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Client:  The client is a large food processor (multi-billion-dollar entity) with highly perishable product.  The company re-organised into 5 new divisions.  There was little performance data for the newly re-organised business units.  The CEO needed the new divisional heads to agree performance targets but found this difficult due to lack of meaningful historical data/ reporting.

Task:  Using r4apps, the client re-created the results as though the new divisions had existed for 2 years.  r4apps went through 2 years SAP BW data and re-processed the data as though the new organisational structures had existed, creating the required performance data in a fully flexible, dynamic model.  This was completed in 4 weeks.  Internal IT and Finance, using their BW deployments, estimated more than 4 months to produce a static, inflexible model of the same.

Follow-up use cases: Following the success of the above, r4apps was deployed in is a complex use case which resulted in very high value delivered.  r4apps was used for challenging simulations of production and logistics to optimise for profit.  Over 400 million data elements are used to optimize profitability in a these complex simulations and the calculations are performed 100x faster than the alternate approaches they examined.  As input to the simulations, the delivery route, expected traffic (live), and location of every supply truck together with its specific raw material is combined in a simulation with customer orders and pricing of those orders, inventory, production capacity by plant to produce a profit optimised production schedule.

Client Value:  In a very short time frame, gained direct insights into each of the newly organized business units and their absolute performance.   Realistic target were set gaining buy-in from senior executives and staff.  The profit optimized production scheduling drives significant performance improvement, delivering in excess of an additional 8% profit.