book

Knowledge Management Toolkit, The

Name: Knowledge Management Toolkit, The
Author: Amrit Tiwana
ISBN: 9780130128539

by Amrit Tiwana

December 1999

Beginner to intermediate

608 pages

15h 49m

English

Pearson

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Copyright
Dedication
Preface
Acknowledgments
I. The Rubber Meets the Road
1. Introduction
Knowledge Management: A Goldmine or an Empty Piggy-bank?Why Knowledge?What's Knowledge?So What's Knowledge Management?KM's Value PropositionWhy Now?Who Should Be Pursuing Knowledge Management?What's Behind the Buzz?Under the Magnifying GlassWhat Knowledge Management Is Not AboutWhat This Book Is AboutThank You, Dr. DavenportWhat This Book Will DoThe 10-Step Roadmap Helps You—Identify Knowledge That Is Critical to Your BusinessAlign Business Strategy and Knowledge ManagementAnalyze Knowledge Existing in Your CompanyBuild Upon, Not Discard, Existing IT InvestmentsFocus on Processes, and Tacit, Not Just Explicit KnowledgeDesign a Future-Proof, Adaptable KM System ArchitectureBuild and Deploy a Results-Driven KM SystemImplement Reward Structures, Leadership, and Cultural Enablers Needed to Make KM WorkCalculate ROI and Apply Knowledge MetricsLearn From War StoriesWhy Not the "M" Word?How to Use This BookHow This Book Is OrganizedAssumptions About Your CompanyMy Vocabulary: More than Words Can SayWhat This Book Is Not AboutEndnotes
2. The Knowledge Edge
Getting to Why: The New WorldThe Missing PiecesAccounting for Abnormal DifferencesA Common ThemeIntellectual CapitalKnowledge, Market Value, and ProsperityThe Back of the Envelope at Ford Motor CompanyThe 24 Drivers of KMKnowledge-Centric DriversFailure to Know What You Already KnowThe Emergent Need for Smart Knowledge DistributionKnowledge SluggishnessKnowledge VelocityTacitness of KnowledgeKnowledge Walks Out of the DoorKnowledge = PowerSystemic Unlearning RequirementsTechnology DriversTechnology—Trials, Triumphs, and TribulationsCompression of Product and Process Life CyclesThe Need for a Perfect Link Between Knowledge, Business Strategy, and ITOrganizational Structure-Based DriversFunctional ConvergenceEmergence of the Project-Centric CompanyDeregulationGlobalizationProduct and Service ConvergencePersonnel-Focused DriversCross-Functional CollaborationTeam Mobility and FluidityComplex ExpectationsProcess DriversRepeated Mistakes and Reinvention of SolutionsPredictive AnticipationResponsiveness of CompetitorsEconomic DriversExtraordinary Leverage and Increasing ReturnsBeyond Economics: Increasing Returns on KnowledgeOverdependence on IT for Competitive BreakthroughsThe Quest for a Silver BulletCreating the Knowledge EdgeCompeting Through ProcessEliminating the Wrong TradeoffsBeware of Relabeled Cans of WormsThe Road AheadLessons LearnedEndnotes
