Performance measurement of a manufacturing company using fuzzy analytical network process

Abstract

Performance measurement (PM) is a combination of characteristics of a company that are numerically expressed. The aim of the PM is to provide a feedback about success of current activities and provide insight about future performance. Performance of a company depends on its vision and goals, so the definition of performance can vary within time. While the PM literature provides various models for PM, the most accepted model is balanced scorecard (BSC). BSC supplies four inter-related perspectives that the companies can define indicators for performance. These perspectives are: financial, internal business processes, customer and finally learning and growth perspectives. In this study, PM is transformed to a multi attribute decision making (MADM) problem and a performance measurement model based on fuzzy analytical network process (FANP) is proposed. The performance measurement criteria are built with respect to four perspectives of BSC. The proposed model utilises FANP in order to determine the relative importance of perspectives and indicators. The performance scores for each indicator are determined based on the predefined goals. A numerical example, representing performance measurement for two periods, is given for a manufacturing company.