Centralize Forecasting for Customer and Interplant Demands Using Planning Materials

Centralize Forecasting and Improve Delivery Lead Times by Planning Non-Variable Components of the Family of Products

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  1. Centralize Forecasting for Customer and Interplant Demands Using Planning Materials

    Reading time: 11 mins

    In a typical supply chain, organizations have field locations or distribution centers that stock inventory to cater to customer demands (sales orders) and the stocks are replenished by the manufacturing locations via stock transport orders. Without an SAP planning strategy, manufacturing locations would have trouble forecasting for sales orders and stock transport orders. Organizations can…
  2. Step-by-Step Statistical Forecasting Using SAP APO

    ManagementLearn a 15-step methodology for executing forecasting projects in SAP Advanced Planning and Optimization. Understand the most common methods of statistical analysis. Learn best practices for implementing these methods in practice. Key Concept Forecast strategies are used in SAP Advanced Planning and Optimization to decide how forecast values are calculated. Selecting a method depends on…...…
  3. Improve Forecast Accuracy by Measuring Forecasting Errors

    Learn how implementing Business Add-In (BAdI) /SAPAPO/SDP_FCST4 enables you to store the results of each forecast run in the system along with the forecasting errors. Analysis of these errors helps you to improve the forecast results and thereby improve the forecast accuracy. Key Concept SAP Advanced Planner and Optimizer (APO) Demand Planning has an SAP…...…
  4. Accurately Predict your Procurement or Production Needs with an ERP Forecasting Tool

    Forecasting in SAP ERP is one of the lesser-used planning tools that can help predict your procurement and production requirements effectively. While advanced planning tools such as SAP Advanced Planning & Optimization (APO) can certainly bring greater business process optimization to the company, using this forecasting tool helps a company get a better return on…...…
  5. Advanced Demand Planning with S&OP and SAP HANA

    Learn how to meet the challenges of integrating SAP Advanced Planning and Optimization (APO) statistical forecasting with SAP Sales and Operations Planning (S&OP) and SAP HANA. Key Concept SAP Sales and Operations Planning (S&OP) is a solution powered by SAP HANA that supports an organization’s end-to-end sales and operations planning business process. In SAP S&OP,…...…
  6. 5 Reasons Why the Quality of Your Statistical Forecasts Can Deteriorate

    Learn why the quality of your statistical forecasts can deteriorate and ways to prevent the deterioration from occurring again. Key Concept Historical data is used in statistical forecasting to identify patterns, trends, and seasonality. Those factors are then used to effectively predict future demand. This can be achieved by using the appropriate forecast methods or…...…
  7. 10 Challenges of APO Implementation in the Consumer Goods Industry

    This case study by Rajesh Ray shows the innovative solutions companies adopted to meet challenges when implementing SAP Advanced Planning and Optimization. Key Concept Disaggregation is a process by which values at a higher level of the product hierarchy are distributed to individual products. The consumer goods industry has many industry-specific characteristics that present planning…...…
  8. 10 History Cleansing Best Practices for Reliable Statistical Forecasting

    Generate the most reliable and accurate sales data history for your statistical forecasting as part of your SAP Advanced Planning & Optimization Demand Planning project. See how to implement an efficient and effective history cleansing process. Key Concept The baseline history of a product is its normal historical demand without promotion, external stimulation, or any other abnormal…...…
  9. Improve Current Forecast Models in SAP MM

    Learn how to increase the accuracy of the current forecast models in SAP materials management (MM). This alternative strategy consists of combining different forecasting models by placing weights on individual forecasts. The idea behind the combination of forecasting techniques is that no forecasting method is fully appropriate for all situations. You can apply this improved…...…
  10. Leverage SAP Integrated Business Planning for Forecasting

    Robust is a difficult term to define. It’s something that is useful for the organization, something that makes sense. A robust demand forecasting process must be able to handle variances in demand and enable control your supply chain — with the intent of avoiding situations where you have 1,000 days of inventory or are missing…