میزان کارایی در شرکت های سرمایه گذاری کوچک و متوسط انگلیسی

The Authors

Sérgio D. Sousa, School of Engineering, University of Minho, Braga,

Portugal

Elaine M. Aspinwall, School of Engineering, University of Minho, Braga,

Portugal

A. Guimarães Rodrigues, School of Engineering, University of Minho, Braga,

Portugal

Acknowledgements

The authors are grateful to all the companies that participated in this

survey. This work was partially supported by British Chevening

Scholarships (Grant POR 0100109) and Fundação para a Ciência e a

Tecnologia (Grant SFRH/BD/6939/2001). This paper is an extended version of

the work presented at the First International Conference on Performance

Measures, Benchmarking and Best Practices in New Economy – Business

Excellence 2003, 10-13 June 2003, University of Minho, Portugal.

Abstract

Purpose – To determine the current state of knowledge related to

performance measures and their degree of implementation in small and

medium enterprises (SMEs) in England.

Design/methodology/approach – The paper starts with a literature review

and then goes on to discuss the methodology used. The survey is briefly

presented together with the analysis of the resultant data. General

opinions regarding performance measurement in English SMEs are described,

including the most important measures and the biggest obstacles to the

adoption of new ones. Hypotheses about differences between groups are

tested and discussed.

Findings – This work concludes that there is a gap between the

theory/knowledge of performance measures and the practice in English SMEs.

Training of employees and difficulty in defining new performance measures

were highlighted as the major obstacles to the adoption of new performance

measures.

Research limitations/implications – The low response rate of the survey

precludes the generalisation of the findings.

Practical implications – Innovation and learning measures should be

applied more widely.

Originality/value – This paper is relevant to academics and SME managers

because it supports the existence of a gap between the theory of

performance measurement and its degree of implementation. In addition, it

introduces both theoretical information on performance measurement,

including that based on the balanced scorecard perspectives, and practical

information from a survey conducted in English SMEs.

Article Type: Research paper

Keyword(s): Performance measures; Small to medium-sized enterprises;

Balanced scorecard; Total quality management; England.

Benchmarking: An International Journal

Volume 13 Number 1/2 2006 pp. 120-134

Copyright © Emerald Group Publishing Limited ISSN 1463-5771

Literature review

For the purpose of this research “performance measurement” (Neely et al.,

1995) has been defined as the process of quantifying the efficiency and

effectiveness of action, and “performance measure” as a metric used to

quantify that action. Small and medium enterprises (SMEs) were taken to be

those companies with less than 250 (50 for small ones) workers (Commission

of the European Communities, 2003) and:

no more than 25 per cent of the capital or voting rights were held by

one or more enterprises which were not, themselves, SMEs; and

the annual turnover was less than ∈40 m (∈7 m for small companies) or

the total balance sheet was less than ∈27 m (∈5 m for small companies).

Traditional methods of measuring a company’s performance by financial

indices alone have virtually disappeared from large organisations (Basu,

2001). Non-financial measures are at the heart of describing strategy and

of developing a unique set of performance measures that clearly

communicate strategy (Kaplan and Norton, 1992, 1996), and help in its

execution (Frigo, 2002).

Frigo (2002) reported the existence of a gap between strategy and

performance measures, which failed to support the communication of

strategy within an organisation. André and Saraiva (2000) noted that there

was quite a large gap between available models and current company

practices in Portuguese companies. Hudson et al. (2001) concluded that

although there was a widespread acceptance of the value of strategic

performance measurement amongst the SMEs that they studied, none had taken

steps to redesign or update their current performance measurement systems.

Many excellence models and performance measurement frameworks, like the

EFQM (2001) excellence model, Kanji’s business scorecard (Kanji and Sá,

2002), the performance prism (Neely et al., 2002), and the balanced

scorecard (Kaplan and Norton, 1992), have proposed ways of using the TQM

philosophy. According to Ahmed (2002), the most popular ones to have drawn

the attention of researchers include the balanced scorecard and the EFQM.

