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  • SLM Hub Topics

  • New SLM Resource from Industry Week

    No longer a tired after-sales routine, service is now the strategy that builds and establishes reputations, sells the product, and creates new business potential for vendors and customers. However, many manufacturers still haven't tapped into the profit potential of post-sales service. Learn how many companies are organizing their service processes under the umbrella of Service Lifecycle Management, in much the same way as they’ve done in areas like Supply Chain Management and Product Lifecycle Management.

  • On Demand Webinar

    Learn why an integrated approach to parts pricing and planning helps boost service profits.

Servigistics and MCA? Really?

By Mark Vigoroso

Anything I say on this topic will sound like an advertisement for Servigistics, right? Although I did spend 5 years as an impartial analyst covering this space. Perhaps you will permit me to speak from the latter perspective? Not buying it? Well, here goes anyway… This merger IS indeed good for the market.

At global 5000 durable goods manufacturers, post-sales service operations are incredibly complex value chains with innumerable points of failure upon which billions of dollars of revenue and profit rely. Service parts planning and optimization is all about minimizing capital tied up in inventory while maintaining or improving service performance – measured by fill rate, asset availability, or some other metric of SLA compliance.

For this – and all the other potential points of failure in the service lifecycle – service organizations need to balance two important factors when choosing technology partners: 1) Level of functional specialization, and 2) Staying power. Weight the first factor too heavily, and you risk ending up with a mish-mash of point solutions costing you more than they’re benefitting you. Weight the second factor too heavily, and you risk ending up with a monolithic IT provider that’s a jack of all trades, master of none. The mission of Servigistics is to deliver the perfect balance of these two factors, and this merger furthers this mission.

Regarding the Service Lifecycle Management space as a whole, this is a marathon, not a sprint. Scratch that, this is the Iron-Man. Not only for solution providers like Servigistics, but also for our current and prospective clients. The merger with MCA is a step along the way. Servigistics will be making build/buy/partner decisions for the foreseeable future to both DEEPEN and BROADEN our SLM portfolio to meet the needs of our clients and the market as a whole. MCA fits mostly into the “deepen” category. There will be others that fill white spaces in our existing footprint.

So, buckle up. Better yet, get your cycling shoes ready, because I’d say we’re just about approaching the end of the 2.4 mile swim!

 Mark Vigoroso is SVP Global Marketing and Alliances for Servigistics.

Dysfunctional Service Network? 3 Reasons Why You Need SLM

By Jim Schoessling

Many organizations today employ a depot-based model to manage their service assets.  In this scenario, the asset that needs to be repaired is usually transported from its installed location to another location to be serviced, such as a repair depot. This is typical for most industrial equipment and high tech service networks. Unfortunately, more often than not, the service network is disjointed, lacking the visibility, integration and coordination to function in a manner that fosters good customer service let alone potential to generate positive revenue growth instead of additional costs. Is your service network Depot-based?  Does this sound uncomfortably familiar?

A recent Gartner report mentioned that “industrial and high-tech companies are pursuing strategies in support of total customer experiences” and “reducing complexity that merely leads to inefficiency and lower profitability.” With this in mind, it got me thinking about how truly dysfunctional these depot-based service networks can be for most of these companies and what steps they can take to become more agile. The processes in a depot-based service network usually include complex order management and orchestration, routing optimization, scheduling, warehouse management, repair management and shop floor controls, end-to-end network visibility, knowledge management, service parts planning and business performance management. With such a complex service network, the opportunity to cut out inefficiency and profit erosion by adopting a Service Lifecycle Management (SLM) approach is compelling. Depot-based SLM provides the necessary coordination and visibility to improve service productivity, customer asset availability, and overall service profitability.

