Most planning teams already produce a forecast. The question is whether anyone trusts it enough to change a purchase order because of it.
Four properties tend to separate a forecast that drives decisions from one that gets overridden in the last meeting before the cycle closes.
It matches the decision it feeds
A forecast built at the wrong granularity is unusable no matter how accurate it is. If you place orders by SKU and warehouse, a forecast at brand and country level cannot answer the question you are asking.
Start from the decision: what is being committed, at what level, and how far ahead. The forecast granularity and horizon follow from that, not the other way around.
It comes with an error estimate
A single number invites false confidence. A forecast that reports its own historical error tells the planner how much safety stock the decision actually needs.
The useful comparison is not "how close was the forecast" but "how much better was it than a naive baseline". A model that cannot beat last period's actuals is not adding information.
It can be explained
When a forecast contradicts what the commercial team expects, someone has to reconcile the two. That conversation only works if the drivers behind the number are visible: seasonality, trend, promotions, price changes, and the events the model saw in history.
An unexplainable forecast gets overridden. An explainable one gets debated, and debate is where the planning value is.
It is reproducible
If rerunning the same inputs produces a different answer, the forecast cannot be audited. Versioned inputs, recorded model choices and stored metrics turn forecasting from an exercise into a process.
Where teams usually get stuck
Rarely at the modelling. Most teams stall on data preparation: inconsistent item codes, returns mixed into sales, stockouts recorded as zero demand, and history that lives across three systems.
That is the work worth investing in first. Model selection matters, but it matters less than feeding the model demand that reflects what customers actually wanted.