Design for Warranty Cost Reduction

Transcription

1 Desgn for Warranty Cost Reducton Robert H. Mueller, Ops A La Carte & Marsan Group Key Words: warranty, warranty cost model, desgn for warranty, computer, electroncs ndustry SUMMARY & CONCLUSIONS Ths paper develops a process based cost model for warranty events and apples t to a number of product nstances n the computer and related hgh tech busnesses. It dentfes the prncple support meta-processes that typcally contrbutes >70% to the total cost of warranty. From ths model the key warranty cost drvers are dentfed and the set of strateges are derved that product development teams can use to reduce the cost of warranty for products under development. Proven frameworks for applyng the model and warranty cost reducton strateges durng the product development cycle are presented. Case study nstances are presented that llustrate how product development teams have appled the model, strateges and frameworks that reduced the total warranty costs by 35% are dscussed. 1. INTRODUCTION The total cost of warranty for computer and related hghtechnology US based companes s now ~$8B per/year [1]. For many companes, ther warranty costs approaches what they spend on new product development and often matched ther net proft margns; ths s partcularly true for the commodty type busnesses such as PCs or personal prnters. Many companes are movng toward an extended warranty strategy to manage warranty costs. But, ths s no panacea. Whle extended warranty repars costs may be consdered an operatonal expense and not a warranty expense from a SEC [10-K] perspectve, the effects of poorer product qualty than planned mpacts the busness s bottom lne wth the same force as warranty costs. In the past few years the avalable choces of servce processes used to resolve warranty ssues has expanded to nclude phone support, Web based and customer self-fx schemes. Ths trend has been drven by need to reduce warranty cost and accelerated by the maturaton of the nternet. As both consumer and commercal products contnue to ncrease the software/frmware to hardware component mx, these less costly processes need to be utlzed more and more Why? The costs per repar of these servce processes range over 1½ orders of magntude; from $30/call for a warrant resolved over the phone to >$700 for on-ste repars. More mportantly, the repar process costs are the largest contrbutor to the total cost of warranty; part cost contrbuton s typcally less than 30% for most products. Because of the busness mpact of the cost of warranty, product development teams are now beng challenged to desgn products that are both less costly to repar (busness metrc: warranty $s) and more relable (busness metrc: annual falure rates, AFR). To more easly meet ths challenge wll requre warranty costs models that make explct not only the mpact of AFR on cost, but also the effect of the process costs assocated wth the repar of specfc falure modes. Currently used warranty cost models are domnated by tradtonal Falure Modes and Effects Analyss (FMEA), cost pool based models or models utlzng statstcs and smulaton forecastng technques [6]. FMEAs are heavly used by the hardware engneerng communty n the Aerospace, Mltary and Auto busness segments. Cost pool based models are most frequently used by the fnancal and supply chan communtes. FMEA s a proven methodology for frst dentfyng falure modes or falure mode scenaros [2,3], then developng strateges to mtgate the rsk for each falure mode durng a product s development cycle nstead of after product launch. The most popular FMEA methodologes use the RPN scheme to prortze the falure modes, or when cost s used [4], the method s mute on how a product team calculates cost of repar. Cost pool based models aggregate warranty costs nto large cost pools such as monthly costs for labor, call centers, materal, labor and nventory/logstcs. These cost pool based models [5] are a natural ft for warranty cost reducton efforts for the supply chan and procurement areas. Yet, none meets the full needs for modelng of the development team: the model needs to have the followng characterstcs: The customer s problem beng resolved s explct. The support processes used to dagnose and resolve the warranty event are explct. Estmatng warranty costs s relatvely quck and easy to do, especally when evaluatng desgn alternatves. Ths paper develops a servce process based warranty cost model for warranty events that s grounded n both the customer s problem and the support process used to resolve t. It wll dentfy the prmary meta-processes used by most computer and hgh-tech busnesses to servce warranty events. Typcal standard costs for each of these wll be dscussed. We wll demonstrate that these process based cost models are partcularly useful for the computer and other hgh technology busnesses for both the commercal or consumer market spaces. They are less useful for the Automotve,