Here’s why it is an imperative:

1. Few service organizations today have established the needed execution capabilities, coordination and visibility across their service network. Disjointed technology and silo’d business processes across the contributing stakeholders engender inefficiencies and bleeds profits.  In addition, companies often deploy systems that were designed for their fulfillment (forward logistics, NPI, etc.) services and try to shoehorn it into working for their aftermarket, reverse logistics services.  Most systems built for the forward side (like ERP’s and other point solutions) cannot handle the complexity of the Services/Reverse side when it comes to complex orders, changing ownership, product condition, and the associated cost changes

2. Though there are numerous return models in a typical service session, an Advanced Exchange model is a common process that attempts to get a replacement part to a customer as soon as possible.  But without the proper underlying systems, capable of creating and orchestrating the complex order flows and the full stream network visibility, vendors ultimately under-perform for the customer and create a network of inefficiencies that result in significant and avoidable costs.

3.  A classic example of a disjointed service session for an asset failure can result in excessive process steps that result in expensive downtime for the customer with high service costs for the OEM and/or service provider. Without SLM, Depot-based organizations lack the underlying tools and processes to enable effective diagnosis, order management, optimized repair and warehousing and integration and visibility into the extended service network. For most organizations there is no closed-loop integration back to manufacturing, planning or quality detailing the root cause of the defect, thereby creating a void in vital information that can prevent future defects.

Still not convinced? With a service session that has depot-based SLM and an integrated process; the major stakeholders have improved visibility and control of the service network and the maintenance event, creating a more seamless execution scenario. Everyone from call center to shop floor technicians are well armed and make more informed decisions in order to coordinate effectively among the nodes. The steps taken to service the asset are reduced which can yield around 89% uptime improvement, 57% lower service costs and $500 in over-stock avoidance. Pretty good ROI if you ask me!

Jim Schoessling is Vice President of the Service Logistics Business Unit at Servigistics. Prior to joining Servigistics, Mr. Schoessling spent 7 years at Lucent Technologies (now Alcatel-Lucent) within the Supply Chain Networks (SCN) division in various key management positions including IT Systems and Processes, Demand Planning, Order Management, Order Fulfillment, and Strategy & Optimization. Jim has a Bachelor’s degree in Mechanical Engineering from Marquette University and a MBA from the Kellogg Graduate School of Management at Northwestern University.

Now you see it, now you don’t! The challenge of intermittent demand

By Dr. Nezih Altay and Dr. Andy Litteral

If you are a frequent reader of this blog you already know some of the challenges of managing service parts.  It starts with operational questions such as where should we store them, how much safety stock do we need, or what are the demand forecasts for the next, say quarter;  and extends to broader strategic level decisions like how to incorporate  after-sale service business into the strategic plan.

Recently, we published an edited book that touches some of these issues: Service Parts Management – Demand Forecasting and Inventory Control.  There are two main reasons for focusing our book on forecasting and inventory control: first, in a 2008 Delphi study by Boone, Craighead and Hanna (published in Operations Management Research) SLM executives unanimously identified service parts forecasting as one of the main challenges. Secondly, although  a handful of books on SLM already exist in the market, none focus on the interaction of forecasting with inventory control. We wanted to close this obvious and critical gap in SLM literature.

Authors hailing from more than ten countries contributed to our book. Although their approaches to solving service parts related problems are widely divergent, everyone involved in this project agreed on two things: the management of service parts is important due to its prevailing nature and the problems associated with the management of service parts are complex and really difficult. The first point is the motivation for the book and we think that the second point is moderated somewhat by the talent, experience, and hard work of the contributors.

We think that academics and practitioners will find Service Parts Management – Demand Forecasting and Inventory Control valuable, as a starting point for their research or to augment their current knowledge. The results presented in it, as well as the foundation upon which those results are built, are indicated in the extensive literature reviews and reference sections of each chapter.

The book starts with describing the statistical properties of intermittent demand, shows the bias Croston’s approach introduces to the forecast and proposes a correction for it (Chapter 1).  Although Croston’s forecasting method labels service parts demand casually as intermittent, the discussion on demand categorization schemes in Chapter 10 reveals that not all service parts items are created equal. Chapter 2 further dives into demand characteristics testing three large datasets (approximately 13,000 SKUs) and identifies which statistical distributions provide good representations of service parts demand for parametric forecasting and simulation.  Four different forecasting methods with varying difficulty are also described in the book: Bayesian forecasting (Chapter 5), decision trees (Chapter 3), bootstrapping (Chapter 6) and a causal demand modeling approach which makes use of a wide range of information available in the production system (Chapter 8). While the above chapters mainly focus on individual item forecasting, Chapter 4 takes on aggregation and discusses the effects of it on demand management.