Kanji and Sá (2002) state, for example, that the new approach to

performance measurement suggested in the balanced scorecard is consistent

with business excellence and TQM. The balanced scorecard is relevant to

both small and large organisations, however, neither a comprehensive

literature review nor any empirical research exists on implementing the

balanced scorecard in SMEs (Andersen et al., 2001).

The interest, over the last decade, in TQM and quality awards has

highlighted the importance of performance indicators in achieving quality

excellence. Quality measures represent the most positive step taken to

date in broadening the basis of business performance measurement (Bogan

and English, 1994). Models of excellence and improvement initiatives based

on TQM principles reflect the importance of not only complying to

specifications but also to delighting an organisations’ stakeholders.

The relationship between TQM practice and organisational performance is

significant (Samson and Terziovski, 1999), and TQM implementation

correlates with quality performance (Brah et al., 2002), despite some

contradictory cases (Shaffer and Thomson, 1992; Ittner and Larcker, 1997;

Sterman et al., 1997; Wilbur, 2002). Many of the failures of TQM in small

organisations are related to bad implementation strategies and processes

(Hansson and Klefsjo, 2003). Wood and Childe (2003) showed that it was

possible to establish relationships between process improvement actions

and performance requirements.

The adoption of the process approach to quality management systems (QMS)

was one of the most important aspects of the year 2000 revisions of ISO

9001 and ISO 9004 (Hooper, 2001). The new ISO 9001 standard (ISO, 2002)

requires fact-based decisions and continual measurement and improvement of

performance results (Karapetrovic and Willborn, 2002). These changes have

narrowed the gap between the requirements of a QMS and those of the EFQM

excellence model. Both reinforce the need to measure not only the critical

success factors of an organisation but also the satisfaction of its

stakeholders, to allow and assure continuous improvement aligned with

strategy.

Juran and Godfrey (1999) and Campanela (1999) considered quality costs to

be the main driver, when selecting quality improvement projects. This can

also be done with the support of the balanced scorecard, making it a

strategic management tool as suggested by Cobbold and Lawrie (2002).

The EFQM (2003) recognises that organisations, on their journey to

excellence, may show different levels of maturity. The selection of the

best approach to measure the effectiveness of a system will ultimately be

based on the maturity of the quality efforts, the type of organisation or

process, and other TQM tools applied concurrently (Campanela, 1999). Brah

et al. (2002) reported that the size of a company and the extent of its

experience with TQM affect the rigor of implementation and the resulting

level of performance quality. However, the nature of a company

(manufacturing or service) does not seem to have a significant effect on

either aspect.

Hudson et al. (2001) concluded that a discrepancy between theory and

practice was identified in the development processes employed by SMEs,

including a lack of strategic forethought, lack of communication between

managers and the lack of a structured process for development. They also

suggest that there are substantial barriers to strategic PM systems’

development in SMEs. Neely et al. (1995) pointed out that measurement is a

luxury for SMEs – success and failure are obvious. They have concluded

that the cost of measurement is an issue of great concern to managers in

SMEs.

Methodology

The steps followed in this research are similar to those followed by

Saraph et al. (1989) and Yusof and Aspinwall (2000b).

Following a literature review, the subject of performance measurement was

discussed with both academic and non-academic specialists and hypotheses

were formulated. This provided the basis for the construction of a

questionnaire which was pre-tested and revised. The final survey form was

sent by e-mail, to privately owned SMEs in England (both from the service

and industrial sectors).

The data was analysed using the SPSS package v11.0. The reliability and

validity of the questionnaire were also verified. A test for possible bias

from respondents was analysed as suggested by Armstrong and Overton

(1977).

Survey

The questionnaire consisted of three main sections: the company

background, the level of knowledge about performance measures, and the use

of specific performance measures. The first section was intended to

determine general information like number of employees, sector of

activity, number of clients, types of product made, whether a certified

quality system was held, the level of TQM and quality measures adoption

and confirmation that the company was indeed an SME. Each respondent was

also asked to select, from a list of nine, the quality initiatives that

had been adopted in their company. In addition, they were asked to state

their company’s strategic objectives to establish whether or not they

adopt adequate performance measures to track their evolution.

