Quangos: Trends, Causes and Consequences by Sandra van Thiel

Author:Sandra van Thiel [Thiel, Sandra van]
Language: eng
Format: epub
Tags: Political Science, General
ISBN: 9781351748933
Google: UJwuDwAAQBAJ
Goodreads: 35866874
Publisher: Routledge
Published: 2001-08-01T00:00:00+00:00

Presence of a Performance Paradox

The performance paradox refers to a weak correlation between reported and actual performance (see chapter 3 for a more detailed explanation). Sometimes performance indicators (PIs) report on limited aspects of performance only, giving information about easily quantifiable aspects of performance, but leaving out less tangible aspects. In that case, reports underestimate actual performance. PIs can also be manipulated to make performance appear better than it really is, or to hide ill performance. In that case, reported performance provides an overestimation. It is important to keep in mind that a performance paradox has to do more with the reports on performance than actual performance. If present, a performance paradox invalidates the conclusions about the performance of the selected cases.

To uncover a performance paradox, reports of performance need to be studied and compared to actual performance. However, because all reports of performance can be subject to the performance paradox, it is nearly impossible to assess actual performance. We are faced with a conundrum.

Other solutions to overcome the problem of gathering information on the actual performance of quangos are to (i) collect information from other sources than the quango itself (e.g. competitive quangos3 or other organizations, clients, regulators, or the Ombudsman) and compare that with the reported performance, or (ii) develop new PIs that are not already being used by the quango itself, and use these to reassess performance.4 A lack of information from other sources increases the chance of a performance paradox occurring. If new indicators lead to different assessments, one might conclude that there is a performance paradox.

If other information sources are absent or new PIs cannot be developed, a third solution can be applied. Meyer and Gupta (1994) argue that certain characteristics of the performance assessment system increase the chance of a performance paradox arising (cf. chapter 3). For example, when only a limited number of PIs are used for a long time, positive learning can lead to a loss of the discriminating value of those indicators. Meyer and Gupta recommend the use of many, non-correlated indicators, and to vary those over time. Moreover, for each policy objective indicators should be developed; if, for example, PIs only stress quantifiable objectives, reports will underestimate non-quantifiable aspects of policy implementation. To investigate whether such a situation exists, an analysis of the performance assessment system is necessary. Aspects that need to be studied are: the translation of policy objectives into PIs, by whom the translation has been made and how; the amount and type of PIs used in annual reports and other reports on performance; and changes in the use of PIs over time. Furthermore, it is important to establish how much and what type of information on the performance of a quango is required and to which extent the quango complies with accountability demands. Finally, if information on performance is present but not reported, the cause for this lack needs to be determined, especially when reporting the missing information would lead to different conclusions on the efficiency and effectiveness of policy implementation.

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