Demand Metrics in SAP APO Web Workshop: Understanding the intricacies of APO calculations

- presented by Mark Chockalingam, Ph. D., Managing Principal
Jan 28, 2010, 11AM - 2PM EST / 8AM - 11AM PST

Overview

SAP APO is a powerful tool that can help you create better demand forecasts and finished goods plans, when properly implemented together with appropriate training for the planning professionals. APO DP demand planning uses a variety of Error measurements as model diagnostics to assess the quality of the forecasting model. Model Diagnostics measures are computed for the same SKU/Product over time

In this workshop, you will learn the mechanics behind the Forecast Error metrics available in the System. Most of these error metrics are familiar to demand planners. However, APO DP defines them with its own unique formula that is different from conventional calculations. So it is critical for planners to know how they are being calculated and how to use them to diagnose forecast quality.

Though APO DP engine creates six different error metrics, you need to only look at a couple of them to accurately assess the quality of the forecast. We illustrate with examples the calculations of MAPE, RMSE and MPE and the pros and cons of using each. We then explain the concept of Tracking Signal that is being used by the exponential smoothing models in APO.

Forecast Alerts are a big part of Demand Modeling by Exception. We show you how to leverage the error measures to define and use Univariate Forecast Alerts. The final tool to compare among alternative forecast models is to use the Forecast Comparison Report.

On completion of the course, you can take advantage of the exception management practices built into APO DP to model, forecast and manage the process by exception through

Forecasting exception alerts and
Forecast Model comparisons.

Who Should Attend?

Demand Planners & Directors
Forecast Analysts & Managers
Director of Value Chain
Analysts in the Supply Chain
Director of IT
Inventory and Operations Planners
Financial Analysts
Director of Logistics
Product Managers
IT Business Analysts
IT Managers
APO support professionals
Director of ERP applications
Director of Supply chain applications
IT Business Managers

Topics

Part One: Introduction Introduction to Forecast Modeling Qualities of a good Statistical Forecast Balancing between Model Fit vs. Model Robustness	Part Three: Model Diagnostics Model Diagnostics through Forecast Error How to identify a biased Forecast? Which metric is the best indicator of Forecast quality? In-Class Exercises
Part Two: Forecast Errors Definition of Demand Forecast Errors Errors over time vs. Errors Across Products Demand Forecast Metrics Computations in APO Mechanics behind MAD, ET, MPE, MSE, MAPE and RMSE	Part Four: Additional Considerations Impact of Outlier adjustments on Model What is Tracking Signal? Comparison of alternative Forecast Models Forecast Modeling through Exception Univariate Forecast Alerts Summary and Conclusions

Pricing

Value Chain Metrics: Theory and Practice
Value chain Metrics	$199USD
Demand Metrics in APO DP	$199USD
Value Chain Metrics: both sessions	~~$379USD~~ Now $299USD*