THE USE OF PERFORMANCE MEASURES IN SMALL TO MEDIUM
ENTERPRISES (SMEs) – AN EXPLORATORY STUDY
Brendan Phillips, Thomas Tan Tsu Wee and Tekle Shanka
Curtin Business School
Keywords: SMEs, performance measures, strategic marketing
Abstract
The need for organizations to align their performance measurement (PM) systems with their
long term goals is well established in the literature (Kaplan and Norton, 1996; Wheelen and
Hunger, 2002). As a result, many PM frameworks have emerged, one of which being that
proposed by Kaplan and Norton (1992), emphasising financial and non-financial measures
that are aligned with strategic objectives (Bremser and White, 2000; Hudson et al. 2001).
Hudson et al. (2001) argue that measurement systems such as the balanced scorecard have
been designed primarily for medium to large corporations and argue that the context of
SME’s requires a different approach. In line with this assertion, this exploratory study
explores how financial and non-financial measures have been used in SMEs in Australia and
South-East Asia. Exploratory factor analysis was performed and two factors were revealed
from the 21 measurement items explaining 59% of the variance. The first factor (alpha 0.89)
represents a customer service dimension of performance. The second factor (alpha 0.67)
represents the financial dimension of performance. Significant differences were identified on
the customer service dimension based on location of the organization and size of the
organization. Results are discussed and directions for future research are proposed.
Introduction
The need for organizations to align their performance measurement (PM) systems with their
long term goals is well established (Kaplan and Norton, 1996; Wheelen and Hunger, 2002).
Many PM frameworks have emerged, the most popular being the balanced scorecard (Kaplan
and Norton, 1992) which emphasizes financial and non-financial measures that are aligned
with strategic objectives (Bremser and White, 2000; Hudson et al. 2001). Hudson et al. (2001)
argue that measurement systems such as the balanced scorecard have been designed primarily
for medium to large corporations and argue that the context of SME’s requires a different
approach. Despite the apparent simplicity of this management principle, it has proven to be an
ongoing challenge to translate effectively into practice. Performance measurements link
business strategy to operational performance thereby identifying critical factors of success in
the long run (Kaplan and Norton, 1996). Wheelen and Hunger (2002) describe three types of
performance measures necessary for effective strategic management namely, resource input
(e.g. employee skills and organisational commitment), behavioural (e.g. operational process
and compliance to procedures) and outcome measures (e.g. sales, profit, customer
satisfaction, customer loyalty).
Since the introduction of the BSC and other similar integrative measurement systems, there
has been considerable attention paid to their adaptation to large corporations and government
organizations around the world (Wheelen and Hunger, 2002; Ahn, 2001; Malmi, 2001; Butler,
Letza & Neale, 1997). Owing to the fact that measurement systems like the BSC have been
designed to be used in the context of large corporations, Hudson et al (2001) argue that
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additional problems exist when trying to develop PM systems for the context of SMEs. The
unique characteristics of SMEs suggest that a different set of issues arise when attempting to
develop and implement PM systems in this context.
Objectives of Study
This paper explores the use of financial and non-financial performance measures among 270
SMEs based in Australia and South East Asian countries. Organisation size ranges between
10 and 250 employees which is consistent with current SME definitions (European
Commission, 1996, cited in Hudson et al., 2001). Whilst there has been considerable attention
paid to the use of performance measures in large enterprises and government departments,
relatively little research has been conducted on performance measures in SMEs. This is in
spite of the fact that SMEs have very unique characteristics compared to large corporations
(Hudson et al. 2001). The characteristics include the size of the companies, a simplified
product and service offerings in homogeneous or niche markets, a centralized organizational
structure with a lack of specialized occupations and departments. SMEs account for over
95% of all businesses and 85% of all new jobs in developed economies (Wheelen and
Hunger, 2002; Hanson et al., 2002). This exploratory study aims to identify the dimensions of
performance measurement that are being used and the differences in the use of performance
measures between organisations of different sizes, age and business location (country) and
industry type.
Research Methodology
An initial exploratory study was conducted on 99 organisations based in Australia and South
East Asian countries to determine the range and type of performance measures used in the
SMEs in these locations (Phillips and Shanka, 2002). The results of this initial study were
used to develop a standard survey instrument for the current study.