3. From Information to Knowledge
From Data to Information to KnowledgeKnowledgeHow Is It Different From Information?Tacit KnowledgeFrom Data to KnowledgeDataThe More, the Better?Information and NoiseThe Data-Rich and Information-Poor SocietyThe Big Slip Between the Swipe and the RefrigeratorShared DataInformation Flow Is Not Knowledge FlowBeyond Information FlowClassifying KnowledgeCategories of KnowledgeTypes of KnowledgeComponents of KnowledgeGround Truth and Truth MaintenanceJudgmentExperiential Knowledge and Knowledge ScriptsValues, Assumptions, and BeliefsIntelligenceIntegration of Knowledge SourcesThe Three Fundamental StepsKnowledge AcquisitionProfessional Intellect: Know-What to Care-WhyKnowledge SharingThe Collaborative Nature of KnowledgeKnowledge UtilizationThe Telephone as a Role Model for KM Systems DesignSupporting Informal KnowledgeThe Perils of Excessive FormalizationKnowledge Management Systems and Existing TechnologyDifferences Between a KM System and a Data WarehouseTypes of Information ManagedContextSizeContent FocusPerformanceNetworksDifferences Between a KM System, an Intranet, and an ExtranetContent FocusPerformanceBroader BaseProductizing KnowledgeReciprocityDifferences Between a KM System and GroupWareDifferences From Project Management ToolsRetrofitting Knowledge to Information TechnologyTaming the Tiger's TailThe Survival ImperativeDifficulties and Coping Mechanisms for Knowledge ManagementKnowledge Management Is ExpensiveIncompatible Combinations of Technology and PeopleSharing Knowledge: The New Way of ThinkingKnowledge Markets, Not HierarchiesBusiness and KnowledgeHow Companies Learn to LearnKnowledge-Friendly CompaniesKnowledge-Sharing CompaniesIs Your Company Ready for Knowledge Management?Lessons LearnedEndnotes
II. The Road Ahead: Implementing Knowledge Management
4. The 10-Step KM Roadmap
The 10-Step Knowledge Management Road mapPhase 1: Infrastructural EvaluationStep 1: Analysis of Existing InfrastructureStep 2: Aligning KM and Business StrategyPhase 2: Knowledge Management System Analysis, Design, and DevelopmentStep 3: Knowledge Management Architecture and DesignStep 4: Knowledge Audit and AnalysisStep 5: Designing the Knowledge Management TeamStep 6: Creating the Knowledge Management System BlueprintStep 7: Developing the Knowledge Management SystemPhase 3: DeploymentStep 8: Pilot Testing and Deployment Using the RDI MethodologyStep 9: The CKO, Reward Structures, Technology, and Change ManagementPhase 4: Metrics for Performance EvaluationStep 10: Metrics for Knowledge WorkLessons Learned
IIA. The First Phase: Infrastructural Evaluation and Leverage

