Using SPC to measure a national supermarket chain's suppliers' performance

Abstract

Purpose

This research paper aims to explore the application of Statistical Process Control (SPC) methods to measure the performance of a national supermarket chain's problem suppliers. The use of SPC control charts was expected to help in the understanding of the management of buyer/supplier relationships and the effect of the suppliers' performance in the supermarket's replenishment system.

Design/methodology/approach

The data analysed were based on the performance of 12 suppliers to the national supermarket over a period of 77 weeks. Quantitative data were supplemented with qualitative data obtained from the suppliers' managers and the supermarket's buyers. The paper compares the measurement of the suppliers' performance using descriptive statistics such as skewness, kurtosis and correlation, with those obtained using SPC‐based control chart techniques.

Findings

The results of this analysis indicate that neither descriptive statistics nor the SPC approach were a complete answer to monitoring supplier performance in the supermarket environment. Instead a composite approach was most likely to be effective in improving buyer/supplier relationships. The use of descriptive statistics is important in establishing consistent and achievable performance targets; the use of SPC facilitates performance monitoring and enables meaningful problem‐solving dialogues to be established.

Practical implications

From a retail managerial perspective these results help both in the design of the performance measurement system and in the establishment of realistic performance standards throughout the supply system.

Originality/value

The results suggest that performance measurement of supermarket replenishment systems needs to use a range of performance measures and extend beyond conventional dyadic buyer/supplier analysis.

Citation

Morgan, C. and Dewhurst, A. (2007), "Using SPC to measure a national supermarket chain's suppliers' performance", International Journal of Operations & Production Management, Vol. 27 No. 8, pp. 874-900. https://doi.org/10.1108/01443570710763813