A review of lean and agile management in humanitarian supply chains: analysing the pre-disaster and post-disaster phases and future directions

Upadhyay, Arvind ORCID: https://orcid.org/0000-0002-6906-5369, Mukhuty, Sumona, Kumari, Sushma, Garza-Reyes, Jose Arturo ORCID: https://orcid.org/0000-0002-5493-877X and Shukla, Vinaya ORCID: https://orcid.org/0000-0002-2546-4931 (2020) A review of lean and agile management in humanitarian supply chains: analysing the pre-disaster and post-disaster phases and future directions. Production Planning & Control . pp. 1-14. ISSN 0953-7287 [Article] (Published online first) (doi:10.1080/09537287.2020.1834133)

Abstract

Disasters have quadrupled over the last two decades leading to unprecedented loss of life. The objective of disaster-focussed humanitarian supply chains (HSCs) is to ensure saving maximum lives with limited resources; despite severe uncertainties. Therefore, significant research has investigated lean and agile in HSCs; to effectively source and speedily deploy resources, with minimum wastage; in each disaster life-cycle phase. However, the literature and research findings are currently highly disjointed regarding how lean and agile principles may be aligned with different HSC activities in the disaster management lifecycle; and do not provide a collective understanding for practitioners and researchers. This paper reviews and organises the literature on HSCs in relation to lean and agile paradigms, focussing on the pre-disaster (mitigation and preparedness) and post-disaster (response and recovery) phases. Findings reveal, all phases benefit from both lean and agile, with agile benefitting the response phase most. The phases are inter-dependent and identifying optimum decoupling points for lean and agile principles are crucial. Majority research has focussed on individual or a couple of phases. Therefore, authors recommend research on integrating the functions of the different phases by employing lean and agile principles, to generate rapid response, economies of scale and cost minimisation.

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