2 Aerospace or Mltary busness segments because of the support strateges used n those market spaces. From ths model, the key cost drvers wll be extracted from whch we wll also develop the prmary strateges that product development teams can use to both mprove product relablty and deduce ts warranty costs. Results from case studes wll demonstrate how product development teams have used ths model to develop desgn alternatves and acton plans to reduce warranty costs. Whle presentng the case study a few frameworks wll be ntroduces that the development team used to evaluate what strateges may be affectve for reducng costs of specfc event types and to dentfy dependences deeded to realze the planned cost reductons. 1.1 Nomenclature & Notaton AFR = Annualzed Falure Rate ASP = Authorzed Servce Provder PCA = Prnted Crcut Assembly TotalCost = the total cost of warranty for the product N = number of occurrences of an event type for a specfc tme nterval n = number of occurrences for th warranty event type C = standard servce process cost used to resolve the th warranty event type M = number of warranty event types needed to account for an acceptable fracton of the total warranty expense for a specfc tme nterval 2. PROCESS BASED WARRANTY EVENT COST MODEL At the heart of the cost model s the concept of a warranty event. To llustrate what a warranty event s let s consder ths example. A customer s gettng a warnng message from the OS that her hard drve s predcted to be falng n her PC. She calls the call center for support. The call center agent, after confrmng warranty enttlement, talks the customer through a dagnostc process that confrms a specfc hard drve caused falure type known by the support team as HD1. The prescrbed resoluton s to replace the hard drve. In ths case the customer s drected take the PC to a local Approved Servce Provder for bench repar servce. Notce that ths warranty event has a process to dagnose the customer problem (the call center workng wth customer to dagnose), a specfed support process (walk-n servce by a local ASP to repar) and a part beng consumed (hard drve) to resolve the warranty event. In ths model, every warranty event type has a unque lnkng of a dagnosed problem, a specfc support process to resolve the event and specfc materal costs(components), f consumed. The materal cost n ths case s the cost of the hard drve tself. All costs such as spare-part nventory management or nventory logstcs are treated as drect, n-drect or overhead costs to the support process used. The total warranty cost for all of the hard dsk falures of event type HD1 can be smply calculated, for a specfc tme nterval as: Warranty Cost = n HD1 x (process cost + materal cost) where: n HD1 = the number of occurrences of the HD1 event type Now the total warranty cost for all event types can easly be calculated. Lettng N be the total number of warranty event types for a specfc product, the total warranty cost for a specfc tme nterval s smply gven by: Total Cost = N = 1 n Often, dozens or even hundreds of event types may exst for complex products. Yet, t s seldom necessary to sum over all event types to get an excellent estmate of a products warranty costs. Experence has shown that for most products, only a handful of warranty events domnate the total warranty cost; the Pareto prncple apples. Hence, t s useful to defne M, where M s the number of warranty event types that account for an acceptable percentage, say 90%, of a product s total warranty costs. Then the cost equaton can be re-expresses as: Total Cost = M = 1 n C + N C n = M + 1 As the second term of (2) becomes much smaller than the frst term, then we can re-wrte t as: Total 2.1 Emprcal Trends Cost M = 1 n C Fgure 1 shows a Pareto chart of warranty event types for a recently modeled commercal computer/prnter product. Each bar represents a specfc warranty event type. The Y- Axs s the total warranty cost for each event type for a oneyear perod. The total number of event types havng any actvty n ths tme nterval was about % of the product s warranty costs were accounted for by only a few event types, n ths case M s ~15. Experence has shown that most products have a smlar behavor; almost all products modeled had less than 20% of the warranty event types accountng for more than 80% of the costs. The cost of each warranty event type s further broken down nto the total labor, travel, materal, call center and support overhead costs. The total contrbuton of materal costs to the total warranty cost s less than 35%. Ths s also a typcal dstrbuton of total costs. An mportant consequence of these cost breakdowns s that, durng the desgn and prototypng phase of product C (1) (2) (3)

