Chicago, IL, July 22, 2017 --(PR.com
)-- Visit http://demandplanning.net/modeling_metrics_in_apo_IL.htm for details on workshop outline and current prices for registrations.
Early bird price of $895
Highly recommended as a 3 day workshop along with the Demand Planning Tutorial 2 day DP + 1 Day SAP APO $1695
The main focus of the workshop is Statistical modeling and forecasting in SAP APO. It will cover the various modeling strategies including the automatic model selection procedures and will also explain data analysis and graphical review in APO.
This will give attendees a chance to discuss their challenges in using SAP APO from technological and analytical point view.
The tool also uses a variety of Error measurements as model diagnostics to assess the quality of the forecasting model and enables exception management through reporting and alerts. The workshop will explain the mechanics behind the Forecast Error metrics available in the System.
SAP APO has six different error metrics. There is a lot of confusion and which ones to use and how to use and what they really mean.
1. How many of them are currently in use while modeling?
2. How many of them should be in use?
3. Which metric is the best indicator of forecast quality?
APO DP defines the error metrics 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. The workshop will illustrate with examples the calculations of MAPE, RMSE and MPE and the pros and cons of using each.
Forecast Alerts are a big part of Demand Modeling by Exception. The workshop will help the attendees to know 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, attendees will have a better understanding of the different modeling strategies and can take advantage of the exception management practices built into APO DP to model, forecast and manage the process by exception.
Learn how to leverage:
Forecasting exception alerts and
Forecast Model comparisons