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Data Management and the CMM/CMMI: Data Management and the CMM/CMMI: Translating Capability Maturity Models to Translating Capability Maturity Models to Organizational Functions Organizational Functions Cynthia C. Hauer Cynthia C. Hauer Millennium Data Management, Incorporated Millennium Data Management, Incorporated Huntsville, Alabama Huntsville, Alabama CDM Industry Data Management Chair CDM Industry Data Management Chair NDIA TID Technical Information Division Symposium NDIA TID Technical Information Division Symposium Royal Sonesta Hotel, New Orleans, LA Royal Sonesta Hotel, New Orleans, LA August, 2003 August, 2003 Because Data Transcends Time Because Data Transcends Time

Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

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Page 1: Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

Data Management and the CMM/CMMI:Data Management and the CMM/CMMI:Translating Capability Maturity Models to Translating Capability Maturity Models to

Organizational FunctionsOrganizational Functions

Cynthia C. HauerCynthia C. Hauer

Millennium Data Management, IncorporatedMillennium Data Management, Incorporated

Huntsville, AlabamaHuntsville, AlabamaCDM Industry Data Management ChairCDM Industry Data Management Chair

NDIA TID Technical Information Division SymposiumNDIA TID Technical Information Division SymposiumRoyal Sonesta Hotel, New Orleans, LARoyal Sonesta Hotel, New Orleans, LA

August, 2003August, 2003

… … Because Data Transcends TimeBecause Data Transcends Time

Page 2: Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

AgendaAgenda

• Address the role of Data Management Address the role of Data Management in the CMM/CMMIin the CMM/CMMI

• Assess CMMI guidance for DMAssess CMMI guidance for DM

• Identify Missing Links Identify Missing Links

• Share the DM Maturity ModelShare the DM Maturity Model

Page 3: Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

DM in the CMMIDM in the CMMI

• Under project Management, Project PlanningUnder project Management, Project Planning• Description and definition of DMDescription and definition of DM• Data Requirements Data Requirements • Data ContentData Content• Data CollectionData Collection• Data CostData Cost• Typical work productsTypical work products• Sub-practicesSub-practices

Page 4: Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

Plan for Data ManagementPlan for Data Management

• Various forms of documentationVarious forms of documentation– Administrative, engineering, CM, financial, Administrative, engineering, CM, financial,

logistics, quality, safety, manufacturing, and logistics, quality, safety, manufacturing, and procurementprocurement

• Various formatsVarious formats• Deliverables or non-deliverableDeliverables or non-deliverable• Distribution forms (physical or electronic)Distribution forms (physical or electronic)

SP 2.3-1 Plan for Data ManagementSP 2.3-1 Plan for Data Management

Plan for the management of project data.Plan for the management of project data.

Page 5: Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

Description/Definition of DMDescription/Definition of DM

• CMMI does not really define DMCMMI does not really define DM– Functionally described, rather than definedFunctionally described, rather than defined

• Data is described in terms of Data is described in terms of “documentation”“documentation”

Page 6: Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

Data ContentData Content

• FormsForms

• MediaMedia

• ““Deliverability”Deliverability”

• DistributionDistribution

Page 7: Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

Data RequirementsData Requirements

• Established for the project Established for the project – For data items, content, and formFor data items, content, and form

• Based on a common or standard set of Based on a common or standard set of “data requirements”“data requirements”

• ““Uniform content and format requirements Uniform content and format requirements for data items facilitate understanding of for data items facilitate understanding of data content and help with consistent data content and help with consistent management of the data resources”. management of the data resources”.

Page 8: Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

Data Collection & CostsData Collection & Costs

• Reason should be clearReason should be clear• Task includes analysis and verification applies to Task includes analysis and verification applies to

– project deliverables and non-deliverablesproject deliverables and non-deliverables

– Contract deliverables and non-contract data Contract deliverables and non-contract data requirementsrequirements

– customer-supplied datacustomer-supplied data

• Stipulates understanding of how data will be used, Stipulates understanding of how data will be used, prior to collectionprior to collection– Data is costly, and should be collected only when Data is costly, and should be collected only when

neededneeded

Page 9: Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

Typical Work ProductsTypical Work Products

• DM PlanDM Plan• Master List of managed dataMaster List of managed data• Data content and formal descriptionData content and formal description• Data requirements listsData requirements lists• Privacy requirementsPrivacy requirements• Security requirementsSecurity requirements• Mechanism for data retrieval, repro, and distributionMechanism for data retrieval, repro, and distribution• Schedule for collection of project dataSchedule for collection of project data• Listing of project data to be collectedListing of project data to be collected

Page 10: Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

Sub-PracticesSub-Practices

• Establish requirements and procedures to ensure Establish requirements and procedures to ensure privacy and security of the dataprivacy and security of the data– Procedures must be established to identify who has access Procedures must be established to identify who has access

to what data as well as when they have access to the datato what data as well as when they have access to the data

• Establish a mechanism to archive data and to access Establish a mechanism to archive data and to access archived dataarchived data– Understandable form or represented as originally generatedUnderstandable form or represented as originally generated

• Determine the project data to be identified, collected, Determine the project data to be identified, collected,

and distributedand distributed..

