Supply chains now cope with a lot of uncertainties, and their stakeholders are intensely interconnected, revealing new opportunities at a tremendous pace. In this context, companies must rethink their decision support systems to remain competitive. Particularly strategic supply chain capacity planning systems that should ensure resource availability. Unfortunately, existing systems do not satisfactorily consider this new deal. Therefore, this paper develops a conceptual framework providing guidelines for designing a decision support system for strategic supply chain capacity planning under uncertainty. To validate the conceptual framework, a decision support system has been designed accordingly, and two industrial experiments have been conducted.

Many authors have highlighted gaps at the interfaces between supply chains (SCs) and demand chains. Generally, the latter tends primarily to be ‘agile’ by maximising effectiveness and responsiveness while the former tends to be ‘lean’ by maximising efficiency. When, in the SC, disruptions (that lead to stock-out situations) occur after customer orders have been accepted, managers are faced with the problem of maximising customer satisfaction while taking into consideration the conflicting objectives of the supply and demand sides of the order fulfilment process. This article proposes a cross-functional multi-criteria decision-making (advanced available-to-promise) tool that provides different strategic options from which a solution can be chosen. It also proposes a performance measurement system to support the decision-making and improvement process. The results of some experimental tests show that the model enables to make strategic decisions on the degree of flexibility required to achieve the desired level of customer service.