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Inventory

Inventory requires a significant investment by an organization. High inventory investment if not matched to sales negatively impacts an organization by reducing its return-on-asset utilization, however, and if excessive or obsolete it may not be useable. The inventory turnover ratio measures how much inventory is on hand to support sales. It is defined as the average inventory investment necessary to support the COGS. In many organizations, inventory investment represents a significant proportion of the COGS (i.e., ~5% to 20% of COGS or more). This is for several reasons such as the types of industry and process design (e.g., batch versus continuous flow), process issues, and poor planning.

Inventory turnover directly relates to a products lead time, its expected demand, and the required service levels. Organizations periodically take actions to reduce inventory levels by applying improvement projects. But how far inventory can be reduced depends on the ability to reduce lead time and mange demand. In fact, benchmark statistics show inventory turnover ratios vary across diverse industries in a range of one to one hundred or higher. These ratios depend on the type of industry and process, but also on the effectiveness of inventory management. As an example, in organizations that have many different products and limited capacity (e.g., consumer products), inventory will be created and stored in distribution centers. When an organization produces many different products, it is difficult to reduce economic production lot sizes without applying significant process engineering redesign through technology, although Lean significantly helps (e.g., single-minute exchange of dies and many other effective methods). Inventory management practices also vary based on the underlying process design. There are make-to-order, assemble-to-order, and make-to-stock systems. Inventory investment strategies are different for each one. Make-to-order and assemble-to-order processes will not have a large finished goods inventory compared to make-to-stock systems. Make- to-stock systems have high finished goods inventory levels because of the number of products which need to be produced in advance of demand because of limited available production capacity. In contrast, investment in raw material and WIP inventories is usually higher in make-to-order and assemble-to-order systems if system throughputs are low. It is important that organizations understand what is necessary to manage and optimize inventory investment to efficiently allocate investment resources.

Inventory models use lead time, expected demand, and service levels to calculate an optimum inventory quantity. This quantity is the amount of inventory an organization should have available for an item at a specific location to satisfy customer demand and meet the required service level. A model could also be used to re-calculate inventory investment by simulating changes in lead time or demand. This helps identify improvement projects to reduce lead time and better manage demand, including forecasting models. But, an organization may be constrained as to how best to achieve in practice the calculated optimum inventory quantities. Constraints are associated with product and process designs, quality and other issues, inventory management policies such as economic order quantities, supplier issues, and other constraints. There may also be legacy inventory investment that impacts inventory turnover targets. Legacy is a significant quantity of excess and obsolete inventory from prior years. It is caused by purchasing or producing too much inventory in advance, poor forecasting, and other issues. It may not be possible to immediately use or dispose of legacy inventory, but organizations should develop plans to reduce excess and obsolete through write-offs, selling at a discount, or sending materials back to suppliers. In addition, the causes of excess and obsolete inventory should be eliminated by systematically reducing lead times and demand variation using Lean, Six Sigma, and supply chain best practices.

Inventory investment problems can be exacerbated by where a product is in its life cycle. As an example, in the introduction phase of a product, demand forecasts may be in error. In fact, actual demand for some new products may not occur, resulting in obsolete inventory. If demand is higher than forecasted, there may not be enough inventory to satisfy customer demand, and sales will be lower than forecast. When a product enters its growth phase, there is increasing competitive pressure on sales. Higher operational efficiencies and effective inventory management are required to maintain profit margins. Even moderate amounts of excess or obsolete inventory can significantly reduce a product’s profitability at this point in its life cycle. Differentiation of a product into several design variants also complicates inventory management. This occurs if a design has been slightly modified to satisfy different market segments and these design variants are be inventoried separately. A common example is packaging differences between similar products that are sold to different market segments or major customers. Finally, in a product’s maturity and decline phases, demand may decline and become sporadic, resulting in a mismatch between inventory availability based on forecasting models and actual customer demand. These issues increase excess and obsolete inventory.

Inventory accumulates value as it progressively moves through a process. As an example, WIP inventories are valued using accumulated material cost and direct labor as well as allocated overhead costs. Inventory is an investment of available capacity and is built because a process cannot produce on demand. It could also be built for anticipated future interruptions caused by labor issues, plant closures, or interruption to supply. Because inventory is an asset with monetary value, it must be accurately accounted for to ensure correct financial reporting. It must be protected from damage, spoilage, and pilferage to prevent loss of value.

