making process by means of gathering, elaboration and analysis of
information (Neely et al., 2002). Following the criticism of traditional models, focused on
financial measures, multidimensional and balanced models were created supporting the
organizational and management development of big companies.
In recent years, literature has highlighted the SMEs’ need of managerial culture and rational
management systems able to support the management of increasing environment complexity
(Marchini, 1995; Bernardi and Biazzo, 2003; Martins and Salerno, 1999). It has often been
said that the critical factors for the SMEs’ success can mostly be found in the attributes of a
“model of a company whose success basically depends on the figure of the entrepreneurowner, who is personally responsible for managing the activities of the company” (Cagliano
and Spina, 2000). This model is characterized by flexibility and an ability to react quickly and
adapt to the competitive environment; organizational processes which are not very structured
or “engineered”; significant concentration of decision-making processes in the figure of the
entrepreneur-owner; a focus on technical aspects and production; the existence of specialist
and tacit knowledge which is essentially technological and that evolves through learning
processes based on learning by doing (Jennings and Beaver, 1997; Marchini, 1995).
This paper aims to investigate the relationship between PMS and SMEs. In the first two
sections a brief literature review of performance measurement in SMEs is given; in particular,
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in the first section diffusion and specific characteristics of performance measurement in SMEs
are summarized, and in the second one several factors influencing the performance
measurement in SMEs are described. The third section summarizes the principal dimensions
characterizing PMS models developed after the mid-1980s. Finally, using these dimensions,
the principal models, developed in the last 15 years, are compared and similarities and
differences are highlighted with an explicit reference to the firm’s size.
1. Performance measurement in small and medium enterprises: diffusion and
characteristics
Empirical and conceptual research on PMS in SMEs is actually poor. The most active
countries in studying PMS for SMEs are Australia (Barnes et al., 1998), where a specific
organization supporting the development of PMS for SMEs (called Commenwealth Scientific
and Industrial Research Organization - CSIRO), was created, Finland (Laitinen, 2002;
Rantanen and Holtari, 2000; Tenhunen et al., 2001), United Kingdom (Bhimani, 1994; Bititci
et al. 2000; Collis and Jarvis, 2002; Neely and Mills, 1993; Jarvis et al. 2000) and Denmark
(Hvolby and Thorstenson, 2000).
Although an explicit comparison is not available in the literature, differences in PMS due to
the context have not been found when analysing the studies mentioned above. Common
characteristics, regarding performance measurement in SMEs, are identified and they are
discussed in the following part of this section.
Firstly, it is difficult to involve SMEs in performance measurement projects. Moreover the
companies taking part in these projects rarely continue to the last phase. This is due to the
time shortage used for not current operational activity and to the poor involvement of
entrepreneurs or top managers (Tenhunen et al., 2001). A substantial difference characterizes
the companies with a quality culture: quality management experiences highlight the
inadequacy of current managerial practices and they have a positive impact on the
development of managerial systems (Barnes et al., 1998).
Secondly, there are shortages in performance measurement models and frameworks
developed for small and medium enterprises and these companies often implement only some
parts of a general model or an altered one. Unfortunately, these modifications are not planned;
they are often made by elimination of some dimensions, without a whole analysis of the
characteristics of both the model and the company. Consequently, the approach adopted is
incomplete and not aligned with SMEs needs (Tenhunen et al., 2001; CIMA, 1993).
Moreover, some researchers consider the complete application of generic models inadequate
for SMEs needs. These firms have particular characteristics “the small enterprise is different
from the big company; its needs cannot be seen to turn the binoculars upside down making
small all that are implemented in the big” (Marchini, 1995). Some authors assessing the
implementation of Balanced Scorecard in SMEs conclude that this model is not suitable for
the SMEs needs (Hvolby and Thorstenson, 2000; McAdam, 2000).
Thirdly, performance measurement implemented in SMEs rarely has a “holistic approach”.
The studies of Barnes et al. (1998) and Rantanen and Holtari (2000) highlight the fact that
SMEs do not implement integrated PMS, i.e. systems aiming to support the integration
process between company functions, and that there is also poor knowledge of integrated
models. The small companies are focused on operational and financial performance and
balanced models are seldom used; innovation, human resources, work atmosphere, R&D and
training are rarely measured (Addy et al., 1994; Hudson et al. 1999; Hvolby and Thorstenson,
2000; Chennell et al., 2000; Tenhunen et al., 2001). The study of Antonelli and Parbonetti
(2002) highlights that the need of balanced models proposed by Kaplan and Norton (1996) are
not yet perceived by SMEs, though sometimes SMEs use indicators of customer satisfaction,
internal processes and training.
