Hauser, John R. (1998), "Research, Development, and Engineering Metrics." Management Science, 44, 12, December, 1670-1689.

We seek to understand how the use of Research, Development, and Engineering (R,D&E) metrics can lead to more effective management of R, D&E. This paper combines qualitative and quantitative research to understand and improve the use of R, D&E metrics. Our research begins with interviews of 43 representative Chief Technical Officers, Chief Executive offices, and researchers at 10 research-intensive international organizations. These interviews, and an extensive review of the literature, provide qualitative insights. Formal mathematical models attempt to explore these qualitative insights based on more general principles.

Our research suggests that metrics-based evaluation and management vary according to the characteristics of the R, D&E activity. For applied projects, we find that project selection can be based on market-outcome metrics when firms use central subsidies to account for short-termism, risk aversion, and scope. With an efficient form of subsidies known as "tin-cupping," the business units have the incentives to choose the projects that are in the firm's best long-term interests. For core-technological development, longer time delays and more risky programs imply that popular R, D&E effectiveness metrics lead researchers to select programs that are not in the firm's long-term interest. Our analyses suggest that firms moderate such market-outcome metrics by placing a larger weight on metrics that attempt to measure research effort more directly. These metrics include standard measures such as publications, citations, patents, citations to patents, and peer review. For basic research, the issues shift to getting the right people and encouraging a breadth of ideas. Unfortunately, metrics that identify the "best people" based on research success lead directly to "not-invented-here" behaviors. Such behaviors result in research empires that are larger than necessary, but lead to fewer ideas. We suggest that firms use "research tourism" metrics, which encourage researchers to take advantage of research spillovers from universities, other industries, and, even, competitors.

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