Selected Collaborative Problem-Solving Methods for Industry Dr. A. Mark Doggett Dept. of Industrial Technology Humboldt State University (707) 826-4980 [email protected]
Despite thethe availability ooff a wiwidede rrangeange ooff prproblemoblem solvinsolvingg mmethods,ethods, inindividualsdividuals concontinuetinue to struggle with problems.problems. SciScientistsentists attempt to adaddressdress rrecurringecurring econeconomic,omic, socisocial,al, politipolitical,cal, anandd ororganizationalganizational prproblemsoblems throughthrough ththee eexpansionxpansion ooff knknowledgeowledge anandd ththeory.eory. GoldGoldrattratt (1990) hhypothesizedypothesized that every sciscienceence ggoesoes thrthroughough threethree phases ooff ddevelopment:evelopment: classifi cation,cation, correlation,correlation, andand cause-effect. In thethe classifi cationcation phase,phase, a phenomenonphenomenon is logicallylogically categcategorizedorized rresultingesulting in a systemsystematicatic iidentifidentifi cation.cation. ExamplesExamples includeinclude thethe locationlocation ofof stars or thethe phphylumylum nnamesames ooff varivariousous planplantsts anandd animanimals.als. In corrcorrelationelation phasephase,, sciscientistsentists ddetermineetermine how thethe phphenomenonenomenon works thrthroughough observatiobservationsons anandd rroughough calculaticalculations.ons. Early astrastronomersonomers used corrcorrelationelation to suggestsuggest ellipticalelliptical solar orbits anandd mmodernodern phphysicistsysicists use it to estimestimateate ththee locatilocationon ooff an electrelectronon araroundound thethe atom. WhWhenen askaskeded about his inninnovation,ovation, ththee TToyotaoyota kanban system, Dr. Taiichi Ohno replied, “My system doesdoes notnot mmakeake sensensese at all, but by God it’s workinworking”g” (Gold(Goldratt,ratt, 1990, p.28). ThThee thirthirdd phase ooff cause-effect is characterizedcharacterized by ththee why question.question. NNewton'sewton's mmethodsethods crcreatedeated ththee sciscienceence ooff astrastronomyonomy anandd chanchangedged fforeverorever thethe way people viviewew ththee starsstars.. Cause-effect rrelationshipselationships advanadvancece logilogicalcal eexplanations,xplanations, prpredictedict futurfuturee evenevents,ts, andand forecastforecast conconsequences.sequences. ThTheorieseories anandd thinkinthinkingg based on cause-effect fi ndingsndings becomebecome recognizedrecognized sciencescience (Goldratt,(Goldratt, 1990) anandd mmoveove ththee fi eld ofof inquiry fromfrom "art" to that ofof disciplineddisciplined examination.examination.
In problemproblem solvinsolving,g, ththee rrootoot cause ooff ththee prproblemoblem prproducesoduces an unundesirabledesirable effect. AnAnyy pursuit that ddoesoes nnotot seek thethe rrootoot cause leads only to ththee symptom ooff ththee prproblemoblem anand,d, by ddefiefi nition,nition, solvingsolving a symptom will notnot solve a problem.problem. PrProblemoblem solvers iidentifydentify rrootoot causes ooff prproblemsoblems to be able to prpredictedict futurfuturee cause anandd effect relationships.relationships. ThThee purposeful appliapplicationcation ooff an ananalysisalysis mmethodethod can adaddressdress complecomplexx prproblemsoblems usinusingg a structuredstructured apprapproachoach rratherather than ememotionotion or inintuition.tuition. Problem Solving Methods TheThe sciscientifientifi c methodmethod is thethe generallygenerally accepted frameworkframework forfor solvingsolving problemsproblems in WesternWestern culture.culture. NoNo discussiondiscussion ooff prproblemoblem solvinsolvingg mmethodsethods would be complete withwithoutout mmentioningentioning it. ThThee sciscientifientifi c methodmethod has nono particularparticular inveninventor;tor; it seemseemss to have evolved over timtimee based on ththee work ooff fi fteenth-centuryfteenth-century scholars.scholars. ItIt is,is, however,however, ththee basis fforor mmostost prproblemoblem solvinsolvingg apprapproachesoaches used todtoday.ay. ThThee basibasicc sciscientifientifi c methodmethod is as follows:follows: 1. Defi ne the problem 2. Formulate a hypothesis 3. Gather appropriate data 4. Test the hypothesis 5. Develop conclusions (Wilson et al., 1993, p. 74)
