Demand Planning Course

Lesson 1 • What Demand Planning Is

Defines demand planning and distinguishes it from forecasting and replenishment. Establishes shared vocabulary used throughout the course.

Lesson 2 • Business Value of Accurate Demand Plans

Quantifies the cost of poor demand planning through service levels, inventory, and waste. Motivates precision as a financial and operational imperative.

Lesson 3 • Key Performance Indicators in Demand Planning

Introduces the metrics used to evaluate demand plan quality and process health. Students can select and define KPIs appropriate to their organisation.

Lesson 4 • Organisational Roles and Responsibilities

Identifies who owns, contributes to, and approves demand plans across functions. Clarifies accountability structures students will navigate on the job.

Lesson 1 • Internal Data Sources

Surveys transactional systems—ERP, POS, and order management—as primary data inputs. Students learn to extract and validate historical sales records.

Lesson 2 • Data Cleaning and Preparation

Teaches detection and correction of missing values, duplicates, and outliers in demand data. Clean data is the prerequisite for accurate statistical modelling.

Lesson 3 • Demand History Segmentation

Explains how to segment SKUs and customers to apply appropriate planning approaches. Segmentation reduces complexity and improves forecast accuracy.

Lesson 4 • Data Governance and Quality Standards

Establishes policies for data ownership, access, and ongoing quality monitoring. Students design a lightweight governance framework for their planning environment.

Lesson 1 • Trend and Seasonality Models

Introduces Holt's double smoothing and Holt-Winters triple smoothing for trended and seasonal data. Students calibrate models to minimise forecast error.

Lesson 2 • Regression-Based Forecasting

Applies linear and multiple regression to model demand as a function of causal variables. Students build and interpret regression equations for planning use.

Lesson 3 • Moving Average and Smoothing Methods

Covers simple moving average, weighted moving average, and exponential smoothing models. Students apply each method and compare outputs on sample datasets.

Lesson 4 • Demand Pattern Recognition

Trains students to identify trend, seasonality, cycle, and irregular components in time series. Pattern recognition drives method selection in later sections.

Lesson 1 • Qualitative Forecasting Techniques

Covers expert opinion, Delphi method, and structured sales input as complements to statistical models. Students evaluate when qualitative methods add value.

Lesson 2 • Promotional and Event Uplift Modelling

Teaches how to quantify the demand impact of promotions, holidays, and events on baseline forecasts. Students build uplift factors from historical promotion data.

Lesson 3 • New Product Demand Estimation

Addresses forecasting for products with no sales history using analogues and market research. Students apply analogue modelling and diffusion curves.

Lesson 4 • Adjusting Statistical Forecasts with Judgement

Establishes a disciplined process for applying and documenting manual overrides to statistical outputs. Students learn override governance to prevent bias accumulation.

Lesson 1 • Cross-Functional Collaboration Skills

Develops techniques for facilitating productive demand review meetings across sales, marketing, and finance. Students practise structured agenda design and conflict resolution.

Lesson 2 • Building the Consensus Demand Plan

Guides students through reconciling statistical forecasts with commercial and operational inputs. The output is a single agreed-upon number used for supply planning.

Lesson 3 • S&OP Process Architecture

Maps the five-step S&OP cycle and positions demand planning within it. Students understand how demand plans feed supply, financial, and executive reviews.

Lesson 4 • Demand Plan Communication and Reporting

Covers how to present demand plans clearly to different audiences using dashboards and exception reports. Students design outputs tailored to operational and executive needs.

Lesson 1 • Safety Stock Fundamentals

Derives safety stock formulas from demand variability and lead time uncertainty. Students calculate safety stock targets for different service level requirements.

Lesson 2 • Inventory Performance Monitoring

Establishes metrics and review cadences to track inventory health against demand plan assumptions. Students design an inventory performance dashboard.

Lesson 3 • Inventory Segmentation Strategies

Applies ABC-XYZ segmentation to differentiate inventory policies across the product portfolio. Students assign appropriate replenishment strategies to each segment.

Lesson 4 • Supply Constraint Integration

Teaches how to adjust unconstrained demand plans when supply capacity or lead times are limited. Students produce constrained plans and communicate trade-offs.

Lesson 1 • Continuous Improvement Frameworks

Applies Plan-Do-Check-Act and maturity model thinking to sustain forecast accuracy gains over time. Students build a roadmap for advancing planning maturity.

Lesson 2 • Statistical Model Recalibration

Covers techniques for updating model parameters, reselecting methods, and retraining models on fresh data. Students apply recalibration cycles to improve baseline accuracy.

Lesson 3 • Override and Bias Management

Analyses the accuracy and bias impact of manual overrides and establishes governance to reduce harmful adjustments. Students audit override history and redesign approval rules.

Lesson 4 • Root Cause Analysis of Forecast Error

Applies structured diagnostic tools to identify whether error stems from data, method, process, or behaviour. Students distinguish random from systematic error sources.

Lesson 1 • Demand Planning Strategy and Roadmap

Synthesises course learning into a strategic capability roadmap aligned with business objectives. Students present a multi-year demand planning transformation plan.

Lesson 2 • Collaborative Planning with Trading Partners

Covers CPFR frameworks for sharing forecasts and replenishment plans with key customers and suppliers. Students design a collaborative planning agreement and data-sharing protocol.

Lesson 3 • Global and Multi-Echelon Demand Planning

Addresses planning complexity across multiple geographies, distribution tiers, and currency environments. Students design a multi-echelon planning hierarchy and aggregation logic.

Lesson 4 • Scenario Planning and Risk Quantification

Builds probabilistic demand scenarios to quantify upside and downside risk for supply and financial planning. Students present scenario ranges to executive decision-makers.