Fourthly, the SMEs’ approach to performance measurement is informal, not planned and not
based on a predefined model; performance measurement is introduced to solve specific
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problems and the PMS grows spontaneously rather than as a result of planning and
anticipation (Barnes et al. 1998). Consequently, a poor alignment between strategy and
measures characterizes the measure of performance in SMEs (Addy et al. 1994; Chennell et
al. 2000; CIMA, 1993; Hudson et al. 1999). With the exception of SMEs with quality
management experiences, usually in SMEs planning is absent or limited to the operation level
even if the performance is measured. Using this approach SMEs lose the opportunity to use
PMS implementation to introduce strategic planning. Moreover, usually the focus of the
performance measured is on the past; the aim is to gather information not for forecast and
planning process, but for supporting control activities.
Fifthly, SMEs have limited resources for data analysis; gathering and analysis of processes
are carried out without care and an unformalized approach increases the ambiguity of the
measurement objectives. The same happens with the information exposure: SMEs usually
present the information processed in tabular form without a formalized format (Antonelli and
Parbonetti, 2002; Barnes et al., 1998); only SMEs with quality management experience start
to develop graphical presentation of the information. The case is the same for performance
measurement review, necessary for the alignment of the system with changes in internal and
external context. The companies with quality culture place more attention on information
gathering, analysis and exposure and indicators review, probably because quality programs
support the improvement in management information (Barnes et al., 1998).
Despite the recognised importance of performance measurement in SMEs, there is an in depth
gap between theory - that highlights the importance of PMS in supporting the development of
managerial systems - and practice, where models and tools aligned with the SMEs’
characteristics are almost absent. In the next section the main factors influencing performance
measurement in SMEs are summarized.
2. Factors influencing performance measurement in SMEs
Many researchers state that PMS implementation and use are influenced by the firm’s size.
Literature underlines main elements that influence performance measurement in SMEs; these
elements are briefly described in the following paragraphs.
 Lack in human resources. SMEs have shortages in human resources. All staff is involved
in current activities to manage daily work, and time for additional activities, like the
implementation of PMS, is not available (Barnes et al., 1998; Hudson, 2000; Hvolby and
Thorstenson, 2000; McAdam, 2000; Noci, 1995; Tenhunen et al., 2001). Very often
employees occupy different positions at the same time; organizations are flat; the
entrepreneur is in charge of both operational and managerial functions, but he usually
neglects managerial activities (Marchini, 1995);
 Limited capital resources. The impact of resources necessary to implement PMS is
proportionally more onerous in SMEs than in big companies (Barnes et al., 1998; Burns
and Dewhurst, 1996; Hudson et al., 2000; Hvolby and Thorstenson, 2000; Ghobadian and
Gallear, 1997; Neely and Mills, 1993; Noci, 1995). Moreover, the absence of cheap
software platforms focusing on SMEs needs, further obstructs the introduction of
performance measures in these companies (Bititci et al., 2002);
 Reactive mentality. SMEs are characterized by poor strategic planning and low formalized
decision-making processes. The lack of explicit strategies and methodologies supporting
the control process promotes both a short term orientation and a reactive management
approach (Marchini, 1995, Brouthers et al., 1998);
 Tacit knowledge and little attention to the formalization of processes. One of the main
barriers to the organizational development in SMEs is the lack in managerial system and
in formalized management of the processes. In the small and medium enterprises
knowledge is mainly tacit and context specific, and consequently the information
necessary for the implementation and use of PMS is difficult to gather.
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
Wrong perception of performance measurement. Bourne (2001) underlines that one of the
main drivers of the implementation and use of performance measurement is the right
perception of the benefits; nevertheless, very often, SMEs do not understand the potential
advantages that could derive from the implementation of PMS; on the contrary, 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).
 Technical and operational orientation. Technical excellence in products and operational
processes is often perceived as the only key critical factor.
