Hospital, retail and tender demand don't behave alike. Plan them apart.
Take a portfolio forecast bias of −0.5%. It looks like a team doing its job. Cut the same demand by channel and it can turn out to be +3.0% on hospital and −3.2% on tender.
That is what happens when demand is planned at the level it is reported at instead of the level it behaves at. Hospital volume is contract-shaped. Retail pharmacy is seasonal.
Tender is lumpy, binary and enormous when it lands. Average them into one line per SKU and the plan is wrong in a different way every month.
You can only fix a forecast problem you can see. Segmented demand shows you which part of the business to work on this month.
Channel, therapy area, customer, market: you define the demand dimensions your business actually plans by. It is your catalog, not a fixed list we ship.
Switch the grouping and the entire demand hierarchy re-cuts along the dimension you picked. No rebuild, no export, and no second plan to keep in step.
Forecast accuracy, error and bias report against the same dimensions as the plan, so a healthy portfolio number cannot hide two unhealthy segments.
A demand node is item × location × your dimensions, and the dimensions are part of the node’s identity rather than a tag added afterwards. The same SKU can be hospital demand in one market and tender demand in another, and the plan treats them as the different things they are.
Channel and therapy area are examples, not built-ins. The catalog is defined per customer, and a value that is not in it is rejected rather than quietly creating a new node, so segments stay clean as the data grows.
The grouping selector offers product family, location and item alongside every dimension that has values on your nodes. Pick one and the plan, the drill-downs and the numbers all follow. The same demand, seen the way you need to see it.
The forecast review stops being a conversation about one number and becomes a conversation about which segment to fix first.
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