Demand Planning is a collaborative forecasting solution that helps businesses create more accurate and reliable demand forecasts.

Rather than relying solely on historical sales, Demand Planning combines statistical forecasting with planner insight to produce forecasts that better reflect expected future demand.

Historical demand is first prepared to remove or correct anomalies. A statistical forecast is then generated using that prepared history. Planners refine the forecast using their business knowledge before approving it for use throughout the app.

This creates a forecasting process that is both data-driven and flexible, allowing forecasts to evolve as new information becomes available.

Demand Planning provides greater control over the forecasting process while maintaining a consistent planning methodology across the business.

Key capabilities include:

Together, these capabilities help create forecasts that are transparent, explainable, and consistently aligned with business expectations.

Demand Planning consists of four primary stages.

Historical demand forms the foundation of every forecast.

Before forecasting begins, historical demand should be reviewed to ensure it represents meaningful demand patterns rather than temporary or exceptional demand.

Preparing history first improves the quality of the statistical forecast and reduces the need for unnecessary forecast adjustments later.

➜ For more on this topic, read: Demand Planning: Cleansing Sales History

Demand Planning uses hierarchies and attributes to organize demand into meaningful structures.

These structures allow planners to review and refine demand at the level that best supports the current planning decision.

Navigation is used throughout the planning process rather than only after historical demand has been prepared. A hierarchy must already be applied before demand information can be displayed and reviewed.

➜ For more on this topic, read: Demand Planning: Navigating

Demand Planning provides multiple views that present the same demand from different perspectives.

Each view is designed to support a particular planning activity, whether reviewing demand, comparing hierarchy levels, or analyzing forecast performance.

Although each view displays the same underlying data, it provides a different way to interpret and work with that information.

➜ For more on this topic, read: Demand Planning: Utilizing Views

Once historical demand has been prepared, Demand Planning generates a statistical baseline forecast.

Planners then refine that forecast using business knowledge, promotions, adjustments, overrides, lifecycle planning, and other forecasting tools to create a Working Forecast that better reflects expected future demand.

When planning is complete, the Working Forecast is finalized as the Final Forecast for use throughout the app.

For example:

➜ For more on this topic, read: Demand Planning: Forecast Refinement & Demand Planning: Forecasting Effectively

⚠️ Watchout: The four stages provide a logical structure for the articles in this collection. Navigation and Selecting Views are used throughout Demand Planning and may be revisited during cleansing, refinement, and performance review.

Demand Planning separates forecasting into three distinct forecast measures.

Each represents a different stage of the planning process and serves a specific purpose.

Understanding how these measures relate to one another provides a clearer picture of how forecasts evolve from statistical predictions into approved planning decisions.

The Computer Forecast is the statistical forecast generated from prepared historical demand.

It represents the app's recommended forecast before any business knowledge has been applied, providing an objective baseline from which planners can begin forecasting.

The Computer Forecast remains available for comparison throughout the planning process.

The Working Forecast represents the forecast currently being refined.

As planners apply promotions, adjustments, overrides, lifecycle planning, and other forecast refinements, the Working Forecast evolves to reflect expected future demand.

This allows planners to compare the original statistical forecast with the forecast shaped by business knowledge before it is approved.

The Final Forecast is the approved version of the forecast.

Once finalized, it becomes the forecast used throughout the app for downstream planning activities.

If business conditions change, the Working Forecast can continue to be refined and finalized again, ensuring the Final Forecast always reflects the latest approved planning decisions.

Demand Planning supports planning at multiple levels within the hierarchy.

Rather than requiring forecasts to be refined item by item, planners can work at the level where they have the strongest business insight.

For example, one planner may review demand at a product category level, while another may refine forecasts for a specific customer, location, or individual product.

When changes are made at higher levels, Demand Planning automatically distributes those changes throughout the hierarchy while maintaining proportional relationships between lower-level members.

This enables efficient planning across both small and large demand models while preserving consistency throughout the hierarchy.

Demand Planning is an ongoing process rather than a single planning activity.

As demand changes and new information becomes available, forecasts should be continually reviewed, refined, and improved.

Forecast performance provides valuable feedback that helps planners make better forecasting decisions over time, creating a continuous cycle of improvement rather than a single forecasting exercise.

Demand Planning follows a continuous improvement cycle.

Repeating this cycle helps improve forecast quality while ensuring planning decisions remain aligned with changing business conditions.

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