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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]
The average inventory is the average of inventory levels at the beginning and end of an accounting period, and COGS/day is calculated by dividing the total cost of goods sold per year by the number of days in the accounting period, generally 365 days. [3] This is equivalent to the 'average days to sell the inventory' which is calculated as: [4]
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. Lag is based on the leadtime from order placement to order delivery. For example, if the lead time of an order is three months, then the forecast snapshot should be Lag 3 months.
By using many variables as inputs the MPS will generate a set of outputs used for decision making.Inputs may include forecast demand, production costs, inventory money, customer needs, inventory progress, supply, lot size, production lead time, and capacity.
Reorder level = Average daily usage rate × Lead time in days = 50 units per day × 7 days = 350 units. When the inventory level reaches 350 units an order should be placed for material. By the time the inventory level reaches zero towards the end of the seventh day from placing the order materials will reach and there is no cause for concern.
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Quantitative methods use available data and analytical tools in order to produce predictions. Demand forecasting may be used in resource allocation, inventory management, assessing future capacity requirements, or making decisions on whether to enter a new market. [3]
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