Background
In Supply Chain management, pretty often manufacturing companies store goods ahead of season. In such case, one of the critical factor is storage space in network being DCs or factories. Best example I found was in Water business at Ne.. or Da…
Often additional storage space is contracted to 3rd pty logistic. From the execution side, this is never a big problem, even if expediting is the most common way to proceed (nervousness and stress).
Downside of spreading goods in network is about planning DRP as it is organized to have demand placed (Forecast and orders) on normal DCs. Therefore the DRP planning engine determines shortage situations and calls for replenishment, as on the other hand additional storage place are out of reach of DRP engine, not being modelled thru transportation lane or even in hidden locations. To avoid this unwanted effect, and optimize production requirement to the only real required qty, many scenario are possible which are either complex, tedious or not robust, and in all case not easy for users.
Encountered solutions
Solutions 1
- Mass change product master to set deployment mode to Push.
- Run fake deployment to simulate a push back of goods onto real DCs.
- Heuristic.
- Delete fake deployment.
- Mass change product master back to normal deployment mode.
This solution is a sensitive solution, depending of too many steps (what if job fails), not performant, all products to have similar setting for deployment. Typical solution inherited of constraining corporate organizations, that do not give access to ABAP or advanced method. Therefore consultant try their best with available tools.
Ranking : Low.
Solutions 2
Setup a SNP Optimizer project for DRP concerns. Probably the best result any DRP calculation can provide. Downside is a huge cost of implementation and design, ownership by users of the solution is close to 0 as complexity is huge. Only consultant doing it would pretend this is simple (for him). Solution can only be reliable with tight control and operations (jobs, master data etc..) Not the tool for medium sized companies.
Ranking : High.
Solutions 3
Aggregated planning in SNP. For those of you who know SNP aggregation, I imagine you smiling. Concept is great in SNP, setup and usability is just very poor along with series of frustration, complexity and cumbersome steps. SAP would invest a little money to kill the hierarchy management and change for a simple group maintenance, this solution would really the one for all. Never happened since 1998 and APO 1.0. Just a pity.
Ranking : Solution to go.
Solutions 4
Write an ABAP program that deals with stock balancing ahead of heuristic, creating a fake distribution (like in solution 1). One program, one variant this is it! Implementation time about 5′. By the way we, at DOWAP, provided this solution to several of our customers (Delpeyrat, Kraft Mondelez, Bledina…). Running silently since years is our best feedback.
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