AnotherAnother problemproblem solvinsolvingg mmodel,odel, PDCA (Plan, Do, ChCheck,eck, AAct),ct), was ddevelopedeveloped by WW.. EdEdwardswards DeminDemingg (1986) whowho dderivederived it frfromom ShShewhartewhart (1986). IItt is a ffour-stepour-step prprocessocess fforor concontinuoustinuous prproblemoblem solvinsolving.g. ThThee ffourour stagesstages ooff PDCA rrepresent:epresent: (1) ththee ananalysisalysis anandd planninplanningg ooff prproblemoblem solvinsolving,g, (2) ththee actiactionsons taktakenen to rresolveesolve thethe prproblem,oblem, (3) ththee evaluevaluationation ooff ththee rresults,esults, anandd (4) ththee mmodifiodifi cationcation ofof activitiesactivities that eithereither confi rm or disconfi rm thethe desireddesired results.results. PDCA is sometimessometimes referredreferred to as thethe DemingDeming Cycle because hehe introducedintroduced thethe conceptconcept to thethe JJapaneseapanese whwhoo subsequensubsequentlytly nnamedamed it after him (Co(Cox,x, et al., 1995). ThThee PDCA mmodelodel rrepresentsepresents a simplifi ed versionversion ofof thethe scientifiscientifi c method.method. Unfortunately,Unfortunately, its simplicitysimplicity misleads manymany problemproblem solvers in that it leaves open thethe mmethodethod ooff accomplishmaccomplishment.ent.
AndersonAnderson andand FagFagerhaug’serhaug’s (2000) prproblemoblem solvinsolvingg mmodelodel conconsistssists ooff prproblemoblem iidentifidentifi cation,cation, problemproblem defidefi nition,nition, problemproblem understanding,understanding, rootroot cause identifiidentifi cation,cation, rootroot cause elimination,elimination, andand symptom monitoring.monitoring. This particularparticular mmodelodel rrepresentsepresents a comprcomprehensiveehensive anandd timtime-consuminge-consuming apprapproachoach to prproblemoblem solvinsolving.g. AAss susuch,ch, detaileddetailed modelsmodels liklikee this shshouldould be used only whwhenen ththee prproblemoblem to be solved is worth ththee effeffortort to solve ththem.em. In otherother worwords,ds, ththeyey shshouldould nnotot be used fforor easy prproblemsoblems (Br(Brown,own, 1994).
2004 Selected Papers • www.nait.org • 193 LatinoLatino anandd LatinLatinoo (1999) suggsuggestedested a prproblem-solvingoblem-solving mmodelodel usinusingg ththee acracronymonym PROPROACT,ACT, whiwhichch stanstandsds ffor:or: PReserve eventevent ddata;ata; OrOrderder ththee ananalysisalysis team; AnAnalyzealyze ththee ddata;ata; CommCommunicateunicate fi ndingsndings andand recommendations;recommendations; andand TrackTrack fforor rresults.esults. ArArcarocaro (1997) oofferedffered a six-step prproblem-solvingoblem-solving mmodel:odel: (1) iidentifydentify anandd select ththee problem,problem, (2) ananalyzealyze ththee prproblem,oblem, (3) ggenerateenerate potenpotentialtial solutisolutions,ons, (4) select anandd plan ththee solutisolution,on, (5) implementimplement ththee solutisolution,on, anandd (6) evaluevaluateate ththee solutisolutionon implemimplementation.entation. Wilson et al. (1993) selected an approachapproach based on ththee sciscientifientifi c methodmethod that includesincludes thethe followingfollowing elements:elements: set up appropriateappropriate reportingreporting systems;systems; ddefiefi nene thethe criteriacriteria forfor problemproblem selection;selection; select candidatescandidates forfor analysis;analysis; select analysisanalysis techniques to be used; developdevelop solutisolutions;ons; anandd test solutisolutions.ons. FinFinally,ally, SprSproulloull (2001) used ten steps to ddescribeescribe ththee prprocess:ocess: (1) identifyidentify thethe prproblem,oblem, (2) ddescribeescribe anandd ddefiefi nene thethe problem,problem, (3) list thethe symptoms,symptoms, (4) list thethe knownknown changeschanges (that occurredoccurred priprioror to ththee prproblem),oblem), (5) ananalyzealyze ththee prproblem,oblem, (6) hhypothesizeypothesize possible causescauses,, (7) test possible causes,causes, (8) taktakee actiactionon on ththee causescauses,, (9) test anandd implemimplementent ththee solutisolution,on, anandd (10) implemimplementent thethe apprappropriateopriate concontrols.trols.
