Inventory planning and management is generally a well-researched and documented and applied discipline. However, the vast majority of work and associated software products are directed at servicing the needs of the new parts production supply chains, moving product from the likes of Proctor & Gamble to Wal-Mart across the globe (see Linking Planning and Execution Systems for Retailers' Nirvana—Improved Visibility and Fulfillment). It cannot be understated that significant differences exist between the new parts production supply chain and the service and replacement parts supply chain. Companies attempting to manage their service and replacement parts using conventional, new product inventory methods are missing significant opportunities for improved efficiency and effectiveness in their operations, if not working at their peril.
Part Three of Lucrative but "Risky" Aftermarket: Service and Replacement Parts SCM series.
Table 1 depicts how new parts production and service supply chains operate differently and require systems that cater to their differing needs. For example, demand (inventory turnover) for new products is generally much higher than for the counterpart service parts, particularly if the serviceable product is a brand new model with an unknown behavioral history. Increasing product reliability requirements further intensify this difference. Inventory turnover (synonymous with inventory turns) is the number of times that an inventory cycles, or "turns over," during the year, and a frequently used method to compute inventory turnover is to divide the average inventory level into the annual cost of sales. For example, an average inventory of $3 million divided into an annual cost of sales of $21 million means that inventory turned over seven times.
Also, conventional inventory ordering/cost management strategies, like economic order quantity (EOQ), are based on the assumption that there is a strong, continuous demand or velocity of product throughout the system. For example, EOQ (synonymous with economic lot size and minimum cost order quantity) is a type of fixed order quantity model that determines how much of an item is to be purchased or manufactured at one time, with the intent to minimize the combined costs of acquiring and carrying inventory. The basic formula takes into consideration annual demand, average cost of order preparation, annual inventory carrying cost percentage, and unit cost. Needless to say, such simplified formulas are not applicable for spare parts where there is demand for an item is little, uncertain, or not at all.
Thus demand variability or uncertainty is another issue that complicates service and replacement parts planning. Variability in new products supply chains is magnified by the bullwhip effect. The bullwhip effect is an extreme change in the upstream supply position in a supply chain resulting from a small change in demand, downstream in the supply chain. As a result, inventory can quickly move from being backordered (needed in an expedited manner) to being in excess. Such a state is caused by the serial nature of communicating orders up the chain combined with the inherent transportation delays of moving product down the chain. In new parts production supply chains, this negative effect can be mitigated or even eliminated by synchronizing the supply chain, through, for example, collaborative planning, forecasting and replenishment (CPFR), and other more adaptive supply chain management (SCM) techniques. Promotional pricing can also be used, to some extent, to manage demand fluctuations by stimulating demand of new products.
However, demand for spare parts is driven mostly by breakdowns, and much less by planned maintenance. Therefore, safety stock, which is often a minor component of new product inventory levels, remains the sole component for service parts and the only method for managing variability. In general, safety stock (synonymous with buffer stock and reserve stock) is a quantity of stock planned to be in inventory to protect against fluctuations in demand or supply.
While supply chains can be complex and multi-echelon for both new products and service parts, the impact is much different. Namely, in new product supply chains, echelons and nodes increase the complexity of distribution planning and the scheduling of material transfers. In the case of service parts, echelons offer opportunities that significantly reduce safety stock by aggregating volume at higher levels.
Pooling spare parts among divisions and companies with similar assets is a strategy being increasingly considered, since pooled inventories can reduce costs while ensuring that service requirements are met for all parties. Namely, to meet same-day service requirements for products with very low demand rates, inventory must be positioned in a large number of geographic locations. For example, Cisco, maintains inventory in over 700 locations including field locations, distribution centers, and repair centers. These locations may be owned by the manufacturer, distributors, third party logistics providers, or repair providers, and must manage not only the forward movement of inventory, but also the reverse logistics flows for return of damaged items.
Incidentally, basic multi-echelon inventory optimization strategies (regardless of the part being a new or a spare one) involve either pooling demand by keeping inventory at central locations, or forwarding position/push stock into field locations to give great customer service. A very general rule of thumb is for the first approach to be used when demand volatility is high and demand volume is low. The latter is more appropriate for the opposite—low demand volatility and high demand volume. For some new parts, there may also be anassembly or light manufacturing postponement strategy, in order to store basic product configurations, rather than variations.
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