3 development, the choce of the components based only on ts mpact on manufacturng cost may have very costly consequences to the product s overall warranty costs and, therefore on the busness s overall proftablty. Fnally, the fact that the Pareto prncple has held true for all products modeled, ths model can be an effectve tool n prortzng that warranty even types should be prortzed by what on value to the busness as measured by real costs. $1,200,000 $1,000,000 $800,000 Pareto of Warranty Event Costs labor Travel Materal Call Center Servce OH The servce engneer, after recevng the parts, goes on-ste to perform on-ste dagnostcs, as necessary, replace faled parts and fnsh the repar servce process for ths repar mode. Note that the total cost of ths overall process ncludes: call center costs, part logstcs (ncludng all overhead costs for spare part management), labor and travel expenses. For the computer busness and many smlar hgh-tech ndustres, the number of frequently used support processes s very small and are lsted n table #1. They range from call center phone support only to on-ste repar. Also lsted n the table for each servce process are the nomnal costs and ther costs. The costs lsted n ths table have been derved from a dozen dfferent products lnes n a number of dfferent companes. Many of the products modeled used dfferent strateges to deploy ther product support ncludng a mx of n-house and 3 rd party partners mplementng ther call centers, spare parts management (logstcs), on-ste servce engneerng and bench repar. Warranty Event Total Costs [$] $600,000 $400,000 Process Example On-ste Repar A warranty event support process Start Step 1: Customer makes call, call center determnes enttlement Step 2: Call center dagnoses problem; determnes on-ste repar requred and orders needed replacement parts $200,000 $- Event 2 Event 3 Event 4 Event 5 Event 6 Event 7 Event 8 Event 9 OS Patch 1 3 Warranty Event Fgure 1 Pareto of Warranty Events 2.2 Warranty Servce Meta-Processes SN Event 21 Event 22 A key step n buldng an nstance of the cost model s sortng out how many support processes are used to resolve warranty events for that product. For effcency reasons, most support organzatons (or, f support has been outsourced, ther 3 rd party agents) have just a handful of meta-processes to resolve the vast majorty of warranty or servce events. The bench repar servce process from the hard drve example was one of these meta-processes. Another s the on-ste repar process often used for hgher end or dffcult to move products n the computer, medcal and other related hgh tech busnesses. Let s look at ths process n more detal (Fgure 2). As wth the bench repar example, the frst steps are focused on confrmng warranty enttlement, problem dentfcaton, dagnostcs and determnaton of what servce process wll be used for ths event. For ths process, the nterventon s an on-ste servce call performed by an authorzed servce engneer. The call center wll also ntate the logstcs processes needed to get the parts to the servce engneer dentfed by the dagnostc process for replacement. Step 3: Servce contractor gets parts, travels to ste and replaces parts. Step 4: Defectve part s dscarded or returned. Step 5: Case s closed RAMS Fgure 2 On-ste Repar process flow Note that the process cost range covers almost 2-orders of magntude; from as low as $10 for events resolved by phone support resolved events outsourced to off-shore 3 rd partes to over $1,000 for a mult-vst on-ste repars due to msdagnosed problems. Web based self-dagnostcs and repar processes and on-lne chat-room support schemes are not ncluded because of the nherent dffculty of determnng f any specfc web ste ht s a true warranty event or not. Ths large cost dfference s one of the economc drvers pushng the product desgn teams toward desgnng for customer self-fx or bench repar processes for new products.

