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  2. Tracking signal - Wikipedia

    en.wikipedia.org/wiki/Tracking_signal

    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.

  3. Inventory planning - Wikipedia

    en.wikipedia.org/wiki/Inventory_planning

    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.

  4. Inventory optimization - Wikipedia

    en.wikipedia.org/wiki/Inventory_optimization

    Scheuffele and Kulshreshtha refer to inventory optimization engines or IO engines, whose function is to analyze inventory data using a holistic approach across the supply network. They note growing interest in their use and application in specific inventory fields, such as plant operations, assembly lines, and within transportation. [1]: 4–7

  5. Mean absolute percentage error - Wikipedia

    en.wikipedia.org/wiki/Mean_absolute_percentage_error

    It is a measure used to evaluate the performance of regression or forecasting models. It is a variant of MAPE in which the mean absolute percent errors is treated as a weighted arithmetic mean. Most commonly the absolute percent errors are weighted by the actuals (e.g. in case of sales forecasting, errors are weighted by sales volume). [3]

  6. Supply chain optimization - Wikipedia

    en.wikipedia.org/wiki/Supply_chain_optimization

    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 ...

  7. Dynamic lot-size model - Wikipedia

    en.wikipedia.org/wiki/Dynamic_lot-size_model

    The dynamic lot-size model in inventory theory, is a generalization of the economic order quantity model that takes into account that demand for the product varies over time. The model was introduced by Harvey M. Wagner and Thomson M. Whitin in 1958. [1] [2]

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