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Calculating forecast attainment periodically (monthly for example) provides visibility to the overall achievement of the plan and the total business bias. The time period of shipping activity should be compared against the forecast that was set for the time period a specific number of days/months prior which is call Lag.
The key word here is forecast. What is the SCOR scenario that resembles a production based on a forecast? The answer is, M1 "Make Build to Stock". How does the company supply materials from the Far East? The diagram explains that the company supplies raw materials in bulk from the Far East against a monthly forecast. Forecast is again the key word.
We have available a forecast of product demand d t over a relevant time horizon t=1,2,...,N (for example we might know how many widgets will be needed each week for the next 52 weeks). There is a setup cost s t incurred for each order and there is an inventory holding cost i t per item per period ( s t and i t can also vary with time if desired).
The S&OP process includes an updated forecast that leads to a sales plan, production plan, inventory plan, customer lead time (backlog) plan, new product development plan, strategic initiative plan, and resulting financial plan. Plan frequency and planning horizon depend on the specifics of the context. [1]
The classic supply-chain approach has been to try to forecast future inventory demand as accurately as possible, by applying statistical trending and "best fit" techniques based on historic demand and predicted future events. The advantage of this approach is that it can be applied to data aggregated at a fairly high level (e.g. category of ...
Collaborative planning, forecasting, and replenishment (CPFR) is an approach to the supply chain process which focuses on joint practices.This is done through cooperative management of inventory through joint visibility and replenishment of products throughout the supply chain.
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By integrating accurate demand forecasting with inventory management, rather than only looking at past averages, a much more accurate and optimal outcome is expected. Integrating demand forecasting into inventory management in this way also allows for the prediction of the "can fit" point when inventory storage is limited on a per-product basis.