4 Table 1 Support Meta-processes and ther typcal costs Process Costs w/o Materal Costs [avg./(mn/max)] Servce Process Phone Support On-Ste Servce Customer self-fx Bench Repar Product Exchange Descrpton A warranty event s resolved by Call Center (CC) agent /w no materal. Cost=CC(labor rate*call length) A warranty event ths s referred by CC agent to servce engneer for an onste servce call Cost = CC + labor + travel +logstcs + part cost Parts only process where customer replaces parts. Cost = CC + part cost + logstcs Customer brngs the product to Busness/ASP for repar Cost = CC + part costs + logstcs + ASP costs Customer exchanges defectve product for a new / Re-furbshed one Cost = CC + cost of product + logstcs $45 ($10 - $60) $600 ($300 - $1,200) $65 ($40 - $100) $125 ($70 - $200) $ 65 ($30 - $100) Havng so few standard meta-processes greatly smplfes buldng a product specfc cost model snce only a very small number of standard process costs need to be dentfed and quantfed by the support and accountng communty when buldng the model. The other ndependent varables of the model, event type s frequency of occurrence and actual materal costs are usually readly avalable to the product development team through the support and procurement team members. Because of ts smplcty, the model can readly be bult n off-the-shelf data base and analyss tools such as Mcrosoft Access and Excel. 3 COST DRIVERS AND REDUCTION STRATEGIES By nspecton of (3) and from the table of support metaprocesses, two prmary warranty cost drvers are apparent (e.g., performng a varance on t): Number of occurrence for an event type We wll use the Annualzed Falure Rate (AFR) of the component (or sub-system) assocated wth that specfc event type as ts surrogate snce we can easly calculate n from the AFR and the number of unts under warranty. Cost of support process used These cost drvers drectly lead to a number of prmary strateges that development teams can use to mpact warranty costs durng product development (depcted n Fgure 4). They are: Reducng the frequency of the event type by: o Reduce the component s AFR o Desgn out the event type Reducng the process cost contrbuton by: o Swtch event type to a cheaper support process (sometmes called changng Support Process Mx) o Develop better dagnostcs tools to: a) allow support to swtch to cheaper support processes; b) reduce dagnostc errors of currently used support processes. o Improve product servceablty to: a) support customer self-repar for an event type; b) reduce total servce call length (tme to replace any other servce actvtes requred n repar/calbrate process). Desgn Phase Warranty Cost Reducton Strateges Wc Σ n * ( Cost + C materal ) Reduce number of occurrences: Desgn out the event s occurrence Change product features Change how product works Implement feature dfferently Reduce the number of occurrences Increase HW relablty (reduce AFR) Improve SW/FW robustness M For each sgnfcant event type Reduce event s process cost: Desgnng new (cheaper) processes Desgn process around new technology. Desgn process to meet new market needs Swtchng to a cheaper process ID features/capabltes needed to support dfferent process Reduce standard process costs by: Product changes Process mprovements Outsourcng Supply Chan re-engneerng RAMS Fgure 3 Warranty Cost Reducton Strateges 4. USING COST MODEL IN PRODUCT DEVELOPMENT Ths model has been used to support the development team s economc decson-makng process for the for varous desgn alternatves that affect warranty costs n the followng ways: To calculate estmates of both the product s total warranty costs and costs of specfc warranty event types. To prortze the engneerng efforts for product mprovements based on warranty costs, not just manufacturng cost reducton To calculate the dfference n warranty costs due to dfferent desgn alternatves. To facltate the dentfcaton of necessary product features, capabltes and dagnostc tools needed to realze projected warranty savngs of the chosen desgn alternatve. To facltate the economc trade-offs between manufacturng costs for specfc desgn alternatves and the warranty costs (and post warranty perod support costs).