For this new study, a standard survey questionnaire was used and administered through faceto-face interviews with top management. A total of approximately 1000 telephone requests
for interviews were made to organisations to take part in the survey in 4 countries namely
Hong Kong, Singapore, Malaysia and Australia. After an initial period, the management of
these companies were contacted by phone to remind them of the interviews and to set a date
and time for the interviews to take place. A total of 270 interviews were successfully
conducted by trained interviewers in each country.
The questionnaire itself consisted of scale items to identify performance measures being used,
the frequently of usage, and the importance of each measure. Additional questions included
demographic characteristics of the participants, the organisation’s industry classification, age
of the organization, scope of the organisation’s activities (i.e. local, international etc.), number
of staff, and annual turnover. As mentioned a total of 270 businesses participated in the
survey and the completed survey data were analysed using the SPSS statistical package
version 11.0.
Results and Discussion
Profiles of organisations
The majority (95.6%) were represented by for-profit enterprises. Apart from Malaysian
organisations (4.4%), there was a fairly even representation of organisations from Hong Kong
(38.1%), Western Australia (31.1%) and Singapore (26.3%). 51% of organisations were
established from 1990 onwards. The three main industry sectors represented were services
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(46.4%), wholesale and retail trade (27.7%) and manufacturing/construction (25.8%). 29.9%
had 15 or less employees, 20.5% had 16 to 17 employees, 24.3% had 28 to 65 employees and
25.4% had more than 65 employees.
Performance measures currently in use
The mean scores on the degree of importance of the 21 performance measure scale items
ranged from a high of 6.4 (profit and loss) to a low of 4.7 (employee satisfaction/turnover,
new product/revenue growth and client referrals) (Table 1). The most popular measures used
monthly were sales/revenue (76% of organisations), followed by accounts receivable/payable
(72%), inquiry/complaint follow-up (61%) and profit/loss (60%). Not surprising was the
finding that it was most common to use employee performance measures on an annual basis
(35%).
Of interest was the finding that 48% of organisations did not have any measure for client
referrals as a new source of customers. Other areas not measured included customer feedback,
new product revenues (31%), employee satisfaction/turnover (30%), and customer
retention/loyalty/profitability (29%).
The three scale items with lowest mean scores that were also reported as not being in use
together with customer retention/loyalty/profitability and employee training and development
were dropped from further analyses due to the higher percentage of respondents indicating
that these measures were not in use.
Table 1. Mean scores and usage patterns of Performance Measures
Measures
Profit and loss
Sales/revenue
Accounts receivable/payable
Inquiry / complaint follow up
Customer retention/loyalty/profitability
Customer complaints/returns
Cost efficiency
Operational efficiency/effectiveness
Quality/continuous improvement
Conformance to delivery standards/service request
Conformance to service standards
Customer feedback/survey
Risk management/quality control
Employee performance management
Employee training and development
Sales/inquiries/market share
Financial ratios
Inventory control
Employee satisfaction/turnover
New product revenues/growth
Client referrals
Mean*
Importa
nce
6.4
6.3
5.5
5.5
5.4
5.3
5.3
5.2
5.2
5.2
5.2
5.2
5.1
5.1
4.9
4.9
4.9
4.8
4.7
4.7
4.7
1
Usage patterns (Per cent mentioning)
2
3
4
5
60.0
76.0
72.0
61.0
28.0
49.0
42.0
38.0
35.0
40.0
34.0
33.0
36.0
18.0
20.0
32.0
29.0
49.0
16.0
22.0
32.0
15.0
10.0
10.0
8.0
16.0
8.0
20.0
19.0
18.0
18.0
16.0
12.0
21.0
15.0
13.0
15.0
18.0
9.0
12.0
18.0
9.0
8.0
5.0
6.0
7.0
14.0
6.0
11.0
13.0
11.0
9.0
10.0
9.0
8.0
18.0
19.0
11.0
8.0
9.0
15.0
12.0
6.0
16.0
7.0
4.0
2.0
13.0
6.0
9.0
8.0
11.0
4.0
10.0
12.0
12.0
35.0
20.0
15.0
18.0
8.0
27.0
17.0
5.0
*On a scale 1 = least important to 7 = most important.
Usage pattern: 1 = monthly, 2 = quarterly, 3 – bi-annually, 4 = annually, 5 = not in use.
