Purpose-By constantly working in environments with high degree of uncertainty, humanitarian organizations end up becoming specialists in the implementation of agile systems. Their counterparts in profit-making organizations have a lot to learn from them in this domain. Volatility of demand, imbalance between supply and demand and disruptions are all factors that affect commercial supply chains and call for a high level of agility. The aims of this paper are twofold: first, to clearly define the concept of supply chain agility, and second, to build a model for assessing the level of agility of a supply chain. Design/methodology/approach-Three approaches are used in this research: literature review, case study and symbolic modeling. Findings-The paper developed first, a framework for defining supply chain agility and second, a model for assessing and improving the capabilities of humanitarian and commercial supply chains in terms of agility, based on an analysis of humanitarian approaches. Research limitations/implications-The model has been developed thanks to inputs from humanitarian practitioners and feedbacks from academics. The practical application to various humanitarian relief operations and commercial supply chains is yet to be done. Originality/value-This paper contributes significantly to clarifying the notion of supply chain agility. It also provides a consistent, robust and reproducible method of assessing supply chain agility, which seems appropriate for both humanitarian and business sectors. Finally, it is complementary to existant research on humanitarian logistics. It shows that though humanitarian professionals have a lot to learn from the private sector, the reverse is also true.

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International audienceIncreasingly, humanitarian organizations have opened regional warehouses and pre-positioned resources locally. Choosing appropriate locations is not easy and frequently based on opportunities rather than rational decisions. Dedicated decision-support systems could help humanitarian practitioners design their supply networks. Academic literature suggests the use of commercial sector models but rarely considers the constraints and specific context of humanitarian operations, such as obtaining accurate data, high uncertainties, limited budgets and increasing pressure on cost efficiency. We propose a tooled methodology to properly support humanitarian decision makers in the design of their supply chains. Our contribution is based on the definition of aggregate scenarios to reliably forecast demand using past disaster data and future trends. Demand for relief items based on these scenarios is then fed to a mixed-integer linear programming model in order to improve current supply networks. The specifications of this model have been defined in close collaboration with humanitarian workers. The model allows analysis of the impact of alternative sourcing strategies and service level requirements on operational efficiency. It provides clear and actionable recommendations for a given context, bridging the gap between academics and humanitarian logisticians. The methodology was developed to be useful to a broad range of humanitarian organizations, and a specific application to the supply chain design of the International Federation of Red Cross and Red Crescent Societies is discussed in detail

Humanitarian supply chains (HSC) can be considered a new research area. The number of applied scientific publications has considerably increased over the past 15 years. About half of this research work uses quantitative techniques as optimisation decision-support systems. But due to the recentness of this academic area, researchers are finding it difficult to develop accurate, and above all, reliable mathematical models to support their steps towards improvement. This is particularly true concerning the crucial problems of coordination in HSCs. This paper tackles the issue by developing an original quantitative modelling support method. Based on enterprise modelling methodologies, we propose a business process modelling approach that helps in understanding, analysing, evaluating and then developing the formal expression of an HSC. Such a model, therefore, clearly has an added value for practitioners and should enable relevant quantitative models to be produced. Finally, an application on the emergency response processes of the International Federation of Red Cross is detailed in order to validate the relevance and the applicability of our proposal. This experiment allows all the variables and parameters that should be useful for improving the efficiency of the network to be identified.