SAP IBP is a popular supply chain planning tool among many Fortune 1000 companies today. SAP IBP can help you create better demand forecasts and finished goods plans when properly implemented together with appropriate training for the planning professionals.
The main focus of the workshop is Statistical modeling and forecasting in SAP IBP. We will cover the various modeling strategies including the automatic model selection procedures. We will spend quality time on explaining data analysis and graphical review in IBP.
Please bring your laptops with access to your IBP DP environment so you can test a couple of models on the fly.
This is a chance to discuss your challenges in using SAP IBP from a technological and analytical point of 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. In this workshop, you will also learn the mechanics behind the Forecast Error metrics available in the System.
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SAP IBP has seven different error metrics. There is a lot of confusion and which ones to use and how to use them and what they really mean.
1. How many of them are you currently using in your modeling?
2. How many of them you should really be using?
3. Which metric is the best indicator of forecast quality?
IBP 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. We illustrate with examples the calculations of WMAPE, MASE, MAPE, RMSE and MPE and the pros and cons of using each.
On completion of the course, you will have a better understanding of the different statistical models and you can take advantage of the exception management practices built into IBP DP to model, forecast and manage the process by exception.
Introduction to IBP and forecast profiles
IBP DP Terminology and Statistical Modeling
Statistical Modeling continued
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