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Utilizing a cluster approach to measure performance in industrial research organizations

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IPERF-innovation-traininglpp

Authors: Tatjana Samsonowa, Wolfgang Gerteis

In: The XX International Society for Professional Innovation Management (ISPIM) Conference: The Future of Innovation

This paper describes research concerned with a highly-controversial topic in innovation management: performance measurement of industrial research departments. It is particularly difficult to assess a research department’s performance separately from a development department due to certain characteristics, like intangibility, and the time-lag of research outputs. Based on case studies of eight companies from ICT sector we analyze two dimensions of performance measurement: a) organizational goals of research departments and b) Key Performance Indicators (KPIs) that are applied to measure the achievement of the goals. In a first step, we introduce performance clusters as a high-level abstraction of activities in industrial research organizations in the ICT sector and related KPIs as a framework to promote comparability between industrial research departments, consisting of eleven clusters. In a second step, starting with KPIs we establish now a connection to the research goals dimension using spectral analysis [1] as a means to compare organizational goals from a content perspective. A set of examples from case studies is given, that proves the evidence of the spectral analysis approach. The contribution of this article is a description of a performance measurement framework for industrial research departments, within which we explore the extent to which performance indicators summarized in clusters reflect the strategic planning and measuring practices established in companies.