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1.0
1.0
8.0
21.0
29.0
31.0
18.0
22.0
25.0
29.0
30.0
33.0
23.0
14.0
28.0
27.0
27.0
25.0
30.0
31.0
48.0
Factor analysis
Principal component analysis with varimax rotation was performed on the 16 measurement
items. Factorability of the items was verified by the use of KMO and Bartlett’s test of
sphericity (KMO = .864, _2 = 719.470, df = 55, p < .001). Two components were extracted
that explained 59% of the variance (Table 2). The first component consisting of seven items
(eigen value = 4.810, _ = 0.89) accounted for 44% of the variance and represents measures
related to the customer service perspective. The second component, consisting of four items
(eigen value = 1.678, _ = 0.67) accounted for 15% of the variance represents measures
related to financial perspective.
Table 2. Principal Component Matrix
Performance Measures
Customer feedback/survey
Customer complaints/returns
Inquiry / complaint follow up
Quality/continuous improvement
Conformance to service standards
Sales/inquiries/market share
Employee performance management
Sales/revenue
Profit and loss
Accounts receivable/payable
Financial ratios
Dimensions
1 Customer service
2 Financial
.835
.820
.801
.770
.766
.690
.610
.825
.767
.628
.619
Eigen value
Per cent of Variance
Cronbach’s alpha coefficient
Summated mean score
4.810
43.7
.8876
5.2
1.678
15.3
.6687
5.8
Differences in performance measures dimensions
One-way between groups ANOVA test showed statistically significant differences on the
customer service dimension for location of business (F = 9.99, sig. = .000). The mean
differences were significant between businesses located in Australia and those located in
Singapore or Hong Kong. Australian businesses scored significantly higher mean (M = 5.7)
compared with those from Singapore (M = 5.2) or Hong Kong (M = 4.8). Furthermore,
statistically significant difference was reported on the customer service dimension for
employee size (F = 4.026, sig. = .008). The mean scores for organization with 15 or less
employees were significantly lower (M = 5.0) compared with those organizations that employ
28 to 65 staff (M = 5.6). The latter group also had significantly higher mean score compared
with organizations with 16 to 27 employees (M = 4.9). However, no statistically significant
difference was reported for age of business or length of time respondents were in current
position, current organisations or current industry. Neither was there any statistically
significant difference between sectors of the industry (manufacturing/mining/construction,
wholesales and retail trade, and services).
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Implications and Conclusion
This exploratory study has identified two dimensions of performance measurement in use by
SME’s namely customer service and financial dimensions. These two dimensions explain
59% of the variance. It is noted that only two of Kaplan and Norton’s (1992) dimensions of
performance were identified in this study.
Statistically significant differences were identified in the degree of importance for using
measures on the customer service dimension based on the location and size of the
organisation. Australian organisations reported higher levels of importance for using customer
service measures than Hong Kong and Singapore SME’s. Larger SME’s with 28 to 65
employees also reported higher levels of importance for using customer service measures than
organisations with 27 or less employees.
These results appear to support the earlier findings by Llonch et al. (2002) who identified
differences between Spain and UK organizations in the use of measures of marketing success.
Findings also lend some support for the argument by Hudson et al (2001) that the
organisation’s size influences the measurement system and measures used. It would appear
that smaller size companies tend to use basic financial measures and a modicum of non
financial measures such as customer feedback and customer retention/loyalty/profitability
(29%). This would suggest an emphasis among these companies on financial indicators and a
neglect of non financial but nevertheless important measures on marketing and customer
issues. This lack of marketing or customer orientation has serious implications for these
companies if they wish to be proactive, build customer loyalty, increase its market share or be
export oriented in order to gain market expansion.
No significant differences were identified between organizations based on their age. This
appears to contradict the proposition by Thain (1969) cited in Wheelen and Hunger (2002)
that organizations of different stages of corporate development apply different measurement
and control systems and key performance indicators.
Some limitations of this study are non-random sample used in that only those approached and
who agreed to participate were included. The face-to-face interview process may be another
limitation. Future studies will confirm these findings with larger sample sizes. Subsequent to
this, only those items loading on the two components identified in this study will be used in
future surveys. In addition, the future survey will include as a dependent variable, overall
perceived performance in relation to the competition. This will enable some additional
important and interesting relationships to be explored between dimensions of performance
measured and self reported organisational performance as an outcome.
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