Demand Management and Forecasting

Course Info

Length: 1 Week

Type: In Classroom

Available Dates

Venue

  • Dec-23-2024

    Paris

  • Dec-23-2024

    Dubai

  • Dec-30-2024

    Singapore

  • Dec-30-2024

    Barcelona

  • Jan-13-2025

    Kuala Lumpur

  • Jan-13-2025

    Istanbul

  • Jan-13-2025

    Paris

  • Jan-13-2025

    Barcelona

  • Jan-13-2025

    Amsterdam

  • Jan-13-2025

    Singapore

  • Jan-27-2025

    Dubai

  • Jan-27-2025

    London

  • Mar-10-2025

    Dubai

  • Mar-10-2025

    London

  • Apr-14-2025

    Amsterdam

  • Apr-14-2025

    Barcelona

  • Apr-14-2025

    Paris

  • Apr-14-2025

    Istanbul

  • Apr-14-2025

    Kuala Lumpur

  • Apr-14-2025

    Singapore

  • May-05-2025

    London

  • May-05-2025

    Dubai

  • July-14-2025

    Paris

  • July-14-2025

    Istanbul

  • July-14-2025

    Barcelona

  • July-14-2025

    Kuala Lumpur

  • July-14-2025

    Singapore

  • July-14-2025

    Amsterdam

  • July-28-2025

    London

  • July-28-2025

    Dubai

  • Oct-13-2025

    Barcelona

  • Oct-13-2025

    Singapore

  • Oct-13-2025

    Paris

  • Oct-13-2025

    Amsterdam

  • Oct-13-2025

    Istanbul

  • Oct-13-2025

    Kuala Lumpur

  • Oct-20-2025

    Dubai

  • Oct-20-2025

    London

  • Dec-15-2025

    Dubai

  • Dec-15-2025

    London

Course Details

Course Outline

5 days course

 

Keys to successful forecasting process and function
 
  • Problems and Needs

  • Goals and Objectives

  • Coordination and Leadership

  • Process Management

  • Forecast Model Development

  • Communication with Participants and Users

  • Four Forecasting Process Approaches

  • Independent

  • Concentrated

  • Consensus

  • One Number

  • Myths About Forecasting

  • Silo Forecasting Impact on Organization

 

 Data patterns and demand variability
 
  • The Bullwhip Effect

  • Demand Variability and the Methods to Minimize It

  • Recognition of Data Patterns

  • What kind of problems to look for in the data and how to treat them

 

 Inputs and outputs of demand plan
 
  •  Profit Potential

  •  Risk Management Input

  • Operations Planning

 

 Forecasting models: Qualitative / Quantitative
 
  •  How much data to use for different statistical models

  • Subjective assessment models overview

 

Time series models
 
  • Inherent assumptions

  • When time series work and when they don’t

  • Time series elements: Level, Trend, Seasonality, Cyclicality, Noise

 

Cause and effect models
 
  • Regression models

  • When to use regression models

  • Steps in development

  • Key assumptions

 

Minimizing forecasting error
 
  • Forecast error metrics

  • Uses of forecast error measures

  • Sources of error

  • Error analysis, communication and remediation

  • Exception driven forecasting process

  • Relationship between MAPE / Bias, Customer Service and Inventory KPIs

 

 New product forecasting
 
  • New product success and error rates

  • New product success and failure factors

  • Issues to consider when developing new product forecasts

  • Qualitative and Quantitative methods used in new product forecasting 

 

 

Promotions forecast
 
  • Promotions forecast error rates

  • Manage the process for unplanned and abnormal demand

  • Factors, issues, and considerations in developing romotions forecasts

  • Cannibalization impact of promotions on base / open stock SKUs

 

Worst forecast practices summary and discussion
 
  • Worst practices in the mechanics of forecasting

  • Worst practices in forecasting process

 

 Best forecasting practices summary
 
  • Forecasting process

  • Data collection and analysis

  • Methods and models

  • Software and systems

  • Communications & People

Course Video