While thesethese mmethodsethods sharsharee somsomee commcommonon ththemes,emes, ththeireir grgreatesteatest similarity is that ththeyey all rrepresentepresent strustructuredctured approachesapproaches to prproblemoblem solvinsolving.g. While ununstructuredstructured apprapproachesoaches susuchch as inintuition,tuition, nnetworking,etworking, anandd priprioror experienceexperience mmayay be valivalidd fforor solvinsolvingg prproblems,oblems, ththeyey araree also mmoreore subjective anandd less rrepeatable.epeatable. PrProblemoblem solvingsolving that is nnotot rrepeatableepeatable has a hihighergher potenpotentialtial fforor ffailureailure because prpractitionersactitioners will liklikelyely rrepeatepeat ththee samesame mistakmistakeses to gain ththee inintuitiontuition anandd eexperiencexperience nnecessaryecessary to solve ththemem again. LikLikewise,ewise, ununstructuredstructured approachesapproaches ggenerallyenerally rresultesult in outcomoutcomeses that adaddressdress symptomsymptomss onlyonly.. ConConsequently,sequently, whwhyy shshouldould people spenspendd thethe timtimee anandd effeffortort to solve ththee samsamee prproblemsoblems concontinually?tinually? Good prproblemoblem solvinsolvingg techniques will ggenerallyenerally uncoveruncover thethe rrealeal rreasoneason behinbehindd ththee effect. Root Cause Analysis AccordingAccording to AndersonAnderson anandd FagFagerhaugerhaug (2000), “Root cause ananalysisalysis is a strustructuralctural investiinvestigationgation that aimaimss to identifyidentify thethe true cause ooff a prproblem,oblem, anandd ththee actiactionsons nnecessaryecessary to elimineliminateate it” (p. 10). IItt is ththee prprocessocess ofof identifyingidentifying causal ffactorsactors usinusingg a strustructuredctured apprapproachoach with techniques ddesignedesigned to prprovideovide a ffocusocus fforor identifyingidentifying anandd rresolvingesolving prproblems.oblems. Root cause ananalysisalysis prprovidesovides objectivity fforor prproblemoblem solvinsolving,g, assists in developingdeveloping solutisolutions,ons, prpredictsedicts othotherer prproblems,oblems, assembles concontributingtributing circircumstances,cumstances, anandd ffocusesocuses attenattentiontion on preventingpreventing rrecurrences.ecurrences. MMostost ooften,ften, rrootoot cause ananalysisalysis techniques araree utiutilizedlized aass input to ththee ddecision-makingecision-making process.process. If rrootoot cause ananalysisalysis is used in a rreactiveeactive mmode,ode, it prprovidesovides objective iidentifidentifi cationcation ofof organizationalorganizational faults.faults. In ththee prproactiveoactive mmode,ode, rrootoot cause ananalysisalysis iidentifidentifi es andand preventsprevents futurefuture mistakes.mistakes. Wilson et al. (1993) wrote,wrote, “Root cause ananalysis,alysis, prproperlyoperly implemimplemented,ented, will tell you ththee rrealeal rreasonseasons fforor prproblems”oblems” (p. 20).