The book also includes parametric heuristics to calculate safety stock and replenishment levels (Chapter 11), meta-heuristics such as reactive tabu search to design and stock a service parts network (Chapter 13), as well as reliable rules to decide when to stop carrying an item in stock (Chapter 12).  There are also two chapters in the book that focus solely on inventory control of aircraft spares (Chapters 7 and 9).

The final chapter in the book – contributed by our friend Andrew Huber of Xerox Corp. – provides a practitioner’s view to service parts management. Andy lists some of the misperceptions about service parts management along with the mistakes they cause in operations, and offers ways to alleviate the pain.

We leave you with the following misperceptions: 1) service is not that profitable; 2) parts management is not that hard; 3) good planning is all that is required; and 4) forecasting is purely statistical. We are sure that you can recall some of your own misperceptions and the consequent mistakes when you started in this business.  Some or all of these perceptions may as well be gone now for you experienced SLMers but the challenges of managing service parts are still there.

The co-editors of Service Parts Management, Drs. Nezih Altay of DePaul University (naltay@depaul.edu) and Andy Litteral of the University of Richmond (llittera@richmond.edu) teach statistics and operations management in their respective schools and have published several articles on service parts forecasting. They are very much interested in your feedback and input regarding service parts forecasting and inventory control.

SLM Hub Exclusive: Disgruntled elf blows whistle on Santa’s SLM program!

Jingle McSorley was the former Lead Elf of the Land of Misfit Toys.  Last Tuesday after a heated exchange with Santa, he threw down his miniature apron and stormed off the North Pole ice.  The SLM Hub conducted the first-ever exclusive live interview with a Christmas Elf, revealing shocking details of the massive and controversial inner workings of Santa, Inc.

SLM Hub:  “Jingle, thank you for joining us today, and apologies for this hot Atlanta air.  You were the esteemed Lead Elf at the Land of Misfit Toys for 325 years.  Why are you leaving now, and why so suddenly?”

Jingle:  “Bah!  The Land of Misfit Toys is a ghost town.  That was a cushy job watching those islands.  I got to know each toy over the years, and each island evolved its own culture, unaware of the others.  Now Santa knows what toys are where, and the toys are never there for more than a few days before they’re repaired or recycled into newer toys.  Even Rudolph doesn’t visit anymore.  He went and got a nose job last year, now that Santa’s sleigh has fog lights.”

SLM Hub:  “Jingle, it sounds pretty rough.  Did you consider transferring to the main warehouse?  I hear they have excellent benefits there”.

Jingle:  “Yeah, the pay is higher at the warehouse now, but there’s no bonus stock left for us anymore on December 26.  That used to be our holiday, when we’d get the inventory surplus that the good kids didn’t want.  Santa’s so darn accurate at predicting wish lists now.  He has databases of prior wish lists and even wires the Mall Santas to listen in on the kids’ current requests.  It’s maddening.  The stats elves are to blame. My elf kids are still playing with TeleTubbie dolls and “Who Wants to be a Millionaire” board game surpluses from 10 years ago.  Do you have any idea how annoying TeleTubbies are, let alone after 10 years?  Santa, have mercy…overstock on some Legos and PlayStations, please!”

SLM Hub:  “Well, surely Christmas Eve must be a blast for the elves.  Is it still the biggest party north of the Arctic Circle?”

Jingle:  “Christmas Eve ain’t what it used to be either.  It was smooth sailing before the population started exploding in 1945.  We’d have a few drinks, load up a few sleigh loads and that was it – Santa was off for the night and we’d party like it’s 1899.  Now we have a zillion good kids, and no extra staff.   Santa doesn’t even deliver presents himself anymore, except to the very best kids, like Yankees fans.  He outsources the rest on GPS-fitted sleighs and watches them like a hawk from his command center.  If any of them veers off course, stops too long for spiked eggnog, or idles the Flux Capacitor on a rooftop, an alarm sounds, and he’s all over them.”