5 $500,000 $450,000 $400,000 $350,000 $300,000 $250,000 $200,000 $150,000 $100,000 $50,000 $- labor Travel Materal Call Center Warranty Event Servce OH $500,000 $450,000 $400,000 $350,000 $300,000 $250,000 $200,000 $150,000 $100,000 $50,000 $- labor Travel Materal Call Center Warranty Event Servce OH How teams have used the model durng the product development phase to support the decson makng process when choosng between features, functonalty and desgn alternatves can best be exemplfed by wakng through a case study. Also two frameworks used to develop and choose desgn alternatves wll also be ntroduced. In ths case study, the development team was startng another desgn cycle for a follow-on hgh volume, moderately prced ($5,000 $7,000 dependng on optons) product. They had easy access to most support nformaton. The current product s annualzed cost of warranty was ~5.6 % of total revenue; a compettve poston when compared to ther competton, but not a compettve advantage. Strategcally, management had set a goal of reducng warranty costs by 30% for all products under development to avod engneerng expense reductons n the future. 4.1 Buldng cost model and Pareto chart. Snce the new product would have very smlar archtecture and functon to exstng products they choose to buld a cost model for a smlar product currently n producton for whch they had easy access to product support nformaton. The frst step was to dentfy the man support processes used by support for the current product. They used all the processes n Table 1 except for the bench repar and product exchange processes. From accountng, they obtaned the current standard process costs. Wth the standard process costs known, buldng the ntal warranty event cost model was reasonably straghtforward. Together wth the support team they tabulated the frequency of occurrences for the top 50 warranty event types. Combnng each event type s assocated materal costs, process costs and ts frequency, they then constructed (usng Mcrosoft Excel spreadsheets) the cost model and ts correspondng Pareto charts. Fnally, they added a number of new event types for the new features and functonalty planned for the new product usng smlar event types from the current product as a gude to estmate both support process costs and frequency of occurrence for them. [Note: Ths team dd not use the FMEA methodology for product desgn rsk assessment. But, the nformaton from a FMEA would very ncely feed nto ths cost model. Also, for green feld products, the ntal FMEA s falure mode scenaros could also very easly be used to seed the cost model. Each falure mode would be pared wth ts approprate support process and a relatve frequency of occurrence for the falure could be estmated.] 4.2 Evaluatng desgn alternatves Havng the ntal model (and ts Pareto tables and charts) the desgn team started the exploraton and evaluaton of specfc event types to determne how they were gong to meet ther warranty cost budget. Ther Event Pareto was very smlar to Fgure 1, where the top 20 event types accounted for over 90% of ther annualzed warranty costs. Ther strategy to meet ther goal of a 30% reducton n warranty costs was to develop, desgn and mplement desgn alternatves for each event type on the Pareto that, when evaluated by the model, predcted a total warranty cost of less than 3.9% of projected product revenue. The framework n Fgure 2 was developed to facltate these dscussons. It llustrates the dfferent desgn optons or handles that can be turned to reduce warranty costs. Snce many of the desgn alternatves nvolved ether mprovng the effcency of the on-ste servce process or desgnng the product for customer self-repar, sgnfcant nvolvement by the support and techncal marketng groups n the early desgn phase was crtcal. 4.2 Projectng warranty cost savng The teams used a combnaton of graphcs and tables to specfy and document what the reducton n warranty costs would be for the chosen set of acton plans and desgn alternatves. Calculatng and vsualzng the effects of desgn alternatves, n both frequency and dollars, s a relatvely straghtforward task n the Excel based model. For example, Fgure 4 depcts the effects alternatves for two specfc event types. The frst labeled Event1 shows the effect of two changes to the product: reduce AFR of a PCA board by 50% and reduce the total tme necessary to complete the on-ste repar by 50%. The second event labeled Event2 show the effects of a sngle change: redesgn the product so that qualfed customer resources can replace the faled component. Ths example graphcally depcts the equalty of AFR reductons and support