Business-focused studies generated from the simulation engine. Each case is written from a planning decision perspective, with explicit assumptions, observed trade-offs, and measurable KPI impact.
Where should the network invest to improve service economics: more inventory, more capacity, or shorter lead times?
A multi-echelon network tested across lead-time profiles, capacity multipliers, and demand families, with results read through service, required coverage, total cost, and upstream cost burden.
Lead-time structure dominates the economics: capacity trims coverage needs at the margin, but shorter lead times shift the entire cost-service frontier and reduce the inventory burden most visibly.
Open case study 1Stock allocation under shortage, forecasting under demand distortion, and inventory policy comparison under service-level constraints.