RigorousRigorous rootroot cause ananalysisalysis mmayay involve askinaskingg diffi cult or embarrassingembarrassing questionsquestions about howhow an organizationorganization is managedmanaged (Dew(Dew,, 1991). A charcharacteristicacteristic ooff rrootoot cause ananalysisalysis is to assumassumee that bad ddecisionsecisions araree based on erroneouserroneous logilogic,c, ffaultyaulty assumptiassumptions,ons, or obsolescenobsolescentt systemsystems.s. ThThee ininterestterest ooff rrootoot cause ananalysisalysis is nnotot whwhoo mademade thethe errerror,or, but whwhy.y. AnAnalysisalysis mmethodsethods that ffocusocus only on hhumanuman errerroror araree ggenerallyenerally nnotot susuccessfulccessful ddueue to dwindlingdwindling participationparticipation fforor fear ooff rrepercussions.epercussions. If ththee rrootoot cause ananalysisalysis prprocessocess is fl awedawed,, ddecisionecision errerrorsors will continuecontinue (Latin(Latinoo & LatinLatino,o, 1999). Graphic Displays UseUse ooff grgraphicaphic displays in ththee ananalysisalysis ooff prproblemsoblems appears to have mmerit.erit. WhWhenen viviewingewing grgraphics,aphics, a person fi rst comprehendscomprehends thethe overalloverall structurestructure (patterns,(patterns, symmetry,symmetry, trendstrends ofof dotsdots andand lines),lines), thenthen focusesfocuses on what is interesting.interesting. RegarRegardless,dless, ooff nnationalityationality or culturculture,e, mmostost people ununderstandderstand pipictures.ctures. AAccordingccording to MizunMizunoo (1988), humanhuman beinbeingsgs ggoo thrthroughough thrthreeee stagstageses ooff ddevelopmentevelopment startinstartingg as ““contactcontact beinbeings”gs” whwhoo eexchangexchange informationinformation thrthroughough phphysicalysical concontact,tact, susuchch as ththee concontacttact between an infinfantant anandd mmother.other. ConContacttact beinbeingsgs thenthen grgrowow inintoto “pi“picture-beings”cture-beings” whwhoo ununderstandderstand infinformationormation thrthroughough pipicturesctures anandd ddrawingsrawings anandd fi nallynally becomebecome ““charactercharacter beinbeings”gs” that trtransmitansmit infinformationormation thrthroughough written charcharactersacters anandd symbolssymbols.. AAss susuch,ch, ththee humanhuman capability to understandunderstand grgraphicaphic commcommunicationunication appears to be ddevelopmental.evelopmental. ThTherefore,erefore, tools that incorporateincorporate grgraphicsaphics ememergeerge as powerful techniques because mmostost people comprcomprehendehend ththemem quiquickly.ckly.
In 1977, computer theoristtheorist YYoshikawaoshikawa (Mizun(Mizuno,o, 1988) distindistinguishedguished pipicturesctures with lanlanguageguage frfromom pipicturesctures that containcontain only drawingsdrawings with ththee ddesignationesignation “gr“graphicsaphics lanlanguage.”guage.” Within this ddesignation,esignation, hhee iidentifidentifi ed fourfour types: relational,relational, nnetwork,etwork, column-rcolumn-row,ow, anandd coorcoordinate.dinate. Of ththee ffourour typestypes,, ththee coorcoordinatedinate anandd column-rcolumn-rowow systemssystems araree ththee oldoldestest anandd mmostost strustructured.ctured. ThThee othotherer two typestypes,, rrelationalelational anandd nnetwork,etwork, araree mmoreore inintuitivetuitive andand allow greatergreater ddegreesegrees ooff frfreedomeedom dduringuring useuse.. NNotot surprisinsurprisingly,gly, rrelationalelational anandd nnetworketwork system tools have becomebecome inincreasinglycreasingly popularpopular.. "As we move toward socio/technical systems, this graphic language may be used as a tool to assist the reader in integrating the social and technical requirements of his or her job. Effective communication of relevant data within and between work teams is essential to ensure successful results. …a strong graphic is worth more than a thousand words" (Moran et al., 1999, p. vii).
2004 Selected Papers • www.nait.org • 194 ResearchResearch by HHauserauser (1991) ffoundound that ththee nnumberumber ooff conconstructsstructs anandd ddensityensity ooff rrelationshipselationships in a causal networknetwork display inincreasescreases ththee perperceivedceived complecomplexityxity ooff a system, but ddoesoes nnotot nnecessarilyecessarily rreduceeduce understanding.understanding. A conconstructstruct rrefersefers to ththee varivariablesables or nnodesodes ddepictedepicted in ththee display while a rrelationshipelationship refersrefers to ththee connconnectionsections mmadeade between ththee nnodes,odes, usuusuallyally with arrarrows.ows. In adaddition,dition, HHauserauser discoverdiscovereded that clusteringclustering or grgroupingouping conconstructsstructs inintoto mmeaningfuleaningful sectors anandd adaddingding adadditionalditional pipictorialctorial infinformation,ormation, susuchch as dotteddotted lines,lines, inincreasedcreased overoverallall ununderstandingderstanding ooff ththee displaydisplay.. ThThus,us, it appears that causal nnetworketwork displays araree appropriateappropriate fforor ununderstandingderstanding complecomplexx prproblemsoblems anandd fi ndingnding rootroot causes.causes.
