Customer Demand Planning Workshop

Improve Forecasting with POS and Channel Inventory - relevant for CPG, FMCG, Consumer Electronics, High-tech, Automotive, and Food and Beverage

Oct 6th(Wed) and 7th(Thurs), 2010 - 2 Day Interactive Workshop,
at the Hyatt Place, Fair Lawn/Paramus, NJ

view and print seminar brochure (PDF)

This workshop will explain the process to create a demand-driven pull forecast that incorporates the effects of changes in market, consumption patterns, and inventory cycles to model a supply chain forecast. Customer based Demand Planning works by leveraging customer sell-through and inventory data. Some times the customer may also provide you their own forecasts through the CPFR process.

We take on the challenges and work through the mechanics of obtaining and using customer data and syndicated POS data from sources like Nielsen's and IRI. If you are using Wal-Mart Retail Link or Target Partners Online data, this will be a productive workshop that helps you build the analytics to create the correct forecasts.

You will learn to...

Understand the unique characteristics of Demand Planning for CPG
Work the Mechanics of Forecast Modeling
Leverage Time Series Models and Exponential smoothing
Calculate Demand Metrics and perform Model Diagnostics
Utilize retail data to increase the accuracy of your forecasts
Appreciate the Dynamics of Retail and channel inventory
Derive the total supply chain forecast using Account Based Forecasting
Set up a consensus demand planning process

Who Should Attend?

Demand Planners & Directors
Forecast Analysts and Managers
Director of Value Chain
Analysts in the Supply Chain
Inventory and Operations Planners
Financial Analysts
Director of Logistics
Marketing Managers
Product Managers
Sales Managers
Customer Business Managers

Detailed Outline of the Workshop:

Day 1

8:30AM to 5:00PM

Day 2

8:30AM to 5:00PM

7:30AM Registration & Breakfast
8:30 AM Welcome
9:00 AM Demand Planning Overview
- Definition of 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
10:30AM Coffee Break
10:45AM Data Analysis for forecasting
- Data Requirements for POS based forecasting
- Graphical review of POS and Channel Inventory Data
- Outliers and Missing Data
- Structural Changes and Data Shifts
- Forecast Model
- Introduction to Demand Components
- Ex-Ante versus Ex-Post Forecasting
- Hold out Sample Methodology
- Optimal Model Selection
12:30PM Lunch Break
1:30 PM 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
2:30PM Coffee Break & Networking Exercise
3:00 PM Demand Driven Forecasting Continuation
- Understanding your Distribution Channel Network
- Demand Volatility created by Channel inventory
- Changes in Retail Inventory Policies
- Calculation of the total supply chain forecast
- Challenges in setting up the process - Data mapping. calendar conversations
4:30 PM Assignment of Forecasting Exercises to Participants

7:30 AM Breakfast
8:30am Forecast Modeling for POS DATA
- Smooth patterns in the POS data
- Effect of Marketing and Sales Promotions
- Data Anomalies - Shifts, Outliers & POS Converge
- Statistical Modeling
- Model Diagnostics using Demand Metrics
- MAPE vs. Root Mean Squared Error
- Ex-post Forecasting
- Modeling Level, Trend and Seasonality
- Exponential Smoothing Models
- Promotional Planning using Intervention Models
- Baseline Forecast and Lift for Promotional events
- Change in the Promotional Calendar
- Phase-in and Phase- out Modeling
10:30PM Morning Break
10:45 PM Modeling (cont'd)
- Baseline vs. event forecasting
- Introduction to Box-Jerkins Models
- Multiple Linear Regression Models
- Time and Seasonal Index in and Excel based model
12:00 PM Lunch Break
1:00 PM POS to Order Forecast
- Challenges in converting the POS forecast to shipment forecast
- Special situations that affect the conversion
- Numerical examples to illustrate

2:45 PM Coffee Break
3:00 PM Measuring Forecast Performance
- Definition of Demand Forecast Errors
- Errors over time vs. Errors Across Production
- Calculation Methodology for Model Diagnostics
- Mechanics behind MAD, MPE, MAPE, and RMSE
- How to identify a biased Forecast
- Importance of measuring forecast performance
- Management Reporting and Continuous Improvement
- Measurement Methodology
- Mean Percentage Error (MPE)
- Mean Absolution Percentage Error (MAPE or PMAD)
- Weighted Mean Percentage Error (WMAPE)
- Forecast Bias and SKU Mix Error (SME)
- Relationship between Bias and Error

4:45 PM Discussion and answers to assigned exercises

Pricing

$895 10% discount for groups of 2 or more. For special Hotel rates, please call the office at (781) 995-0685.

Consulting

Diagnostic | DP Design | Exception Management | S&OP | Solutions

Training

Demand Planning | S&OP | Retail Forecasting | Supply Chain Analysis: » Value Chain Metrics » Inventory Optimization | Supply Chain Collaboration

Industry

Knowledge Base

Planning: » Budgeting » S&OP | Metrics: » Demand Metrics » Inventory » Customer Service | Collaboration: » VMI & CMI » Account Based Forecasting
Forecasting: » Causal Modeling » Market Modeling » Ship to Share | For Students