Data, analytical techniques and collaboration between researchers and practitioners in humanitarian health supply chains: a challenging but necessary way forward

Author:

De Boeck Kim,Besiou Maria,Decouttere Catherine,Rafter Sean,Vandaele Nico,Van Wassenhove Luk N.,Yadav Prashant

Abstract

PurposeThis paper aims to provide a discussion on the interface and interactions between data, analytical techniques and impactful research in humanitarian health supply chains. New techniques for data capturing, processing and analytics, such as big data, blockchain technology and artificial intelligence, are increasingly put forward as potential “game changers” in the humanitarian field. Yet while they have potential to improve data analytics in the future, larger data sets and quantification per se are no “silver bullet” for complex and wicked problems in humanitarian health settings. Humanitarian health supply chains provide health care and medical aid to the most vulnerable in development and disaster relief settings alike. Unlike commercial supply chains, they often lack resources and long-term collaborations to enable learning from the past and to improve further.Design/methodology/approachBased on a combination of the authors’ research experience, interactions with practitioners throughout projects and academic literature, the authors consider the interface between data and analytical techniques and highlight some of the challenges inherent to humanitarian health settings. The authors apply a systems approach to represent the multiple factors and interactions between data, analytical techniques and collaboration in impactful research.FindingsBased on this representation, the authors discuss relevant debates and suggest directions for future research to increase the impact of data analytics and collaborations in fostering sustainable solutions.Originality/valueThis study distinguishes itself and contributes by bringing the interface and interactions between data, analytical techniques and impactful research together in a systems approach, emphasizing the interconnectedness.

Publisher

Emerald

Subject

Management Information Systems

Reference49 articles.

1. Big data and disaster management: a systematic review and agenda for future research;Annals of Operations Research,2019

2. Resource allocation with sigmoidal demands: a data-driven approach to managing mobile healthcare units;Manufacturing and Service Operations Management,2022

3. Big data for development: applications and techniques;Big Data Analytics,2016

4. Addressing the challenge of modeling for decision-making in socially responsible operations;Production and Operations Management,2015

5. Humanitarian operations: a world of opportunity for relevant and impactful research;Manufacturing & Service Operations Management,2020

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