The second section consisted of 22 statements about the performance

measurement system of the company, including aspects such as the company’s

strategy, the selection of performance measures, their implementation and

the results. The respondents were asked to rate their degree of agreement

with each statement according to a five-point Likert scale from 1

“strongly disagree” to 5 “strongly agree”. Zero was added in case of

doubt. This section also contained a question to determine the most

important performance measures used in the company, and one for the

obstacles likely to be encountered if adopting new ones. The actual

criteria that allow companies to win new orders, as suggested by Neely et

al. (1994), were also assessed.

The balanced scorecard (Kaplan and Norton, 1992, 1993) was chosen as the

basis for the third section of the questionnaire mainly because of its

simplicity, general acceptance among practitioners and researchers, and

its close association with strategy (Kaplan and Norton, 1996). The

objective of this section was to investigate the importance and use of

different performance measures. A Likert scale similar to that used in the

second section was used to rate the importance and the use of each

measure.

Questionnaire reliability and validity

The reliability of the questionnaire, which measures internal consistency,

was studied through Cronbach’s α. This method allows for the calculation

of the α coefficient if one variable is removed from the original set,

making it possible to identify the subset that has the highest reliability

coefficient. If all the results are above 0.7, the scales are judged to be

reliable.

In the second section, of the questionnaire, all four groups (components)

were considered reliable after deleting 2 of the 22 statements

(variables). The α coefficients varied between 0.744 and 0.890.

Measures in third section were organised as suggested in the balanced

scorecard, and as can be seen in Table I, all groups of measures were

considered reliable.

Within the customer measures group, delivery was not considered reliable,

and therefore, was removed from further analysis. This is not critical to

this study because other components regarding customer performance

measures are being considered.

Content validity is always subjectively evaluated by the researcher

(Churchil, 1979; Saraph et al., 1989). An instrument has content validity

if it contains a representative collection of items and if sensible

methods of test construction were used (Yusof and Aspinwall, 2000b). It is

strongly believed that the second and third sections of this survey

instrument have content validity as they were well received by the pilot

respondents and by several academics and company managers who assessed

them.

Construct validity was tested for the second and third sections using

principal components analysis. Each measure or variable within a component

should have a significant correlation with variables of the same component

and low correlation with others (Hair et al., 1998). The objective of

construct validity analysis is to verify if all the statements that

translate the concept under study are unifactorial. If this happens the

group is considered homogeneous.

In the second section, only one variable was deleted to assure that all

groups were unifactorial (Table II), i.e. in each group only one component

was extracted, thus all groups were considered homogeneous. The

Kaiser-Meyer-Olkin (KMO) indicator, which is a measure of sampling

adequacy and should not be lower than 0.5, was also verified in all cases.

Variables within each component gave correlations higher than 0.635 in all

cases.

Eight variables out of 61 were deleted in the third section to make each

group unifactorial (Table III). The results indicate that in both sections

each set of variables constitutes a homogeneous group. Thus each one

translates one concept.

Predictive or criterion-related validity was tested as suggested by Owlia

and Aspinwall (1998) and Yusof and Aspinwall (2000a). A greater use of

performance measures should correspond to a greater understanding of the

company’s performance measurement system.

A linear regression analysis was performed on the overall use of

performance measures (from the second section) against the components

identified in the third section. The adjusted R2 value was 68.2 per cent,

suggesting a good fit. To improve this value, a reduction in the number of

factors was considered. Using the stepwise method to select the variables

to be added to, or removed from, the regression model, the adjusted R2

value increased marginally to 68.6 per cent. The overall perception of the

performance measurement system (OPPMS) can be expressed through the

following model: Equation 1 A residual analysis was carried out to

validate the assumptions of normality, constant variance and zero mean.

The model suggests that English SMEs report a higher use of performance

measures if they use financial, quality performance and training of

employees’ measures. The negative relationship associated with the use of

customer performance and innovation measures, suggests that these measures

may not be perceived as performance measures.

The results, overall, show that the instrument reflects predictive

validity.

