Servce Operatons ManagementPoo|a B R B007Poo|a B R B007Saket |an B030Saket |an B030Soham Kadam

B033Soham Kadam

B033Mayank KshoreB039Mayank KshoreB039Apoorva Kushwaha B040Apoorva Kushwaha B040Nrmt Mehta B042Nrmt Mehta B042Pawan Kumar Pandey B049Pawan Kumar Pandey B049Asan Pants Presented by Group 4Ratona for Extenson from Products to ServcesEconomicTypcay, hgher margns n servces than productsResstant to economc downturns to some extentCustomerThey are demandng more servcesCompetitive AdvantageMuch more dmcut to repcateBut, ony some manufacturers have successfuy extended to servces.WHY?"It s dmcut for an engneer who has desgned a mut-mon doar pece of equpment to get excted about a contract worth $10,000 for ceanng t"They thnk provdng servce s not ther core competencyBusness mode changes from Transactona to Reatonshp basedFaure n mpementaton e.g. Lakme Beauty Saon, HLL Surf Exce Laundry WashChaenges n transtonng from Products to ServcesDmcut to create brand dherentaton Estabshng compettve poston n the mnd of the consumerBrand personaty s a reecton of companys vaues and cutureBrand budng requres bottom-up approach and whoe company nvovementBrand PostonngOperatons ManagementIntangibility - Engaged n creatng a product whch they cannot see but ony feeVariability - Hghy characterzed by varatonsConsistency - Chaenge of consstency n experenceSubjectivity - Dmcut to measure processesPerishability - Chaenge to recreate servces contnuousy as there s no InventoryStandardization - Chaenge to standardze as drecty nvoves customer nteractonServce v Product n Pant IndustryService in Paint Industry Product in Paint IndustryCustomer partcpates Customer does not partcpateExperence for the customer Commodty for the customerVares from customer to customerStandardzed processDrect nteracton of customers wth company saesforceNo drect nteracton wth company executvesRecreated to order Made to stockPrce vares for dherent customersPrce s xedAsan PantsOne of the most conc brands of IndaChaked out a rura marketng strategy to counter mutnatonasLeveraged dstrbuton, ogstcs, technoogy and product nnovaton to stay aheadOhered the customers hghest choces of shades and types of pantsIt was the rst company to set up turnkey pant contractng servceHome SoutonsAn end to end souton mode deverng quaty and convenencePanters are traned & supervsed by the Home Soutons teamCurrenty on oher n 13 ctesIn 1998, the company reased that customers were ookng for a turnkey contractCustomers had tte knowedge about the tota pant cyceAsan Pants tsef had contro ony on the seng cyce of the processHence, the company took on the garb of a consutant and got nvoved n the entre cyceMoment of TruthPointsintimehenthecustomercomesincontactiththeservice production!deliverysystem"he#ormsanimpressiono#theservicereceived$%hese moments are termed as &'oments o# %ruth($Cyce of Servce for Home SoutonsCustomer contactsHome SoutonsSaes Assocate vsts and evauates the surfaces to be pantedCustomer nases the saes order makes payment for the sameThe work s handed over to Reatonshp AssocateHe manages & supervses the work t t s competedLet down for customersP r e m u m B r a n dDespte 10-15 % premum, the servce was not exhaustveP a n t I n s p e c t o r sReatonshp Assocate was often the same frendy contractorA s a n P a n t s E x p e r tCustomers refused to accept same standards from Home Soutons as they had from contractorsImpcatonsCustomers began suspectng the credentas of Asan pantsThe company was hard put to |ustfy the premumDssatsfacton among customersDeverng an Ehectve ServceInvestment n sk deveopment of contractors. Traned contractor w be abe to serve the customers at Moment of Truth.Asan