Supply Chain Management: Morphing the Functional Scope of Service Parts

The Morphing Functional Scope of Service Parts SCM

There are many requirements involved in the supply chain management (SCM) of service and replacement parts that make the process different from traditional, "new parts" SCM (see Part One). As a result, some specialist SCM solutions have been developed to address these challenges. Some might resemble conventional SCM solutions, but feature different approaches. The requirements of service and replacement parts SCM solutions also vary given the wide range of members that exist across multi-node supply chains. Each of these members can be grouped into a few major solution functional categories.

Part Two of the Lucrative but Risky "Aftermarket" Business: Service and Replacement Parts SCM series.

Service and replacement parts resource management, which is the main focus of this article, consists of a variety of solutions that are comparable to supply chain planning (SCP) components in conventional SCM suites. Service and replacement parts management has inventory optimization at its core that determines the best way to stock inventory across the supply chain to maximize service levels while minimizing investment. In other words, the basic goal is to maintain the optimal placement of resources, including parts, tools, and service technicians, across service regions to meet service level agreement (SLA) commitments at the lowest possible cost.

These spare parts planning systems provide the means to define and implement a spare parts inventory strategy that meets enterprise objectives. In other words, they tend to help enterprises understand the relationship between a customer service target level and the value of the inventory required to support it. To that end, they combine forecasting with replenishment logic to determine the optimal level and mix of parts to carry at each stocking tier, given certain capital investment targets and customer service level goals. Unlike finished goods, where nearly 100 percent customer service levels are desirable, here only certain classes of spare parts need to be available all the time, at all supply chain nodes.

Spare parts planning systems might also improve user productivity, since by automating the basic forecasting and replenishment process, planners and inventory managers can focus on exceptions and more-strategic planning activities, such as how to handle expensive, slow-moving items or how to use substitute parts to reduce costs or obsolescence.

Achieving this goal requires a mix of tools. These range from strategic tools identifying demand profiles, service objectives, and the best way to position resources to meet demand, to tactical tools determining what orders need to be placed to meet strategic objectives. Such goals include managing the risk inherent in allocations and transships; repair or new purchase orders; new product introductions (NPI) or discontinuations; and the replenishment and redeployment decisions.

Tactical refinements of inventory optimization entail setting minimum and maximum inventory levels, which recognizing stochastic, changing demand and lead-time. The algorithms required to provide this support are significantly different from those found in conventional, new parts production SCM, and justify the use of focused, point solutions, including dynamic programming, simulation, mixed integer optimization, etc. In the case of inventory optimization, two parts may be present:

  1. Multi-echelon optimization determines optimal stocking levels of an item at a particular location, based on the item's possible investment levels. In this case, an echelon is the level of supply chain nodes, or disintermediation. For example, a supply chain with two independent factory warehouses and nine wholesale warehouses delivering product to 350 retail stores is a supply chain with three echelons between the factory and the end customer. One echelon consists of the two independent factory warehouses, the other echelon consists of the nine wholesale warehouses, and the third echelon consists of the 350 retail stores. Each echelon adds operating expenses, holds inventory, adds to the cycle time, and expects to make a profit.
  2. Multi-item optimization determines the optimal allocation of inventory investment across items in a product group.

Even fundamental concepts like customer service level are different in the service and replacement parts milieu. Namely, in new parts production, the customer service level (synonymous with customer service ratio, fill rate, order-fill ratio, and percent of fill) is a measure of the delivery performance of finished goods, usually expressed as a percentage. In a make-to-stock (MTS) company, this percentage usually represents the number of items or dollars (on one or more customer orders) that were shipped on schedule for a specific time period, compared with the total that were supposed to be shipped in that time period. Likewise, in a make-to-order (MTO) company, the customer service level is usually a comparison between the number of jobs or dollars shipped in a given time period and the number of jobs or dollars that were supposed to be shipped in the same period. Yet, in the service and replacement parts world, with a high level of unpredictability, how can one forecast the dollar amount of service or repair parts that were supposed to be shipped during a particular period?

