Two-step model for performance evaluation and improvement of New Service Development process based on fuzzy logics and genetic algorithm

摘要

The problem of assessment, selection and improvement of key performance indicators in the New Service Development process is one of the most important tasks of process managers, and it has a critical effect on the considered process effectiveness which is further propagated on the competitive advantage of each service small and medium enterprises. The relative importance of the introduced key performance indicators and their values are assessed by decision makers in selected enterprises (total of 187 persons). The assessment of decision makers are described by pre-defined linguistic expressions which are modelled by using fuzzy sets theory. Aggregated relative importance is determined according to approach developed in this paper. The ranking and improvement of key performance indicators is stated as multi-criteria decision making problem that could be solved by the genetic algorithm. Priority of management initiatives that should lead to the improvement of selected key performance indicator is based on fuzzy if-then rules and single-objective genetic algorithm. In this way, more appropriate improvement strategy, which demands lower costs, may be defined. By applying the proposed model it is possible to identify weak points in organizations, to provide corrective measures, and to enhance the effectiveness of new service development process. The model presents a suitable solution for reengineering and improvement of the process performance. The application of this model could be introduced in other industrial branches.