Stock levels, lanes and lead times were planned in separate spreadsheets. When a supplier slipped or demand moved, nobody could see the knock-on effect across the network until it had already happened.
Case study — Supply chain
An operational digital twin for an enterprise supply network.
How a planning team began testing inventory and routing decisions on a model of their network before committing real stock.
Client
Enterprise distributor (name withheld)
Disciplines
Simulation, forecasting, software
Engagement
Feasibility study, build, support
Delivered
Network simulation, demand forecasts, scenario planner
Fig. 1 — One of the warehouses represented in the model.
01The problem
02Our approach
The feasibility study rebuilt a past quarter of the network in simulation and checked it against what actually happened. Once it matched, we added demand forecasts and a scenario planner, so the team could try a change — a new lane, a different safety stock — and compare outcomes side by side.
“We argue about scenarios now, not about whose spreadsheet is right.”
Planning lead, client team — quote to be confirmed
SCENARIO B · SAFETY STOCK −10%
98.2%
service level held
Fig. 2 — The scenario planner (figures shown are illustrative).
03What we delivered
A simulation of inventory, lanes and lead times across the network, demand forecasts feeding it, and a scenario planner that reports results in service level, stock cover and cost.
04The result
Planning changes are now tested on the model before they reach the network. Replace this paragraph with the measured outcome once the client has approved the figures.