The factors mentioned above underline some differences between SMEs and big companies
and the need of a different approach to PMS; moreover, these factors could be useful in the
study of the dimensions of PMS in SMEs.
The limited resources of SMEs require a specific and efficient approach and models, which
are easy to implement. Short and long terms advantage have to be evident to keep enthusiasm
and commitment of the employees’ involved (Hudson et al., 1999). PMS for SMEs has to
permit a dynamic and flexible approach but, at the same time, support the structured approach
and activity planning (Barnes et al., 1998; Hudson and Smith, 2000; Hudson et al., 2001).
The PMS design has to be aligned with strategy, but with a strong focus on operational
aspects, that traditionally are critical for the SMEs success. And finally performance
measurement process has to be based on a management information system aligned with the
limited financial and human resources of the small and medium enterprises.
3. Main dimensions of PMS models
In the following, the main dimensions that characterize the models introduced after the mid1980s are analysed. Each dimension is first described in general and than specific reference
to SMEs is presented.
Strategy alignment
It has been recognised for many years that performance measurement can influence behaviour
and consequently affect successful strategy implementation (Skinner, 1971).
Design and implementation of a performance measurement system have to follow business
strategy to link strategy to the objective of functions, groups of people, individuals (Bierbusse
and Siesfeld, 1997; Kaplan and Norton 1996; Nanni et al., 1992; Schneiderman, 1999) and to
operational aspects (Greatbancks and Boaden, 1998; Lynch and Cross, 1991; Meekings, 1995;
Neely et al., 2002).
Lack of alignment between performance measurement and business strategy was one of the
main obstacles to the achievement of 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); consequently, the models proposed after the mid-1980s, such as
Balanced Scorecard (Kaplan and Norton, 1996, 2001) and Performance Pyramid System
(Lynch and Cross, 1991), stress the alignment between strategy and PMS.
The alignment between strategy and performance measurement is particularly important in
SMEs. These companies lack formalized strategy, and PMS implementation could promote
the definition or formalization of business strategy. The first step in PMS design and
implementation in SMEs should be strategy definition (Cook and Wolverton, 1995; Hudson et
al., 2000; Tenhunen et al., 2001), but also a clear relationship with operational activities has
to be made explicit to avoid losing the focus on the operational aspects (CIMA, 1993)
Strategy improvement
The mutual relationship between PMS and business strategy is underlined in the literature. As
stressed above, performance measurement system should derive from the strategy. Moreover,
some authors explicitly state that PMS should also support definition and redefinition of
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business strategy to support continuous improvement (Bititci, 1997; Bourne et al., 2000;
Tonchia, 2001). Neely et al. (2002) write that performance measures are designed to help
people track whether they are moving in the intended direction. They help managers establish
whether they are on track to reach the planned destination. 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”.
Performance measurement system is both a guide in strategy implementation and in finding
the method of improving it continuously. Environment changes require changes in strategy
and in defined objectives. To achieve that, availability of knowledge is necessary (Feurer and
Chaharbaghi, 1995) and mechanisms to gather information are required. A performance
measurement system can allow to quantify effectiveness and efficiency of activities and
support the assessment of achievement of business strategy (Neely et al, 1995, Suwignjo,
2000); moreover, PMS can provide information on the effectiveness of actions before their
full implementation and it can support changes in defined objectives (Feurer and
Chaharbaghi, 1995).
Stakeholder approach
In the last 20 years the attention to stakeholders has increased drastically. Freeman (1984; p.
46) gave the first definition of stakeholders as the groups of people who can influence or who
are influenced by the achievement of the company’s objectives. Other definitions and studies
were introduced afterwards. Atkinson et al. (1997) underline that each organization should
know stakeholders’ expectations well and strive to achieve their objectives. 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 each group of stakeholders has different needs, wishes and level of
satisfaction, and each company has to monitor these aspects. To achieve this, in recent years
some authors started to introduce the stakeholder in performance measurement studies
(Atkinson et al, 1997; Bititci, 1994; Kanji, 2002; Neely et al., 2002; Sharman, 1995). Some of
the more recent performance measurement models propose stakeholders’ needs rather than
business strategy as the starting point in performance measurement system design.
Performance Prism (Neely et al., 2000) is probably the most popular model based on
stakeholder needs. However, other models have been introduced for both big companies and
SMEs (Bititci et al., 1997; Chennell et al, 2000).
