Materials Planning: How the New Algorithms Help

Two new materials planning methods combine the benefits of traditional material requirements planning (MRP) and consumption-based planning (CBP) in supply chain management.

One is demand-driven planning, which allows companies to plan materials based on consumption without a forecast, rather with a preview of future requirements. And the other is the Theory of Constraints, which is particularly suited to situations where accurate forecasting is difficult.

Anyone who has been involved in materials planning in recent years will be familiar with MRP and CBP. MRP uses a demand forecast as an input for planning and, therefore, usually requires access to historical data or to reliable sales order data. CBP, on the other hand, does not use forecasts to determine longer-term future requirements, using the reorder point to trigger purchase orders and production orders. In practice, the decision about whether to use MRP or CBP depends on whether generating a forecast is worth the effort involved.

Forecasting Demand Is Costly and Time-Consuming

It makes sense for consumer goods manufacturers who sell large quantities of laundry detergent, for example, to use an MRP forecast for planning because washing machines are in continuous use. So, as Ferenc Gulyássy, an SCM Business Processes senior consultant at SAP, explains, “There are likely to be only relatively minor unexpected fluctuations in demand for laundry detergent.”

But not every industry can generate forecasts simply and reliably. At companies in the mechanical engineering industry, for example, planners have to plan several hundreds of thousands of materials. “For them, the effort of creating a detailed forecast for every single material is just too great,” says Gulyássy. Therefore, many companies use statistical algorithms to generate forecasts for active items. However, this automated approach cannot adequately account for the specific aspects of certain materials.

Push Control in Procurement: Forecasts 80 Percent Accurate at Best

The downside of MRP, as a push type of inventory control, is that “Quantities are pushed into the process even though the company does not have an accurate picture of customer demand,” says Gulyássy. At best, he says, the likelihood of a forecast – even a good one – being accurate is usually between 70 and 80%.

The downside of CBP, as a pull type of inventory control, is that the long-term perspective is lost. Suppliers rely on forecasts to produce and deliver parts reliably, and they even give their customers discounts where forecasts are available. A preview of future quantities is required for capacity planning and availability checks, too – but is not possible as a standard in consumption-based planning. A blend of push and pull control would therefore be ideal.

MRP and CBP: Advantages to Both

The compromise companies adopt is to vary the use of pull and push control according to material or material group. “This means that they have to classify all their materials,” says Gulyássy. For example, the purchasing department might use consumption-based planning and others might use MRP. That would mean suppliers wouldn’t get a forecast, but the company would be able to perform accurate capacity planning and availability checks.

In practice, this compromise means that resource management is not ideal, because companies often compensate for uncertainty by building in buffers. So, sometimes stock levels are too low and sometimes too high. “That could mean that a company works in three shifts when two would be sufficient,” explains Gulyássy, “or that it spends money on expensive and higher-performing machines to provide flexibility – when it doesn’t actually need to.”

Demand-Driven Planning and the Theory of Constraints as a Basis

The two new materials planning methods leverage the benefits of both the push and pull strategies – though each focuses on just one of those two strategies. The new methods are derived from the planning philosophies of demand-driven planning (demand-driven replenishment planning) and the Theory of Constraints (bottleneck-oriented planning) that are possible with the SAP SCM consulting solutions from release 2018. The idea is to create the optimal pull-push hybrid and therefore benefit from the advantages of both planning methods for each individual material at the same time – without losing information about future quantities in the multi-level context.

Leveraging the Benefits of MRP and CBP in SCM

With the customized MRP type add-on in SAP Supply Chain Management (SAP SCM), SAP gives customers the option of using two new algorithms. The “DD” (demand-driven) approach is based on consumption-based planning, which is augmented by aspects of MRP such as, notably, the preview function, which, if required, also takes account of dependent requirements. The “TOC” (Theory of Constraints) approach is based on demand management but also follows the reorder point strategy for triggering procurement and production proposals and has consumption-based planning embedded in it.

At operational level, planning is consumption-based, while demand management creates a forecast of the longer-term perspective. In both cases, this happens directly in production, not in a simulated environment. “This means that planners have immediate and full transparency across the entire planning period in the current stock/requirements list,” says Gulyássy.

DD and TOC for Planning: Four Benefits at a Glance

Now, no matter whether they use SAP ERP or SAP S/4HANA, companies can supplement the familiar materials planning methods with one of the new algorithms – provided that they have the customized MRP type add-on. The benefits include:

  • Both new methods enable a preview of future quantities, which is calculated from known sales orders or is based on a forecast, that is reflected in the planning of the entire bill of material and bill of distribution structure at all levels.
  • The functions for capacity planning, previews of future requirements for suppliers, and availability checks (similiar to MRP) can be used at all times.
  • Consumption triggers replenishment, which means buffers that were often required in the past for subordinate bill of materials and distribution levels are no longer necessary.
  • The preview of future requirements can be created directly from the operational environment. A separate simulation, such as long-term planning for consumption-driven materials, is not necessary.

DD: The More “Reactive” Sibling of TOC

The two add-ons for SAP ERP and SAP S/4HANA were developed by SAP consulting in conjunction with customers.

One of them, a tool manufacturer from Switzerland, benefits specifically from TOC. “It can perform consumption-based planning without the added effort of a forecast – and still has an overview of future requirements,” says Gulyássy.

Another, a mechanical engineering company, is using DD, the more “reactive” sibling of TOC, which is particularly suitable where forecasts are difficult to generate.

This story originally appeared on the SAP Germany News Center.