5. The Leveraged Infrastructure
The Approach: Leverage, Leverage, LeverageLeveraging the InternetGlobal ReachPlatform IndependenceEnabling Technologies for the Knowledge Management Technology FrameworkKnowledge Flow Meta ComponentCollaborative Environments and GroupWareIntranets and ExtranetsPointers to ExpertiseInformation Mapping Meta ComponentDocument ManagementInformation Source Meta ComponentProject Management ToolsMultimediaInformation and Knowledge Exchange Meta ComponentTransparent Capture EnablersWeb Conferencing, Water Coolers, and TelephonesMind MappingIntelligent Agent/Network Mining Meta ComponentIntelligent Decision Support SystemsIntelligent Agent-Based ToolsIntegrating TechnologyKnowledge ServersLessons LearnedEndnotes
6. Aligning Knowledge Management and Business Strategy
From Strategic Programming to Strategic PlanningMoving Beyond Fallible Data PatternsMoving Beyond SWOT AnalysisCodification or Personalization?Knowledge Maps to Link Knowledge to StrategyStarting at the TopCreating a Knowledge MapAnalyzing Knowledge GapsAdding Up the NumbersSummaryStrategic Imperatives for a Successful KM SystemTwenty-four Lessons: Critical Success FactorsLesson 1: There Is No "One Right Way"Lesson 2: Reach a Working Definition of KnowledgeLesson 3: Focus on Processes and Not Just TechnologyLesson 4: Live with Vague Knowledge MeasuresLesson 5: Salability Necessitates Demonstration of Short-Term ImpactLesson 6: Count in Tacit KnowledgeLesson 7: Create a Shared ContextLesson 8: Begin with What You HaveLesson 9: Accommodate Reasoning and AssumptionsLesson 10: Future ThinkLesson 11: Minimize Routing RetransmissionsLesson 12: Give Incentives, Not Faster ComputersLesson 13: Allow Everyone Access, and Allow Everyone to ContributeLesson 14: Allow ConfidentialityLesson 15: Allow Access Anytime, AnywhereLesson 16: Update AutomaticallyLesson 17: Supply Resource Maps to Ease NavigationLesson 18: Use Other Databases in Addition to Corporate Best Practices DatabasesLesson 19: Provide Management SupportLesson 20: Focus on Technology and Internal Consulting Support for CollaborationLesson 21: Support InformalityLesson 22: Remember that Less Is More—The Art of Packaging KnowledgeLesson 23: Provide Logical Business ExtensionsLesson 24: Determine Your Knowledge Delivery WeltanschuungThe Knowledge-Strategy Link RevisitedAssessing FocusLessons LearnedEndnotes
IIB. The Second Phase: KM System Analysis, Design, and Development
7. Infrastructural Foundations
Technology Components of the KM ArchitectureTwo Primary Enablers: Storage and CommunicationsSelecting TechnologyProcess SupportCost Versus Value-Added TechnologyThe Seven-Layer KM System ArchitectureFoundation for the Interface LayerSelection Criteria for the Collaborative PlatformThe Web or Notes?The Vital Integrator: The World Wide WebClient SoftwareServer SoftwareServer HardwareGatewaysGroupWare Versus Web Client Interface?Collaborative Intelligence and Filtering LayerInfrastructural Elements of Collaborative IntelligenceDriving Decisions With DataArtificial IntelligenceData WarehousesGenetic Algorithm ToolsNeural NetworksExpert Reasoning and Rule-Based SystemsCase-Based ReasoningVideo ConferencingPush or Pull?Summary: Technological FitLevel of Knowledge Granularity in ObjectsInfrastructural Elements for Searching, Indexing, and RetrievalMeta SearchingHierarchical SearchingAttribute SearchingContent SearchingCombining Search StrategiesTagging Knowledge Elements With AttributesActivities AttributeDomain AttributeForm AttributeType AttributeProducts and Services AttributeTime AttributeLocation AttributePush/Pull RevisitedSummaryLessons LearnedEndnotes
8. Knowledge Audit and Analysis
Hindsight + Insight = ForesightWhy Audit Knowledge?Measuring Knowledge GrowthThe Road From Art to ScienceMaking Coffee: A Knowledge-Based ExampleStage 0: Total IgnoranceStage 1: You Can Tell Good From Bad CoffeeStage 2: You Have Created a List of VariablesStage 3: You Can Determine the Significance of VariablesStage 4: You Can Now Measure VariablesStage 5: Repeatable Methodology or RecipeStage 6: Repeatable Methodology + Localized AdaptabilityStage 7: A Formal or Informal ModelStage 8: Perfect KnowledgeThe Knowledge Audit TeamPlanning a Knowledge AuditConducting the Knowledge AuditDefining the GoalsConstraint-Based PruningDetermining the Ideal StateSelecting the Audit MethodDocumenting Knowledge AssetsAnalyzing the Populated Capability QuadrantsChoosing Your Company's K-SpotsStrategic Positioning Within the Technology FrameworkThe Four Positioning ChoicesStrategic Position AStrategic Position BStrategic Position CStrategic Position DLessons LearnedEndnotes