The stakeholder approach has also begun to adopt in PMS studies focusing on SMEs.
However, literature underlines that only the SMEs taking part in quality awards gather
information about stakeholder satisfaction (Barnes et al., 1998). A simple approach to
assessing stakeholder satisfaction is required. Vinten (2000) writes that the small business,
fighting for survival, cannot be expected to take into consideration the range of stakeholders
appropriate to a multi-national company. Thomlison’s (1992) specification about primary and
secondary stakeholder could be applied to SMEs.
Balanced approach
The most relevant criticism of the traditional PMS was its focus on financial measure;
consequently, all the models developed after the mid-1980s are more balanced. However,
scholars use different approaches to balance: Keegan et al. (1989) write about the balance
between internal and external measures; Lynch and Cross (1991) propose to balance measures
related to all the different organizational levels; Fitzgerald et al. (1991) pay attention to the
results and determinants relationship; Kaplan and Norton (1992) propose to balance four
different perspectives based on both the measures’ nature (financial and non-financial
measures) and the measures’ object (internal and external measures).
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In this study balanced models (also called multidimensional) are defined as the models
adopting different perspectives of analysis and supporting a coordinated management of
these. The innovations introduced in information technology systems, in recent years,
promote the gathering and elaboration of large amount of data with low cost. These
innovations are potentially able to support the implementation and use of balanced
performance measurement systems. However, the use of innovative software has often
brought an excessive use of measures, introduced without a planned design, and the
performance measurement generated is difficult to use and understand (Neely et al., 2000).
The balanced approach issue is particular important in SMEs. These companies are
characterized by focus on operational and financial aspects and they often measure only the
performance of a single aspect (Hvolby and Thorstenson, 2000; Bhimani, 1994). As
emphasised above, SMEs have specific characteristics; operation aspects are very important
but they need to increase their strategic managerial approach, and to do that the balanced PMS
could be an important support tool (Tenhunen et al., 2001).
Dynamic approach
A performance measurement system should include review systems of measures and
objectives ensuring both a quick alignment between PMS and changes in internal and external
context, and a systematic assessment of a company’s strategy supporting continuous
improvement. Many scholars 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 et
al., 1997, Ghalayini and Noble, 1996; Lingle and Schiemann, 1996; Lynch and Cross 1991;
Neely et al., 2000; Maskel, 1989; McMann and Nanni, 1994, Wisner and Fawcett, 1991). In
this research, using the study of Bititci et al. (2000), dynamic PMS is defined as a system with
the following characteristics:
 An external and internal monitoring system. A system should continuously monitor
developments and changes in the external and internal environment.
 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).
Despite the importance of dynamic PMS underlined in the literature, most companies use
static models. This is mostly due to the lack of models able to distinguish measures useful for
the control aspect from measures supporting improvement and a causal relationship between
strategic objectives, process and activity.
In particular, performance measurement in SMEs, despite the importance of flexibility and
quick reaction to change of the competitive context, rarely have external and internal
monitoring systems and review systems and an internal deployment system. The lack of
models, of the cultural approach and of a flexible platform developed for the needs of SMEs
creates a barrier to the periodical review of performance measurement used.
Process oriented
Process management is becoming a part of the language and the actions of many
organizations. It is defined as an approach based on organization as a whole of interconnected
activities, that aims to map improve and align organizational processes (Benner and Tushman,
2003). Its importance is underlined by both quality awards and new edition of ISO 9001:2000
(Garvin, 1998; Ittner and Larcker, 1997), that recognize process management as particularly
useful to meet stakeholder expectation and to promote integration.
Different studies provide evidence that performance of business processes has to be
monitored because they have a direct impact on stakeholder satisfaction. However, there are
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many operational difficulties in introducing the process management approach in companies.
Some organizations start to reengineer their processes moving from vertical function
structures to horizontal structures focused on internal business process, but most of them are
still organized by functional units (Beretta, 2002). A study by Bititci et al. (1999) shows that
few companies define and manage business processes. Consequently, PMS based on process
approach is difficult to implement. Turner and Bititci (1999) highlight that failure in
delivering consistent output to the stakeholders is caused by lacking in coordination between
functions. Often objectives of different functions conflict because of measurement and reward
system. Measurement and reward systems operate functionally in vertical direction and they
contrast with the objectives of business processes operating across functional boundaries.
