Market Versus Location
Demand forecasting is supposed to estimate market demand. Customers in a region buy products. The forecast should therefore represent demand from that market.
Yet many planning systems store forecasts against warehouses or factories. The demand is effectively assigned to a specific supplying location even before the supply plan begins.
This practice introduces a conceptual mistake.
Forecasts represent customer demand. They do not represent where the product will be supplied from.
The supply plan should decide that.
The Location Illusion
This confusion usually appears in organizations that operate multiple supply options. A product might be produced internally. It might be sourced from an external plant. It might be manufactured by a subcontractor. It might even be shipped directly from another distribution center.
Enterprise systems such as SAP explicitly support these possibilities through mechanisms like special procurement, subcontracting, drop shipping, and inter plant transfers.
When these options exist, attaching demand to a specific warehouse or factory prematurely restricts the planning model.
The demand becomes artificially tied to a location that may not be the best source of supply.
Service Level Distinction
The real reason companies sometimes value forecasts at intermediate locations is not operational necessity but service level management.
Different customers receive different service priorities. Some customers are strategically important. Some are geographically distant. Some generate high volumes. Others operate through specific channels such as distributors or retailers.
To handle these distinctions planners often group customers according to meaningful criteria. Size, geography, strategic importance, and order volume all become possible grouping dimensions.
These groups can then be represented as virtual demand locations within the supply network.
Forecasts are valued against those demand clusters rather than against individual factories.
Supply planning then determines which manufacturing or distribution location should fulfill that demand.
Virtual Demand Locations
This structure reflects the true logic of network planning.
Customer demand is aggregated into logical groups. These groups behave like demand nodes in the network. Multiple supply nodes can potentially serve them.
The planning system then evaluates sourcing options based on cost, capacity, service rules, allocation priorities, and other constraints.
The network remains flexible.
No single plant is assumed to be the permanent source of supply.
Default Plant Myth
Many organizations resist this approach because their order processing systems contain a default delivery plant within the customer master record.
That default value often becomes the basis for forecasting and planning.
In practice it represents little more than a starting assumption.
Real operations frequently override that assumption. Large orders may be split across several plants. Urgent deliveries may be sourced from a different warehouse if inventory exists there. Capacity constraints may force production to shift temporarily between plants.
The existence of a default delivery plant does not mean the supply network behaves that way.
Network Reality
Over time supply networks behave in ways that no planner originally intended.
A manufacturing plant located in the south may occasionally supply a northern distribution center. A subcontractor may temporarily produce a product that normally belongs to an internal facility. Inventory may be transferred across regions to handle unexpected demand spikes.
These deviations occur because capacity constraints, transportation costs, and demand fluctuations continuously reshape the optimal supply path.
The network evolves.
Planning models must therefore reflect that flexibility.
Forced Demand
When forecasts are attached directly to specific plants or warehouses, the planning model quietly forces demand onto those locations.
The supply network disappears from the calculation.
Instead of exploring multiple sourcing possibilities, the system simply assumes that a particular plant will serve the demand because that is where the forecast was placed.
Planners sometimes justify this approach with historical evidence. Ninety five percent of past demand may have been supplied from that plant.
Historical behavior does not define future optimal supply paths.
It merely describes how the network happened to function previously.
Forecast Consumption
Another layer of complexity appears in discussions about forecast consumption.
Many planning systems contain elaborate mechanisms for reducing forecast quantities when actual customer orders arrive. Consultants often treat these features as essential components of demand planning.
For companies operating entirely in make to stock environments, this concern is frequently exaggerated.
If production is driven almost entirely by forecasts, the operational focus should remain on maintaining adequate inventory to serve expected demand.
Complex forecast consumption logic rarely improves decision quality in such environments.
Planning Discipline
Demand forecasts should therefore represent market demand independently of supply locations. Customer groups or regions provide a more accurate anchor for forecasting.
Supply planning should then determine how the network fulfills that demand.
When forecasts are prematurely attached to factories or warehouses, planning quietly abandons network optimization. Demand is forced into predetermined supply paths.
A supply network with multiple plants and warehouses will never remain static for long. Capacity shifts, demand growth, and operational disruptions constantly reshape how products move through the system.
Planning models should reflect that reality rather than pretending that supply always originates from a fixed location.