Thus, given the random nature of service and breakdown events, it is clear that demand uncertainty (which can be measured by the standard deviation, mean absolute deviation [MAD], or variance of forecast errors) cannot be eliminated through traditional forecasting methods. Hence, trade-offs must be evaluated on the basis of captured future risk assessments; estimates of demand probability distribution, relevant to specific customer products; and locations at future points in time. The decisions made across the planning horizon thus constitutes an exercise in risk management

This is Part Two of a four-part note.

Part One discussed the business challenge.

Part Three will continue analyzing service parts planning.

Part Four will cover players and benefits and make user recommendations.

Comparing Traditional Planning to Risk Management

Table 1 compares the traditional planning approach found in enterprise resource planning (ERP), supply chain planning (SCP), and first generation service supply chains to elements of advanced, contemporary risk management planning approaches. It should clarify why traditional, new products SCM approaches are not able to handle the demands of the service parts supply chain.


Traditional Planning Approach

Risk Management Approach


Creation of service offerings with limited understanding of cost and service tradeoffs. Budgets are created through crude estimation, guesswork and historical extrapolation.

Intelligent design and modeling of service offerings include pricing of offering, SLA and inventory tradeoffs, and network configuration scenarios to optimize investment in assets to achieve maximum return.

Strategic Forecasting

Production-based forecasting from historical demand that does not recognize probabilistic nature of demand.

A proprietary composite forecasting methodology that combines time series demand history with causal factor projections to generate item-location specific estimates of usage probability distributions.

Strategic Positioning

Each part location and inventory echelon is planned in isolation or in planning groups, without considering multi-echelon, multi-indenture, and system interactions.

Up to date multi-echelon optimization based on rapid solution algorithms and strong model or system architectures that can be applied across a wide range of industries and company contexts.

Tactical Planning

Deterministic distribution requirements planning (DRP) type logic using deterministic forecasts not suited to intermittent demand environment. Characterized by unplanned, reactive expediting.

Risk-based decision-making that incorporates the probability of stock-out in all order generation and deployment activities, integrating strategic and tactical planning.

Event Management

Fulfillment to traditional fill rate metrics, whereby fulfillment strategy is not tied to asset management strategy, and responses are reactive.

Differentiated SLA commitments enabled by strategic positioning of inventory, including availability-based planning, which maximizes product up-time for budget constrained multi-echelon, multi-indenture, multi-period environments. Consequently, responses are pro-active through asset re-deployment prior to service event based on risk projections and optimized post-event fulfillment.

Table 1: Traditional versus risk management approaches.
Source: MCA Solutions

Another functional category, service and replacement parts delivery management solutions, are analogous to supply chain execution (SCE) components in conventional supply chains. The execution side of inventory optimization takes into consideration constraints on supply, transportation, and warehouse resources, perform detailed tactical cost minimization (such as possible consolidation opportunities, etc.), enable visibility into stock movements, leverage lateral transfers, etc. For more information, see SCP and SCE Need to Collaborate for Better Fulfillment.

Bundled with these, customer relationship management-like (CRM) solutions provide a means to manage service requests considering contractual or SLA entitlements (or restrictions) and resource availability. Additionally, relevant logistics management solutions manage the rapid dispatch of parts to customers and the return, repair, or discontinuation of broken or condemned parts. Service requests can come from many places in addition to a problem report from a customer, and these service requests must be routed to the right company representative and then efficiently dispatched for field service.

In addition to reported problems, effective service management requires that service problems and preventative maintenance calls be proactively generated by these applications. As the service request is reviewed, company representatives must have the ability to review all past service requests, as well as all relevant contracts, SLAs, and warranties in order to determine customer entitlements and the best course of action. Near real-time tracking of service delivery and repair activities across depots and service centers are other crucial components of the execution side. In this regard, mobile, wireless technologies are playing an increasingly important role.

