The Power of SAP S/4HANA #3 – Predictive Material and Resource Planning
With SAP S/4HANA 1909, the new SAP Fiori apps “Schedule pMRP Simulation Creation” and “Process pMRP Simulations” are shipped in order to support production planners in identifying and solving capacity issues early in the requirements planning process.
To get a better understanding of Predictive Material and Resource Planning (predictive MRP/pMRP) and its value, it is useful to have a closer look at the term and its single components.
In the context of pMRP, the term “predictive” exceptionally does not indicate machine learning capabilities. Rather, it is related to the comprehensive mid-term simulation capabilities of the solution: Besides simulating the impact of capacity on the planned requirements for selected materials, it also simulates in real-time, how potential requirements, production and capacity adjustments would impact the overall delivery performance.
The term “material” aims to describe one of the central perspectives covered by pMRP, the material perspective. Having entered the initial high-level material requirements for a defined planning horizon, the simulation is capable of end-to-end pegging across all levels. Thus, the interdependencies between the high-level requirements and the resulting lower-level component requirements are mapped and the total impact of a change can always be traced exactly.
The second central perspective of pMRP is the resource perspective. In contrast to the “R” in MRP (Material Requirements Planning), the “R” in pMRP stands for “resource”. This exactly indicates the difference between a pMRP simulation run and an actual MRP run. Although the set-up of both looks quite similar, they have one main difference: The MRP run is infinite, meaning that it breaks down all requirements according to the BOM structure, without considering capacity constraints.
In this context, experts will argue that the SAP solution “Production Planning and Detailed Scheduling” (PP/DS) exactly fulfills the purpose of adjusting requirements and production planning to available capacities. This is absolutely true, if the nature of your production or your branch requires the high degree of sophistication that is offered by the planning capabilities of PP/DS. In this case you can create complex formula-based heuristics to optimize your capacity in situations of any complexity. However, this requires heavy customization efforts which need to be compared with the benefits, a company derives from PP/DS.
As a result, for some companies PP/DS will not be suitable, although they need to plan their capacity and solve potential capacity issues. For such companies, pMRP will be a light-weight alternative offering a quick set-up without dedicated customizing or master data.
Finally, the last “P” in pMRP stands for “planning”. Thus, it once again emphasizes the main purpose and the strengths of the solution. Predictive MRP offers a planning horizon, which is ideally suited for mid-term planning. At the same time, it allows high planning flexibility through the interactive simulation capabilities, which provide the planner direct feedback, in case a variable (may it be requirements, the production or the capacity) is changed.
Having a clear understanding of the term “pMRP”, the following screens will emphasize the explained functionalities:
The “Demand Plan Simulation” view shows, which weeks of the planning horizon (2) will be affected by the identified capacity issues (1).
The inspector provides details about the extent of the capacity issue as well as its impacts and offers links to the most likely next navigation steps.
The Multi-Level Material Simulation allows to drill down into the BOM of a selected material in order to identify the origin of a bottleneck (1). Based on the findings it offers strategies like “Change Source of Supply” or “Preproduce” (2) to resolve the bottleneck.
By selecting the “Preproduce” button, the system identifies underutilization in earlier weeks and allocates the production of missing units to such weeks. As a result, the overall utilization increases and the overall impact of capacity issues is reduced. The system automatically proposes values for the identified weeks, which may be directly adopted and applied.
The alternative to preproduction is to change the source of supply. In this case the system looks for other active production versions and proposes, how production should be distributed across them in order to minimize the impact of capacity issues. Once again, the system proposes values, which can be adopted and applied. However, the option to define values manually always exists.
As counterpart to the “Demand Plan Simulation” view, the “Capacity Simulation View” shows the available capacity per work center and per week. It also indicates the capacity utilization and the resulting underutilization or overloads (1). The latter can also be visualized for a selected work center (2). Having identified a capacity issue, the system once again offers different strategies to handle it. Thus, you can either “Disregard Capacity Issues” or “Change Available Capacity” (3).
The option “Change Available Capacity” results in a proposal of the capacity increase that would be required to avoid a particular issue. If you are confident that your work center can provide this additional capacity, you can adopt the proposal and apply it to resolve the capacity issue.
The simple set up without customization resulting in a mid-term planning tool with flexible end-to-end simulation capabilities makes pMRP highly valuable for production planners and related stakeholders. Watch the video to get a first impression.
The introduced solution is only one of the manifold innovations enabled by SAP S/4HANA. To find out more, stay tuned for our upcoming videos and blogs and feel free to have a look here:
SAP S/4HANA Feature Scope Description: http://spr.ly/6009Ds0UT
SAP Fiori Application Library: http://spr.ly/6006Ds0Uw
SAP S/4HANA Trials: http://spr.ly/6005Ds0Uc