Quantitative relationships between key performance indicators for supporting decision-making processes

  • Authors:

  • Raul Rodriguez Rodriguez;Juan José Alfaro Saiz;Angel Ortiz Bas

  • Affiliations:

  • Research Centre on Production Management and Engineering, Polytechnic University of Valencia, Camino de Vera S/N, Edificio 8G, Acceso D Planta 1 Valencia, 46022 Spain;Research Centre on Production Management and Engineering, Polytechnic University of Valencia, Camino de Vera S/N, Edificio 8G, Acceso D Planta 1 Valencia, 46022 Spain;Research Centre on Production Management and Engineering, Polytechnic University of Valencia, Camino de Vera S/N, Edificio 8G, Acceso D Planta 1 Valencia, 46022 Spain

  • Venue:
  • Computers in Industry
  • Year:
  • 2009

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Abstract

Performance measurement systems (PMS) are tools widely used by enterprises for managing and making strategy-based decisions. A PMS defines a group of strategic objectives and associated performance indicators (KPIs) that provide information as to whether the upstream objectives are being reached or not, but with no further information about the causes. Up to now, if an objective is not being reached managers do not have further information regarding the causes; in terms of accurate information they are limited to the associated KPI. However, regarding the decisions to be made: What would they be based on? How and where to dig to find cause-effect relationships? And, even more difficult: How to make it objective? This study presents a unique proposal able to objectively - not based neither on experience nor subjective judgments - identify and quantify relationships between performance elements defined within a PMS, offering additional information to managers to make cross-enterprise decisions. Finally, the paper presents the main results obtained from applying the proposal to a real world enterprise and future research lines.