Service Life Cycle Management

This brings us to service life cycle management (SLM), which is a holistic business initiative focused on the after-sale service of products and clients. Simply put, SLM focuses on making more money from the product after the initial sale and is a way to become a strategic part of the customer's business after the sale is completed. Another benefit of SLM is the automation and optimization of the service processes in the field, since resource utilization and efficiency can be increased through effective call scheduling, allowing more service to be performed with fewer technicians. Companies see the value of completing service calls on the first visit through deploying the right technician with the right skills and service parts at the right time.

Perhaps most importantly, SLM can integrate service-oriented business processes that span from the time of the service request, to the satisfaction of need, to billing or warranty. SLM, like any other business initiative that involves new business processes is best implemented alongside other strong enterprise applications. Two primary capabilities that are required in this process are call center and field service applications. These two categories of software provide support for capturing or generating the initial service request and manage them through to completion all the way to the back-office. In order to manage the total life cycle of the service requirement in a continuous business process, integrated call center and field services capabilities are essential.

Call center applications must manage the demand for service through to completion, in order to satisfy the needs of the customer and the manufacturer or distributor. The initial service request may come from a number of different sources, all of which must be captured and processed through the call center. In addition to telephone, self-service, or e-mail requests, an increasing number of products are being embedded with self-monitoring capabilities that can evaluate the health of the product and self-report on service needs.

Once the service request has been reviewed and targeted for service, field service applications must then be able to ensure that optimal resources are deployed to provide the service. Once dispatched, technicians or service representatives should have ready access to information about the product they are servicing; the customer; and the product's maintenance history and configuration in order to complete the service on the first call. In addition to being knowledgeable, the technician should be armed with the appropriate parts and tools for the job—parts that may have been planned months in advance, when applicable (e.g., in case of periodic maintenance).

Service representatives should then be able to close the loop on the service call and provide the home office with appropriate information on the time and materials used to complete the call, which is then used to generate appropriate billing and update warranties and SLAs. For more information, see Service Lifecycle Management—Tapping into the Value of the Product Aftermarket.

Moreover, given the existence of a number of various third party providers in the service and replacement parts supply chains, there is a need for service and replacement parts network management applications to coordinate all the parties involved in supporting the needs of OEMs and asset owners. This requires a collaborative infrastructure that integrates business processes and automates transactions across SCM trading partners. The integration and role-based portal presentation of network information, like product designs, service contracts, and asset and service histories are another key responsibility of this functional suite of solutions.

Last but not least, enterprise asset management (EAM) or computerized maintenance management systems (CMMS) solutions are also related, despite their focus on asset owners instead of the service and replacement part providers per se (for more information, see EAM Versus CMMS: What's Right for Your Company?).

Nevertheless, integrating information about assets (e.g., drawings, service history, etc.), and asset owners and their activities into the service and replacement parts supply chain is critical, as companies shift to newer outsourced EAM business models. Proactive maintenance strategies, such as reliability driven maintenance (RDM), enabled by external access to plant instrumentation monitoring and alerts is a prime example of how tight integration between EAM and spare and replacement parts SCM can facilitate better handling (for more information, see Reliability Driven Maintenance—Closing the CMMS "Value Gap"?).

This concludes Part Two of a four-part note.

Part One discussed the business challenge.

Part Three will continue analyzing service parts planning.

Part Four will cover players and benefits and make user recommendations.

About the Authors

Olin Thompson is a principal of Process ERP Partners. He has over twenty-five years experience as an executive in the software industry. Thompson has been called "the Father of Process ERP." He is a frequent author and an award-winning speaker on topics of gaining value from ERP, SCP, e-commerce and the impact of technology on industry.

He can be reached at

Predrag Jakovljevic is a principal analyst with (TEC), with a focus on the enterprise applications market. He has nearly twenty years of manufacturing industry experience, including several years as a power user of IT/ERP, as well as being a consultant/implementer and market analyst. He holds a bachelor's degree in mechanical engineering from the University of Belgrade, from the former Yugoslavia, and he has also been certified in production and inventory management (CPIM) and in integrated resources management (CIRM) by APICS.

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