Organizations control inventory using inventory models that are incorporated into IT systems. These systems manage the receipt and shipments of materials as well as inventory status. The most common inventory model is a perpetual inventory model, which records receipt and shipment transactions for all items as they occur. These transactions may not be 100% accurate because in some organizations materials receipt and product shipment files are separate and they may not be synchronized until they are periodically refreshed. This refreshment cycle varies. If all transactions are in the same system, the inventory status will be up to date. If they are in different systems, there will be a mismatch of inventory status. This is important from a process perspective because additional inventory may be ordered or shipments may be backordered if inventory records are not synchronized. The periodic review model is a second common inventory model. Using this model, receipts and shipments are periodically adjusted, which means there will always be a mismatch between receipts and shipments until the next review point when they are balanced. There are many other types of inventory models having pros and cons that influence effective inventory management.

Inventory valuation also varies by organization. Some organizations use a first in, first out (FIFO) valuation method in which materials are used in the order in which they are purchased for use. A FIFO valuation system matches the flow of materials through a system. The COGS valuation method reflects a net calculation of beginning inventory plus purchases minus ending inventory. The last in, first out (LIFO) valuation method calculates the COGS based on the cost of the most recently purchased materials. Inventory valuation using a LIFO method varies depending if the perpetual or periodic review inventory management systems are used as the inventory model. If material costs are increasing over time, the LIFO method may be more useful to an organization because its COGS sold will be higher, effectively lowering income taxes. Another inventory valuation method is the average cost valuation method. In this method, inventory value is calculated as the current inventory investment divided by the current inventory quantity.

Fraudulent inventory valuation practices may occur if an organization does not have the financial and operational controls necessary to ensure receipts, shipments, and other inventory transactions are accurately recorded during day-to-day operational activities. An organization can distort its financial performance by not correctly entering receipt, shipment, or inventory transaction information or by delaying their entry into the various systems that manage these transactions. Process breakdowns such as these distort estimates of income, asset level, and cash flow. Inventory valuation problems also occur from a variety of other process issues. These are found and eliminated using frequent cycle counting audits.

Inventory has useful purposes. It maintains the independence of internal operations by serving as a buffer for both internal and external demand variation. Inventory also provides production scheduling flexibility, maintains the independence of supplier deliveries, and ensures that economic order quantities and lot sizing targets are met in practice. Maintaining adequate inventory levels to ensure operational independence is critical for maintaining a process takt time. This is particularly true at a system’s bottleneck to keep it utilized. Recall that a bottleneck resource must be kept operating to maintain process throughput at the takt time rate. Regardless of the reasons for inventory, systematic reductions in investment can be made using projects that reduce lead time or demand variation.

Each inventory type has a service-level target. Raw materials and WIP normally have high service levels because a process depends on their availability. In contrast, finished goods service levels vary by a product’s annual demand and its gross margin. Low-volume products having a low gross margin will normally have lower service levels than products with a high annual demand and gross margin. Raw material and WIP inventories use a service target that is expressed in units, whereas a finished goods service target can be expressed in units, lines, or orders. It should be noted that units must be used in the calculation for safety-stock calculations. A line item is one product with an associated quantity. Orders consist of one or more line items, and each line item has an associated quantity. Organizations will use all three service-level metrics depending on the discussion. External customers speak in terms of order fill, logistics speaks in terms of line fill, and inventory managers speak in terms of unit fill.

A service target should be very carefully defined and calculated to ensure an organization can fulfill orders to meet customer requirements. Once a service-level target has been set for each inventory classification, or for specific items within a classification, inventory safety-stock calculations are made to ensure product availability at the service-level target. Available implies that the probability of not running out of a product during its replenishment lead time or the reorder point lead time equals its service level. If the per-unit service level target is 95%, the probability of not running out of a product will be 95%. One way to think of this is that, for every 100 units ordered, five will be backordered if the per-unit service level is 95%.

This situation is complicated by the fact that not every order contains the product in question, and different orders may require different quantities of a product. For this reason, order fill, although correlated to per-unit fill, will usually have a lower actual service level than unit fill. This situation is common where orders consist of several high-volume products that drive higher per-unit fill rates of an order despite the fact that lower-volume products may be missing from the same order. In fact, the per-unit fill rate in these situations could be 99%, but the order fill rate, as measured by the “order being 100% complete,” could be less than 50%. For this reason, as mentioned earlier, organizations often use three service-level metrics to measure fill rates. Inventory service-level targets are set on a per-unit basis because to do otherwise would require conducting simulations based on the order profiles. In simulations, an order distribution, as represented by the products that make up an order, is modeled and service targets are set on individual products to ensure they were available to fill orders 95% of the time. Inventory levels are then set based on an order fill rather than a per-unit fill statistic.

 
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