Smart buyer: A performance based framework for achieving procurement excellence

Abstract

Procurement, the act of buying goods or services from an external supplier, plays an important role in any organisation. To assess how well an organisation undertakes this activity, all associated Key Performance Indicators (KPIs) and other targets need to be measured. The current literature’s major drawback in performing such a measurement is the challenge of integrating different KPIs, each of which captures a specific aspect of the organisation’s performance. In my thesis, I highlight this drawback and present a Smart Buyer framework that is based on a Bayesian Network (BN) model capable of capturing and integrating the different KPIs. I firstly identify the metrics required for measuring and evaluating the procurement performance and, secondly, develop a Bayesian Network based model for integrating them. The measured procurement performance value can then be used by organisations to identify the areas in which they need to improve and develop. Four scenarios are presented to show how the proposed BN model can be further used for analysis and decision-making within organisations. Finally, a recent real-world procurement example is studied to demonstrate the applicability of the proposed Smart Buyer framework. In addition to procurement performance measurement, I demonstrate a novel methodology and technique for procurement performance management and prediction. While performance measurement measures the performance of procurement practices in the past, performance management focuses on strategies and methods to maintain an acceptable level of performance in the organization’s procurement practices. Finally, performance prediction focuses on the organisation’s prospective procurement performance, which is also important for strategic planning in the organisation.