Fuzzy analysis of customer dimension key performance indicator

Abstract

Mathematical approaches of calculation of quality evaluation of systems involving human factors do not reflect a significant feature of the processed data - their natural uncertainty – vagueness. Data that have their origin in human assessment of phenomena using integer numerical values are a typical example of such a vague information. Unconventional methods of soft computing are able to formalize this uncertainty and complete information about the size evaluation also its degree of uncertainty. Appropriate theoretical background for the formalization of vagueness data is fuzzy set and fuzzy logic theory. In this paper, these approaches are presented and applied to one of the key performance indicators – Balanced Scorecard CSI Customer Satisfaction Index. Uncertainty resulting criteria is new information leading to increased efficiency in their use in decision making processes