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Journal of Education for Business
ISSN: 0883-2323 (Print) 1940-3356 (Online) Journal homepage: http://www.tandfonline.com/loi/vjeb20
Learning Lean: A Survey of Industry Lean Needs
Gene Fliedner & Kieran Mathieson
To cite this article: Gene Fliedner & Kieran Mathieson (2009) Learning Lean: A Survey of Industry Lean Needs, Journal of Education for Business, 84:4, 194-199, DOI: 10.3200/ JOEB.84.4.194-199
To link to this article: http://dx.doi.org/10.3200/JOEB.84.4.194-199
Published online: 07 Aug 2010.
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ABSTRACT.
R
ean,orwastereductionefforts,has beenaprominentbusinessstrategy in the past two decades (Ohno, 1988; Standard & Davis, 1999; Womack, Jones, & Roos, 1990). Lean practices are found in service and manufactur-ingfirms,smallandlargebusiness,and for-profit and nonprofit organizations (Ohno). A driving force behind many Lean initiatives is globalization, which hasreducedproducers’controloverpric-es.Cooper(2007)stated,“Intensification of competitive forces limits the ability of companies to simply mark up prices based on cost increases. It has made cost control, rather than pricing power, thedrivingforcebehindcorporateprofit margins and earnings growth” (p. 25). Businesses must increasingly rely on cost cutting, waste elimination, produc- tivityimprovement,andqualityenhance-ment as strategic means to achieving profit objectives. Lean methods address these concerns and do work (Clanton, 2004). Furthermore, there is a growing needforemployeestoparticipateinand lead the necessary changes to existing businesscultures,operatingsystems,and practices to (a) cut costs, (b) eliminate waste,and(c)improveproductivityand quality(Drickhamer,2004).Lean is not widespread in higher education curricula. Stand-alone Lean classesarerare.Leanisnormallyfound inoperationsmanagementorengineer-ing courses, which are not
multidisci-plinaryanddonotattractmanystudents outsidethetwodisciplines.Consequent-ly,themajorityofstudentsleavehigher education with little understanding of Lean. Subsequent to graduation, many organizations invest a large amount of time and money to educate and train employeesinLean(Standard&Davis, 1999). Universities could help compa-niesavoidsomeofthisexpense.
InAugustof2005,academiciansand practitioners met at a seminar at Ohio StateUniversitywheretheycreatedthe Lean Education Academic Network (LEAN), a group of university tors seeking to promote Lean educa-tion in U.S. higher academia. LEAN also works to improve Lean education throughsharedknowledgeandteaching materials, collaboration, and network-ingamongcolleagues.LEANmembers attheinitialmeetingagreedthatuniver-sitiesshouldlearnwhatindustrywants graduatestoknowaboutLean.Industry participants at the seminar highlight-ed the importance of academic curri-cula maintaining a constant awareness of current industry needs. The present studyisasteptothatend.
ResearchMethodology
We conducted aWeb-based survey to betterprovideuniversitieswithanunder-standingofindustryneedsregardingLean. Inthebeginning,wecirculatedapilotsur-veyto15practitionerschosenbyindustry
LearningLean:ASurveyofIndustry
LeanNeeds
GENEFLIEDNER KIERANMATHIESON OAKLANDUNIVERSITY ROCHESTER,MICHIGAN
L
ABSTRACT.Theauthorsexamined businesspractitioners’preferencesfor highereducationcurriculadesigningen-eralandforwhatgraduatesshouldknow aboutLean,orwaste-reductionefforts.The authorsconductedaWeb-basedsurvey andfoundthatpractitionersarenotascon-cernedaboutgraduates’possessingspecific technicalskillsastheyareaboutthempos-sessingasystemsviewoforganizationsand valuestreams.Thesurveyfindingssuggest severalimplicationsforundergraduateand graduatebusinessschoolcurriculumdesign, Leaneducation,andabroadersystems approachtoprofessionaleducation.
Keywords:businessschoolcurricula design,Lean
Copyright©2009HeldrefPublications
representativesatthefirstLEANmeeting. Werefinedthesurveyonthebasisoftheir feedback.WethencreatedtheWeb-based versionoftherefinedsurvey.