HitchinsHitchins ((2002)2002) ssuggesteduggested ttherehere aarere tthreehree ggraphicraphic aarchetypesrchetypes fforor ddisplayingisplaying ccauseause aandnd eeffectffect rrelationships.elationships. TThehe fi rstrst simplysimply linkslinks thethe twotwo togethertogether withwith anan arrow,arrow, asas shownshown inin FigureFigure 1A,1A, wherewhere effecteffect followsfollows cause.cause. TheThe advantageadvantage ofof tthishis ddisplayisplay iiss tthathat iitt iiss uuncomplicated.ncomplicated. TThehe ddisadvantageisadvantage iiss tthathat rrelationshipselationships bbetweenetween mmultipleultiple ccausesauses aarere nnotot shown;shown; ii.e.,.e., ttherehere iiss nnoo oobservablebservable cconnectiononnection bbetweenetween oonene ccauseause aandnd aanother.nother. TThehe ssecondecond aarchetyperchetype iinn FFigureigure 11BB buildsbuilds rrelationshipselationships bbetweenetween ccausesauses aandnd eeffectsffects ttoo fformorm llinearinear cchains.hains. TThehe aadvantagedvantage ooff tthishis ddisplayisplay iiss tthathat tthehe llogicogic cancan bbee ttracedraced wwhilehile tthehe ddisadvantageisadvantage iiss tthathat iitt ddoesoes nnotot sshowhow ssystemystem ddynamics.ynamics. TThehe tthirdhird aarchetyperchetype iinn FFigureigure 11CC showsshows ccause-and-effectause-and-effect wwithith ffeedbackeedback lloops.oops. TThehe aadvantagedvantage ooff tthishis ddisplayisplay iiss tthathat iitt ccanan ddescribeescribe nnon-linearon-linear aandnd chaoticchaotic ssystemsystems ddynamics.ynamics. TThehe ddisadvantageisadvantage iiss tthathat iitt mmayay aappearppear ccounterintuitiveounterintuitive aandnd ccomplicated.omplicated.
Cause Cause Cause
DisjointedDisjointed ViewpointViewpoint A. Effect Effect Effect
Cause Effect/ Effect/ Effect Cause Cause
Linear,Linear Control, Contro lViewpointViewpoint B.
Effect/ Cause
Effect/ Causal-loop,Causal-loop Non-linear, Non-linea r Cause FeedbackFeedback ViewpointViewpoint Effect/ Cause C. Figure 1. Cause and Effect Linkages ������������������������������������ Collaborative Problem Solving Approaches Avouris,Avouris, Dimitracopoulou, and Komis (2002) asserted that the research on collaborative problem solving began by assessing the effectivenesseffectiveness of various independent variables such as group composition, media, and task structure. The next phase of problem solving research explored the role of group interaction and verbal processes. Thus, the focus shifted from attribute research design to the dynamics of the group itself. More recently,recently, the research has concentrated on the analysis methodologies used and the quality of the group collaboration. Thus, popular research design has focused on the group, the method, and the output generated during problem solving process.
GroupsGroups appear to be able to ddealeal with mmoreore complecomplexx types ooff prproblemsoblems because grgroupsoups have a larlargerger rrangeange ofof skills andand abilitiabilitieses than a sinsinglegle inindividualdividual (Finn(Finneganegan & O’MO’Mahoney,ahoney, 1996). GrGroupsoups also tentendd to operoperateate moremore effi cientlyciently over timetime as theythey establish cohesivenesscohesiveness throughthrough establishedestablished normsnorms ofof behavior,behavior, increasedincreased interaction,interaction, anandd rrepetitiveepetitive commcommunicationunication (Sch(Scholtes,oltes, 1988). ThThee grgroupoup ddynamic,ynamic, while timtimee conconsuming,suming, generallygenerally resultsresults in better solutisolutionon outputs than solutisolutionsons ggeneratedenerated thrthroughough inindividualdividual ananalysis.alysis. ThThus,us, ththee benefibenefi ts ofof collaborativecollaborative problemproblem solvingsolving methodsmethods farfar outweighoutweigh thethe processprocess ineffiineffi cienciesciencies (Hohmann,(Hohmann, 1977).
