Multidimensional benchmarking

Benchmarking is a process of comparison between performance characteristics of separate, often competing organizations intended to enable each participant to improve its own performance in the marketplace (Kay, 2007). Benchmarking sets organizations’ performance standards based on what “others” are achieving. Most widely adopted approaches are quantitative and reveal numerical performance gaps where organizations lag behind benchmarks; however, quantitative benchmarking on its own rarely yields actionable insights. It is important for organizations to understand key drivers for performance gaps such that they can develop programs for improvement around them. In this thesis, we develop a multidimensional analysis approach to benchmarking to characterise the properties of key drivers as a step towards “qualitative” benchmarking. Specifically, our approach systematically identifies significant benchmarks, compares organizations in statistical manners, and reveals the most manifesting aspects of uniqueness of an organization of interest. We also evaluate our algorithmic development using systematic empirical studies and show that our methods are effective and efficient.