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## What is Period Order Quantity?

Period Order Quantity (POQ) is an inventory management technique used to determine the optimal order size and timing for replenishing stock. It is a method of balancing inventory costs and customer service levels. The goal of POQ is to minimize the total cost of inventory while maintaining an acceptable customer service level.

### How Does Period Order Quantity Work?

POQ is based on a set of assumptions about the demand for a product and the costs associated with ordering and holding inventory. The assumptions are used to calculate the optimal order quantity and frequency for a given product. The first step in calculating POQ is to determine the average demand for the product over a given period of time. This can be done by looking at historical sales data, or by using a forecasting model. Next, the cost of ordering and holding inventory must be determined. This includes the cost of ordering the product, the cost of holding the inventory, and the cost of any lost sales due to stockouts. Finally, the optimal order quantity is calculated using a formula that takes into account the demand rate, the ordering and holding costs, and the desired customer service level. The resulting order quantity is the POQ.

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### Benefits of Period Order Quantity

The main benefit of POQ is that it helps to minimize the total cost of inventory while maintaining an acceptable customer service level. This is accomplished by balancing the cost of ordering and holding inventory with the cost of lost sales due to stockouts. In addition, POQ can help to reduce the complexity of inventory management. By using a formula to determine the optimal order quantity and frequency, it eliminates the need to manually calculate the best order size and timing for each product.

### Conclusion

Period Order Quantity is an effective inventory management technique that can help to minimize the total cost of inventory while maintaining an acceptable customer service level. It can also reduce the complexity of inventory management by eliminating the need to manually calculate the best order size and timing for each product.