Organizations need to revaluate their performance measurement systems and to replace
functional performance measures with process related measures. The adoption of processoriented performance measurement can facilitate business process modeling, show the
inadequacy of functional organizations (Beretta, 2002) and promote the use of performance
measurement as a an important support of the decision making process. Process performance
is one of the main factors affecting the reliability of business processes, defined as “a process
that will continue to provide a high level of stakeholder satisfaction over time” (Turner and
Bititci, 1999). These authors write that the application of reliability engineering, process
thinking and active monitoring concepts to business processes support the systematic
identification of key performance measures to actively monitor business throughout the
company. They also propose an active monitoring technique for improving and maintaining
the reliability of business processes.
The increased importance of process management is influencing PMS frameworks (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 PMS design
(Bititci, 1997).
Increasing attention to process management involves also SMEs. PMS based on business
processes can provide information that allows companies to be more proactive in meeting
stakeholders’ requirements. Both PMS models for SMEs are based on the business processes.
Depth and breadth
The PMS’ depth, i.e. the level to which measures are applied to detailed indicators, could
support the definition of aims and it allows focus on operational implementation. Tenhunen et
al. (2001) write that an in depth framework could support SMEs to concentrate on few
objectives and develop focused PMS in a short time and using limited resources. However,
for other scholars it is necessary first of all to design a breadth framework representing the
whole organization, and only after that it is possible to focus on a specific object and develop
an in depth PMS.
The PMS’ breadth indicates the number of functions (or macro-processes) involved in
performance measurement. A broad model includes all the company’s functions (or macroprocesses) and supports a “holistic” assessment of the firm’s performance. The breadth of a
PMS supports the integration of the systems; Lynch and Cross (1991) write “you can’t
improve only a company’s performance, because all are connected, as an elastic. Take an area
for improve its performance as lead times, and pull. Something moves, but soon something
stops ….. something that pulls from another performance area”. This is aligned with what
Neely et al. (2000) write: “a PMS should give a synthetic and general description of company
performance”, it has to “provide comprehensiveness”; moreover for Lynch and Cross (1991)
the performance measurement has to create a base for the management system, so the
company can not consider only 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, p. 107). Models, like the Balanced Scorecard of Kaplan
and Norton and the Performance Pyramid of Lynch and Cross, support in depth measurement
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process, but these models are difficult to implement in SMEs. Dickinson et al. (1998) and
McAdam (2000) claim that these companies have to use breadth and not in depth PMS. By
doing this SMEs should achieved a simple framework and an integrated approach to corporate
governance.
Causal relationship
Many scholars write about the causal relationship between results and their determinants in
performance measurement; Lynch and Cross (1991) develop a tool to find out the causality
link; Fitzgerld et al. (1991) call their model “Results and determinants” to highlight that the
results have to read as function of specific determinants. Kaplan and Norton (1996) underline
that the evidence of causal relationship between performance indicators and objectives
supports strategy review and learning. Owing to performance measurement support planning
and control (Ballantine and Brignall, 1994), PMS should measure not only the results but also
their determinants and to quantify the “causal relationship” between them, to support the
monitoring of past actions and the process improvement (Bititci el al., 2000; Neely et al.,
2000). However, causal relationships between determinants and results are still very complex
to analyze and further research is necessary on this issue (Neely, 1999). Performance is
affected by a large number of multidimensional factors characterized by a dynamic behavior.
In PMS many factors are involved and quantifying their effects on performance is very
difficult to do in practice. Suwignjo et al. (2000) analyse different techniques like cognitive
maps, cause and effect diagrams, tree diagrams and analytic hierarchy processes. Using these
techniques, the authors develop a specific model, called Quantitative Models for Performance
Measurement Systems (QMPMS), supporting the identification of factors affecting
performance and their relationships. Effects of the factors on performance are expressed in
quantitative terms. The model is easy to understand and implement, however some difficulties
in defining the relationships between factors and their determinants exactly still exist, for
example the need to use subjective measures.
The relationship between results and determinants support a periodic feedback on measures
used, on performance results (Hynes, 1998) and on incremental changes (Appiah-Adu and
Singh, 1998). This is very useful for the improvement processes in SMEs, where incremental
changes prevail rather than radical changes.
