مفاهیم کارایی اندازه گیری عملکرد استراتژیک در شرکت های خدمات مالی

This study examines the relation between measurement system satisfaction, economic performance, and two general approaches to strategic performance measurement: greater measurement diversity and improved alignment with firm strategy and value drivers. We find consistent evidence that firms making more extensive use of a broad set of financial and (particularly) non-financial measures than firms with similar strategies or value drivers have higher measurement system satisfaction and stock market returns. However, we find little support for the alignment hypothesis that more or less extensive measurement than predicted by the firm's strategy or value drivers adversely affect performance. Instead, our results indicate that greater measurement emphasis and diversity than predicted by our benchmark model is associated with higher satisfaction and stock market performance. Our results also suggest that greater measurement diversity relative to firms with similar value drivers has a stronger relationship with stock market performance than greater measurement on an absolute scale. Finally, the balanced scorecard process, economic value measurement, and causal business modeling are associated with higher measurement system satisfaction, but exhibit almost no association with economic performance.

Managerial accounting is evolving to encompass a more strategic approach that emphasizes the identification, measurement, and management of the key financial and non-financial drivers of strategic success and shareholder value (Institute of Management Accountants, 1999 and International Federation of Accountants, 1998). In response, many firms are adopting strategic performance measurement (SPM) systems that (1) provide information that allows the firm to identify the strategies offering the highest potential for achieving the firm's objectives, and (2) align management processes, such as target setting, decision-making, and performance evaluation, with the achievement of the chosen strategic objectives (e.g., Gates, 1999 and Otley, 1999). Proponents of strategic performance measurement advocate two general approaches for developing SPM systems. The simplest approach calls for firms to measure and use a diverse set of financial and non-financial measures. Advocates of this “measurement diversity” approach argue that a broad set of measures keeps managers from suboptimizing by ignoring relevant performance dimensions or improving one measure at the expense of others. As a result, these advocates claim that firms achieve higher performance when they place greater emphasis on a broad set of financial and non-financial performance measures (e.g., Lingle & Schiemann, 1996). A second approach is based on contingency theory, which argues that strategic performance measures must be aligned with the firm's strategy and/or value drivers (Fisher, 1995 and Langfield-Smith, 1997). Under this approach, performance theoretically is enhanced when “measurement gaps” between the firm's strategic priorities and measurement practices are minimized. Thus, performance is expected to be lower when the SPM system places either less or more emphasis on a measurement practice than the level required by the firm's strategy and value drivers. Closely related to the contingency perspective is the use of measurement techniques such as the balanced scorecard process, causal business modeling, and economic value measurement. Advocates argue that these techniques help companies improve the alignment between their performance measurement systems and their organizational objectives (Gates, 1999, Kaplan & Norton, 1992, Kaplan & Norton, 1996, Kaplan & Norton, 2001, Stewart, 1991 and Young & O'Bryne, 2001). Despite these arguments, the extent to which firms claiming to use these techniques actually link their performance measures more closely to strategic priorities is unknown. Using data from 140 US financial services firms, we extend prior research on the performance implications of strategic performance measurement along several dimensions. First, we examine a broader set of measurement system uses (goal setting, capital investment decisions, identification of improvement opportunities and development of action plans, performance evaluation, and external disclosure) and measurement capabilities than prior studies that typically focus only on performance evaluation and compensation. Second, we investigate the relation between SPM practices and actual financial outcomes (accounting and stock returns) rather than relying exclusively on self-reported measurement satisfaction or firm performance. Third, we examine each of the SPM approaches and compare their relative ability to explain firm performance. Fourth, we extend prior contingency research by looking at the alignment between specific value drivers and measurement, in addition to the traditional alignment with firm or manufacturing strategy. Fifth, we provide evidence on the use and performance consequences of the three measurement alignment techniques (balanced scorecard, economic value measurement, and business modeling), an area that has received surprisingly little attention in the research literature. Finally, we examine potential lags between the implementation of performance measurement systems and economic results. We find consistent evidence that SPM practices are associated with 1- and 3-year stock returns, but not with our two accounting measures (return on assets and sales growth). In particular, financial services firms that make more extensive use of a broad set of financial and (particularly) non-financial measures than those with similar strategies or value drivers earn higher stock returns. These results are even stronger in the subsample of firms with more mature performance measurement systems, suggesting that these measurement practices yield economic results with some lag. We find little support for the hypothesis that more or less extensive measurement than predicted by the firm's strategy or value drivers adversely affect performance. Instead, our results indicate that greater measurement emphasis and diversity than predicted by our benchmark model is associated with higher satisfaction and stock market performance. These findings suggest that the average measurement practices of firms pursuing similar strategies or value drivers currently are not optimal in this industry. We also find that greater measurement diversity compared with firms with similar strategies or value drivers has a stronger relationship with stock market performance than greater overall measurement. This evidence suggests that the appropriate benchmark for assessing measurement diversity is greater measurement relative to competitors with similar strategies or value drivers rather than greater measurement on an absolute scale. On average, firms claiming to use a balanced scorecard exhibit few differences in their emphasis on non-financial performance categories than non-users, and make little use of the causal “business models” of leading and lagging indicators that balanced scorecard advocates claim is a foundation of the scorecard process. In contrast, economic value and business model users place significantly greater emphasis on non-financial value drivers and measures than firms that do not use these practices. Although balanced scorecard, economic value, and causal business model users all rate satisfaction with their measurement systems higher than non-users, we find almost no evidence that these techniques are associated with accounting or stock market performance. The remainder of the paper is organized as follows. The following section reviews related literature and develops our hypotheses. We then discuss our sample selection and measurement methods. The next section reports our contemporaneous performance results, followed by our analysis of lagged performance effects in the subset of more mature systems. A summary of our results and limitations to our study conclude.

