Scenario Modeling in Demand-Constrained Supply Chains: A Forecast to Delivery View

Demand-limited supply chains are continually challenged by the issues of globalizing production, stock, and delivery to satisfy the needs of customers that are dynamic and, in most cases, unpredictable. Scenario modeling is an analytical study technique that introduces a considered approach to the prediction of perturbations, optimum resource utilization, and the introduction of adaptive decision-making across the forecast-to-delivery spectrum. A recently performed survey provides an analysis of modern methods and the use of scenario modeling in the context of a demand-limited environment, with references to different industries, i.e., automotive manufacturing, healthcare, energy systems, and satellite communications. It explains the idea of supply chain responsiveness and resilience being enhanced with the assistance of systems thinking, simulation, additive manufacturing, edge computing, digital twins, and mixed-integer linear programming.
Another aspect that the paper demonstrates regarding supply chain design and performance is the impact of telecommunications infrastructure, policy intervention, climate needs, and macroeconomic forces. Using a multidisciplinary methodological approach to the solution, it can be indicated that the emergence of a situational framework—supported by the introduction of technologies and policy-oriented strategies—is one of the appropriate choices, offering a general response to an integrated and beneficial approach to supply chain management under circumstances of demand variability.