Business Planning and Analytical Services
Business Planning and Analytical Services is split into the variants Business Planning and Analysis Process Design. These variants conceptually base on the BI platform. They enable customers to implement business planning and use analytical methods for further analyses.
- Business Planning
The variant business planning in general delivers generic planning and forecasting functionality for any type of planning application for either strategic or operational planning in integrated planning processes.
Main features and functions Business Planning:
- Open and flexible planning framework for all SAP applications
- Fully integrated with BI and analytics services
- One user interface, one design environment, one engine
- planning workbench for the creation and maintenance of planning models
- Shared services and persistency and integrated meta data
- top-down planning and bottom-up contribution
- automatic planning functions with a rich set of planning functions
The scenario variants are based on the different UI options available for the needs of different planners
Option I: Excel-based Business Planning provides the planner with a full-featured Excel-environment on a solid foundation for central data storage.
Option II: Web based Business Planning provides planners in remote locations with easy and intuitive to use planning applications without front-end installation
- Analysis Process Design
Analysis Process Design enables companies to define complete processes which can disclose relationships within their data. An analysis process collects data from InfoProviders, queries or other BI objects, transforms this data in various ways (and possibly multiple steps) and writes back the new information either into some BI objects (like InfoObjects or ODS objects) or even into a SAP CRM system. The transformations reach from simple filter, aggregation or projection operations to complex data mining methods.
Main features and functions Analysis Process Design:
- Data Mining
- Meta data integration
- Master data and transactional data integration
- Market basket analysis
- Clustering of customers with similar buying behavior
- Construction of decision trees with a prioritized sequence of customer attributes and their influence on potential insurance frauds
- Data Mining