We distributed the refinedWeb-based survey with the assistance of the Lean LearningCenterinNovi,Michigan,and theWebsitewww.Superfactory.com.The LeanLearningCenterprovidesLeancur-ricula for industry professional develop-ment.Itplacedaparticipationinvitation in its electronic newsletter, which was senttoapproximately2,000opt-ine-mail addresses. The number of people who actuallyreadthenewsletterisunknown. Superfactory.com,whichfocusesonhelp-ing readers achieve manufacturSuperfactory.com,whichfocusesonhelp-ing and enterprise excellence, invited industry participantswithapostingonitsWebsite andanoteinitsmonthlyelectronicnews-letter.Superfactory.comclaimsmorethan 45,000 opt-in subscribers. However, the numberofpeoplewhosawtheWebpost-ingornewsletterannouncementwasalso unknown. The fraction of those readers whowereinterestedinLean,asopposed to some other aspect of Superfactory. com’s coverage, was also unknown. A 2-week window was allowed for participantresponses.
Theactualsurveyresponseratetothe refined survey could not be computed because of the method of distribution. However,thereislittledoubtthatitwas low. In all, we received 45 completed surveys.Therefore,wedonotclaimthat thesamplereceivedisrepresentativeof Lean practitioners. It may be that only those who were particularly interested in Lean education responded and that theyaresomehowdifferentfromothers. People were able to respond anony-mously or were given the option to provide an e-mail address to receive a complimentarycopyoftheresults.
For the survey, we used rank order scores and a 7-point Likert-type scale rangingfrom1(veryimportant)to7(very unimportant) to solicit responses from participants about the degree of impor- tanceofavarietyofLeanskills,knowl-edgeareas,concepts,andtools.Weused parametric and nonparametric statistical analysestoexamineresponsedifferences.
SurveyDesign
Aftercollectingsomeinitialdemo-graphicdata,thefirstpartofthesurvey
asked participants to rank in order of most important (low score) to least important (high score) 10 broadly identifiedareasofLeanskills,knowl-edge, and expertise. On the basis of pilot study results and anecdotal evi-dence from conversations with prac-titioners, these 10 areas were chosen because of their importance as key building blocks that were desirable for graduating students to possess to make a quick contribution to a Lean program.Rankorderswererequested because each of these items poten-tiallyrepresentedasignificantamount ofcoursecontent.Itmaynotbepos-sible to include all 10 of these broad areas in a single, semester-long Lean course.Therelativenatureoftherank-ingsshouldbetterenableeducatorsto prioritizecoursecontent.
In the second part of the survey, we asked participants about a variety of skills in three more specific Lean skill sets relating to particular business dis-ciplines: (a) financial and accounting skills; (b) human relations skills; and (c)engineering,operations,andmarket-ing skills. These more specific Lean skill sets may be viewed as traditional programs of study (majors) commonly foundinhighereducation.Inadditionto rank ordering, participants were asked touseafine-grainedLikert-type(FGL) scaletoindicatetheabsoluteimportance of Lean skills in each of these three sets. Traditional coarse-grained Likert-typescalesforcerespondentstochoose among distinctive anchor points, usu-allyfiveorseven.AnFGLscaleallows participantstoselectvaluesbetweenthe anchor points. Mathieson and Doane (2005)foundthatanalysesofdatagath- eredusingFGLscalesaremorestatisti-cally powerful than analyses of data gathered using coarse-grained scales. Throughoutthepresentstudy,theFGL scalerangedfrom1(veryimportant)to 7(veryunimportant).
Thefinalportionofthesurveyasked participantstoindicatetheimportance ofavarietyofspecificLeanconcepts and tools commonly examined in existing college curricula. Both rank-ings and an FGL scale were used to solicitparticipantviewsoftheimpor-tanceofthesespecificLeanconcepts andtools.
