Causality in Performance Measurement Model

49 Pages Posted: 20 Jan 2004 Last revised: 31 Aug 2009

See all articles by Mary A. Malina

Mary A. Malina

University of Colorado at Denver - Business School

Frank H. Selto

University of Colorado, Boulder

Date Written: May 1, 2004

Abstract

Causal relations among performance measures are key features of performance measurement models (PMM), such as the balanced scorecard that has been popularized by Kaplan and Norton [1992, 1996, 2000]. Nørreklit [2000], however, cautions that the notion of causality in Kaplan and Norton's balanced scorecard is confused among concepts of (a) empirically refutable causes and effects, (b) internal logic of accounting, and (c) (equi)finality of alternative means and desired ends. Furthermore, Nørreklit [2002] suggests that the balanced scorecard's popularity might be due to the persuasiveness of balanced scorecard-inspired rhetoric rather than its demonstrable cause and effect nature. Because causal relations are important to the validity and perhaps the viability of PMM, this study investigates causality within a PMM that is similar to "the balanced scorecard." This study addresses two research questions about causality in the context of one organization's enduring and reportedly successful PMM. The first question is: Are causal relations perceived by the designers and users of the PMM? The second question is: Are valid causal relations apparent in PMM archival data?

This study discusses three reasons for the importance of separating cause-and-effect relations from logical and finality relations within PMM. First, a reliable, predictive financial model requires measurement of leading and lagging cause-and-effect relations among performance outcomes at different links in the value chain. Second, consistency between empirically established cause-and-effect and finality relations can improve organizational communication and learning. Third, cause-and-effect relations that are understood, communicated, and made part of an incentive system can improve the effectiveness of motivation and incentives. The study first uses qualitative analyses of interview data to demonstrate evidence of perceptions of cause-and-effect, logical, and finality relations by employees at several levels in the firm. The study then uses econometric analyses of performance data to refute claims of causal relations among performance measures. The findings support the primacy of logical and finality relations championed by top management as drivers of the design and use of the PMM. This raises the question of whether a PMM without reliable cause-and-effect relations can serve purposes of financial prediction, learning, communication, and motivation. If not, perhaps logical and finality relations are sufficient to make a PMM successful in practice. Alternatively, more attention to measurement and PMM construction might be warranted.

Keywords: Causality, performance model

JEL Classification: M40, M46

Suggested Citation

Malina, Mary A. and Selto, Frank H., Causality in Performance Measurement Model (May 1, 2004). Available at SSRN: https://ssrn.com/abstract=488144 or http://dx.doi.org/10.2139/ssrn.488144

Mary A. Malina

University of Colorado at Denver - Business School ( email )

1250 14th St.
Denver, CO 80204
United States

Frank H. Selto (Contact Author)

University of Colorado, Boulder ( email )

419 UCB
Boulder, CO 80309-0419
United States

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