Using data from US financial services firms, we examine the relative ability of various strategic performance measurement approaches to explain firm performance. These approaches include greater measurement diversity, improved alignment with firm strategy and value drivers, and the use of performance measurement alignment techniques including the balanced scorecard, economic value measures, and causal business modeling. We find that a variation of the measurement diversity approach has the strongest association with stock market performance. In particular, firms that make more extensive use of a broad set of financial and (particularly) non-financial measures than those with similar strategies or value drivers earn higher stock returns. These results are even stronger when the performance measurement system has undergone no significant changes in the past 3 years. In contrast, we find little evidence that SPM practices are associated with accounting measures (ROA and sales growth). One potential explanation for these contrasting results is that the performance implications of SPM systems are more likely to be captured in forward-looking stock market measures than in short-term, historical accounting measures. Finally, the measurement alignment techniques proposed in the performance measurement literature are positively associated with measurement system satisfaction, but exhibit almost no association with economic performance. As with any study of this type, our results are subject to a number of limitations, including potential response biases, endogeneity of our predictor variables, model specification, and the difficulty in using a survey instrument to obtain factual, detailed information on exactly how firms measure performance. In addition, our results may not generalize to other industries or competitive settings. Future studies can also extend our analyses by examining a broader set of performance measurement system attributes, such as the level of aggregation and integration, that other studies have found to be determinants of the perceived usefulness of measurement systems (e.g., Chenhall & Morris, 1986) but are not included in our survey. Finally, prior research on management accounting and performance measurement system innovations indicates that technical and organizational factors can play an important role in the perceived success of system implementation (e.g., Anderson & Young, 1999, Cavalluzzo & Ittner, in press and Shields, 1995). Although we do not examine these factors in our tests due to the absence of data on these issues, future studies can make a significant contribution by examining how these factors interact with system design choices to influence actual performance outcomes. Despite these limitations, our findings carry a number of implications for research and practice. First, the differing results for measurement satisfaction and stock market performance raise important questions about the validity of using perceptual satisfaction or outcome measures to evaluate measurement system success. Although recent practitioner publications promote the benefits of balanced scorecards and economic value measures by citing surveys on measurement system satisfaction (e.g., Kaplan & Norton, 2001, pp. 356–357), we find no evidence that these higher satisfaction levels translate into improved financial performance. Second, the descriptive statistics on the use of the various performance measure categories and business modeling practices by adopters and non-adopters of balanced scorecards indicate that many firms that claim to have implemented this technique have not fully adopted Kaplan & Norton, 1992 and Kaplan & Norton, 2001 prescriptions. Future studies will need to devise improved methods for eliciting what firms mean by a “balanced scorecard” and how this information is actually being used. Third, the significant performance implications of positive deviations from our benchmark models indicate that (subject to the validity of these models) average measurement practices of firms pursuing similar strategies or value drivers currently are not optimal in this industry. Instead, our results indicate that greater measurement emphasis and diversity than similar firms is associated with higher stock market performance. The results also indicate that the appropriate benchmark for assessing measurement diversity is greater measurement relative to competitors with similar strategies or value drivers rather than greater measurement on an absolute scale. Finally, the greater explanatory power of stock return models using value driver alignment as predictor variables suggest that researchers and practitioners should go beyond the alignment of measurement practices with organizational strategy to investigate and measure the specific value drivers underlying strategic success.