9. Designing the KM Team
Sources of ExpertiseLocal Experts and Intradepartmental GurusInternal IT DepartmentsNonlocal Experts and Extradepartmental GurusConsultantsManagersTeam Composition and Selection CriteriaTemporary Versus Permanent Team MembersTeam Life Span and Sizing IssuesThe Knowledge Management Project LeaderInternal DynamicsTranslation and DelegationUser ParticipationPrototypes: A Stitch in Time Saves NineThe KM Team's Project SpaceManaging Stakeholder ExpectationsTeam Constitution Validity: Summarizing the ProcessPoints of FailureThe Breakpoint: Buy-In FailureCategorizing RisksControlling and Balancing RequirementsSolving User Buy-In ProblemsLessons LearnedEndnotes
10. Creating the KM System Blueprint
Analyzing Lost OpportunitiesThe Knowledge Management ArchitectureComponents of a Knowledge Management SystemThe Knowledge RepositoryThe Evils of Integrative RepositoriesContent CentersOpen and DistributedKnowledge Aggregation and MiningFrom Skills Databases to Knowledge DirectoriesAutomated CategorizationPersonalized Content Filtering and Push DeliveryThe Collaborative PlatformCollaborative FilteringCommunity-Centered Collaborative FilteringMeta KnowledgeAccommodating Multiple Degrees of ContextTechnology ChoicesDesigning Integrative and Interactive Knowledge ApplicationsIntegrative Application SupportKnowledge Flow Models: Centripetality and CentrifugalityThe Interactive Application ComponentThe Fit Into Overall ArchitectureBuild or Buy?Interoperability ConsiderationsPerformance and ScalabilityUser Interface Design ConsiderationsA Network View of the KM ArchitectureFuture-Proofing the Knowledge Management SystemLessons LearnedEndnotes
11. Developing the KM System
The Building Blocks: Seven LayersThe Interface LayerChannels for Tacit and Explicit KnowledgeContextual Expression at the InterfacePlatform IndependenceLearning From IntranetsOptimizing Video ContentUniversal AuthorshipA Walkthrough: Urban MotorsThe Opening PageSearch MechanismsPeople and PointersThesauriPlacesDocumentsLicensesDocument Management through the Interface LayerApplying DMA StandardsComplementing DMA with WebDAVEventsReferenceServices and LinksCustomizabilityThe Access and Authentication LayerVirtual Private NetworksStandards and Protocols for Expansive NetworksBiometrics and Other Forms of AuthenticationThe Collaborative Filtering and Intelligence LayerFrom Static to Dynamic StructuresVirtual FoldersAutomatic Full Text IndexingAutomatic Meta TaggingFrom Client/Server to Agent/ComputingBenefits of Agent MobilityMobile Agents for Knowledge ManagementAgents and Push Models for Knowledge DeliveryThe Application LayerThe Transport LayerThe Middleware and Legacy Integration LayerThe Repositories LayerLessons LearnedEndnotes
IIC. The Third Phase: KMS Deployment
12. Prototyping and Deployment
Moving From Firefighting to Systems Deployment?PrototypingPilot DeploymentsSelecting a Pilot ProjectLessons From Data WarehousesPre-RDI Deployment MethodsThe Information Packaging MethodologyThe Big-Bang Approach to DeploymentEnterprise Integration: Boon or Bane?The Results Driven Incremental MethodologySteps Involved in the RDI MethodologyBusiness ReleasesThe Traps in Selecting the Release SequenceProcess Divisibility and RDI ReleasesRDI's Role in Tool and Task ReinventionCross-Functional SynergyFunctional ComplexityAvoiding OverengineeringDeveloping Clear Communication ProcessesHuman Barriers in Technology DesignOne Infinite LoopLessons LearnedEndnotes
13. The CKO and Reward Structures
From the CIO to the CKOKnowledge Management Leadership RolesThe CKO's Job DescriptionThe CKO as Organizational GlueInitiatives and the CKOThe Successful CKOHistoryReward Structures to Ensure Knowledge Management SuccessLessons LearnedEndnotes
IID. The Final Phase and Beyond: Measuring ROI and Performance
