Demand Planning and Forecasting Tutorial
Sharpen your supply chain with accurate modeling and metrics!
May 6th and 7th, 2010 - 2 Day Interactive Training: Bring your laptops
Boston, MA
Register Now!
view and print seminar brochure (PDF)
In this specialized two-day course, we will explain the modeling methodology and process behind
accurate demand forecasts and how to effectively use promotional information to arrive
at a consensus forecast. The focus will be on demand modeling using statistical
techniques, the methodology to perform model diagnostics, forecast accuracy
measurement and the process to incorporate market intelligence.
If you are a new demand forecaster or looking to enhance your knowledge of
business forecasting, you cannot afford to miss this opportunity!
Get skills you can use at work
We will explain and demonstrate best practices in model selection,
illustrate how to use forecast error to improve model quality, and teach you how to
reconcile top-down and bottom up forecasts.
Learn from industry experts
Each training day will also include an industry-specific presentation from a senior
supply chain manager.
Network with peers
You will have ample opportunity to meet, interact,
and learn from other demand planning professionals with team challenges and networking exercises.
Add to your credentials
Upon completion of the tutorial, you will be awarded a certificate of completion
from Demand Planning LLC, attesting to your newly-acquired skills in Demand Planning
and Forecasting.
Detailed Outline of the Workshop:
Day 1
8:30AM to 5:00PM
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Day 2
8:30AM to 4:30PM
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- 8:30AM Registration & Breakfast
- 9:00 AM Opening Address
-
9:15 AM Demand Planning Overview
- Definition of Demand
- Introduction to Demand Planning
- The Service - Cost - Balance Model
- Distinction between Forecasting and Demand Planning
- What to forecast - shipments vs. orders
- Forecast Horizon, Buckets & Periodicity
- Constrained vs. Unconstrained forecasts
- Demand Management
- Organization Structure and Culture
- Role of the Demand Forecaster
- Consensus and communication
- 10:45AM Coffee Break
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11AM Data Analysis for forecasting
- Data Requirements for Demand Planning
- Graphical review of the Data
- Central Tendency and measures of Dispersion
- Outliers and Missing Data
- Structural Changes and Data Shifts
- What is a Forecast Model?
- Introduction to Demand Components
- Ex-Ante versus Ex-Post Forecasting
- Hold out Sample Methodology
- Optimal Model Selection
- 12:30PM Lunch Break
- 1:30pm Guest Speaker
TBD
- 2:30pm-3pm Coffee Break & Networking Exercise
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3:00pm Modeling & Graphical Decomposition
- Decomposition of the Demand Profile
- Understanding the components -
Trend, Seasonality, Cyclicality
- Predictable and unpredictable volatility
- Stationarity and Stability
- Diagnostics review to improve model quality
- Modeling by Exception
- 4:30pm Assignment of Forecasting exercises to participants
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8:30am Modeling
- Introduction to Forecast Modeling
- Qualities of a good Statistical Forecast
- Balancing between Model Fit vs. Robustness
- Time Series versus Multi-Variate Methods
- First Order Exponential Smoothing Models
- Holt Models to accommodate Trend
- Holt Winters Models
- How to set up a simple forecast model in Excel
- Additive vs. Multiplicative Seasonality in Models
- Baseline vs. event forecasting
- Introduction to Box-Jenkins Models
- Multiple Linear Regression Models
- Time and Seasonal Index in an Excel model
- 11:30PM Lunch Break
- 12:30pm Guest Speaker
TBD
- 2:30pm-2:45pm Coffee Break
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2:45pm Measuring Forecast Performance
- Importance of measuring forecast performance
- Management Reporting and Continuous Improvement
- Measurement Methodology
- Mean Absolute Deviation (MAD)
- Mean Percentage Error (MPE)
- Mean Absolute Percentage Error (MAPE or PMAD)
- Weighted Mean Percentage Error (WMAPE)
- Forecast Bias and Sku Mix Error (SME)
- Relationship between Bias and Error
- 4pm Discussion and answers
to assigned exercises
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Register Now!
Pricing
$1,045 Early bird pricing: $995 for registrations by Apr. 17, 2010. 10% discount for groups of 3 or more.