SAP IBP for Demand
| Course Details | Find Out More |
|---|---|
| Code | IBP600-v054 |
| Tuition (CAD) | N/A |
| Tuition (USD) | Array |
In this advanced configuration course, you will gain a solid understanding of the SAP IBP for Demand business processes including Demand sensing with Machine Learning algorithm and their associated configuration. Instructor-led training is supplemented with hands-on exercises.
Who Can Benefit
- Application Consultants
- Business Process Architects
- Business Process Owner / Team Lead / Power Users
- Solution Architects
Skills Gained
- This course will prepare you to:
- Outline model components of SAP IBP for demand
- Perform Data Preparation
- Execute a mid- / long-range forecast
- Configure Demand Planning functions
- Work with forecast accuracy
- Execute Demand Sensing processes
Prerequisites
- Essential: IBP100 – SAP IBP for Supply Chain, Overview
- Recommended: IBP300 - SAP IBP Advanced Configuration
Course Content
Introduction to SAP IBP for demand
- Explaining Demand Planning
- Describing Model Components - Master Data Types and Key Figures
Data Preparation
- Cleaning Data Manually
- Cleaning Data Automatically
Forecasting
- Using Forecast Profiles
- Determining the Best Forecast Model
- Assigning Forecast Models
- Using Multiple Linear Regression
- Using Composite Forecasting
- Incorporating Market Input
- Measuring Performance Using Alerts
Lifecycle Planning
- Planning product lifecycles
- Using Phase-in and Phase-out Profiles
- Manual Forecasting
- Realigning Data
Promotion Planning
- Planning Promotions
- Creating Promotions
- Managing Past Promotions
Demand Plan Release
- Using Financial Key Figures and Pricing
- Releasing a Demand Plan
- Measuring Forecast Performance
- Using Analytics and Dashboards
- Using Snapshots
Forecast Accuracy
- Using ABC and XYZ Segmentation
- Using Time Series Analysis
- Setting up Alerts for Forecast Accuracy
- Performing Analysis in the SAP Fiori Web UI and the Excel UI
- Tailoring Your Forecasts
Demand Sensing
- Introducing Demand Sensing
- Describing the Model Component Demand Sensing
- Setting up Demand Sensing with Gradient Boosting (2.0) Algorithm
- Managing Demand Sensing
- Tailoring the Demand Sensing Algorithm
- Approving the Demand Sensing Results