Demand Planning and Forecasting Course
Build a reliable demand-planning process covering history, baseline forecasting, accuracy and bias, overrides, promotions, new products, consensus planning and S&OP handoff. Includes practical cross-functional tools and applied decision exercises.
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The Forecast Is Not a Number the Demand Planner Owns. It Is a Decision the Business Has to Live With.
Every downstream plan inherits the demand signal.
If the forecast is consistently high, inventory builds, cash is trapped and capacity is booked unnecessarily. If it is consistently low, service fails, expedites increase and sales opportunities are missed. If the forecast changes constantly inside the operational time fence, supply teams stop trusting it. If sales overrides the model without evidence, the process becomes politics. If planners refuse commercial input because "the system says otherwise," it becomes equally fragile.
Current ASCM guidance describes demand planning as a cycle role measured on forecast accuracy, bias and service rather than modelling alone. IBF similarly treats demand planning and forecasting as both process and analysis, with consensus, demand management, new-product planning and S&OP/IBP interfaces as core parts of the discipline.
This course builds that whole operating system: the data, the forecast, the judgment, the metrics, the collaboration and the monthly decisions that convert uncertainty into a usable plan.
ASCM Demand Planning 2026 · IBF Demand Planning & Forecasting 2026 · IBF Forecasting Curriculum. Source-specific requirements always depend on the controlling agreement and current guidance.
Demand planning becomes unreliable when:
- the business cannot agree what level or horizon the forecast should be produced at
- historical data is used without correcting for stockouts, one-off events or structural changes
- every forecast error is blamed on the model even when assumptions or data caused the miss
- sales, marketing and finance maintain separate numbers
- planner overrides are accepted without reason codes or later review
- forecast accuracy is measured in a way that hides persistent bias
- new products are forecast as though they have stable history
- promotions and price changes are added manually without learning from prior events
- forecast changes inside frozen or constrained periods destabilise supply
- demand planning ends with a number instead of a documented view of risks, opportunities and assumptions
- the demand plan does not connect cleanly into supply planning and S&OP/IBP.
How This Applies Across the Markets MATSH Serves
GCC
Applications include fast growth, imported supply, long lead times, seasonal demand, major promotions, new market launches and planning across regional distribution networks where forecast changes can have large inventory consequences.
Africa
The course addresses volatile lead times, intermittent demand, multi-country planning, stockout-distorted history, imported versus local supply and the need for practical forecasting processes even where systems and data maturity vary.
Asia
Participants work with high-volume planning, manufacturing dependencies, product proliferation, channel complexity and short commercial cycles where granularity and process discipline become critical.
Europe
Applications include mature S&OP/IBP environments, multi-market demand, promotional planning, regulatory or sustainability-driven product changes and structured measurement of forecast performance. These are contextual lenses, not assumptions about every organisation in a region.
Who Should Attend
Demand Planners and Forecast Analysts
Responsible for producing and improving the demand plan.
Supply Chain and Planning Managers
Accountable for the process that connects demand with supply, inventory and capacity.
Sales and Commercial Planning Professionals
Contributing market intelligence, promotions, customer changes and opportunity/risk assumptions.
Inventory and Supply Planners
Needing to understand the quality and behaviour of the demand signal they plan against.
S&OP / IBP Teams
Using demand planning as the first formal input into cross-functional business planning.
Analysts Moving Into Planning Roles
Building the practical process and forecasting discipline expected in demand-planning work.
What You Will Leave With
A complete demand-planning cycle you can operate and improve.
Programme Curriculum
Why this module matters: Many forecasting disputes are actually process-design disputes. Teams argue about the number when they have never agreed the forecast level, time horizon, ownership or decision rules. Participants learn to:
- distinguish demand planning, demand management and statistical forecasting
- define what the demand plan is used for across supply, inventory, finance and commercial teams
- choose forecast level: item, item-location, customer, channel or product family
- define planning horizon and time buckets
- understand forecast lag and why accuracy depends on when the forecast is frozen
- set time fences and change-control rules
- define roles for demand planning, sales, marketing, finance and supply
- establish one consensus-demand process
- define which assumptions must accompany the number
- build a monthly demand-planning calendar.
Workshop: Design the demand-planning operating cycle for a sample business.
Why this module matters: Historical sales are not the same as historical demand. Stockouts, lost sales, promotions, one-off orders and supply constraints can all corrupt the signal before the model sees it. Participants learn to:
- distinguish shipment/sales history from unconstrained demand
- identify missing, abnormal and censored demand history
- correct for stockouts and known exceptional events
- identify level, trend, seasonality and intermittency
- segment items by demand behaviour
- choose simple baseline methods appropriately
- understand moving average, weighted average and exponential-smoothing logic at an applied level
- avoid overfitting with unnecessary model complexity
- establish a statistical baseline before applying judgment
- document data adjustments so the process remains auditable.
Workshop: Clean a demand-history dataset and choose baseline methods for different product patterns.
Why this module matters: A single accuracy percentage can create the wrong behaviour if the metric, denominator, hierarchy or lag is poorly chosen. Bias can be even more damaging because persistent over- or under-forecasting quietly drives inventory and service problems. Participants learn to:
- define forecast error and compare common accuracy approaches
- understand practical strengths and weaknesses of MAPE and related measures
- measure bias separately from absolute error
- choose the level at which performance should be reviewed
- avoid averaging metrics in mathematically misleading ways
- compare model forecast versus final consensus forecast
- measure Forecast Value Added from overrides and process steps
- identify persistent planner, customer, product or channel patterns
- separate random variation from systematic process failure
- build a monthly forecast-performance review.
Workshop: Diagnose forecast performance and identify which process steps add or destroy value.
Why this module matters: The hardest demand-planning cases are exactly the ones where history is least trustworthy. Judgment is necessary, but unmanaged judgment can destroy a good baseline faster than any statistical model. Participants learn to:
- use commercial intelligence without turning forecasting into opinion
- require reason codes and evidence for material overrides
- evaluate whether overrides improved the forecast after the event
- forecast promotions using comparable-event logic
- separate base demand from incremental promotional uplift
- approach new-product forecasting using analogues, ranges and staged learning
- manage product phase-in and phase-out
- identify demand that can be shaped when supply is constrained
- distinguish real demand sensing from reacting to short-term noise
- create scenario ranges where uncertainty is genuinely high.
Simulation: Resolve a forecast dispute involving a promotion, constrained supply and conflicting commercial assumptions.
Why this module matters: Demand planning creates value only when the rest of the business can plan against it. The monthly process needs to convert data and market intelligence into a single approved view of expected demand and its risks. Participants learn to:
- prepare the demand review around exceptions rather than every SKU
- reconcile sales, marketing and planner assumptions
- distinguish base forecast, opportunities, risks and management actions
- define approval and escalation rules for disputed forecasts
- connect demand scenarios to supply and capacity consequences
- prepare demand inputs for S&OP/IBP
- communicate uncertainty without weakening accountability
- monitor customer service, inventory and forecast performance together
- maintain assumptions between planning cycles
- continuously improve the planning process as products, markets and systems change.
Capstone: Present a complete monthly demand review pack with forecast, assumptions, risks, opportunities and S&OP handoff.
Common Questions
A Forecast Nobody Trusts Is Just Another Spreadsheet. A Demand Plan the Business Can Operate Against Is a Management System.
Build the process, analytical judgement and cross-functional discipline behind a credible demand plan.
📅 Upcoming Schedules — View dates and locations ▾
We run this course as a private programme for organisations. Bespoke dates, tailored content, group pricing.
Every course starts with a needs assessment and includes structured follow-up at three points after it ends.
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