Basel, CH – June 2015

Planning Scenarios with DPS

Planning Scenarios with DPS


DPS in brief


Data Process System (DPS) enables you to select, arrange and map any data from the ERP system:





The basis for any DPS process is the selection of data from the SAP ERP system. Depending on the customizing settings, all SAP tables can be used as a data source. Before the selected information is displayed for the user, it can be amended and expanded by means of determinations, conversions, conditions (requirements, allocations) and function modules. User-specific selection options can be defined and amended at runtime in each process.





The selected data can be transferred back to the SAP ERP system or to another subsystem using DPS functions or customer-specific function modules.





DPS processes can be run both in SAP GUI and with touchscreen applications using the Remote Application Framework (RAF) (see Newsletter 12/2014). The standard functionalities of an ALV grid are used in SAP GUI. The user receives access to all DPS processes via a single SAP transaction and can navigate between the authorized processes.


Disassembly planning with DPS


DPS is used in the meat industry for various planning scenarios along the entire supply chain in areas such as production, packaging, task allocation, disassembly push-pull planning and many more. This article will look at disassembly push-pull planning (the balance between supply and demand) as an example. Other areas will also be explained in future newsletters.


DPS enables customers to tailor disassembly planning to their individual needs, depending on how the planning process should work. The starting point for planning is usually the live animals which are to be slaughtered on a specific day (or another planning horizon) at a specific plant. Further possible inputs for supply-oriented planning may include the stock of carcasses in the cold store or stocks in other storage locations.




All of these quantities can be input materials in a Softproviding Meat MRP calculation, which is created in the background from the DPS planning cockpit. If required, various calculations simulating different quantities can be created. These can also use different cut lists as a basis for the calculation.


The pull planning, which takes the required quantities of the output materials in the cut list as a starting point, is performed in a second step (the push/pull planning can also be performed in a single step depending on the system configuration). The calculation then works out the number of animals, carcasses or primal cuts required to meet the demand. If an MRP calculation has already been created (the push planning has already been performed), it is now updated automatically with the requirements, and the supply and demand are optimized.


The optimization shows how much of each output material in the cut list is obtained when the animals are slaughtered and disassembled and the actual level of demand. All relevant data can also be displayed in the planning cockpit (such as the contribution margin of the output materials). Optimization is now a job for the relevant employee, who needs to answer questions like the ones below based on his or her experience:


  • Should certain materials be put into storage?
  • Do we have storage space for frozen goods?
  • Should we discuss postponing live animal deliveries with the suppliers?
  • It’s barbecue time! We should take the good weather into account and focus on our barbecue range … and many more besides!

After optimizing supply and demand, the planning can be approved and disassembly orders created for the individual organizational areas with the appropriate planned quantities and values. This enables a comprehensive planned/target/actual comparison to be made during and after work on the corresponding orders.


If we have awakened your interest and you would like to see an example of disassembly planning in Meat Management by Softproviding, please don’t hesitate to contact us at or call Stephan Kronbichler directly on +41 (0)61 508 21 42.