Demand Planning Fundamentals

• Purpose of Demand Planning beyond Forecast Accuracy
• The Service–Cost–Balance Model and real-world trade-offs
• Connecting demand plans to service, inventory, and cost
• Defining a fit-for-purpose demand plan for your business
• Budgeting vs. Forecasting vs. Planning — roles, tensions, and alignment
• Key planning terminology – Forecast horizon, Time buckets & periodicity, Level of aggregation

Data Integration and Cleansing

• It is all about the data
• The Forecast Problem and Data Collection
• Define True Demand Data challenges – Shipment Vs. Orders – Gross Demand Vs. Net Demand
• Historical shifts in Demand
• Data filtering
• Outliers– Identification and Correction
• Tolerance band Methodology for outlier correction

Statistical Modeling

• Foundations of Demand Modeling
• Key components of Demand
• Seasonality: Additive vs. Multiplicative
• Modeling by decomposition
• Introduction to Demand Modeling
• Model Selection: Fit vs. Robustness
• Time Series Approaches
• Forecasting Technique – Moving Average

Advanced Smoothing Models

• Why Smoothing Models Still Matter?
• First Order Exponential Smoothing
• Modeling Trend with Holt’s Methods
• Capturing Seasonality with Holt–Winters
• Exponential Trend and Dampening
• Interaction between components
• Higher order Smoothing Models

Modeling Special Demand Scenarios

• Why do Special Demand Cases need different approaches?
• Product Life Cycle & Long-term Demand Planning
  • Product Life cycle and trend
  • Forecasting Product Launches
  • Managing Volume Effects & Channel Extensions
• Event – Based Demand Modeling
  • Introduction to Event Modeling
  • Baseline vs. Incremental
  • Illustrating Event Models
• Planning for Intermittent Demand
  • What is Intermittent Demand?
  • Strategies for Intermittent Demand
  • Modeling for Intermittent Demand

Advanced Product Portfolio & Demand Management

• Understanding Data Volatility in Supply Chains
• Measuring and Interpreting Volatility
• Managing Extreme Observations
• SKU Segmentation for Strategic Planning
• Exception-Based Modeling Approaches

Demand Planning Analytics Toolkit

• Understanding Demand Forecast Errors
  • Forecast Accuracy
  • Forecast Bias vs. Forecast Error
• Measuring Forecast Accuracy & Performance
  • MAD, MAPE vs. MPE, WAPE, Root Mean Squared Error
  • Comparing errors across SKUs vs. errors across time periods
  • How to measure and interpret forecast performance effectively
• Improving Forecast Accuracy and Actionability
  • Techniques for error and volatility reduction
  • Understanding sources of forecast error
  • SKU mix errors
  • Actionable insights from forecast errors

Machine Learning for Demand Planning

• Why Machine Learning in Demand Planning?
• ML Fundamentals, Data Readiness & Feature Engineering
• Ensemble Learning and Model Choices
• SKU Segmentation & Model Selection
• Gradient Boosting Models in Practice
• Model Evaluation & End-to-End Forecasting Flow

S&OP – What, When & How?

• Core Components of S&OP
• Fragmented Planning Activities
  • Supply chain challenges
  • Service, costs, and inventories
• Bottom Line challenges from Fragmented Planning
• Benefits of a holistic S&OP Design
• Consensus Demand Planning
• Supply Collaboration
• S&OP Planning Cycle