Clearness and simplicity
The clarity and simplicity of a PMS are of crucial importance for its successful
implementation and use. Many scholars study PMS’ clearness and simplicity: some authors
develop models that they define clear and simple (Lynch and Cross 1991; Neely et al., 2002;
Laitinen, 1996, 2002), others describe the main characteristics of PMS despite clearness and
simplicity (Eccles, 1991; Globerson, 1985; Schneiderman, 1999; Neely et al. 1996; 2000;
Maskel, 1989; Bierbusse and Siesfeld, 1997).
However, clearness and simplicity are not simple to assess, because these characteristics have
a subjective component. The literature review highlights the following components as
characterizing clear and simple PMS.
 Clear definition and communication of the fixed objectives, that the company aims to
achieve using the adopted measures (Globerson, 1985; Maskel, 1989; Neely et al.
1996, 2000).
 Essentiality of the measures. One of the main problems in PMS is that there is too
much data and often the data are not useful but the easy to gather (Neely, 1998).
Bierbusse and Siesfeld (1997) write that the excess of data makes worst the whole
systems work; for Dickinson et al. (1998) the set of measures is enough when all the
stakeholder needs are assessed without uselessness indicator. Ewing and Lundahal
(1996) fix at 25 the limit of strategic indicators controlled by each manager, and they
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believe that if this limit is exceeded, the PMS is difficult to manage and causes
demotivation for the users.
 Clear definition of measures. The measures have to be defined using objective criteria
that make clear the meaning of each one (Schneiderman, 1999; Globerson, 1985;
Neely et al. 2000).
 Clear definition of the gathering and elaborating methodology. The aim is to avoid
elements that could damage data gathered (Globerson, 1985; Neely et al., 2000). As
Neely et al. (2002) write, during the definition and implementation process of a PMS
there are many factors that could influence the quality of the data, for example the
place and the time have a big influence on responses. A clear definition of these
elements supports the quality of the data.
 Use of relative instead of absolute measures because the relative data are easier to
read and understand than the absolute (Globerson, 1985; Neely et al., 2002).
 Definition of how the processed information has to be shown (Globerson, 1985; Neely
et al., 2002).
According to the literature SMEs, need a simple PMS that should give focused, clear and
useful information to the management (Laitinen, 1996; 2002; Hussein et al., 1998). In fact,
SMEs lack resources to implement complex frameworks and they do not need these complex
frameworks (Cook and Wolverton, 1995; Laitinen, 1996; Hussein et al., 1998; Hvolby and
Thorstenson, 2000; McAdam, 2000; Tenhunen et al., 2001; Yeb-Yun, 1999). The number of
measures used should be reduced; the specific requirement of each SME and the PMS
usability need particular attention (Tenhunen et al., 2001; Barnes et al., 1998). Hvolby and
Thorstenson (2000), define single measures (e.g. lead time) able to summarize the
performance of the organization as a whole. Nonetheless, the simplicity and easy of use
should not compromise the completeness of the system, as could happen using of single
measure or as the result of PMS models developed for big companies simplified by reducing
the measures’ numbers, but without keeping the holistic vision given by the original
architecture (McAdam, 2000)
4. A comparison between models
In this section eight PMS models, developed by the mid-1980s, are compared. The traditional
models, which Bourne et al. (2000) defined as models based on accounting systems and
financial information, are not included in this study because many researches stress the
inadequacy of these models for current managerial needs of the companies.
The models are compared using the eight dimensions mentioned above (strategic alignment,
strategy improvement, stakeholder approach, balanced approach, process oriented, depth,
breadth, dynamic approach, causal relationship, clearness and simplicity). Moreover, to
complete this classification with a further comparison, these models are compared according
to the three typologies defined by De Toni and Tonchia (2001) (vertical, balanced and
horizontal)1; this last comparison is useful to summarize the comparison based on the eight
dimensions mentioned above (see Table 1)
1
De Toni and Tonchia (2001) classified the main PMS models found in the literature in five typologies:
 Models that are strictly hierarchical (or strictly vertical), characterised by cost and non-cost performances on
different levels of aggregation, till they ultimately become economic-financial
 Models that are balanced scorecard or tableaux de board, 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
 Models that can be called ``frustum’’, where there is a synthesis of low-level measures into more aggregated
indicators, but without the scope of translating non-cost performance into financial performance; typically the
economic-financial measures are kept separate from the aggregate ones of customer satisfaction
 Models which distinguish between internal and external performances; the latter are the only ones directly
perceived by customers
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Six of the most popular generic models, i.e. the models developed without reference to
company size, developed in the last 15 years, are compared with the two PMS models created
for SMEs.
