Be Certain, Be Trillium Certain© Harte Hanks Trillium Software 2012Session 2Lean MeanData Governance MachineKiran Gill, Se...
© Harte Hanks Trillium Software 2012Introduction and OverviewWaste Elimination – 7 Wastes(TIMWOOD)TransportationInventoryM...
© Harte Hanks Trillium Software 2012What isLEAN DataGovernance?5. Convergenceof 7 wastes, 5Lean Principlesand 5 DataGovern...
© Harte Hanks Trillium Software 20124
© Harte Hanks Trillium Software 2012LeanMethodologies5
© Harte Hanks Trillium Software 2012Lean Data GovernanceWaste EliminationTaiichi Ohno’s 7 Wastes (TIMWOOD)Example applicat...
© Harte Hanks Trillium Software 2012Lean Data GovernanceCase Study: Luxury Fashion labelExistence of some governance proce...
© Harte Hanks Trillium Software 2012Transportation:Waste during transportation to end destinationAssess Transportation wit...
© Harte Hanks Trillium Software 2012Inventory:Responding to the pull of the customer ensures minimal InventoryT I M W O O ...
© Harte Hanks Trillium Software 2012Motion:Motion refers to the movement within a process.T I M W O O DRisk: Introduction ...
© Harte Hanks Trillium Software 2012Waiting:Waiting is a common wasteThis can be easily avoidedT I M W O O DRisk: Introduc...
© Harte Hanks Trillium Software 2012Over Processing:Processes that do not add valueCorrelates with the identification and ...
© Harte Hanks Trillium Software 2012Overproduction:Excessive production of data or informationWait for the internal data c...
© Harte Hanks Trillium Software 2012Defects:Defects spread to the entire organisationDefective data and processes have a n...
© Harte Hanks Trillium Software 2012T I M W O O DHelps!Suitable structure for data governance reviewWaste definitions are ...
© Harte Hanks Trillium Software 2012Turning an Approach into RealityLean Data Governance is not just an approach - it is a...
© Harte Hanks Trillium Software 2012The Lean Mean Data GovernanceMachine1. Avoidbatches andqueues -Enable speedand agility...
Be Certain, Be Trillium Certain© Harte Hanks Trillium Software 2012Questions?Suggested further reading:Trillium White Pape...
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Lean Mean Data Governance Machine Webinar Part 2

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Lean Mean Data Governance Machine Webinar Part 2

