Purchasing manages and optimises existing product variance

Abstract

Purpose

The purpose of this paper is to present a new optimisation approach for product variance from the purchasing perspective.

Design/methodology/approach

The research is based on a case study of a collaboration with a global acting automotive Tier 1 supplier, who produces steering systems for cars and commercial vehicles. A total of 116 different variants of three components of a car automotive steering system were analysed and evaluated. The data were gathered from 13 sub-suppliers for three different types of a steering system.

Findings

Unnecessary time, money, quality and technology can be saved through a greater understanding of such product variances. The results of the case study lead to a general method to optimise existing product variance and present cost improvements and a new key performance indicator to manage product variance out of the purchasing department.

Research limitations/implications

The research is based on a purchasing case study at a Tier 1 supplier of the automotive branch. The approach can be used for other company departments, e.g. logistics and for different industries than automotive.

Practical implications

A company can be successful and competitive when it meets the customer needs with a maximum on satisfaction without generating of waste. Unnecessary existing product variance is a kind of waste. The insights of this paper support the operative user and the strategic company management to reduce and improve unnecessary variance in different sections.

Originality/value

The structured analysis of product variance from the purchasing perspective and the key performance indicator “variance share” are new to company management. The research focuses on the management of existing variance out of the purchasing department which is a segment that has received limited academic attention in research to date.

Citation

Nabhani, F., Uhl, C.J., Kauf, F. and Shokri, A. (2018), "Purchasing manages and optimises existing product variance", Journal of Manufacturing Technology Management, Vol. 29 No. 3, pp. 430-448. https://doi.org/10.1108/JMTM-03-2017-0053