RESULTS
Because Lean is applicable in small and large service and manufacturing organizations, we collected demo-graphic data concerning job titles and organization sizes. Survey respondents held a broad range of job positions in companies of varying sizes and types. The diversity in job positions includ-ed 28 different job titles ranging from presidents to various types of manag-ersincludingplant,general,production, inventorycontrol,systems,information technology, sales, and supply chain. Other job titles included public infor- mationcoordinatorandunionrepresen-tative.Therangeofcompanysizesand typesisshowninTable1.Wereceived most responses from people in manu-facturingcompanies.Nearlyhalfofthe responses were from people working for companies with more than 1,000 employees.
The median rank values for the 10 broadly identified areas of Lean skills, knowledge,andexpertiseareshownin Table 2. No area was more important thanthatofsystemsplanningandthink-ing.This result is consistent with con-versations with practitioners. Compa-nies that have implemented successful Lean programs have commonly taken intoaccounttheentireenterprise,from suppliertocustomer,andeverythingin between(Yamada&Tracey,2005).
The respondents also perceived the areas of Human relations skills and Lean culture to be important, with median ranks of 3 and 5, respectively. Lean implementations often change
TABLE1.NumberofResponses, byTypeandSizeofOrganization
Numberof
Variable responses
Organizationtype
Service 11 Manufacturing 30 Government 4 Numberofemployees
1–50 5
51–100 5
101–150 0
151–500 9
501–1,000 4 >1,000 22
companies, threatening (or appearing to threaten) both corporate culture and customary ways of conducting work. Leadership and change-management skills, therefore, command a premium. The Society of Automotive Engineers International (1999) noted that Lean is primarily about management, workers, andthetrustthatbindsthetwo,andthat thesearethemostimportantelementsof a Lean system. This point underscores theimportanceofhumanrelationsskills foranyLeanprogram.
The respondents also viewed the areasofreal-worldbusinessknowledge and experience to be important. Prac-titioners seek potential employees who can make a quick contribution. It is commonly argued that learning is best derivedfrompersonalexperience.This sentimentisechoedbythemedianrank valueof3.5fortheareasofreal-world businessknowledgeandexperience,as showninTable2.
OnecommonformofwastethatLean programadministratorstrytoeliminate istheproductionofdefects.Inlightof this observation, it is interesting that theareasofqualityandothersystems-improvement methodologies had the leastimportantranking.
We performed a Friedman rank test oftheparticipants’rankordersforthese 10 broadly identified areas of Lean to
ascertain whether the rank values rep- resentastatisticaldifference.Thecriti-cal test value was 16.919, using a .05 level of significance with 9 degrees of freedom.Thecalculatedteststatisticof 85.475indicatedasignificantdegreeof differences in the relative importance amongtheseskills.
After being asked about the 10 gen-eralskillareas,respondentswereasked about three more specific, discipline- relatedskillsets.TheFGLmeans,stan-darddeviations,andmedianrankvalues for the first of these discipline-specific sets, Lean financial and accounting skills,areshowninTable3.Bothmet-rics,FGLscoremeansandmedianrank
values,demonstratedareasonablelevel ofconsistency.Scorestandarddeviation values are reported to allow the reader toinfertheextentofconsistencyamong theparticipants’FGLscorevalues.
From the survey results, we ascer-tainedthatthemostimportantitemwas enterprise view of money, which had the lowest mean FGL score and low-est median rank. (Lower values mean higher importance.) This echoes the systemsplanningandthinkingconcept. Theskillratedassecondmostimportant wastheunderstandingofthetimevalue ofmoney.
We conducted a one-way analysis of variance (ANOVA) with the relatively smalllevelofdifferencesamongtheFGL scoresoftheseparticularskills.Thecriti-cal value of the test was 2.13, with the seven skill items and 6 degrees of free-dom.WecalculatedFtobe2.70andpto be.01,indicatingahighdegreeofsignifi-cantdifferencesamongtheseskills.
Similarly,anonparametricFriedman ranktestoftherankordersfortheseven financialandaccountingskillswascon-ductedusinga.05levelofsignificance to better understand whether the rank values represented a statistical differ-ence.Thecriticalvalueofthistestwas 12.59.Wecalculatedtheteststatisticto be13.96,indicatingasignificantdegree of difference among the participants’ rankingsforthisskillset.Theseresults suggestthatsurveyparticipantsregard-edtheenterpriseviewofmoneyasthe mostimportantskillandactivity-based costingastheleastimportant.
