Measuring performance via production management: a pattern analysis

Purpose – To propose a pattern analysis method to help firms rectify weaknesses of production management (PM) and thus promote their business performance. Design/methodology/approach – Total factor productivity and the associated partial productivity indices are defined, and four kinds of production planning ranges, i.e. long‐range planning, medium‐range planning, short‐range planning, and execution, are defined based on 14 PM issues. A fuzzy clustering approach is applied to group the sampled firms into several patterns based on the achievement degrees of production planning in order to investigate the particular characteristics of each pattern. Findings – After analyzing the productivity characteristics of each pattern, the correlation between productivity and production management can be determined. In this study, the business performance seems to be not completely correlated with the achievements of production management, since moderate production planning can provide optimal business performance. Research limitations/implications – The patterns produced from the proposed approaches depend on the sampled data set. A solid sampling method is important to this study. Practical implications – The sampled data are collected from the top 50 large‐scale manufacturing firms in Taiwan. The results obtained from this paper may not be consistent with the situations in the other countries. Originality/value – Referring to the findings from each pattern, a firm can further investigate its position in the industry to find ways of increasing its competitiveness.