A Theoretical Decision Making Framework on the Assessment of Leagility Index in a Supply Chain Management

Abstract

Recent market globalization has enforced the manufacturing as well as service industries not only to ensure product variety, but also to make every effort for the lowest product price and the ability to respond quickly to the uncertain volatile marketplace. For successful survival in the highly competitive global business environment, manufacturing paradigm has shifted from ‘lean’ towards ‘agile’ and now towards the more advanced ‘leagile’ principles. Leagile approach is basically the combination of lean and agile principles in which leanness emphasizes on elimination of ‘wastes’ whereas agility introduces speediness, flexibility as well as responsiveness into the manufacturing system. Therefore, leagile concept explores the salient features of both lean and agile approaches which help manufacturing organizations (as well as service sectors) to gain competitive business advantage. The extent of leagility is indeed very difficult to compute due to existence of ill-defined (vague) performance indices whose evaluation is based on human judgment only. Since subjective human judgment often bears some kind of imprecision, uncertainty as well as vagueness; application of traditional decision making tools and techniques seem inappropriate in this context. In order to tackle such inconsistency and incompleteness in the said decision-making process; present work proposes a theoretical framework towards supply chain leagility assessment in fuzzy environment. Fuzzy numbers set theory, fuzzy operational rules and the concept of fuzzy degree of similarity have been explored to compute supply chain’s overall leagility index and finally, to identify ill(poor)-performing supply chain areas (barriers of leagility). A case empirical example has also been provided.