Smart routing and demand prediction across a distribution network.
Warehouse and distribution intelligence covering route optimisation and demand prediction. The client has asked not to be named, and no performance figures are published.
How it is put together
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What we built.
Distribution runs on two decisions repeated endlessly: what to hold and where, and what order to visit. Get the first wrong and stock sits in the wrong depot. Get the second wrong and the fleet drives further than it needs to, every day, permanently.
Moweb built the intelligence layer over both: prediction to inform what the network should be holding, and routing to decide how it moves.
The client is not named here and no figures are published. What follows is the shape of the problem and the approach, not measured results.
Key challenges
The constraints below apply to routing and forecasting work generally; the specifics of this network are confidential.
- 1Routing is constrained, not just optimised. Vehicle capacity, delivery windows, driver hours and access restrictions all bound what counts as a valid route before anything can be made shorter.
- 2Forecasts are only as good as the history behind them. Promotions, stockouts and one-off events all sit in the data looking like demand, and a model that treats them as demand will plan for them again.
- 3Optimising on data the operation does not trust produces precise answers to the wrong question. Data quality is the prerequisite, not a later phase.
- 4A route the drivers will not follow saves nothing. Plans have to survive contact with how the work is actually done.
Our solutions
What was built:
- Route optimisation for distribution, working within the network's real operating constraints rather than against a clean-sheet model.
- Demand prediction feeding what the network plans to hold and move.
- Warehouse and distribution intelligence tying the two together, so forecasting and routing inform each other rather than running as separate exercises.
More case studies.
Proof
Work we have shipped.
Distribution network worth optimising?
The first question is usually whether the data supports it. We can assess that before proposing any modelling.