The main dimensions of the models analysed are summarized in Table 1. Reading from left to
right, first all the generic models are considered in order of date, then two models designed
for SMEs are presented.

Models which are related to the value chain; these models, in respect to the preceding ones, also consider the
internal relationship of customer/ supplier
Then the authors classified the above models using three different architectonic connotations: vertical, balanced (or a
tableau), horizontal (or by process). The vertical structures include hierarchical and frustum models. The balanced structures
include balanced scorecard, Frastrum models and Models which distinguish between internal and external performances. The
horizontal structures include models which distinguish between internal and external performances and models which are
related to the value chain.
10
Table 1 Comparison of some PMS models
Performance
measurement
matrix
(Keegan et al.,
1989)
Strategic
alignment
Strategy
improvement
Stakeholder
approach
Balanced
approach
Dynamic
approach
Process
oriented
Depth


Performance
pyramid
system
(Lynch and
Cross, 1991)
Result and
determinants
framework
(Fitzgerald et
al., 1991,
Fitzgerald and
Moon, 1996)
Balanced
scorecard
(Kaplan and
Norton
1992, 1996)






























Integrated
Performance
Measurement
System
(Bititci et al.,
1997)
Performance
Prism
(Neely et al.,
2002)
Organizational
Performance
Measurement
(Chennell et al.,
2000)
Integrated
performance
measurement for
small firms
(Laitinen, 1996,
2002)









Breadth






Causal
relationship
Easy and
clear
Vertical
Balanced
Horizontal


























Definitions of the dimensions used in the comparison
Stakeholder approach: stakeholders’ requirements are one of the main starting points of the performance measures system design
Strategic alignment: strategy is the key dimension of the framework. Performance measures system has to ensure the adoption of
measures aligned with strategy
Strategy improvement: performance measurement supports improvement of defined objective and strategy
Balanced approach: different perspectives are used. These different perspectives are based on the type of measures (financial and nonfinancial) or/and the measures’ objectives (internal and external measures),
Dynamic approach: review systems of measures and objective are included. These review systems aim to ensure a quick alignment
between PMS and changes in internal and external context.
Process oriented: organization is not seen as a hierarchical structure but as an whole of coordinated processes which create a system
Depth: measures are disaggregated in detailed indicators (single operative activities involved in processes are measured)
Breadth: the whole organization is object of performance measurement. A broad number of functions (or macro-processes) are
included.
Causal relationship: results and their determinants have to be measured to quantify the “causal relationship” between them, to support
the control of past actions and the process improvement
Easy and clear: clear definition and communication of the fixed objects, measures, gathering and processing methodology and
information are shown
(Legend:  fully present;  partially present)
Comparing the eight models (see Table 1), a clear difference is established 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 characterized by a
horizontal structure (IPMS, Performance Prism, Organizational Performance Measurement
and Integrated Performance Measurement for Small firms). This difference supports a double
11
interpretation; on the one hand, a differentiation between models for big companies and
models for SMEs is highlighted, on the other hand, a chronological evolution of the models
can be seen. All the most recent frameworks, including those for SMEs (the right part of
Table 1), have a horizontal structure. That could be a reflection of the evolution in
management practices, where there is progressive change from bureaucratic/vertical systems
to reactive/horizontal systems.
Most of the analysed models are characterized by strategic alignment and they are
used to introduce strategy improvement. However, the presence of these dimensions decreases
moving from left (generic and older models) to right (SMEs and recent models) (see Table 1).
