Demand Planning for S&OP

Demand Planning for S&OP :

In this specialized two-day course, we will discuss a variety of modern trends in Demand Planning and Supply chain forecasting – Machine Learning, AI-driven planning and Big Data analytics. The focus will be on demand modeling with AI-driven planning engines and statistical models, and the process to incorporate market intelligence. We will help you prepare for the role of a winning Data Scientist and a seasoned planning processional. And the two day workshop is the foundation for our Certified Analyst in Demand Planning – CADP program.

This workshop earns a Certificate and eligibility to sit for the CADP certification.

View the seminar brochure 

Demand Planning for S&OP
Detailed Outline of The Workshop

Demand Planning Overview

  • Planning objectives
  • The Service – Cost – Balance Model
  • Define your Plan
  • Budgeting vs. Forecasting vs. Planning
  • Beyond Statistical Forecasting
  • Key Components of a Demand Plan
  • Terminology in Planning – Forecast Horizon, Buckets & Periodicity
  • Forecast Pass
  • Demand Management

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
  • The process to Identify Outliers
  • Tolerance band
  • Methodology for outlier correction

Stat Modeling and AI-driven Planning

  • Demand Modeling
  • Key components of demand
  • Additive Vs. Multiplicative Seasonality in Models
  • Modeling by decomposition
  • Introduction to Forecast Modeling
  • Qualities of a good statistical forecast
  • Balancing between Model Fit Vs. Model Robustness
  • Uni-Variate Time Series vs. Multi-Variate methods
  • Moving Average
  • AI-driven Planning and Expert Models
  • Introduction to Planvida

Advanced smoothing models

  • First Order Exponential Smoothing
  • Holt Models to accommodate the trend
  • Holt-Winters Model
  • Exponential Trend and Dampening
  • Interaction between components

Modeling special cases of Demand Product Life Cycle & Long-term Planning 

  • Product Lifecycle and trend • Launch Forecasting • Volume effect on line extension
  • Event Modeling
    Baseline vs. Incremental • Illustration of Event Models
  • Planning for Intermittent Demand 
    What is Intermittent Demand & what causes it? Strategies to handle intermittent demand & Statistical Models for Intermittent Demand
  • Higher-order Models

Product Portfolio Management

  • Impact of Data Volatility on Forecasting
  • Measuring Volatility
  • Impact of multiple Extreme Observations on Volatility
  • SKU Segmentation for demand modeling & inventory strategies
  • Modeling by exception
  • ABC analysis - Classification philosophy
  • Pareto analysis  based on dollar usage
  • Item criticality
  • Excess, obsolete and Slow-moving Alignment with the product lifecycle
  • Discontinuance and end of life (EOL)
  • Process flow for Segmenting SKUs
  • Example using a three-dimensional matrix; ABC / Volume / Critical / Status; the excess, obsolete impact of Segmentation on Cycle Counting and Inventory Accuracy.

Demand Planning Analytics toolkit

Definition of Demand Forecast Errors

  • Forecast Accuracy
  • Forecast Bias vs. Forecast Error
  • Error and Volatility Reduction
  • Errors across SKUs vs. Errors across time
  • Model Diagnostics vs Performance
     - MAD
     - MAPE vs. MPE
     - WAPE
     - Root Mean Squared Error

Measuring forecast performance   

  • Forecast Performance Metric
  • Forecast errors and actionability
  • Sources of Forecast Error
  • Definition of Demand Planning Metrics - WAPE & Bias
  • Types of Bias
  • SKU Mix Error
  • Error Analysis for Continuous Improvement

Why S&OP

  • Fragmented Planning Activities
  • – Supply chain challenges – Service, costs and inventories
  • Disparities between the Financial forecast and operational forecasts
  • Bottom Line challenges from Fragmented Planning
  • Benefits of a holistic S&OP Design
  • Core Components of SIOP
  • Consensus Demand Planning
  • Rough Cut Planning and Supply Collaboration
  • Executive Presentation
  • Demand-Supply Balancing
  • Modeling by exception

 

 

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