Article Abstract It is critical to control the cost of service support, especially high dollar mission-critical parts. OEMs are already investing in large inventories of spares to cover diverse locations. Further expense can come when the part(s) is no longer manufactured and a lifetime buy (LTB) is necessary to ensure spares availability through several years of the service support life. Forecasting for this LTB is difficult because of the long time horizon and other changing factors. Often a LTB results in gross excess or shortages over the support life. By having an effective repair strategy, the need for LTBs is often eliminated or greatly reduced. It is best to have an effective repair strategy rather than taking on the challenge of long-term forecasting and a costly LTB.

We often see discussions, articles and blog posts addressing the complexities of the service supply chain. Much focus is given to the high-velocity retail segment (i.e. phones, TVs, etc.). On the commercial side, discussion is often centered on the high-volume areas (i.e. laptops, networking, storage, etc.).

Equally important, however, is the service supply chain for low volume, high-mix, parts and products. This group includes parts which are considered business critical and usually are high-cost parts. An example would be an OEM’s mid-range and high-end enterprise servers. These parts and products are integral components of the end customer’s mission-critical applications. These systems of intelligence often address “big data” and enterprise business continuity.

This segment of parts creates quite a challenge for the service supply chain manager. Since these parts are commonly used in mission critical applications, there is a high “stock-out” cost associated with them across a customer’s extremely distributed installed base. With same-day service contracts, companies must stock spare parts across a large network of locations. Even with the best service parts planning tools, a significant inventory investment is required to fill the supply chain.

Filling that supply chain is an expensive proposition. Once filled, supporting that supply chain as part usage occurs is also expensive. OEMs must consider various strategies to fund on-going support of these enterprise customers throughout (and beyond) the support life-cycle.

There are two primary phases of support;

1. Support while product and parts are still being manufactured for sale
2. Support after manufacturing has ceased

While still in the production phase, parts are readily available for purchase to support on-going parts needs. Things get exponentially more complicated, however, once the second phase is in play. There will be a time when the manufacturer announces a last production run for parts, as they plan to re-tool for a new product (EOML – End Of Manufacturing Life). The problem is that the OEM’s customers who bought the old product still need support. This is when the traditional approach of a massive “lifetime buy” (LTB) is used.

The service support life often exceeds the manufacturing period. When this happens, it is very common to order a lifetime buy of parts at the very end of the manufacturing period. You have to be ready to accept a large batch of parts to sustain the customer support needs throughout the remaining support period. Often, this can be another several years (EOSL – End Of Service Life).

What is the one thing that we know for sure about a lifetime buy forecast? The answer is simple, it will be wrong. You will either over-forecast having too many parts and will be faced with a costly write-off, or you will under-forecast and be short, leaving your customers hanging.

Forecasting service parts is already considered a challenge. With long time horizons, beyond the EOML, forecasting accurately is nearly impossible. Further complicating matters is consideration of a declining installed base, a “trade in / trade up” program, credit returns, receiving dock yields and other yields through the process. Each of those streams and yields must be forecasted as part of the LTB calculation. The bottom line is that having to make a lifetime buy decision is a high stakes, no-win situation.

Besides the substantial amount of inventory associated with a LTB purchase to cover expected demand of several years, there is the cost of inventory. Included in this cost is;

1. The opportunity cost of the money used to buy the inventory
2. Warehousing expenses tied to storing, counting and recording the added inventory
3. Transportation and handling costs
4. Obsolescence costs
5. Insurance and taxes

The cost of inventory expenses average between 20% and 25% of the inventory value.

A solution which drastically reduces the lifetime buy decision stress is to adopt a repair strategy. The approach is rather simple. When a unit fails in the field, the core is recovered and the unit repaired / refurbished to be as good as new. Fundamentally, this approach takes the guess work out of predicting how many units are going to fail in the future. You don’t need to know how many are failing; only that you have a reliable means to repair the units now and into the future. A repair strategy can be very cost effective as well, as there is very little wasted expense. By matching the expense (the repair) with the need (field failure) when it occurs, you are not only delaying the expense, but you don’t have to make that lifetime buy guesstimate. Repairing failed inventory is often the best course to take to minimize service parts expense.

If you have an effective repair strategy, the only remaining challenge is effectively balancing your long-term declining demand and your scrap rates. For example, if you were repairing all the parts that failed and demand was level, then all would be fine. However, some parts that fail may be beyond repair and are candidates for scrap. This can happen either because a part was physically damaged or because the part had been previously repaired numerous times and it’s reached a threshold to be categorized as non-repairable and unreliable. Before panicking that the scrap has robbed you of valuable defectives needed for repair, you would need to assess if demand was declining. If demand is shrinking, then even with some level of scrap, you may still have enough spares to support lower safety stock levels. Also, good and defective spares become more available over time as customers exit the installed base and upgrade to newer products. This allows a growing source for a shrinking support population over time.

If demand is not dropping and due to scrap you still have a need for some level of additional inventory, there are still alternatives to a lifetime buy. Many companies utilize partners who are talented in locating used products in the marketplace and harvesting spare parts from these.

Steve Brown, former Global Product Life-cycle Manager for HPE, had concerns about LTB parts that were needed together. Steve said, “In the past, HPE might end up with $1M of inventory we could not use because we didn’t have $100K of inventory that we sorely needed. That is, a LTB is a “formation” of parts flying together over time; some have higher than forecasted demand (shortage), while others end up with lower demand over time (excess). If they’re needed together to effect a customer’s repair, then you’re just out of luck when the high demand part runs out in year 3 and you still have 7 years of support left. Thus, LTBs are how excess and shortage are created. Better to have an on-going form of support (repair) than taking on the challenge of long term forecasting of very expensive parts.”

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On-going repair adds value to a defective only when it is needed, not before. Cash is conserved; need is answered only as it arises. Contrast this with doing a LTB, which involves trying to figure out how many spares you need against demand over 10 years or more.

By using an effective repair partner, you can eliminate the need for multi-year, inaccurate and risky forecasts. Instead, focus on close examination of the declining demand and the attrition of inventory from the supply chain (scrap). By utilizing service parts planning tools and leveraging your repair provider, you can save cost and improve customer service levels.

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Ken Ueltzen Mark Anderson
Ken Ueltzen, Vice President, Business Development, Ken has over 30 years of experience in electronics manufacturing and aftermarket product support. He began his manufacturing career at Unisys and Intel, followed by Packard Bell NEC where he was the Vice President of Manufacturing. Ken came from Dell Computer where he was the Director of Operations for the Home and Small Business PC Division. He has an Engineering Degree from Cal Poly and an MBA from Sacramento State University. Ken is the holder of two patents and has taught for the Graduate School of Business at Sacramento State University. Mark Anderson, Vice President, Repair Solutions, Mark has over 30 years experience in the service parts industry. He began his career at Texas Instruments where he was Customer Service Planning Manager. He joined Hewlett Packard as the Global Support Logistics Planning Manager where he implemented a worldwide inventory management system for HP’s support organization. He later joined Agilent Technologies as the company’s Support Planning Manager where he was appointed to head the Corporate Strategic Supply Chain Development Program. As VP of Supply Chain Solutions, he guided Baxter Planning Systems to a leadership position in the service parts planning industry before joining Cokeva in 2013. Cokeva is a world-class, industry leading third party aftermarket hardware support and services provider of high technology and complex products. Our core competency is in providing high-quality, cost-effective technical repair and supply chain solutions to the high-value, mission critical commodities arena.