Results

The questionnaire was sent to 400 companies and 52 were returned

completed. Four of the respondents were not classified as SMEs resulting

in a response rate of 12 per cent. This is low for a postal survey and so

caution must be exercised when generalising conclusions. The returns were

organised into two groups to test possible bias of respondents. No bias

was found and so it can be assumed that non-respondents would have similar

characteristics to the respondents.

Figure 1 shows the breakdown of respondent companies by number of

employees.

The wide range of activities covered by respondent companies is shown in

Figure 2, and includes SMEs from the service sector.

The majority of respondents were certified to ISO standards (Figure 3),

but only 14 per cent had completed the transition to ISO 9001:2000.

Continuous improvement or total quality management can be implemented

following a Plan-Do-Check-Act (PDCA) cycle. Thus it is fundamental in the

planning phase to define activities to improve strategic objectives, which

will then be monitored. Respondents selected profitability (53 per cent)

as the main strategic objective followed by quality (22 per cent) and

flexibility (10 per cent). When asked about the criteria that most helped

their companies to win orders, manufacturing quality came in first

followed by price (Table IV). It appears that despite other important

factors, the quality/price relationship is still of major importance for

English SMEs and cannot be forgotten when initiatives are deployed within

an organisation.

Table V presents the quality initiatives already implemented in the

respondents’ companies. Setting up a quality department can be explained

as a result of ISO standards or simply as a means of implementing the

necessary activities to improve quality and to track their evolution. As

employee involvement to improve quality and establishing measures of

quality progress received 65 and 46 per cent, respectively, it is expected

that approximately half of companies use measures to assess quality

progress. The same data allow us to conclude that statistical process

control, an efficient tool to understand the variation of a process is

used only in 23 per cent of companies.

General opinions about performance measurement were asked on strategy,

selection of measures, implementation and results (Figure 4), as all of

these are important in the process of continuous improvement. An ANOVA

test on the four means showed a significant difference between them at the

5 per cent level. The assumption of homogeneity of variances was verified

through Levene’s test. The results group has the lowest score, meaning

that the consequence of using performance measures is not well understood,

and a balance amongst these groups should result in better performance

measurement systems.

Obstacles to the adoption of new performance measures in SMEs include

computer systems issues, lack of top management commitment and the

existing accounting system (Bourne et al., 2000; Neely et al., 1997). The

respondents considered (Figure 5) training of employees as the most

important obstacle, followed by difficulty in defining new measures, which

could be the result of lack of skills of employees and leadership,

confirming the importance of top management commitment. The cost of the

performance system must always be analysed and is considered of great

concern to SMEs.

According to the literature, companies should adopt a balanced use of the

four groups of measures, as organised in the balanced scorecard. However,

respondents considered some measures more important than others, as shown

in Figure 6.

It is curious to note that on-time delivery is not perceived to be a

relevant criterion to win new orders (Table IV) but it is considered the

most important performance measure. This may be because, if a problem

occurs in the process or with the supplier it will be reflected in this

measure. In-process quality was perceived to be the second most important

measure.

Balanced scorecard

Grouping all the performance measures together, importance was rated by

the respondents as 3.55, on average, and use as 3.18. This implies that

although the respondents considered performance measures important, they

are not used accordingly. After verifying the homogeneity of the

variances, an ANOVA was performed. This resulted in a p (or significance)

value of 6.3 per cent, which, being just larger than 5 per cent, was too

large to be able to conclude a real difference. However, looking at the

four groups separately, financial measures are considered the most

important and are widely used, while innovation and learning measures are

rated less important and are less used (Figure 7).

The four groups of measures analysed in this study were assessed to find

out if there was a gap between the perceived importance and the practice

or use for each group. Tests were performed, using the ANOVA with a 5 per

cent significance level, to see if there were any differences between the

means of:

importance and use of each group of measures;

use for companies from the service and industrial sectors;

use for SMEs; and

use for companies certified according to a quality standard and others.

