Method
Constraint optimization
Turn forecasts into the best feasible action under real limits.
Constraint optimization explained
What it is
Compare feasible actions under agreed objectives, mandatory limits, risk requirements and authorised trade-offs. Budgets, capacity, lead times, MOQs and service requirements need explicit meanings.
Why it matters
A forecast tells you what is likely; it does not tell you what to do. Optimization does, within the constraints you actually operate under.
Where planning teams fail
Teams optimize one lever locally (e.g. price) and unintentionally hurt another (e.g. labor or cashflow).
How RabbitHawk applies it
RabbitHawk evaluates the objectives and constraints in the agreed deployment scope. Later amendments, transfers or premium supply can be included where genuinely available and worthwhile, with their costs, authority and response windows explicit.
Related methods
Keep exploring
- probabilistic forecasting
Probabilistic forecasting
Represent ranges and likelihoods alongside the central forecast.
- hierarchical reconciliation
Hierarchical reconciliation
Make forecasts coherent across the specified aggregation structure.
- forecast bias diagnostics
Forecast bias diagnostics
Find the systematic errors quietly distorting your plans.
Apply this to your data
See how RabbitHawk would use this method to improve your decisions.
Talk to our team