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Demand forecasting, sales forecasting, and demand planning—three terms that are often used interchangeably in everyday language, yet mean different things. Anyone evaluating software or setting up processes will sooner or later come across these differences. This article clarifies the terms—briefly, precisely, and with a focus on practical applications.
Demand Forecast: What the Market Wants
The demand forecast estimates how much customers want to buy—regardless of whether the business can fulfill those orders. It is the purest form of forecasting: How many guests will come on Tuesday? How many croissants would be bought in this kind of weather?
The subtle but important point: Demand cannot be directly observed. You can only sell what’s available—a product that sold out at 2:00 p.m. may have had more demand than the sales figures indicate. Good forecasting systems take such sell-out effects into account rather than misinterpreting them as “no demand.”
Sales Forecast: What Will Be Sold
The sales forecast estimates the actual quantity sold—the result of demand and availability. In day-to-day retail and foodservice operations, it is the most important metric in practical terms, as it is directly measurable and directly relevant to planning: units sold per item, location, and day.
In practice, demand and sales forecasts are intentionally blurred: Good planning ensures that supply and demand are in balance—in which case both forecasts are identical. You can find the definition of a sales forecast, along with methods and examples, in the introductory article “What Is a Sales Forecast?”
Demand Planning: What This Means
Demand planning (Demand Planning / Material Requirements Planning) is the next step: It translates the forecast into concrete decisions—production volumes, purchase orders, raw material requirements, and, in some cases, staffing. “45 braided rolls will be sold tomorrow” translates into: purchasing flour, butter, and yeast; determining dough quantities in production; and preparing baking instructions for the early shift.
Demand planning thus also includes operational decisions that go beyond mere forecasting: safety stock, lot sizes, minimum order quantities, and shelf life. The forecast provides the foundation—planning sets the rules on top of it.
The Interplay of the Three Concepts
Simplified as a chain: Demand forecast (what the market wants) → Sales forecast (what will be sold) → Requirements planning (what will be produced and ordered). In modern systems, these steps are integrated: GoNina forecasts sales per item and location for the next seven days—including a clearance adjustment to reflect actual demand—and translates the result directly into order recommendations that feed back into the point-of-sale system or production planning. Forecasting and demand planning thus become a seamless process rather than separate Excel steps.
Frequently Asked Questions
What aspect should I evaluate when assessing software?
All three as a chain: Does the system learn from sales data (sales volume)? Does it adjust for sales (demand)? And does it translate the forecast into specific ordering or production recommendations (demand)? A system that covers only one step leaves the work to people.
What about "sales forecast"?
The sales forecast converts sales volumes into monetary terms—which is relevant for financial planning and controlling, but for production and purchasing, it's the volumes that matter.
Is demand planning the same as MRP in an ERP system?
MRP (Material Requirements Planning) is the industrial application of demand planning—the same logic, usually involving bills of materials and longer time horizons. In the baking and foodservice industries, recipes serve the same purpose as bills of materials.
Conclusion
Demand is what the market wants; sales are what is sold; and requirements are what result from this in terms of production and purchasing. Those who clearly distinguish between these three terms can evaluate software more precisely and identify more quickly where the gap lies in their own process—usually between the forecast and the actual order proposal.
To learn what this end-to-end process looks like in practice, check out the guide to AI sales forecasting for bakeries.
