To mitigate costly delays in freight transportation, our sponsor, a leading FMCG multinational, sought a systematic solution to reduce shipment lead times during frequent, low-impact disruptions. While their lane managers typically rely on experience-based decisions, the absence of a standardized approach leaves opportunity on the table. We developed a prescriptive optimization model that recommends intervention actions for delayed shipments, balancing lead time recovery with financial and operational constraints. Our model formulated as a Mixed Integer Program (MIP) suggests which shipments to prioritize and which interventions to apply, given each lane’s budget and operational parameters. It mirrors supplier selection frameworks and was validated through simulation using 12 months of historical shipment data from three distinct lanes.
