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Inventory planning involves using forecasting techniques to estimate the inventory required to meet consumer demand. [1] [2] [3] The process uses data from customer demand patterns, market trends, supply patterns, and historical sales to generate a demand plan that predicts product needs over a specified period.
Forecasting is the process of making predictions based on past and present data. Later these can be compared with what actually happens. For example, a company might estimate their revenue in the next year, then compare it against the actual results creating a variance actual analysis.
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.
Demand forecasting plays an important role for businesses in different industries, particularly with regard to mitigating the risks associated with particular business activities. However, demand forecasting is known to be a challenging task for businesses due to the intricacies of analysis, specifically quantitative analysis. [4]
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.
Forecasts can relate to sales, inventory, or anything pertaining to an organization's future demand. The tracking signal is a simple indicator that forecast bias is present in the forecast model. It is most often used when the validity of the forecasting model might be in doubt.
Inventory management is a broader term pertaining to the regulation of all inventory aspects, from what is already present in the warehouse to how the inventory arrived and where the product's final destination will be. [2] This management involves tracking field inventory throughout the supply chain, from sourcing to order fulfilment.
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 ...