Determining Key Performance Indicators: An Analytical Network Approach

Daniela Carlucci and Giovanni Schiuma
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Daniela Carlucci: Center for Value Management, LIEG-DAPIT, Universita' della Basilicata, Via dell'Ateneo Lucano, 10, Potenza, Italy
Giovanni Schiuma: Center for Value Management, LIEG-DAPIT, Universita' della Basilicata, Via dell'Ateneo Lucano, 10, Potenza, Italy and Centre for Business Performance, Cranfield School of Management, Cranfield, Bedfordshire MK43 0AL, UK

Chapter 21 in Handbook on Business Information Systems, 2010, pp 515-536 from World Scientific Publishing Co. Pte. Ltd.

Abstract: AbstractSelecting performance indicators is one of the major challenges that companies have to face in developing a performance measurement system. This is because selecting means evaluating a set of performance indicators against multiple criteria, sometimes potentially conflicting. This chapter describes a decision model, based on the analytic network process (ANP) method, to drive managers in the selection of key performance indicators (KPI). The model takes into account the main criteria required by performance indicators to enrich the quality of a company's information system, and involves ANP to extract weights for setting the priorities among performance indicators. In particular, by applying ANP, the weights do not only merely result from a top-down process carried out by judging how well the performance indicators perform against the criteria, but also from a judgment process which takes into account the feedback relationships between the criteria and performance indicators as well as the mutual interactions of indicators. This is important because when decision makers select performance indicators, they often do not consider the dependency of criteria on the available performance indicators and the interdependency among indicators or, at most, consider vaguely those dependencies.This chapter provides evidence for the feasibility of the model, through its application to a real case.

Keywords: Information Systems; Systemization; Business Process Development; Health Care; Industrial Management; Data Management; Semantic Web Services; Knowledge Management; Risk Management (search for similar items in EconPapers)
Date: 2010
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