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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.
An inventory management software is a software system for tracking inventory levels, orders, sales and deliveries. [1] It can also be used in the manufacturing industry to create a work order, bill of materials and other production-related documents. Companies use inventory management software to avoid product overstock and outages.
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.
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]
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.
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]
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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.