The group internal business process exhibited a significant difference

between the importance and use of productivity measures, thus there are

measures in this group that should be put to more use, such as “output per

employee or per labour-hour”, “time spent on each stage of product

development”, “time to process an operation”, “number of errors per unit”,

“number of billing errors per unit”, “production volume”, “absenteeism”,

and “injury lost days”. There was insufficient evidence to conclude

differences between the importance and use of quality performance

measures, meaning that if they are considered to be important they are

being used. The same was also true for the financial measures group.

A significant difference was found between the importance and use of both:

Employee training measures (i.e. in the innovation and learning group),

which include measures such as “quality related training provided to

employees”, “percent of employees who have quality as a major

responsibility”, “surveys of employee satisfaction/attitudes” and

“improvement of employee skill/knowledge levels”.

Customer requirement measures (i.e. the customer group), which include

measures such as “ability to adapt or tailor products to customer

needs”; “response time to customer requests for ‘specials’”; and

“accuracy of interpretation of customer requirements”.

Again, there was insufficient evidence to suggest differences in the level

of use of performance measures between industry and service enterprises,

and between SMEs. However, in this sample, medium enterprises make greater

use of internal business process and financial measures while for the

small ones it is the use of innovation and customer measures.

Companies certified to a quality standard and those that were not, did not

show any significant differences between their mean levels of use of

performance measures. Levene’s test for the homogeneity of variances was

violated in customer performance measures. Figure 8 shows this difference

in variance, suggesting that SMEs working to a quality standard are more

likely to adopt customer performance measures. A similar conclusion can be

drawn from other measures but this was the only case that was

statistically significant.

Conclusions

The study investigated the current level of knowledge of performance

measures and their degree of implementation in English SMEs. It identified

differences between some groups of companies and presented the biggest

obstacles to the introduction of new measures.

Results indicate that the SMEs surveyed, recognise the importance of the

performance measurement system but their level of use was significantly

lower. This implies that there is a gap between theory and practice, which

could be considered an improvement opportunity for English SMEs.

Performance measures can be used to influence behaviour and, thus, affect

the implementation of strategy (Neely et al., 1994). The OPPMS as part of

a continuous improvement process, linking strategy to results is not

balanced, meaning that this cycle is not fully understood by SMEs’

managers. Although it is not necessary to use all the measures suggested

in the questionnaire, an alignment between strategy and performance

measures makes them more effective (McAdam and Bailie, 2002).

Training of employees and difficulty defining new performance measures

were highlighted as the most important obstacles to the adoption of new

performance measures. This may reflect a lack of skills by employees and a

difficulty in understanding the process. Only a minority of the respondent

SMEs were applying statistical process control and cultural change

programmes.

The data collected from this survey suggests that there are no significant

differences in the use of performance measures between industry and

service enterprises, and between SMEs. However, this requires further

study, since one limitation of this study was the low response rate, which

precludes a generalisation of these findings.

Overall, financial measures were the most widely used, while innovation

and learning measures were rated less important and were less used. The

most important performance measures were not consistent with criteria to

win new orders.

Based on the data collected, a gap was detected between the importance and

use of some measures suggesting that SMEs should use more productivity,

employee training and customer requirement measures. In particular, the

level of use of innovation and learning measures should increase if SMEs

can resolve the major obstacles, identified in this work, to the adoption

of new measures: training of employees and difficulty defining new

measures.

This research is part of a PhD programme to develop a simple and

easy-to-use framework to allow SMEs to create their own performance

measurement system, aligned with strategy, to allow the achievement of

pre-determined goals.

Equation 1

Figure 1 Number of workers

Figure 2 Sectors of activity

Figure 3 SMEs’ quality assurance system

Figure 4 Overall perception of the performance measurement system

Figure 5 Obstacles to the adoption of new performance measures

Figure 6 Most important performance measures

Figure 7 Importance and use of the balanced scorecard

Figure 8 Use of customer performance measures for SMEs working/not

working according to a quality standard

Table I Reliability of measures in the third section

Table II Principal component analysis of the second section

Table III Principal component analysis of the third section

Table IV Criteria to win new orders

Table V Quality initiatives adopted by English SMEs

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Corresponding author

Sérgio D. Sousa can be contacted at: sds@dps.uminho.pt