14. Metrics for Knowledge Work
Traditional MetricsFinancial ROI and Tobin's qTotal Cost of OwnershipLearning More From the TelephoneThe Metric Is the LimitationCommon Pitfalls in Choosing MetricsUsing Too Many MetricsDelayed and Risky Reward TiesChoosing Metrics That Are Hard to ControlChoosing Metrics That Are Hard to Focus OnChoosing Metrics That Emphasize Hard Results and Neglect the "Soft Stuff"Choosing Metrics That Are Too Rear-View OrientedMeasuring the Wrong ThingsAll the Right Things Not MeasuredThree Ways to MeasureBenchmarkingThe Wise Learn Many Things from Their EnemiesBenchmark TargetsThe Benchmarking ProcessBenchmark LessonsHouse of Quality and Quality Function DeploymentHouse of Quality Metrics MatrixSoftware Tools for QFD AnalysisThe Balanced Scorecard TechniqueAdvantages of KM Balanced ScorecardsLimitations of KM Balanced ScorecardsClassifying and Evaluating ProcessesAlternative MetricsThe Skandia MethodThe FASB MethodLessons LearnedEndnotes
15. Case Studies
Some BackgroundProcess Distribution in High-Performance KM ProjectsKnowledge Management in the Aerospace Industry: The Case of Rolls RoyceThe ProblemProblem ScopeKnowledge Management Project GoalsMeasurementKnowledge Management in Sales and Marketing: The Case of Platinum TechnologyThe ProblemThe SystemDevelopment StagesMeasurementKM in Customer Support: The Case of NortelIssuesThe Three Phases of Organizing KnowledgeKM in the Semiconductor Industry: GaSonics InternationalThe Starting Point: Technical PublicationsThe Goal: Three Months to TargetKM Pilot Case: Monsanto Nutrition and Consumer ProductsKM to Build Economies of Reuse: The Case of Texas InstrumentsLessons Learned
III. Side Roads: Appendices
A. The Knowledge Management Assessment Kit
The 10-Step Populated RoadmapPhase 1: Infrastructural EvaluationAnalyzing Knowledge Management and Your Business StrategyYour Business and Your CompetitionInitial Assessment of KM and Your BusinessChoosing a KM FocusIdentifying and Assessing Key ResourcesAssessing Core ProcessesPhase 2: Analysis, Design, and DevelopmentTags and AttributesIdentifying Activities AttributesIdentifying Domain AttributesForm AttributeType AttributeProducts and Services AttributeTime AttributeLocation AttributeDeploymentRDI Methodology ChecklistsReleasesPutting It All Together
B. Alternative Schemes for Structuring the KM System Front End
Alternative StructuresAlphabeticalAlphanumericDewey Decimal CodesClassification Schemes for Public LibrariesUniversal Decimal ClassificationACM Computing Classification SystemThe Library of Congress Classification SchemePredicast Revised Event CodesCan These Really Be Used?
C. Software Tools
Software ToolsacCrawlacSGMLAlpha StockVue 99AscentBrainForest Professional for PalmPilot PDAsBusinessVue 2.0CBR Content NavigatorConcept ExplorerDataWare Knowledge Management SuiteDeltaMinerEmail FerretEmployee Appraiser 4.0File, Phone, and News FerretsG2 WebMinerHyperKnowledgeHyperwaveInfo FerretInspiration ProfessionalIntraneticsKA2 Knowledge AgentsKeyFlowKnowledgeSEEKERMarketFirstMicrosoft FrontPage 2000Microsoft ProjectMind ManagerMIS AleaMIS InterfaceBuilderOpentext LivelinkPalmPilot AportisDocPalmPilot BrainForest Mobile EditionPalmPilot Datebk3Performance NowPerspectaProfilerRemote Control ToolbarRetrievalWareSemioMapSmartDrawSolutionSeriesThoughtFlowWeb-Enabled ART* EnterpriseWeb Ferret
D. Resources on the Web
Knowledge Management: Web PointersIntellectually Rich Companies
SELECTED BIBLIOGRAPHY
Bibliographic References and Further Reading
Bibliography
Glossary

Content preview from Knowledge Management Toolkit, The

Chapter 11. Developing the KM System

	Now, if estimates made before the battle indicate victory, it is because careful calculations show that your conditions are more favorable than those of your enemy; if they indicate defeat, it is because careful calculations show that favorable conditions for battle are fewer. With more careful calculations, one can win; with less, one cannot. How much less chance of victory has one who makes no calculations at all!
	--Sun Tzu in The Art of War

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Chapter 11. Developing the KM System

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