Framework for measurement of supplier satisfaction

Abstract

Purpose

The purpose of this paper is to design, develop, implement and validate a multi-criteria decision model for measuring supplier satisfaction through a case study.

Design/methodology/approach

A three-stage methodology was used to develop a framework to measure supplier satisfaction. The framework involved factors and Key Performance Indicators (KPIs) from literature and exploratory study. Further, using the framework, a multi-dimensional decision model to calculate Supplier Satisfaction Index was developed. The proposed decision framework was implemented as a real-world case study in an Indian manufacturing organization.

Findings

The study makes two major contributions: first, it develops a framework to measure supplier satisfaction using factors and KPIs suitable to the buyer organization; second, the model developed to calculate supplier satisfaction helps in understanding overall satisfaction of suppliers along with the level of satisfaction of each supplier. The model can also be used to suggest improvements to buyer organizations on specific factors and KPIs under each factor.

Research limitations/implications

Supplier satisfaction plays an important role in multinational companies (MNCs), so the sample of practitioners considered in this study is relevant. However, it is likely that the small sample size of only suppliers and companies selected solely from the Indian manufacturing MNCs may have introduced some bias.

Practical implications

A comprehensive framework for enhancing the relationship with suppliers will be instrumental in deciding, managing and improving the level of supplier satisfaction.

Originality/value

This approach provides purchase managers with the flexibility of selecting factors and KPIs at every level of analysis and also a single index to establish supplier’s satisfaction with a buyer company.

Citation

Hudnurkar, M. and Ambekar, S.S. (2019), "Framework for measurement of supplier satisfaction", International Journal of Productivity and Performance Management, Vol. 68 No. 8, pp. 1475-1492. https://doi.org/10.1108/IJPPM-09-2018-0336