Predictive Material and Resource Planning (pMRP) is a new SAP S/4HANA Cloud product for simulative and interactive long-term demand planning. The aim is to identify potential capacity problems as early as possible on the basis of a predefined demand for finished products and to identify possible solutions. The simulation calculates the demand for components, purchased parts and resources and thus provides production planners with a basis for decision-making in the event of changed conditions, e.g. with regard to demand planning, deployment plans, prefabrication or make-or-buy decisions.
Forward-looking material and resource planning provides production planners with a basis for making decisions when conditions change, e.g. with regard to requirements planning, deployment plans, prefabrication or make-or-buy decisions:
1. Material Forecasts:
Checking the feasibility of forecasts including availability of capacities and suppliers
> Prevention of stock-outs during marketing campaigns
2. Capacity planning:
Adaptation of shift programs or expansion of machine capacity, early communication with employees and production
> Preparation for expected production volume
3. Strategic procurement:
Renegotiation of contracts due to economies of scale
> Reduction of purchasing costs
4. Operational procurement:
Derivation of future component requirements
> Creation of medium and long-term overview on component and purchased part level, improvement of cooperation with suppliers
To create a simulation scenario, the master and transaction data is copied from the operational S/4 environment into a separate pMRP planning area. The most important objects here are materials, bills of material, work centers & work schedules, production versions and planned independent requirements. Instead of pre-planned requirements, sales orders can also be used aggregated in buckets. The predictive MRP then calculates the demand for components and purchased parts as well as the capacity utilization based on a simplified image of the data. Any changes made, for example to capacity availability or pre-planning requirements, can then be transferred back to the operational environment.