Evaluating petroleum supply chain performance: Application of analytical hierarchy process to balanced scorecard

Abstract

Performance evaluation in supply chain management (SCM) is not a straightforward task. This becomes even more complicated while evaluating a process industry supply chain because of its inherently different characteristics. The purpose of this paper is to suggest a method to evaluate the performance of one such process supply chain, namely the petroleum industry supply chain. The paper uses a combination of analytical hierarchy process (AHP) and balanced scorecard (BSC) for evaluating performance of the petroleum supply chain. The choice of factors determining supply chain performance under the four perspectives of BSC has been validated using opinion from subject matter experts (SMEs). In order to determine relative importance of criteria opinion of SMEs has been collected in the form of pairwise comparisons. Using these comparisons, the AHP technique has been applied to determine the relative weights of various perspectives as well as the factors under each perspective. The importance of four perspectives with respect to petroleum supply chain performance in descending order of importance comes out as: customer, financial, internal business process, innovation and learning. Within these perspectives, the following factors seem to be most important respectively: purity of product, market share, steady supply of raw material and use of information technology. Most research work has focused on discrete part manufacturing supply chains. Process industry supply chains deserve a different treatment due to their inherently different characteristics. The methodology suggested in this paper tries to include these characteristics and can help in comparing performance of supply chains of different petroleum companies. The value of this paper lies in the unique approach towards determining the performance of process industry supply chains. By using BSC, non-financial factors have also been taken into account. Opinion of SMEs has been quantified using the AHP technique thus converting qualitative data to quantitative data. © 2008, Emerald Group Publishing Limited