Strategic alignment and strategy improvement characterize the models developed in the 1990s
(left of Table 1). These models were introduced after the criticism of the traditional models
blamed for the lack of links with strategy. Strategic alignment is the heart of many models
analysed here; the Balanced Scorecard of Kaplan and Norton (1996) is introduced as a model
supporting “translation strategy in action”, the Performance Pyramid System of Lynch and
Cross (1991) supports the link between top level strategy and low level objectives. During the
years the strategic alignment dimension, although still important, has reduced its presence
also after some specifications about the role in PMS design (Neely et al., 2002, p. 169).
Moreover the increasing attention to SMEs in PMS could have supported an adaptation of
these dimensions to the SMEs needs. In fact, these companies have to introduce the strategic
dimension on PMS, but focus in operational aspects is still the critical characteristic of
performance measurement in small and medium companies.
Despite the decrease presence of strategic alignment the comparison highlights an increase of
the stakeholder approach in the more recent models; that is probably due to the increasing
importance of stakeholders’ satisfaction and its introduction in performance measurement
system previously described.
All the analysed models are balanced. This dimension is particularly important and it
is explicitly underlined to differentiate these models from the traditional models that are
focused only on financial aspects. As mentioned above, the balanced approach is one of the
main dimensions of recent models and it aims to show an integrate snapshot of the whole
organization.
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 of
integration of the organization and 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, are not included 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 PMS. Except the Performance Measurement Matrix, “so
simple to neglect important measures” (Neely et al., 1995), all the other generic models
emphasise breadth and depth to answer to the needs of completed and detailed information.
These models are often complex to manage, sometimes not very clear and not responsible to
changes in the internal and external context. 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.
Clarity and simplicity characterize the most recent models (including the models for
SMEs), probably in response to criticism of the complex and difficult models that were
introduced in the past.
5. Conclusion
Using literature review, this study describes the characteristics of performance measurement
in SMEs and the main factors influencing performance measurement in these companies. The
research evidence is that, in spite of the importance recognized in the literature, there is a low
12
level of use of PMS in SMEs. An in-depth gap between theory and practice is highlighted;
theory underlines the importance of PMS in SMEs supporting the development of managerial
system, but little research focusing on these companies is available. Studying the introduction
of PMS in SMEs, two main of obstacles are disclosed; firstly “exogenous” barriers, e.g. the
lack in financial and human resources, and secondly “endogenous” barriers, e.g. short-term
strategic planning and the perception of PMS as bureaucratic systems that cause rigidity.
Moreover, our analysis of the models developed in the last 20 years highlights the shortage of
PMS models for SMEs. Many models have been introduced in the last 20 years, but only two
are focused on SMEs (Chennell et al., 2000; Laitinen, 1996, 2002).
Our comparison emphasizes an evolution of the models developed in recent years, where the
SMEs’ models are included. However, it is not clear if these innovations are due to the
evolution of the generic models or to the attempt to introduce models suited to the SMEs’
needs.
The literature claims the need for further research in PMS, both for big companies and SMEs.
Many models for big companies are proposed, but little empirical research is used to assess
their effectiveness. Using empirical studies, the following research questions should be
answered for a better understanding of performance measurement in general.
 Are the dimensions previously analysed the main dimensions characterising generic
effective performance measurement models?
 What is the relationship between the different dimensions of PMS models and what
factors can influence the role played by these dimensions?
Studying the literature on PMS for SMEs, we found that both theoretical and empirical
studies are little developed. Studies focusing on the following research questions would be of
interest.
 Given the differences between small and big companies underlined by the literature,
how should these differences impact on performance measurement? Which are the
main dimensions of performance measurement models suitable for SMEs? Are the
available models suitable for SMEs? Is the development of a new model required?
What are the main differences between performance measurement in SMEs and in big
companies? Is it focused on the model or on the implementation process?
 Literature provides evidence that SMEs rarely use PMS as defined in this study. What
are the main reasons that prevent the use of PMS in the decision making process in
SMEs? Do entrepreneurs or top managers use performance measurement in the
decision-making processes? Which are the main performance measures used? What
are the main forces that would promote performance measurement in SMEs?
 This study has shown that models are moving from the vertical approach to the
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 the research questions listed above an interdisciplinary approach and
empirical studies are required. An in-depth review of literature on MCS, defined as a broad
system that includes management accounting systems and other controls system such as
personal controls (Chenhall, 2003), and SMEs could be useful to answer the questions listed
above and for a better understanding of the contingency factors that influence performance
measurement in SMEs.
13
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