In a study to develop a methodology for describing how emotional and cognitive processes affect group problem solving effectiveness,effectiveness, Khaimovich (1999) found two stages of analysis. The fi rst stage involved the discovery of possible causes through brainstorming activity.activity. The second stage involved the verifi cation of the generated possible causes by examining the validity of causal links. Khaimovich found the verifi cation of the causes to be problematic. Groups were content with their original ideas and reluctant to scrutinize the integrity of their models. Thus, problem-solving methods that provide mechanisms for verifi cation are preferred.
2004 Selected Papers • www.nait.org • 195 Groupware and Collaborative Problem Solving AccordingAccording to Bort (2003), virtualvirtual collaborcollaborationation is ththee ddoorwayoorway to ththee nnext-generationext-generation ooff businbusiness.ess. HHowever,owever, organizationsorganizations that have eexperiencedxperienced susuccessccess in this arareaea ggenerallyenerally limit ththee scope by usinusingg custom-built softwaresoftware on a prproject-by-projectoject-by-project basisbasis.. WWebeb mmeetingseetings anandd ininstantstant mmessagingessaging araree gainingainingg popularity in organizations,organizations, but ththeseese collaborcollaborationation types araree ffairlyairly simplesimple.. UUnfortunately,nfortunately, ththee technitechnicalcal rrequirements,equirements, speed,speed, anandd banbandwidthdwidth fforor collaborcollaborativeative sosoftwareftware eexceedxceed ththee capacity ooff mmostost ddesktopesktop computers (Prisk & Dunn, 2002). Computerized collaborationcollaboration also crcreateseates acceptanacceptancece issues as ororganizationsganizations learn hhowow to work withoutwithout paperpaper.. This acceptanacceptancece prproblemoblem mmayay disappear over timtimee as futurfuturee ggenerationsenerations becombecomee mmoreore comfortablecomfortable usinusingg virtuvirtualal collaborcollaborativeative mmethods.ethods.
Of thethe currcurrentent available mmethods,ethods, grgroupwareoupware seemseemss to oofferffer ththee mmostost potenpotentialtial fforor virtuvirtualal collaborcollaborativeative problemproblem solvinsolving.g. ThThee prinprincipleciple funfunctionsctions ooff grgroupwareoupware araree fforor ddocumentocument sharinsharing,g, computer conferconferencingencing or chat, e-maile-mail anandd mmessaging,essaging, grgroupoup or mmeetingeeting schscheduling,eduling, prprojectoject mmanagement,anagement, iideadea ororganization,ganization, anandd team buildingbuilding thrthroughough sharshareded virtuvirtualal work space (Zwass(Zwass,, 1998). GrGroupwareoupware systemsystemss can ggenerallyenerally be categcategorizedorized as synchronous,synchronous, asynasynchronous,chronous, or a combincombinationation ooff both. SynSynchronouschronous grgroupwareoupware appliapplicationscations support rreal-timeeal-time communicationcommunication susuchch as ininstantstant mmessagingessaging or chat. AAsynchronoussynchronous grgroupwareoupware appliapplicationscations storstoree mmessagesessages anandd transfertransfer ddataata to be viviewedewed at ththee user’s conveniconvenienceence susuchch as e-me-mailail anandd attachmattachmentsents (DeFr(DeFranco-Tommarelloanco-Tommarello & Deek, 2004). Each ofof ththeseese system types has its advanadvantages.tages. SynSynchronouschronous grgroupwareoupware allows fforor lenlengthygthy discussionsdiscussions ooff diverse topitopicscs anandd eexpeditiousxpeditious solutisolutionsons whwhereasereas asynasynchronouschronous grgroupwareoupware prprovidesovides timtimee fforor personalpersonal rreflefl ectiectionon anandd carcarefuleful rresponseesponse to ararchivedchived enentriestries that can be rreadead at ananyy timtime.e. TTableable 1 shshowsows somesome ooff ththee currcurrentent grgroupwareoupware packpackagesages anandd ththeireir collaborcollaborativeative featurfeatures.es. ReadReadersers will nnoteote that mmanyany ooff thethe featurfeatureses ffoundound in collaborcollaborativeative anandd prproblem-solvingoblem-solving sosoftwareftware packpackagesages araree also ffoundound in ededucationucation anandd distancedistance learninlearningg sosoftware.ftware.