SLM Hub:  “Even though you’re a gruff old curmudgeon, Santa would surely ask you to return, and you could name your price.  Think of all the experience you have in servicing toys.”

Jingle:  “If I played that card 10 years ago I’d be a rich little man!  It’s tough to keep good talent in the North Pole, you know.  The smart youth wants to go way down south to Fairbanks or Edmonton where there’s warmth and excitement – no Justin Bieber or Bryan Adams concerts in the North Pole.  We had a huge talent gap a few years ago, but Santa got the best and brightest elves off of the toy making lines and had them write their service wisdom in a knowledge base.  Santa now pays us based on our knowledge contribution rather than toy-saving heroics.  The elf cowboy days are over.”

SLM Hub:  “Sounds like quite an operation.  I bet the good children are happy.”

Jingle:  “Yes, surveys are way up.  We haven’t missed a good kid’s house before dawn in 7 years.”

SLM Hub:  “What do Dasher, Dancer, Prancer, Vixen, Comet, Cupid, Donner, and Blitzen think about all of these changes at Santa, Inc.”

Jingle:  “I don’t know.  I haven’t seen them in five years.  They’re all retired in the Caymans, living off of huge stock dividend checks.”

SLM Hub:  “What do you want for Christmas?”

Jingle (excited):  “A Red-Ryder carbine-action, 200-shot Range Model air rifle!”

 SLM Hub:  “You’ll shoot your eye out.”

 Jingle:  “This interview is OVER.

About Jingle McSorley:

Jingle McSorley is the former Lead Elf of the Land of Misfit Toys.  He was born in 1697 at the North Pole, the son of a wooden toy elf, and began his career in the metal toy shop. But, when toy returns began 1786, he transferred to the repair depot, better known as the Land of the Misfit Toys and stayed there until his untimely exit in 2011.  An avid ice fisherman, Jingle is now retired in Barrow, Alaska, where he is working on his memoirs and consults global toy executives.

Special thanks to frequent SLM Hub guest contributor Dave Duncan for this “exclusive” interview. Happy Holidays!

Defining MEO: What it is… And what it isn’t

By Steven Caldwell

Multi-Echelon Inventory Optimization has been around a long time in the manufacturing supply chain. But what role does “MEO” have in the post-sales supply chain? We’ll get to that… But first, please indulge me in a brief holiday diversion…

It’s the time of year where shoppers are hustling around trying to find the perfect gifts for their loved ones. Many will be purchasing the latest high tech gadgets and a few will be making bigger purchases like new automobiles, boats or other types of motorized vehicles. Few consumers will spend a lot of time thinking about when those purchases will inevitably need to be serviced. But for those of us in service, it’s all we think about.

We know that operating profits can be buried – or unlocked – in our service parts planning, field service and logistics operations. Planning service parts inventory to provide maintenance on these products in the future plays a critical role in ensuring high customer service levels down the road and overall profitability for the service organization.

Why is planning service parts different from inventory planning on the production side? First of all, service parts have unique attributes such as product lifecycle phases, condition statuses, demand variability, replacement causes, configurations, multiple locations, sourcing hierarchies, and warranty dependencies. What’s more, aftermarket parts managers have to deal with a mix of fast- and slow-moving parts with stochastic demand patterns, a large array of part versions due to multiple generations of a product in the field, maintaining service levels through a complex service network, coordinating parts stocking plans with the tactical deployment of labor at the point of service, and a multitude of other challenges unique to the service lifecycle.

Simply stated, the goal of service parts management is to ensure that the right parts are stocked in the right locations in the service network in order to minimize capital tied up in excessive inventory holdings while maintaining or improving customer service levels. Simple to say, extremely complex to execute globally. Part of the reason for this complexity is the existence of multiple echelons in most stocking networks, including central warehouses, field and regional locations, consigned locations, dealer and distributor locations, and trunk stock. Which brings us back to the topic of MEO.

What is MEO in the aftermarket? MEO enables a service parts planner to determine the lowest cost solution to achieve desired service levels across a multi-echelon service network using advanced optimization solvers. True MEO is a proactive balancing of inventory across stocking locations in your supply network and should not be confused with reactive re-balancing. This is a critical distinction.

