A hybrid model for ranking critical successful factors of Lean Six Sigma in the oil and gas industry

Abstract

Purpose The aim of this paper is to find and prioritise multiple critical success factors (CSFs) for the implementation of LSS in the oil and gas industry. Design/methodology/approach Based on a preselected list of possible CFSs, experts are involved in screening them with the Delphi method. As a result, 22 customised CSFs are selected. To prioritise these CSFs, the step-wise weight assessment ratio analysis (SWARA) method is applied to find weights corresponding to the decision-making preferences. Since the regular permutation-based weight assessment can be classified as NP-hard, the problem is solved by a metaheuristic method. For this purpose, a genetic algorithm (GA) is used. Findings The resulting prioritisation of CSFs helps companies find out which factors have a high priority in order to focus on them. The less important factors can be neglected and thus do not require limited resources. Research limitations/implications Only a specific set of methods have been considered. Practical implications The resulting prioritisation of CSFs helps companies find out which factors have a high priority in order to focus on them. Social implications The methodology supports respective evaluations in general. Originality/value The paper contributes to the very limited research on the implementation of LSS in the oil and gas industry, and, in addition, it suggests the usage of SWARA, a permutation method and a GA, which have not yet been researched, for the prioritisation of CSFs of LSS.

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