Productivity/performance measurement. Case application at the government pharmaceutical organization
| Published date | 01 December 2006 |
| DOI | https://doi.org/10.1108/02635570610712573 |
| Date | 01 December 2006 |
| Pages | 1272-1287 |
| Author | Kongkiti Phusavat,Watcharapon Photaranon |
| Subject Matter | Economics,Information & knowledge management,Management science & operations |
Productivity/performance
measurement
Case application at the government
pharmaceutical organization
Kongkiti Phusavat and Watcharapon Photaranon
Department of Industrial Engineering, Kasetsart University,
Bangkok, Thailand
Abstract
Purpose – To address two key problems facing the production department at the government
pharmaceutical organization (GPO). They were a lack of productivity and performance measurement
at the operational level, and a need to assess the functional readiness to undertake its own
performance-analysis work.
Design/methodology/approach – The decision was made to apply the multi-factor productivity
measurement model (MFPMM). This was due to its ability to link with existing data that had been
generated by the accounting department, its explicit integration between productivity and financial
performance (i.e. profitability) at the operational level, and its major features such as information on
opportunity gain/loss.
Findings – For the GPO, it was quite clear that productivity improvement would represent the
critical direction for the production department in the future. Based on its initial deployment at the
Section 3 unit, the MFPMM was generally viewed as a suitable tool for measuring and providing
necessary productivity/performance information.
Practical implications – The database management needed to be improved in order to ensure
timely provision of data into the MFPMM. Furthermore, better performance-analysis capability by the
staffs was required. In other words, both technical and managerial aspects must be recognized in order
to ensure the MFPMM success and sustainability.
Originality/value – This study generated insightful information into operational performance at the
GPO. It was clear that productivity represented the basis for formulating future policy initiatives.
Keywords Productivityrate, Prices, Profit, Measurement
Paper type Case study
Background
Productivity and subsequently performance measurement has become more important
and has been regarded as a prerequisite for continuous improvement (Kaydos, 1991).
When focusing on the industrial, national, and international levels, many approaches
have been designed by economists such as the total factor productivity (TFP), or
Bureau of Labor Statistics (BLS) multifactor productivity techniques (Duke and
Torres, 2005; Meyer and Harper, 2005; Tsai et al., 2006). At the organizational,
functional, program, and project levels, there have been several concepts and ideas
involving in the measurement/assessment work. The balanced scorecard concept
(Kaplan and Norton, 2004) has often been cited. The Sink and Tuttle (1989) approach
has been widely adapted by public/private organizations. Harper (1984) also develops a
performance measurement framework at the organizational/functional levels. The
concepts initiated by Sink (1985), and Harper (1984) share one similar aspect – the use
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IMDS
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1272
Industrial Management & Data
Systems
Vol. 106 No. 9, 2006
pp. 1272-1287
qEmerald Group Publishing Limited
0263-5577
DOI 10.1108/02635570610712573
of a ratio-format KPI that primarily relies on quantitative data (Hoehn, 2003). At the
group and individual levels, there were many concepts such as motivational methods
based on industrial psychologists and performance appraisals for salary
structure/workload analysis extended by human resource specialists, and
piece-rate/standard times determined by industrial engineers (Takala et al., 2006).
According to Sumanth (1985), Hoehn (2003) and Helo (2005), it is generally agreed
that productivity represents one of the major areas reflecting the term performance,
especially for an organization or a production unit. Based on Sink and Tuttle (1989),
there are seven performance criteria; i.e. profitability, productivity, quality of work life,
innovation, quality, effectiveness, and efficiency. Productivity also represents an
essential component of Harper’s performance measurement concept that includes unit
cost, price, factor proportion, cost proportion, product mix, and input allocation (Harp er,
1984). It is vital for an organization to become continuously more productive in order to
sustain its growth (Harper, 1984). Sumanth (1985) and Hoehn (2003) have pointed out
that becoming more productive implies better cost-competitiveness of and long-term
profitability for an organization. Specifically, productivity is simply the relationship
between the outputs (goods and services) generated from a system and the inputs
provided to create those outputs (Sink, 1985). Inputs include labor (human resources),
capital (physical capital assets), energy, materials, and data that are brought into a
system. There have been many techniques for productivity measurement; e.g. the
MFPMM, the Harper’s Performance Network, and Return on Assets (ROA).
According to Sink (1985), the MFPM M was developed by the American
Productivity Center in 1977 (nowadays known as the American Productivity and
Quality Center) for measuring productivity and price recovery, and for explicitly
relating these results with profitability at the organizational/functional levels. Its
primary focus is on a manufacturing/production unit with tangible outputs and inputs.
It is suitable for a process that is stable, implying not-so-often chan ges in products
being offered (Sink and Tuttle, 1989). Finally, the MFPMM can easily adapt the data
from a typical accounting system. Figure 1 for its major components.
To elaborate more on the MFPMM, it is essential to highlight its other key features.
For example, the MFPMM combines the concepts of the opportunity gain/loss, and the
dynamic/static ratios in both single-, and partial-formats (Table I).
It is important to recognize at this point that measuring performance (i.e.
productivity, profitability, etc.) needs to be suitable at a specific level that it is intended.
Based on Sink and Tuttle (1989) and Singh et al. (2000), the analysis difficulties often
arise when a plant manager has to rely on organizational-level or accounting
information for monitoring technical-specific problems and for evaluating operational
Figure 1.
Nine basic components for
the MFPMM
Change in
output quantity
Change in
Productivity
Change in
input quantity
Change in
revenues
Change in
profits
Change in
costs
Change in output
price (unitprice)
Change in price and
cost (price recovery)
Change in input cost
(unit cost)
Productivity/
performance
measurement
1273
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