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Mourik, Greg van --- "Measuring effectiveness - Organisational research" [2008] MonashBusRw 15; (2008) 4(1) Monash Business Review 6

Measuring effectiveness
Organisational research

Greg van Mourik

While many say “The research of organisational effectiveness is like wearing the emperor’s new clothes – we know it’s flawed but we keep doing it”, there are ways around the flaws writes Greg van Mourik.

For starters, defining ‘effectiveness’ itself is an issue. Is it, for example, about achieving goals, using resources efficiently, or satisfying stakeholders? Different models shed light on different aspects of what it means to be effective at the organisational level. For example, an organisation with clearly defined, measurable goals is best assessed using the rational goal model, while an organisation with more ambiguous goals could be assessed by other methods.

Much of the controversy around organisational effectiveness research is due to the fact that a lot of the research assumes that organisational effectiveness is a single variable. More recent approaches have seen an increasing use of multi-dimensional conceptions.

Another issue is whether organisational effectiveness is objective or socially constructed. If it is socially constructed, then it is determined by stakeholder judgements formed in an ongoing process of sense-making and implicit negotiation. This raises issues as to the reliability and comparability of effectiveness measures of different organisations.

Empirical issues

Determining suitable empirical criteria to measure a particular theoretical conception of effectiveness can be problematic. With goal achievement, for example, the best criteria may not be the extent to which an organisation achieves its explicit official goals, but the extent to which it achieves its implicit operating goals.

It can also be argued that the method of combining criteria in order to represent effectiveness is a value judgement, since there is no algorithm or higher order truth to determine it. The result is that, as the research is repeated, different results may arise according to whatever value judgements were originally made.

In the past, researchers have measured overall effectiveness by weighting each criterion value and then adding them up. In doing this it is hoped that an increment in the weighted score corresponds with an increment in organisational effectiveness. An alternative to weighting, given in practice that organisations select strategic goals from a fairly limited set of criteria, like profit, efficiency and job satisfaction, is to use these criteria individually. While any one of these criteria is not fully representative of the overall effectiveness of the organisation, they may still be of great value in research.

Other noteworthy issues relate to criterion stability, time perspective, measurement precision and level of analysis. Criterion stability recognises that indicators of success are likely to change over time, for instance as economic conditions change; while time perspective questions how short run should be considered in conjunction with long run indicators. The issue of measurement precision recognises that measurement errors are made when, for example, responses to survey questions or staff turnover rates are used to measure employee satisfaction. Finally, the levels of analysis issue acknowledges the flaws that are likely to happen if by studying the organisation level, researchers ignore the critical relationship between individual or departmental behaviour at the micro level and organisational effectiveness at the macro level.

Research opportunities

However, there are now a number of techniques that can result in insightful research which is of practical value to organisational managers today.

Integrated, multi-dimensional models recognise that overall effectiveness is about the interaction of many performance-related indicators and draws together goal orientation, internal process and systems, and stakeholder perspectives. They also use objective and perceptual measurements, thus mitigating the possibility that an objective measure may suggest one thing and a perceptual measure something else.

To accommodate issues surrounding levels of analysis, hierarchical linear modelling is appropriate for nested data and can reveal variations at management and program levels, or individual and organisational levels, thereby avoiding bias when data is aggregated or disaggregated.

It is also appropriate to recognise that differences exist between organisations in a number of ways, for example in their contexts and value systems. Cluster analysis identifies sets of organisations that share common profiles. Thus, analysis of effectiveness can proceed by comparing effectiveness within individual clusters and between clusters.

Finally, data envelopment analysis captures the complex interplay between multiple outputs and inputs, without resort to an arbitrary weighting scheme as mentioned earlier or to making limiting assumptions about the variables being examined. This form of analysis enables comparison of organisations on the basis of productivity or efficiency related indicators.

MBR subscribers: to view full academic paper email mbr@buseco.monash.edu.au

Public access: www.mbr.monash.edu/full-papers.html (six month embargo applies)

Cite this article as

van Mourik, Greg. 'Measuring effectiveness'. Monash Business Review. 2008.; Monash University ePress: Victoria, Australia. http://www.epress.monash.edu.au/. : 6–7. DOI:10.2104/mbr08015

About the author

Greg van Mourik

Greg van Mourik is a Lecturer in the Department of Accounting and Finance, Faculty of Business and Economics, Monash University.


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