The results for the second of the three discipline-related skill sets,
TABLE2.MedianRankValuesofTenBroadlyIdentifiedAreasofLean Skills,Knowledge,andExpertise
Broadlyidentifiedarea Mdnrankvalue
1. Systemsplanningandthinking 3.0 (e.g.,seeingthebusinessasavaluestream)
2. Humanrelationsskills 3.0
(e.g.,leadership,changemanagement,teamproblemsolving)
3. Real-worldbusinessknowledgeandexperience 3.5 (e.g.,internships,jobexperience)
4. Leanculture 5.0
(e.g.,kaizen,plan-do-check-act,5Sorvisualmanagement)
5. Leanprinciples,terminology,andtools 5.0 (e.g.,pull,takt,singleminuteexchangeofdie,one-pieceflow)
6. Stabilityandvariancereduction 6.0 (e.g.,sixSigma,standardizedwork,talkingpointsmemo)
7. Financialandaccountingknowledge 7.0 (e.g.,cashflow,workingcapital,returnonnetassets)
8. Delivery 7.0
(e.g.,time-to-marketandlead-timereduction,closedloopdesign)
9. Safety 8.0
10. Qualityandothersystemsimprovementmethodologies 8.0 (e.g.,MalcolmBaldrige)
TABLE3.LeanFinancialandAccountingSkills
Scalepoint
Skill M SD Mdnrankvalue
Enterprise(totalcompany)viewofmoney 2.51 0.81 3
Timevalueofmoney 2.63 1.00 3
Firstin,firstout 2.70 1.21 4
Cashflow 2.98 1.09 4
Workingcapital 3.08 0.78 5
Returnonnetassets 3.11 1.25 4
Activity-basedcosting 3.25 1.49 6
Note.Responsesarefroma7-point,fine-grainedLikert-typescalerangingfrom1( mostimpor-tant)to7(leastimportant).
human relations skills, are shown in Table 4. Again, there was much con-sistency between the participants’ rank order and FGL scores. Leader-ship skills was ranked as the most importantitembyboththeFGLmean score and median rank value. Team-work skills was next on both met-rics. The items basic problem solving skills,teamproblemsolvingskills,and change management followed closely. Negotiationandconflictresolutionwas seenastheleastimportantiteminthis skill set when measured by the FGL andmedianrankings.
We calculated a one-way ANOVA among the FGL scores of these eight particular skills. The critical value of the test was 2.04 for the 7 degrees of freedom,F was calculated to be 1.98 (p > .05,ns). Range truncation may explain this because two of the FGL score means were within 1 standard deviation,andseveralotherswereclose to 1 standard deviation of the end of thescale.
We conducted a Friedman rank test ofthemedianrankordersfortheeight skills using a .05 level of significance. Thecriticalvalueofthistestwas14.07. We calculated the test statistic to be 38.11,indicatingasignificantdegreeof differenceamongtheparticipants’rank-ingsforthisskillset.
Overall, the evidence suggests that there are significant differences in the ratings, so that leadership skills were perceived to be more important than negotiation and conflict resolution. It is interesting that the skill viewed as least important in this set (negotiation and conflict resolution, with a mean FGL score of 2.17 [SD = 0.87]) was perceivedtobemoreimportantthanthe mostimportantskillinthefinancialand accountingskillsset(enterpriseviewof money,withameanFGLscoreof2.51 [SD=0.81]).