Only true MEO extends the capabilities of the part-location pair-based stocking level generation process by providing stocking recommendations to meet target service levels (and/or budget limitations) based on an extensive and holistic analysis of the repair, replenishment, and procurement network for each part. Unlike traditional inventory management theory, where most replenishment decisions focus on the field location level, with nothing taken into account at any distribution center level, MEO considers the network as a whole, where upstream stocking positions directly impact resupply lead times for downstream stocking locations. This methodology of optimizing the entire distribution network enables companies to maximize efficiencies in stocking along the distribution path in such a way as to benefit all subordinate locations without compromising their ability to meet demand.

So what is MEO worth to service parts planning operations? MEO often yields significant inventory cost savings – to the tune of 25-40% – in addition to the savings achievable with pair-based planning, proportional to the complexity of the distribution network.

MEO results in the best combination on both sides of the inventory equation— maximum customer service level with minimum inventory investment. And as companies are looking for cost reductions in 2012 that don’t have proportional negative impacts to the customer experience, they won’t find many as proven as MEO in the post-sales supply chain. If a colleague, competitor, partner, or supplier brings up MEO, don’t assume their definition is the same as yours. Ask them the hard questions. MEO is simple to claim, but extremely complex to pull off on a global scale.

Steven Caldwell is Vice President, Research & Development for Servigistics. With more than 20 years of software engineering experience building world-class commercial software applications, Steven is pivotal in the design and continuing development of Servigistics’ solutions. 

Flying High with a New Service Parts Strategy: A Case Study on Embraer

By Michelle Duke, SLM Hub Editor

Thanksgiving is approaching in the U.S. and many of us will be catching flights to visit family and friends over the next few days. Bustling through crowded airports to board planes and cram our carry-on luggage into the overhead compartments, we are so thankful to finally take our seat and hear the captain say “flight attendants prepare for take-off.” It definitely takes a lot of preparation to get that plane off the ground and to make sure we reach our destinations safely. And if you think about it, it all begins with good Service Lifecycle Management behind the scenes from the moment the aircraft is manufactured.

Here’s a look at how one manufacturer improved service to its aviation customers by implementing a new strategy for service parts planning:

For more than 40 years, Empresa Brasileira de Aeronáutica (Embraer) has been involved in designing, developing, manufacturing, selling and supporting executive jets, commercial jets with up to 120 seats, and defense aircraft. It has produced more than 5,000 aircraft that are in operation in 92 countries worldwide. With its customer base continually growing, the company experienced a dramatic increase in the demand for aftermarket parts services. Embraer’s logistics team concluded that its ERP and legacy systems were not able to meet the needs of its increasingly complex services organization. In addition, the company’s existing parts systems made it difficult to consolidate inventory data and calculate stock requirements. This lack of critical functionality was causing insufficient service levels, low inventory turns, and high levels of obsolete stock.

Embraer needed to implement a more sophisticated parts planning process to address these challenges and chose Servigistics Service Parts Management to replace its existing parts software. As a result, Embraer now employs a single strategy to manage complex interchangeability relationships; rebalance inventory across a global network; create location and part types with associated attributes; forecast different streams of demand; and automate its inventory replenishment process. Embraer’s spare parts planning team can now create accurate parts-consumption forecasts that so far have reduced inventory for commercial aviation by 12.5 percent and improved inventory turns by 35 percent while improving service levels. By leveraging the new resources and processes, the executive aviation group has been able to achieve impressive growth in business volume without an increase in staff headcount.

Vastly improved parts planning information has enabled Embraer to avoid unnecessary purchases, increase inventory turns, lower costs and improve visibility across its service parts network. With the ability to generate accurate forecasts as needed, the logistics staff is able to achieve its challenging targets for off-the-shelf parts availability. And more importantly, the new service parts strategy has helped transform Embraer’s services culture. Planning staff are now able to forecast supplier requirements and perform collaborative planning with the company’s customers which has led to a dramatic improvement in quality scores for key customer groups.

