Just-In-Time (JIT) is an integrated set of activities designed to achieve high volume production with minimal inventory as parts arrive at a work station exactly when they are needed (Jacobs and Chase, 2011). JIT systems work to reduce inventory by allowing management to control the flow of materials. Materials are received, used to finish goods, and sent out of the door as demanded. In an ideal situation, a JIT system would provide goods to meet demand and no more since the ultimate goal is zero inventory. Companies typically hold inventory in three phases; raw materials, work-in-process, and finished goods. Opportunity costs result when holding a supply of inventory in each phase at the same time since the related space and capital that could be put to other uses. A JIT system frees up the resources which might allow warehouse space to be used as retail space or other purpose (i.e. increased production space) without expanding facilities. Costs may be reduced by eliminating the need for additional warehouse staff. With a JIT system, employees can be trained to work different workstations when product demand is low (i.e. employees working with raw materials would be free to train since decreased demand would call for no raw materials in a JIT system). A better trained employees lead to other cost savings and increased customer satisfaction as employees are better able to focus on quality and efficiencies at their workstations. In addition, a JIT system also helps to uncover production problems. In a traditional system, an overstock of finished goods in inventory helps to meet customer demand but could hides unnecessary production down time.

The primary disadvantage to JIT lies within its relative complexity when timing delivery of raw materials and production of goods. Management must consider the work flow and anticipate demand in order to estimate when raw materials should be delivered and when final products should be finished and ready for customers. To make JIT work, managers must put significant time and effort into supply chain management. According to Bhatnagar (2009), there are several ways to improve efficiencies within the supply chain to make JIT successful. To start, managers must improve sales forecasts for production planning so that the suppliers can be better informed about the requirements. Better and timely information to suppliers allows them adequate time to prepare for deliveries. If sales forecasts change, suppliers must be notified as soon as possible. In addition, managers must establish close working relationships with suppliers since JIT can work only when there is mutual cooperation and trust. Managers might consider reducing the number of suppliers to aid in building those relationships. Managers and suppliers must work to eliminate non value added activities within the supply chain and within the production process. To conclude, all goods received from suppliers must meet certain quality requirements to avoid gaps in production due to defects. With a JIT system, there is little room for mistakes. The process is extremely reliant on suppliers and estimates of customer demand. If raw materials are not delivered on time, the entire production schedule could be delayed while workers are paid for down time, etc. If customer demand is forecasted incorrectly, there is no spare finished product available to meet unexpected orders since all products are made to meet actual orders as they come in. Either of these situations may lead to stock-out costs. Stock-out costs are any related costs that result when there is insufficient product to meet demand (Pan and Hsiao, 2001). Demand might be later met with back-orders, or the company might lose those sales. Management understanding the cost of stock-out costs is critical to balancing the costs of holding inventory with the missed profits and other costs associated with an item being out of stock. The task for management then focuses on how to measure stock-out costs.
Stock out costs include both the lost profits from the immediate order because of cancellations, and the long-run costs associated with missed future orders. According to Gaur and Park (2006), stock-out costs are equal to the number of days the company is out of stock multiplied by missed revenue per day (the average number of units sold per day multiplied by price per unit) plus the cost of consequences. The formula is expressed as CS = (NDOS x AUSPD x PPU) + CC. Gaur and Park (2006) build on the Hall and Porteus (2000) result by considering a model with asymmetric customer learning. They found that when customers experience positive or negative service encounters, they update their expectations about future encounters. In their research, Gaur and Park observed significant reductions in long-run demand among customers who experienced a stock-out. The stock-out adversely impacted not just the profits earned on the out-of-stock item, but also other items in that order. In addition, customers who experienced stock-outs were less likely to place future orders with the company. Once managers understand how costly a stock-out can be, they must determine how to respond to mitigate these costs when a stock-out occurs. Gaur and Park found evidence that firms can mitigate the cost of stock-outs by changing the explanations that their customer service representatives offer to customers when items are out of stock. For example, offering discounts encourage customers to backorder rather than cancel their orders. Within the supply chain, stock-out costs may be mitigated with adequate and timely communication. Improvement of demand forecasting with timely updates to changes can help managers plan raw material needs. In addition, these needs must be communicated to suppliers timely and accurately so that the needs are met. Management may also consider keeping some safety stock on hand to fill unexpected orders.