TheFGLmeans,standarddeviations, andmedianrankvaluesforthethirddis-cipline-related skill set—engineering, operations, and marketing skills—are showninTable5.Thereweredifferenc-es in the FGL scorshowninTable5.Thereweredifferenc-es and rank results. However,iftheskillsaresplitintotwo roughly equal-sized sets (high impor-tance and low importance), then skills rated as high importance by the FGL
scales were also rated as high impor-tancebytherankvalues,andskillsrated aslowimportancebytheFGLwerealso ratedaslowimportancebytherankval-ues.Standardizationreceivedthelowest mean FGL rating, followed by vari-ance reduction. The item most similar to a systems view, process thinking, receivedthelowestmedianranking,fol-lowed by translating customer require-mentsintospecifications.Weconducted an ANOVA among the FGL scores of theseskills.Thecriticalvalueofthetest was1.71,withthe15skillitemscom-prising the comparative analysis and 14 degrees of freedom. We calculated
F to be 6.79 (p <.0001), indicating significant differences. However, this resultissuspect,withthelargenumber ofskillsintheengineering,operations, and marketing skill set relative to the sample size. (There are approximately twice as many skills in this set as in thefinancialandaccountingandhuman relationsskillssets.)Wealsoconducted aFriedmanranktestofthemedianrank ordersforthe15skillsusinga.05level of significance. The critical value of this test was 23.69. We calculated the teststatistictobe113.83.Thissuggests therearedifferencesamongthepartici-pants’rankingsforthisskillset.
TABLE4.HumanRelationsSkills
Scalepoint
Skill M SD Mdnrankvalue
Leadership 1.67 0.62 2.00
Teamwork 1.69 0.82 3.00
Basicproblemsolving 1.77 0.71 4.50 Teamproblemsolving 1.79 0.90 4.75
Changemanagement 1.79 0.69 5.50
Interpersonal 1.88 0.66 4.00
Logicalthinking 1.89 0.67 5.00
Negotiationandconflict 2.17 0.87 6.00 resolution
Note.Responsesarefroma7-point,fine-grainedLikert-typescalerangingfrom1( mostimpor-tant)to7(leastimportant).
TABLE5.Engineering,Operations,andMarketingSkills
Scalepoint
Skill M SD Mdnrankvalue
Standardization 1.76 0.65 4.50
Varianceorvariancereduction 1.94 0.59 7.50 Abilitytoassessdeliveredvaluetocustomer 2.10 0.78 5.00
Processthinking 2.19 0.83 2.50
Translatingcustomerrequirementsinto 2.20 0.96 3.75 specifications
Processdesign 2.49 0.99 5.50
Leanproductdesignanddevelopmenttime 2.50 1.00 6.50
Cellularlayouts 2.52 0.96 13.00
Generalstatisticalanalysis 2.62 0.86 11.00 Leanproductdesignanddevelopmentcosts 2.66 0.87 7.50
Debugging 2.73 0.95 10.00
Automation 2.77 1.19 10.00
Statisticalprocesscontrol 2.81 1.05 12.00
Pilottesting 2.88 0.93 10.00
Prototyping 3.13 0.98 11.00
Note.Responsesarefroma7-point,fine-grainedLikert-typescalerangingfrom1( mostimpor-tant)to7(leastimportant).
In the last part of the survey, we askedparticipantstoindicatetheimpor-tance of some Lean-specific concepts and tools. The FGL means, standard deviations, and median rank value resultsareshowninTable6.Standard-izationofworkprocesseswasperceived as important, which is consistent with the standardization item in the engi-neering, operations, marketing skill set (seeTable5).Theitemvaluestreamor process mapping, which emphasizes a systems viewpoint of processes across a supply chain, was also important. Value stream mapping is a technique thatoperationalizesthewhole-firmcon-cept.Weconductedaone-wayANOVA among the FGL scores of these Lean conceptsandtools.Thecriticalvalueof the test was 1.62, with 19 items com-prisingthecomparativeanalysisand18 degreesoffreedom.WecalculatedFto be3.18(p<.0001), indicatingasignifi-cantdegreeofdifferences.Thistoomay be explained by the important differ-encesorbythelargenumberofitems. WealsoconductedaFriedmanranktest
of the median rank orders for the 19 items using a .05 level of significance. Thecriticalvalueofthistestwas28.87. We calculated the test statisticto be 100.33.Thissuggestssignificantdiffer-ences among the participants’ rankings for this skill set. The quality-related items (familiarity with complementary quality and productivity programs and statistical process control tools) were perceivedtobelessimportant.Thesame wasfoundinthepilotstudy,whichused adifferentparticipantsample.