  1. 1. Be Certain, Be Trillium Certain© Harte Hanks Trillium Software 2012Session 2Lean MeanData Governance MachineKiran Gill, Senior Strategic Consultant, Trillium Software1
  2. 2. © Harte Hanks Trillium Software 2012Introduction and OverviewWaste Elimination – 7 Wastes(TIMWOOD)TransportationInventoryMotionWaitingOver processingOverproductionDefectsTurning an Approach into RealityThe Lean Mean Data Governance MachineOverview2
  3. 3. © Harte Hanks Trillium Software 2012What isLEAN DataGovernance?5. Convergenceof 7 wastes, 5Lean Principlesand 5 DataGovernanceDisciplines1. Focus on theInternal dataCustomer4. Delivery offlexible,perfected,value addedoutputs to theinternalcustomers.2. Optimisationof ClassicGovernanceusing LeanPrinciples3. Minimise,eliminate andprevent wastein DataManagement3
  4. 4. © Harte Hanks Trillium Software 20124
  5. 5. © Harte Hanks Trillium Software 2012LeanMethodologies5
  6. 6. © Harte Hanks Trillium Software 2012Lean Data GovernanceWaste EliminationTaiichi Ohno’s 7 Wastes (TIMWOOD)Example applicationsAdopt and adapt the approachWaste definitions unique to the businessNo wrong/right definition6
  7. 7. © Harte Hanks Trillium Software 2012Lean Data GovernanceCase Study: Luxury Fashion labelExistence of some governance processes – no definitionData from multiple sourcesMany risks as a result of bad practiceNo ownership or awarenessWorking in silosWastage occurring across the enterprise
  8. 8. © Harte Hanks Trillium Software 2012Transportation:Waste during transportation to end destinationAssess Transportation within Process, Technology, People and Data ManagementT I M W O O DRisk: Excessive transportation =increased error and degradationMap and ReviewAssess tools and technologyEliminate unnecessary data transfer –refine the process8
  9. 9. © Harte Hanks Trillium Software 2012Inventory:Responding to the pull of the customer ensures minimal InventoryT I M W O O DRisk: Using incorrect data to drivedecisions. Resource utilisationEvaluate internal processesIdentify and eliminate excess dataIdentify critical dataAvoid generating surplus data at sourceReview roles and purpose9
  10. 10. © Harte Hanks Trillium Software 2012Motion:Motion refers to the movement within a process.T I M W O O DRisk: Introduction of error duringtransit. Resource/time wastage.Process review - movement,manipulation and interrogationReliable technologyIntuitive data management with lessstagesAssess people movement –unnecessary process e.g. workarounds10
  11. 11. © Harte Hanks Trillium Software 2012Waiting:Waiting is a common wasteThis can be easily avoidedT I M W O O DRisk: Introduction ofworkarounds, errors and delays.Tool functionalityReliable technologyReview process and eliminate gapsPrioritise resolution activityIntroduce new processes and eliminateold ones. E.g. Issues Management tools11
  12. 12. © Harte Hanks Trillium Software 2012Over Processing:Processes that do not add valueCorrelates with the identification and creation of value streams in the 5 Principles of LeanT I M W O O DRisk: Deterioration of data qualityand integrity. Increased errorsKey stages of data journey by process.Regular review of business rules -central access to definitionsEstablish schedule and scope ofcleanseBuild archiving rules and processes12
  13. 13. © Harte Hanks Trillium Software 2012Overproduction:Excessive production of data or informationWait for the internal data customer demand in order to prevent wasteT I M W O O DRisk: Duplicated effort. Usingobsolete dataDefine owners - manage outputsDefine process for creation of newoutputReview data captureIntroduce central tools - automate e.g.dashboards13
  14. 14. © Harte Hanks Trillium Software 2012Defects:Defects spread to the entire organisationDefective data and processes have a negative impact on the businessT I M W O O DRisk: Brand reputation,compliance, costlyReduce defects at point of captureIdentify workarounds - workbackwards to sourceAll defects to be logged and resolvedEffective monitoring of defects andrisks14
  15. 15. © Harte Hanks Trillium Software 2012T I M W O O DHelps!Suitable structure for data governance reviewWaste definitions are adapted to suit thebusinessAvoid missing crucial processesGuides the business to key areas15
  16. 16. © Harte Hanks Trillium Software 2012Turning an Approach into RealityLean Data Governance is not just an approach - it is a way ofthinking.•ELIMINATION - Taiichi Ono’s seven wastes - TIMWOOD•PREVENTION - 5 principles of Lean – 5S•Trillium’s 5 Data Governance Disciplines= formula for Lean Data Governance.16
  17. 17. © Harte Hanks Trillium Software 2012The Lean Mean Data GovernanceMachine1. Avoidbatches andqueues -Enable speedand agility2. Eliminateand Preventwaste in allareas of datagovernance3. Automate,standardiseand improveprocesses e.g.reporting4. Meticulousmanagementandgovernance ofprocess flows5. DataGovernance isevolving –continuouschanges andupdates to theprogram6. Deliver valueto the internalcustomerswhen theydemand it17
  18. 18. Be Certain, Be Trillium Certain© Harte Hanks Trillium Software 2012Questions?Suggested further reading:Trillium White Paper: “Lean Mean Data Governance” Machine:Available soon at http://www.trilliumsoftware.com/To learn more about Lean: http://www.lean.org/Contact: kiran.gill@trilliumsoftware.com18

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