Surprised to see such a high ranking content in google, try this one: “SAP IBP APO”.Read More
Driving innovation at SAP AppHaus in Heidelberg....
Reposting here the article I wrote for Linkedin.
If you have not yet heard of SAP Integrated Business Planning (IBP), chances are that you will soon hear about it, particularly if you work in IT or in an organization looking at the novelties SAP is pushing to market. In a nutshell, SAP Integrated Business Planning is the new Supply Chain Planning solution meant to replace (sometime in the future) the more mature SAP Advanced Planning and Optimization (APO).
Born to be supporting the Sales and Operations Planning process, this solution supports natively long and mid-term planning as well as specific operational planning processes based on order planning. SAP IBP supports two main planning data structures and integration strategies:
1 - Time series: which means a quantity per a given time interval
2 - Order items: specific order quantities (meant to maintain at any time the pegging information, that is the knowledge of the customer ordering or forecasted to order).
The former data structures is the main structure used for Sales and Operations Planning, Demand Planning, Inventory Optimization, Supply Planning (ruled-based or optimized) and Supply Chain Control Tower. The latter is the new addition to the IBP stack and it mainly supports (near)real-time advanced complex planning algorithms such as Response and Order-based optimization. The integration strategy is very different: while near real time requirements convinced SAP to build a tight integration of ECC or S4/HANA to SAP IBP, time series processes provide an open integration architecture and a very flexible definition of planning structures and segmentations. In fact, a backend from SAP is not required for integrating with SAP IBP when using time-series based business processes.
Architecture openness, reduced change management costs and the cloud option are making of SAP IBP an excellent candidate for mid-size companies. Companies with very diverse landscape or growing according to an M&A strategy can greatly benefit from adopting SAP IBP. In the last years our team served companies ranging in size from 300 Mio US$/year to 40 Bi US$/year and we have experienced a common pattern in the value delivered by IBP:
a - cloud solution and open architecture: the IT team shifts from technical service to true business partner of the business planners
b - limited change management costs: Planners need a very short training due to the Microsoft Excel UI
c - no data latency: Demand and Supply planning have no data latency and impact of changes in the demand or forecast can immediately be evaluated
d - unique centralized planning data model: elimination of human error due to data synchronization among scattered spread-sheets and improved productivity.
For more details directly from one successful SAP customer, please check the next upcoming webinar here.
Join us on April 12th 2018 for the Webinar: The roadmap of SAP Integrated Business Planning at Prestige Brands
You can find the registration here.
- Matthew Flood - VP IT @ Prestige Brands
- Jeff Korol - SAP Solution Experience
- Ernst Perno - AnswerThink
- Marco Santoyo - bizbrain technologies
Great discussions at our booth in Vegas. Thanks Martin and Matthew for the great conversation.
Matthew Flood and Dustin Demmin shares their experience about their SAP IBP implementation
Come and join us at SAPInsider in Vegas at the booth #830.
Here the Abstract and the outline of our presentation:
Speed and complexity: lessons learned and best practices in implementing SAP IBP for companies of different sizes and different business process variants:
- S&OP/IBP global templates rollouts vs one instance implementations of multiple process variants
-Global roll-outs of Demand Planning challenges vs Demand and Supply balance processes
-Integrated planning implementations (i.e. with SAP PPDS) vs stand-alone SAP IBP
-Planning vs Reporting
-How to support IT organization in smaller or larger organizations
-Data quality and governance