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How does SAP ERP forecasting help predict material consumption?
To help you prepare realistic sales, production and procurement plans, try leveraging SAP ERP forecasting to calculate your materials needs.
Planners often face nightmarish situations when a company experiences an unexpected spike in demand for a product...
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or when a slack sales season leads to a huge inventory buildup. Planners strive to avoid these crisis-like situations because they can disrupt the entire logistics and supply chain. The SAP ERP forecasting functionality is a planning tool that helps bring greater sanity to sales, production or procurement plans and minimize out-of-stock or massive inventory buildup situations. Forecasting features can be found in three SAP modules: Sales and Distribution (SD), Production Planning (PP) and Materials Management (MM).
The ERP forecasting functionality uses a material's historical consumption data and chooses the relevant forecasting model to predict the material's future demand. Forecasting models, which consist of relevant formulas and calculations for a particular material, are a statistical tool the system uses to predict a material's future consumption quantities. Available forecasting models include constant, moving average and seasonal moving average. Planners can forecast any type of material, be it raw material, packing material, consumable, semi-finished or finished. This capability to plan material consumption at any level or for any material type helps provide greater organizational efficiency.
When a new material code is created, the system automatically enables the consumption tab. When inventory-related transactions of a material's consumption take place (e.g., goods issuance against production order, maintenance order, sales order or cost center), the system automatically updates the consumption quantities in the material's consumption tab. Not only does the system record planned consumption of the material, but also unplanned consumption. A planned consumption is the predefined quantity that the system expects to consume either against a production order or a maintenance order. When the actual consumption or issuance of material exceeds the planned consumption (e.g., due to production waste), the system marks it as unplanned consumption and adds it to the total material consumption. Forecasting uses a material's total consumption quantities (both planned and unplanned).
Because forecasting needs a material's historical consumption data to forecast accurately, the system provides an option to manually enter the historical consumption figures. This option is especially useful when a company has just implemented an SAP ERP system and does not have enough consumption data, but it wants to immediately start using the forecasting tool for planning purposes.
Forecasting also helps a planner create a sales plan or a procurement plan. To create a sales plan for a material, a forecast model must be assigned to the material. With the constant forecast model, the system provides a fixed quantity for each future consumption period, such as for a week or a month. Similarly, with the moving average forecast model, the system averages all past consumption quantities to determine a quantity for each future consumption period. For the seasonal moving average model, the system determines fluctuating quantities to account for a material's high or low demand for future consumption periods. If a planner is unsure which forecasting model to use, the system can automatically select the correct forecasting model. However, SAP does not recommend that a planner use automatic model selection because the forecast model the system assigns may not be the best fit. Choosing the wrong model may lead to incorrect forecast quantities. It is prudent to periodically evaluate an automatically chosen forecast model for its practical application and suitability to meet business needs.
ERP forecasting is not restricted to an individual material; it's also available for a product group, which consists of a group of individual materials or products and the percentage contribution each makes to the product group. For example, "Tomato Ketchup" may be a product group in which individual ketchup sizes such as Sachet, 100ml PET bottle and one gallon contributes 25%, 35% and 40% of a company's sales volume. The planner enters total historical consumption of this product group and runs the forecast program. The system correspondingly breaks the forecast figures into three different products according to the defined percentages.
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