Performance Measures, Informational Complexity and Measurement Fields

Friday, June 24, 2016: 2:30 PM-4:00 PM
233 Dwinelle (Dwinelle Hall)
Paul Willman, London School of Economics and Political Science, London, United Kingdom of Great Britain and Northern Ireland
Chris Moos, Said Business School, University of Oxford, Oxford, United Kingdom of Great Britain and Northern Ireland
Extended abstract

Field performance measures such as ratings, rankings, audits and accreditations are widespread, but both their incidence and dynamics are poorly understood. First, there is no robust explanation of why field performance measures develop considerable impact and trigger change processes in some organisational fields, but not others. Second, work on the institutional dynamics of performance measures has largely ignored the complexity of field performance measures. This paper addresses these two issues.

The paper revisits the performance measurement and institutional literatures to provide a model of the field characteristics that sustain field performance measures. The key field element is the informational complexity of the organisational field; the paper proposes a curvilinear relationship between the information complexity of a field and the probability of the emergence of an impactful field performance measure. At low levels of informational complexity, field performance measures cannot meaningfully reduce information further. At high levels of informational complexity, there is too much and too different information to provide for a meaningful comparison. As a consequence, impactful performance measures can only emerge in fields with intermediate levels of informational complexity. We thus view field performance measures as both a product of and an influence on the development of organisational fields.

To understand this interaction between performance measure and field change, we explore the dynamics of field performance measures. We identify three components of field performance measures, which we term field members. These field members are measurement agents (producers of performance measures), measurement actors (organisations rated or ranked by measures) and measurement users (broadly, consumers of performance measures). Under conditions of information complexity, field members use field performance measures to form evaluations of field membership, the desirable attributes of organisations in a field, and the distribution of performance across organisations in a field.  The interactions between field members affect the usefulness of the performance measure in reducing informational complexity. Measurement agents, actors and users may have different interests in reducing informational complexity and thus the longevity of the performance measure, thereby moderating the impact of the performance measure on the field.

In particular, we propose that, through reduction of informational complexity, field performance measures may accelerate field change and maturation processes, enhance status orders, contribute to field structuration, and influence the competitive basis of organisational fields. To illustrate the argument, we use findings from the analysis of a longitudinal dataset of the Financial Times Global MBA rankings.

The paper makes two contributions. First, the paper seeks to contribute to a better understanding of how and where field performance measures become influential. The approach sees field performance measures as both product of and influence on field change. Second, the paper seeks to contribute to the understanding of the dynamics of field performance measures and fields. In conclusion, we consider the parallels between the approach developed in this paper, and models of industry dynamics developed in industrial economics. Based on this, we propose some avenues for future research.