A decision framework for the consolidation of performance measurement systems

Numerous performance measurement systems have been expanding over the years. Therefore, they often contain more information than needed as well as irrelevant information. The consequences are high complexity in cognitively processing the enclosed measures and unnecessary costs for operating and maintaining the supporting infrastructure. Against this backdrop, we propose a decision framework that supports the consolidation of existing performance measurement systems such that information processing complexity and costs are balanced with the extent to which decision makers' information requirements are met and alignment with corporate objectives is achieved. We also report on the results of an evaluation based on feature comparison, prototype construction, and a real-world application.