Pants shoud deveop a varety of mantenance pans post warranty perod.Easy mechansm for customers to provde feedback about the contractors and resouton n case of any ssue.Communcaton on how the servce s excusve and ts benets.)orecasting *emand #or ServicesDscussed Topc- Lecture 7 & 8Forecastng Demand for Servces)orecasting %echni+ues)orecasting %echni+uesSubjective 'odelsSubjective 'odels*elphi 'ethod*elphi 'ethodCross,Impact AnalysisCross,Impact Analysis-istorical Analogy-istorical AnalogyCausal 'odelsCausal 'odels.egression 'odel.egression 'odelEconometric 'odelEconometric 'odel%ime,Series 'odels%ime,Series 'odelsE/ponential SmoothingE/ponential Smoothing%rend Adjustment%rend AdjustmentSeasonal AdjustmentSeasonal Adjustment0,Period 'oving Average0,Period 'oving AverageSub|ectve ModesA technoogca forecastng method that uses a group of experts to arrve at a consensus about the futureA technoogca forecastng method that uses a group of experts to arrve at a consensus about the futureDeph MethodDeph MethodAtechnoogcaforecastngmethodthatassumes somefutureeventsreatedtoanearereventwth an estmated probabty-pAtechnoogcaforecastngmethodthatassumes somefutureeventsreatedtoanearereventwth an estmated probabty-pCross-Impact AnayssCross-Impact AnayssA technoogca forecastng method that assumes that thentroductonandthegrowthpatternofanew servce w mmc the pattern of a smar concept for whch data are avaabeA technoogca forecastng method that assumes that thentroductonandthegrowthpatternofanew servce w mmc the pattern of a smar concept for whch data are avaabeHstorca AnaogyHstorca AnaogyDeph MethodConsensus of expert opnonsLabour Intensve ProcessForecastng through quatatve dataVery Expensve & Tme consumng methodInput from persons wth expert knowedgePractca ony for ong-term forecastngCausa ModesAreatonshpbetweenthefactorbeng forecasted,whchsdescrbedasa dependentvarabe(orY),andthefactors thatdetermnethevaueofY,whchare desgnatedasthendependentvarabes (or Xi)Regresson ModeMedum & Long-Term ForecastsA set of smutaneous equatons expressng adependentvarabentermsofsevera dherentndependent varabesEconometrc ModeLong-Term ForecastsTme Seres ModesSmooths out bps n the data by gvng progressvey ess weghttooderdata&feedngbacktheforecasterrorto correct the prevous smoothed vaueSmpe Exponenta SmoothngTrendnasetofdatastheaveragerateatwhchthe observed vaues change from one perod to the next over tme. The changes created by the trend can be treated by usng as a smoothng constantExponenta Smoothng- TrendSeasonaehectsona setofdatasaccountedforby rst removngtheseasonatyfromthedata,thensmooth thosedataandnayputbacktheseasonatyto determne a forecastExponenta Smoothng- SeasonaAsmpetmeseresforecastformedbyaddngtogether themostrecentdataanddvdngbythenumberof observatonsN-Perod Movng Average Mode1. Forecastng expected patentoad n year 20052. Forecastng the annua expense and the tota manpower requred for Oak Hoow n the year 2005 12ES%I30S Oak Hoow s an organsaton that ohers mutdscpnary dagnostc servces. The organsaton s workng n a hghy compettve envronment It s n an vunerabe nanca poston and wants to forecast the expected patent oad n next year as we as manpower oad & annua expense for optmum servce devery.CASE -IG-4IG-%SCase assgnmentMcrosoft Exce WorksheetData Enveopment Anayss (DEA)DEA s a near programmng mode that attempts to maxmze the servce unts emcency, expressed as a ratos of outputs to nputsCompare a partcuar unts emcency wth the performance of a group of smar servce unts that are deverng the same servceOb|ectve Functon:Constrans:Exampe: Burger chan has estabshed sx unts n dherent ctes.Equaton: Max (S1) = U1 * 100Sub|ected to U1*100-V1*2-V2*200