TableTable 1. Groupware Functions and Features
GroupwareGroupware NNameame E-mail & Document IM Meeting Project Idea Shared Message Sharing & & Tools Mgmt. Organizer Work Board Storage Chat Space
CollaborativeCollaborative anandd PrProblemoblem SolvinSolvingg TToolsools GrooveGroove X X X X X X X GroupSystemsGroupSystems X X X X X Lotus NotesNotes X X X X X DominoDomino SametimeSametime X X X QuickplaceQuickplace X X X X WikiWebWikiWeb X X
EducationalEducational andand DistanDistancece LearninLearningg TToolsools ElES X X Vitual-UVitual-U X X X LearningLearning Space X X X X X WebCTWebCT X X X X X CoMentorCoMentor X X X ColloquiaColloquia X X X TopClassTopClass X X BlackboardBlackboard X X X X X IM = InstantInstant MMessagingessaging
2004 Selected Papers • www.nait.org • 196 Conclusion TheThe literliteratureature inindicateddicated that strustructuredctured prproblemoblem solvinsolvingg mmethodsethods that inincorporatecorporate grgraphicaphic nnetworketwork displays forfor rrootoot cause ananalysisalysis araree an effective mmeanseans fforor ununderstandingderstanding anandd solvinsolvingg complecomplexx issuesissues.. ThThee challenchallengege fforor technologiststechnologists is to ddevelopevelop anandd becombecomee prprofiofi cientcient in problemproblem analysisanalysis usingusing virtualvirtual graphicalgraphical approachesapproaches with geographicallygeographically dispersed groups.groups. GrGroupwareoupware has ththee potenpotentialtial ooff becominbecomingg a valuvaluableable rresourceesource fforor this type ooff problemproblem solvinsolving.g. TTechnologyechnology prprofessionalsofessionals shshouldould carcarefullyefully assess ththee rrequirementsequirements befbeforeore selectinselectingg grgroupwareoupware andand continuecontinue to evaluevaluateate both ththee technitechnicalcal anandd socisocialal climclimateate befbeforeore enengaginggaging in virtuvirtualal prproblemoblem solvinsolvingg activities.activities. ThTheseese assessmassessmentsents shshouldould be based upon ththee nneedseeds ooff ththee ororganizationganization anandd ththee partiparticipatingcipating individuals.individuals. AtAt prpresent,esent, grgroupwareoupware has ththee potenpotentialtial fforor ffacilitatingacilitating virtuvirtualal grgroupoup prproblem-solvingoblem-solving activityactivity,, but is limited by technologicaltechnological conconstraintsstraints anandd commcommunicationunication banbandwidth.dwidth. MMoreore rresearchesearch anandd socisocio-technologicalo-technological developmentdevelopment is rrequiredequired befbeforeore prproblem-solvingoblem-solving by rremotelyemotely dispersed grgroupsoups will achiachieveeve its full potenpotential.tial. References Anderson, B., & Fagerhaug, T. (2000). Root cause analysis: Simplifi ed tools and techniques. Milwaukee: ASQ Quality Press. Arcaro, J. S. (1997). TQM Facilitator’s Guide. Boca Raton, FL: St. Lucie Press. Avouris, N., Dimitracopoulou, A., & and Komis, V. (2002). On analysis of collaborative problem solving: an object-oriented approach. Computers in Human Behavior, 19 (2): 147-167. Bort, J. (2003). How far can we go?: Despite technology barriers, the real-time enterprise is the next milestone for today’s extended enterprise. Network World, Inc., p. 70 Retrieved 7 April 2004. [email protected] Brown, J. I. (1994). Root-cause analysis in commercial aircraft fi nal assembly. 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