Waiting for Service Delivery Improved my Chainsaw Skills

By Dave Duncan

Working in aftermarket service I am immersed in countless projects with leading companies that are designed to help improve their customer’s service experience. At the end of the day, we are all someone’s customer and recently I had my own ordeal with a long wait for customer service. As one of the more than 500,000 Connecticut Light and Power customers that lost power after the early season snowstorm on October 29th, I have a renewed appreciation for how a customer feels when waiting for fast and efficient service delivery. Unfortunately, despite the top-notch efforts by the tree and electrical technicians, the utility management lacked the necessary coordination and visibility of contracted resources to operate efficiently. Connecticut Light and Power completed the greatest power restoration in state history, but the feat is widely viewed as too late.  We waited for 11 days for our power to be restored, but at least I was able to hone my chainsaw skills…

Let’s continue the discussion I began on service models in my post on Field Service SLM back in September. As I mentioned then, most post-sales service supply chains operate with one or more of these service models: Field-based, Dealer-based, Depot-based and Performance-based. For this blog post, I’m going to focus on Dealer-Based Service Lifecycle Management (SLM).

Dealer-based SLM is the subset of SLM that covers the processes associated with delivering customer service through dealer networks.  It emphasizes customer asset availability and both OEM/dealer service delivery margins.  It includes remote service, knowledge management, parts planning, parts pricing, and business insight process areas.

Dealers have broad customer reach for both service and support, but also present additional aftermarket service challenges.  Dealer growth and margin incentives do not always align with the manufacturers, particularly for warranty work.  Additionally, dealers generally can sell and service competitor products, creating competitive dimensions that don’t exist with in-house field or depot based service models.  Service part sales are particularly competitive.

Dealer-Based SLM represents a compelling opportunity for service business process improvement.  Few dealer-based organizations today have established the needed coordination and visibility across their service network to align dealer and manufacturer incentives/activities.  Disjointed technology and process across the contributing nodes causes punishing inefficiencies.  Industry analysts have begun to validate these struggles and mitigations:

  • Expensive dealer support phone channels.  “As much as 70% of inbound support calls are finding information that customers have but could not find”…”20% of calls simply for parts identification”.  (Aberdeen)
  • Unnecessary warranty parts expenses.  “25% of orders request multiple parts because the technicians are unsure of the right one.”  (Aberdeen)
  • Unnecessary warranty labor reimbursement.  “Non-linear troubleshooting tools can help techs solve problems faster, reducing #steps by 50%.” (McKinsey)
  • Lost revenue opportunity.  “Third Party service providers, suppliers, and repair shops are believed to own about 75 percent of the service and parts market.”  (Accenture)
  • Conflicting pricing and stocking practices.  “Profit-Driven Parts Management made possible through parts planning and parts pricing optimization can drive 20% higher profit contribution from service.”  (Blumberg Advisory Group)
  • Scaling new product introduction for effective service.  “The percentage of clients who identify their products as high complex has grown from 42% in 2003 to 64% today.”  (TSIA)
  • Coordinating incentives/visibility among dealers, contact centers, repair depots, warranty, and other service nodes.  “(Service Lifecycle Management) tends to be a fractured process, since it incorporates roles and responsibilities from various groups that often have different goals and measures. Typically, these groups have acted semi-autonomously, with no management incentive, to synchronize their activities in the overall context of the business strategy. This limits the potential (read: profitability) of the overall service business. Metrics have been defined and reported independently, which often leads to conflicting outcomes. Leading service companies, however, bring these various roles together under one group or executive and use common technology platforms.” (Gartner)

Dealer-Based SLM provides the necessary coordination and visibility to improve both customer asset availability and service margins. When an OEM has a Dealer-Based SLM program, the improved efficiency of service sessions is significant and many times what was a 12 step process to complete service is reduced to 6 steps, with improvements that can include 89% uptime improvement, 57% service cost improvement, and $500 over-stock avoidance.  It can keep your customers’ lights on at a low cost!

Dave Duncan is Vice President, Product Portfolio Management, for Servigistics. He holds a BSE in Civil Engineering and Operations Research from Princeton University

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