process choce as frst order drvers of warranty costs. Projectng Warranty Savngs Warranty Event Total Costs [$] Planned engneerng actons: Event1: reduce AFR by 50% and reduce tme of repar by 50% (labor cost) Event6: re-desgn for self-fx by qualfed customer IT resources Pareto of Warranty Event Costs current Event 4 Event 2 Event 6 3 OS Patch 1 Event 3 Event 8 8 Event 7 SN Event 21 Warranty Event Total Costs [$] Pareto of Warranty Event Costs planned Event 4 Event 2 Event 6 3 OS Patch 1 Event 3 Event 8 8 Event 7 SN Event 21 RAMS Fgure 4 Projectng warranty savngs 4.4 Identfyng Dependences The team then developed the next level of desgn detals that would be needed to realze the warranty savngs. Specfcally, for each warranty even type targeted for sgnfcant reducton they dentfed the features, functons, capabltes or support dagnostcs tools needed to realze the goal of the desgn change. Fgure 5 shows an example of another framework used to evaluate the dfferent desgn proposals. Because many of the changes requred

6 consderable changes to both the product desgn and n how the product would be supported once released (ncludng the dagnostc tools that would be needed by the support team to correctly dagnose event types that would use a customer self-repar process) ths was a cross-functonal team ncludng R/D, manufacturng, marketng and support resources. Also note that the table s Importance column ncluded customer satsfacton consderatons to help balance the need to reduce warranty costs and customer satsfacton (company brand). In fact marketng frequently calbrated customer satsfacton wth both how well specfc support processes such as phone support worked and customer satsfacton wth the support processes that were used (customer self-repar vs. benchrepar by an ASP). Dependency Plannng 2. J. Ba and H. Pham, Warranty Cost Models of Renewable Rsk-Free Polcy for Mult-Component Systems. European Journal of the Operatonal Research, vol. 146, S. Kmenta and K. Ish, Scenaro-Based MFEA: A Lfe Cycle Cost Perspectve ASME Desgn Engneerng Techncal Conference 4. R. Latno and K. Latno, Root Cause Analyss Improvng Performance For Bottom Lne Results, CRC Press, D. Kuettner, Data-Drven Warranty Management, Warranty Chan Management Conference, Kleyner, Sandborn, Boyle, Mnmzaton of Lfe Cycle Costs Through Optmzaton of the Valdaton Program A Test Sample Sze and Warranty Cost Approach, RAMS 2004 BIOGRAPHY Warranty events naturally fts to how product teams make decsons throughout the product lfe cycle. Warranty Event Event6 Importance * [1to10] 8 7 Planned Actons 1. Desgn for mproved servceablty [1½ hr. total] 2. Reduce AFR by 50% 1. Desgn for self-fx by customer IT staff Requred features, functons, capabltes, or dagnostc tools to realze savngs 1. Cabnet re-desgn 2. ID component wth ½ of current AFR 1. Cabnet re-desgn 2. Wrte/deploy dagnostc tools Projected Warranty Costs [$] $150K/yr. $158K/yr. Note: Importance rankng ncludes both customer satsfacton and brandng consderatons Projected Warranty Savngs [$] $298K/yr $167/yr RAMS Fgure 5 Dependency Plannng After approprate valdaton that the desgns were vable, the goals, new features and functonalty (ncludng dagnostc tools development) where then ncorporated nto the overall Project, Relablty and Test Plans. Approprate metrcs and other crtera were added to the ext crtera of ther development lfe cycle. Robert H Mueller, M.S., CQE Ops A La Carte & The Marsan Group 1030 Oakland Ave Menlo Park, CA USA e-mal: bobm@opsalacarte.com or robert_mueller@marsan.com Robert Mueller has 35 years of experence n product development and management of software ntensve products for the computer, analytcal and medcal ndustres at Hewlett-Packard and Aglent Companes. Robert Mueller receved hs B.S. and M.S. degrees n Physcs from Northern Illnos Unversty before jonng Hewlett-Packard Co. He s currently a senor consultant wth both Marsan Group and Ops A La Carte focused on R/D product strategy development, agle development methodologes, Warranty and SW Relablty engneerng. He s a Certfed Qualty Engneer. 4.5 Case Study Results The warranty costs for the product used n ths case study were carefully tracked through the frst 18 months after market ntroducton. The results were: Actual total warranty costs were 5% less than ther targets. Relatve cost contrbuton by warranty event type of the new product s event types mostly tracked what the model predcted. Customers were very satsfed wth the customer selfrepar process: good dagnostcs (dagnosed problem correctly) and faster tme to repar wth less hassle. REFERENCES 1. E. Arnum, Warranty Week. May, 2007,