DISCUSSION
The consistency of the FGL scores and median rank values allow sever-al important conclusions to be drawn. First, we received a loud message that the surveyed Lean practitioners want university graduates to have a com-prehensive or systems view of orga-nizations. This message is consistent throughout the data. The most impor-tantitemofLeanskill,knowledge,and tions expect employees to provide an immediatecontribution.Becauseofthe more recent emergence of Lean initia-tivesinindustry,theskills,knowledge, and expertise that can be afforded to students prior to employment become a significant means to distinguish an academicprogram.
The importance of a systems view wasechoedthroughoutthesurveydata. Anenterpriseviewofmoneywasiden-tified as the most important financial and accounting skill. Leadership was identifiedasthemostimportanthuman-relations skill. Standardization was identified as the most important engi-neering,operations,andmarketingskill. Many researchersand business practi-tioners would equate these skills with anenhancedabilitytogetallthefirm’s resourcespullingtowardtheattainment of a common set of objectives for the system,namelythefirm.
Most academic curricula emphasize a somewhat deep yet relatively narrow preparation in specific disciplines. This isnecessaryinsomefields.Forexample, competent computer programmers need to know about algorithms, databases, networks,interfaces,andthelike.Their traininginvolvestimeandexpense,and without it they are not able to function intheirspecialties.Itisevidentintry too, because most people in indus-try work in a single, specific functional discipline such as accounting, human resources,oroperations.However,Lean requires something more. Specifically, Leandemandsthatpeopletakeawhole-firm view of their companies. Univer-sity curricula can introduce students to thisconcept.VanTil,Sengupta,Fliedner, Tracey, and Yamada (2005) discussed one approach. Oakland University’s PawleyInstituteoffersaninterdisciplin-Course curricula design and broad-based degree programs should reflect thebeneficialandincreasinglynecessary aspectsofworkplacecollaborationanda
TABLE6.LeanConceptsandTools
Scalepoint
Conceptortool M SD Mdnrankvalue
Standardizationofworkprocesses 1.61 0.82 6.00 Valuestreamorprocessmapping 1.68 0.78 5.50 Defect-freeproduction(poka-yoke,jidoka) 1.74 1.16 7.00
Pullapproach 1.80 0.66 7.00
Takttime 1.82 0.82 6.00
Cycle-timereduction 1.90 0.89 8.00 Operatorinvolvementandteamwork 1.95 1.29 6.50 (e.g.,qualitycircle,kaizenactivity)
Visualmanagement 1.96 1.18 8.00
4W2H(what,when,where, 2.08 1.24 12.75 why,how,andhowmuch)
One-pieceflow 2.16 0.87 6.00
Totalpreventativemaintenance 2.17 0.98 14.00
Kanban 2.19 0.83 10.50
Productionleveling(heijunka) 2.23 0.88 10.50 Processorofficelayoutdesign 2.23 0.99 14.50 Plan-do-check-actcycle 2.25 0.98 13.75 (Demingwheel,Shewhartcycle)
Quickchangeoverorsingle-minute 2.37 0.74 11.00 exchangeofdie
Familiaritywithcomplementaryqualityand 2.60 1.36 16.50 productivityprograms(e.g.,sixsigma,
theoryofconstraints,TS16949)
3Ms:Muda,Muri,Mura 2.71 1.55 12.50 Statisticalprocesscontroltools 2.74 1.30 14.50
Note.Responsesarefroma7-point,fine-grainedLikert-typescalerangingfrom1( mostimpor-tant)to7(leastimportant).
systems point of view for conducting work. Practitioners desire broad-based degree programs to promote greater workerflexibilityandanenhancedabil- itytocopewithrapidlychangingwork-placedemands,competitivethreats,and marketopportunities.
