Demand Planning.Net: Are you Planning By Exception?
Demand Planning.Net
demand planning, forecasting, and exception management

CPG Demand Forecasting
Module One

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Consumer Packaged Goods companies are faced with a changing retail landscape dominated by a few large retailers and higher uncertainty from consumer preferences and retail promotional policies. Just a few of your customers can exert a great influence on your planning, logistics and execution processes. However, the large retail customers have also created the infrastructure and the technology that provides consumer and retail shelf take-away data, as well as enhanced visibility into the inventory positions at both store and warehouse. The key is for the CPG companies to leverage both consumption data and inventory data to create accurate demand plans.

    Demand Planning Overview
  • Definition of Demand
  • Introduction to Demand Planning
    • What, Why and How?
  • The Service - Cost - Balance Model
  • Distinction between Business Forecasting and Demand Planning
  • What to Forecast
    • shipments vs. orders
  • Key Terminology
    • Forecast Horizon
    • Buckets
    • Periodicity
  • Constrained vs. Unconstrained Forecasts
  • Demand Management
  • Organization Structure and Culture
  • Role of the Demand Forecaster
  • Consensus and communication
    Data Analysis for Demand Forecasting
  • Data Requirements for POS based forecasting
  • Graphical review of the POS and Schannel Inventory Data
  • Outliers and Missing Data
  • Use of Sundicated Data - Coverage Ratios
  • Structural Changes and Data Shifts - In and Out packs
  • Forecast Model
  • Introduction to Demand Components
  • Ex-Ante vs. Ex-Post Forecasting
  • Hold out Sample Methodology
  • Optimal Model Selection
    Demand Driven Forecasting
  • Push vs. Pull Methodology
  • Modeling Customer Demand
  • Retail Customer Segmentation - Analysis of your Customer Pareto
  • Modeling the retail shelf take-away- The use of POS data
  • Understanding your Distribution CHannel Network
  • Demand Volatility created by Channel Inventory
  • Changes in Retail Inventory Policies
  • Calculation of the total supply chain forecast
  • Challeneges in setting up the Process - Sata Mapping, Calendar Conversions

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