Advanced Demand Planning and Supply Chain Forecasting Training Course

Overview

Advanced Demand Planning and Supply Chain Forecasting is a one-week course for demand, supply, inventory, procurement, logistics, commercial, operations, S&OP, and IBP functions who leave with a Demand Planning Forecast and Decision File. The course connects demand history, segmentation, statistical baselines, causal events, new-product and intermittent demand, accuracy, bias, Forecast Value Added, scenarios, consensus, inventory, and service decisions through an exception-led planning cycle. Agile Leaders Training Center presents advanced demand planning and forecasting as traceable decision practice.

Who Should Attend

• Demand-planning functions responsible for baseline forecasts, overrides, consensus, and performance review
• Supply-planning functions responsible for capacity, material, inventory, and service handoffs
• Commercial functions responsible for promotions, launches, customer intelligence, and event assumptions
• Operations and logistics functions responsible for constraints, replenishment, and execution signals
• Planning-governance functions responsible for S&OP, IBP, exceptions, and decision records

The course assumes participants work with demand history, planning calendars, or forecast reviews and leaves out introductory spreadsheet skills, software configuration, and AI model development.

Departments and Industries

The course supports demand decisions across product and service supply chains.

• Demand planning, supply planning, inventory, procurement, and logistics departments
• Sales, marketing, finance, commercial analytics, and customer operations teams
• Manufacturing, retail, distribution, and consumer-goods sectors
• Healthcare, energy, transport, technology, and professional-service sectors
• S&OP, IBP, portfolio, and operations-governance functions

Learning Objectives

By the end of this course, participants will be able to:

• Analyze demand history, patterns, segments, hierarchies, and data quality.
• Compare baseline forecasting methods and coherent hierarchy choices.
• Evaluate causal events, launches, intermittent demand, and scenarios.
• Apply accuracy, bias, tracking, and Forecast Value Added measures.
• Build consensus demand reviews, exception routes, and S&OP handoffs.
• Use forecast decisions to assess inventory, capacity, and service effects.

Course Agenda

Day 1: Demand Data and Planning Structure

• Demand History Cleaning and Data-Quality Decision Log
• Trend, Seasonality, Lifecycle, and Event Pattern Map
• Volume-Variability and Planning-Behavior Segmentation Matrix
• Product, Customer, Channel, and Location Forecast Hierarchy
• Planning Horizon, Time Bucket, and Ownership Design Canvas

Day 2: Statistical Baselines and Reconciliation

• Naive, Moving-Average, and Exponential-Smoothing Baseline Comparison
• Trend and Seasonal Component Decomposition Method
• Prediction Interval and Forecast Uncertainty Record
• Bottom-Up, Top-Down, and Reconciled Hierarchy Decision Grid
• Baseline Model Selection and Assumption Register

Day 3: Drivers, Events, and Special Demand

• Causal Driver and Predictor Evidence Map
• Promotion, Price, Campaign, and Calendar Event Adjustment Protocol
• New-Product Analogy and Lifecycle Assumption File
• Intermittent, Lumpy, and Low-Volume Demand Treatment Matrix
• Scenario Range, Trigger, and Contingency Planning Sheet

Day 4: Accuracy, Consensus, and Supply Handoff

• Forecast Error, Accuracy, and Bias Metric Scorecard
• Tracking Signal and Persistent-Bias Escalation Rule
• Forecast Value Added Review and Override Challenge Log
• Collaborative Demand Review and Consensus Decision Agenda
• S&OP and IBP Demand-to-Supply Handoff Pack

Day 5: Demand Planning Decision Simulation

• Exercise: Clean, Segment, and Structure a Demand History
• Exercise: Select and Reconcile a Statistical Baseline
• Exercise: Test Event, Launch, and Intermittent-Demand Adjustments
• Exercise: Diagnose Accuracy, Bias, Inventory, and Service Effects
• Capstone Exercise: Build the Demand Planning Forecast and Decision File

Practical Exercises

The course uses suggested activities to move from demand evidence to traceable cross-functional decisions.

• Suggested activity: clean a demand history, classify patterns, and select planning segments and hierarchy levels.
• Suggested activity: compare baselines and adjustments using accuracy, bias, uncertainty, and Forecast Value Added evidence.
• Suggested activity: conduct a consensus review and record assumptions, overrides, exceptions, owners, and escalation.
• Suggested activity: test demand scenarios against inventory, capacity, procurement, logistics, and service choices.

FAQs

Who suits advanced demand planning and forecasting training, and what does it assume?

It suits demand, supply, inventory, procurement, logistics, commercial, operations, S&OP, and IBP functions; it assumes participants work with demand history or forecast reviews.

How does advanced demand planning differ from general supply chain management training?

Advanced demand planning concentrates on data, forecasting methods, hierarchy, events, accuracy, bias, scenarios, consensus, and supply handoffs rather than the full sourcing, production, logistics, and supplier-management scope.

How should demand planners select a forecasting method?

Demand planners should compare data quality, pattern, volume, variability, horizon, hierarchy, uncertainty, error, bias, operational use, and the stability of causal drivers before selecting and documenting a method.

What do forecast accuracy, bias, and Forecast Value Added show?

Accuracy shows error magnitude, bias shows persistent over- or under-forecasting, and Forecast Value Added shows whether a process step or override improves or worsens the baseline.

How does a demand forecast enter S&OP and IBP decisions?

A demand forecast enters S&OP and IBP through a documented consensus plan, scenarios, assumptions, exceptions, financial implications, and a handoff for supply, inventory, capacity, procurement, logistics, and service decisions.

Conclusion

Participants take back a Demand Planning Forecast and Decision File. It connects demand data, segmentation, baselines, events, scenarios, accuracy, bias, value added, consensus, and supply handoffs. The capstone makes assumptions, exceptions, overrides, ownership, uncertainty, inventory effects, service effects, and escalation visible in one planning record.