In the previous articles of our blog series, we discussed the fundamentals of forecasting models as well as consumption-driven forecasting. These forecasting methods are essential for efficient material requirements planning. In this final article, we focus on the implementation of such forecasting models in SAP systems, one of the leading ERP systems worldwide. SAP offers extensive functionalities to integrate both qualitative and quantitative forecasts into material planning, thereby ensuring optimal supply chain reliability.

The Importance of SAP in Material Requirements Planning

SAP systems play a central role in corporate planning and control, particularly in material requirements planning. The integration of forecasting models into SAP enables companies to accurately predict demands, ensuring efficient inventory management and resource planning. This is achieved through a combination of historical consumption data, advanced analytical tools, and a certain degree of machine learning.

Forecasting Methods in SAP

  1. Qualitative Forecasting in SAP:
    • SAP offers tools such as Demand Planning (DP) within the SAP Integrated Business Planning (IBP) module, which supports qualitative methods. These include expert opinions and scenario analyses, complemented by flexible planning and simulation capabilities.
  2. Quantitative Forecasting in SAP:
    • Time Series Analysis and Regression: SAP enables the use of time series analyses and regression models directly in the Material Management module. These models utilize historical data to identify patterns and predict future demands and are included in SAP’s standard functionalities.
    • Exponential Smoothing: SAP supports various smoothing techniques to capture short-term and long-term trends as well as seasonal patterns. These models can be implemented via the SAP Advanced Planning and Optimization (APO) module or the SAP IBP module.
    • Maschine Learning: By integrating machine learning methods available in SAP Leonardo, companies can identify complex patterns in large datasets and continuously improve their forecasting models.

Advantages of SAP-based Forecasting

  1. Centralized Data Management:
    • SAP provides a centralized platform for managing and analyzing data. This enables a consistent and up-to-date data foundation for forecasts, increasing the accuracy and reliability of predictions.
  2. Automated Processes:
    • SAP allows for the automation of many processes, from data collection to the calculation and application of forecasts, saving time and reducing human errors.
  3. Integration and Collaboration:
    • The information is already available in the system. This makes it easier to use and integrate into daily workflows compared to introducing an additional product.
  4. Flexibility and Scalability:
    • SAP systems are flexible and scalable, meaning they can grow with a company’s needs. Whether it’s a small business or a multinational corporation, SAP can be adapted to specific requirements.

We tend to overestimate the effect of a technology in the short run and underestimate it in the long run!

Roy Amara, American Scientist

Use of Forecasts in SAP

Most companies either do not use forecasting models or use the wrong ones. Selecting the right method depends on the quality of the data—it should be as high as possible, and weaknesses should at least be known—and an understanding of the characteristics of the items being planned.

Before using a forecasting method, some questions about the item to be planned must be answered. Is it at the beginning of a lifecycle, in its peak phase, or nearing the end? Is the consumption seasonal, and how can the consumption be characterized in general (e.g., ABC-XYZ analysis)? These characteristics significantly influence the consumption pattern and, therefore, the appropriate forecasting method.

Let us assume it is a material with a constant or trend-like pattern. In this case, the moving average or weighted moving average model would be suitable, as it smooths out random irregularities and can account for constant patterns well. The model delivers good results if the characteristics of past results do not change significantly.

If different weights are to be assigned to the months of the calculation period, this must be specified in SAP under “Weighting Group.” Here, the respective weighting factors determine the significance of the monthly values, and, for example, more weight can be assigned to recent months.

It’s the Little Things That Matter

In our blog series, we have explored the various facets of forecasting models in material requirements planning. From the basics of qualitative and quantitative forecasting to specific methods of consumption-based forecasting and their implementation in SAP systems, we have discussed the key aspects and application possibilities.

The efficient use of forecasting models is crucial for optimal material planning. It allows companies to predict demands more accurately, optimize inventory levels, and streamline the supply chain. SAP provides a powerful platform that supports this through centralized data management, automated processes, and the integration of advanced analytical tools like machine learning.

While the use of such systems and models may also present challenges, such as data quality and system complexity, the benefits clearly outweigh these drawbacks. A well-implemented forecasting strategy in SAP helps companies reduce manual effort in planning, lower capital costs through reduced inventory levels, improve decision-making processes, and respond more flexibly to market changes..

The American scientist Roy Amara once said: “We tend to overestimate the effect of a technology in the short run and underestimate it in the long run.” The use of forecasting models and a system-supported approach is no panacea, yet it can lead to significant improvements in material planning.

With this summary, we would like to conclude the series and hope to have provided you with valuable insights into the world of forecasting models and their implementation in SAP systems. If we have piqued your interest in optimizing your planning processes using forecasts, we also offer individual coaching with test materials to assess feasibility and benefits. Together, we can work on optimizing your material planning and, consequently, your entire business model!