Multi-Attribute Strategy and Performance Architectures in R&D: The Case of The Balanced Scorecard
RAND CORP SANTA MONICA CA
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Performance multi-dimensionality is an age-old problem. The notion that measurement of an organizations or a systems performance must incorporate, to the extent possible, all key dimensions has been discussed in a number of literatures. The problem of performance multi-dimensionality and hence measurement complexity is most severe in research and development RD settings due to the inherent multi-dimensionality of RDs output and the long-term and intangible nature of the process itself. One of the performance measurement approaches that internalizes the inherent multi-dimensionality of the organizational performance measurement challenge is the Balanced Scorecard. The key insight that triggered the idea of the Balanced Scorecard was the notion that organizational performance cannot be adequately measured by a single metric or a single category of metrics such as profit or financial metrics but must incorporate a whole series of metrics across a number of performance dimensions including input, process and output metrics, leading and lagging metrics, and metrics measuring tangible and intangible aspects of performance. While the use of the Balanced Scorecard has spread in the private and nonprofit sectors, it remains under-utilized and under-appreciated in RD. This dissertation advances the state-of-the-art by asking the critical questions Do RD organizations satisfy the basic assumptions underlying the Balanced Scorecard, and Does the adoption of the Balanced Scorecard in RD settings realize the kind of breakthrough improvements in organizational performance that are hypothesized by the founders of the Balanced Scorecard movement These answers hold the key to unlocking the potential benefit of this framework in RD settings. The authors adopt a multi-pronged analytic strategy that builds upon the relative strengths of quantitative and qualitative methods.
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