Asecondconclusionisthatresearch-ers should recognize the importance that respondents attached to human-relationsskills.Thesurveyrespondents representedavarietyofpositionsanda diverse array of functional disciplines. On the basis of the FGL mean scores, all of the human-relations skills were viewed as more important than any of the financial and accounting skills in spiteofrespondentdifferences.Tomeet industry needs, universities must teach studentsthatLeanisnotsimplyasetof tools,butratherthatitis—asprevious-ly noted by the Society ofAutomotive Engineers International (1999)—also about management, workers, and the trustthatbindsthetwo.Effectivelead-ersmustdealwiththeuncertaintyofthe global market and angst of wrenching organizationalchange.Ifuniversityfac- ultyaretohelpgraduatesbecomeeffec-tive Lean practitioners, faculty must underscore the essential importance of the human element and relationship buildingforattaininggoals,suchascost cutting,wasteelimination,productivity, andqualityimprovement.
A third important conclusion must recognize the desire for prospective employees to possess real-world busi- nessknowledgeandexperience,assug-gested in Table 2. There are a variety of approaches being pursued in aca- demiatoday.Manyofthesearehands-on approaches include semester-long cooperatives,internships,orindustryor academic projects that typically focus on examining a small portion of a firm’sprocess(e.g.,akaizenevent)for improvement.Oneexampleofacurrent universityprogramthatrecognizesthis conceptisthatoftheCollegeofEngi-neering at the University of Kentucky. The faculty there runs a Lean manu-facturing “boot camp.” This approach representsanimmersivelearningexpe- rienceinwhichstudentsworkinateam-orientedenvironmentandparticipatein hands-on, discovery-learning exercises in which concepts introduced in the
classroom are immediately applied. These exercises involve training facto-ries,simulations,andfieldactivities.
Immersivelearningexperiencessuch as internships provide important real-world experiences. They help students understand how real business differs from clinical experiences of the class-room. These opportunities should be expanded on. Furthermore, faculty can become interns as well and improve their understanding of the challenges thatstudentsface.
Thefindingsofthepresentstudysug-gest at least two directions for college curricula to meet industry needs. The firstdirectionistoexploreandinnovate waysofincreasingbroad-based,multi-disciplinary Lean content in university programs. Examples are offered in the presentarticle,buttherearemorepos-sibilities. For example, distance-learn-ing technology may allow universities and companies to offer cooperative, real-worldcoursesacrossinstitutionsto wideraudiences.
The second direction is to explore the details of how Lean is taught. For example,multidisciplinarydegreepro- grams,team-taughtclassesacrosssev-eralschoolsinauniversity,orspecific toolssuchasavirtualsimulationmay better enable students to see a wider view of an organization’s operations. A tool such as a virtual simulation could allow students to play various roles, including sales representatives, productionmanagers,accountants,and evencustomers,allforthesamefirm. This would afford students a greater abilitytoseerespectiveimpactsacross all disciplines of organization when the firm is challenged by events such as the loss of an important market, a suddendropinthecostofacompeting technology, or a dramatic rise in raw materialprices.
New program designs, teaching approaches, and tools all take time to design,build,test,andrefine.Jointuni-versityandindustryeffortscouldmake this happen. Just as Lean initiatives require innovation in the workplace, improving Lean curricula content in universitieswillrequireinnovationand new approaches. Systems approaches to curriculum design, and course con-tent,andhands-onlearningapproaches
forstudentscanprovidethemtheLean skills, knowledge, and expertise that prospective employers desire. This can help companies avoid significant employee training, development time, and cost, and that avoidance may be a significant means to distinguishing an academicprogram.
NOTES
Gene Fliedner is an associate professor of operations management. His research and teach-inginterestsfocusonfamilyorgroupforecasting systems, multi-item forecasting systems, supply chain forecast development, supply chain man-agement and collaboration, and operations plan-ningandcontrol.
KieranMathiesonisanassociateprofessorof management information systems. His research interestsfocusonhowtoolscanhelpgroupsmake difficultethicaldecisions.Histechnicalskillsare mainlyinWeb-applicationdevelopment.
Correspondence concerning this article should beaddressedtoGeneFliedner,SchoolofBusiness Administration, Oakland University, Rochester, MI48309,USA.
E-mail:fliedner@oakland.edu
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