Page 11: Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

AssessmentAssessment

• Rudimentary, but completeRudimentary, but complete

• Functionally-orientedFunctionally-oriented

• Evolved thinkingEvolved thinking

• DM is basically interwoven all over the DM is basically interwoven all over the CMMICMMI

• A clear, concise definition of DM would A clear, concise definition of DM would be of great value to all CMMI usersbe of great value to all CMMI users

Page 12: Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

Transferring CMMI Guidance Transferring CMMI Guidance to the Implementation Levelto the Implementation Level

Page 13: Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

What can Maturity Models MeasureWhat can Maturity Models Measure??

Both the quantitative and qualitative aspects of successBoth the quantitative and qualitative aspects of success

Quantitative FactorsQuantitative Factors

PlanningPlanningTrackingTracking

MeasurementMeasurementQuality GoalsQuality Goals

Documented ProcessesDocumented ProcessesPeer ReviewsPeer Reviews

Allocation of Dedicated ResourcesAllocation of Dedicated Resources

Qualitative FactorsQualitative Factors

LeadershipLeadershipVisionVision

CommunicationCommunicationDecision makingDecision making

CollaborationCollaborationIntegration of Processes & DisciplinesIntegration of Processes & Disciplines

Quantitative is Measured, Qualitative is AcknowledgedQuantitative is Measured, Qualitative is Acknowledged

Page 14: Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

Establishing Value Establishing Value Step One: Measurement CriteriaStep One: Measurement Criteria

• Cost Cost - acquisition and life cycle - acquisition and life cycle (investment potential)(investment potential)

• PricePrice - against risk and investment - against risk and investment (return)(return)

• Re-useRe-use - with metadata and characterization - with metadata and characterization (leverage factor)(leverage factor)

• Measurable consistencyMeasurable consistency - from project to project - from project to project (data (data integrity)integrity)

• EvolvingEvolving - quality decision data - quality decision data (KM or collaborative quality, use, (KM or collaborative quality, use, and outcome)and outcome)

Key: Establishing & calculating visible, measurable worth Key: Establishing & calculating visible, measurable worth for effort and assets expended, saved, re-usedfor effort and assets expended, saved, re-used

Page 15: Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

Establishing Value Establishing Value Step Two: Maturity ModelStep Two: Maturity Model

The three essential macro states of DM maturityThe three essential macro states of DM maturity

InitialInitial TransitionalTransitional ExcellenceExcellence

Manual,Manual,inconsistentinconsistentmethods thatmethods that

are not repeatableare not repeatable(Asset Ignorance)(Asset Ignorance)

Course correctionsCourse correctionsthat are applied inthat are applied in

certain cases, over timecertain cases, over time

Methods improve andMethods improve andgain consistency withgain consistency withunderstanding & useunderstanding & use(Asset Recognition)(Asset Recognition)

Improvements areImprovements arepredictable, proven, andpredictable, proven, and

intentionally createdintentionally created

Repeatable methodsRepeatable methodscreate opportunities forcreate opportunities for

efficiencies & economiesefficiencies & economiesof scaleof scale

(Asset Use)(Asset Use)

TIME, TECHNOLOGY, UNDERSTANDING & QUALITYTIME, TECHNOLOGY, UNDERSTANDING & QUALITY

Page 16: Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

The Data Management Maturity ModelThe Data Management Maturity Model

Maturity Levels 1-5 Process Performance Technology Support Quality, Predictability of Results

Value Determination Comments

5 – Fully Optimized Data support success rate is 100%

Processes are almost entirely automated

Data mining, expert systems, knowledge management are enabled and employed routinely

4 – Predictable Risk Ability to routinely reduce uncertainty and data-related risk 3 – Corporate Competency Capabilities are institutionalized within organization, enabled by mature technology

Statistically stable processes routinely measured against industry standard performance metrics Standard, consistent, statistically capable measurable processes, performance metrics begin to evolve

Automation and background performance of processes, risks; automated decision support services Integrated technology designed to enable emerging best practices, technology suppliers are partners in defining how technology accomplishes best results

2 – Managed Standardized tasks and roles, introduction of advanced technology begins

Individuals develop processes that work for them; not yet institutionalized across individuals or location.

Unintegrated point solutions designed for specific tasks and individuals spent much time figuring out how to integrate processes and technology to accomplish results

1 – Baseline Capable people and heroic efforts

No defined processes. Individual performers may follow a different process or pathway each time

General purpose tools: Excel, Access, or none at all. DM is a project function and not a corporate function

Almost complete certainly of results is achievedAlmost complete certainly of results is achieved

Reliability and predictability of results is Reliability and predictability of results is significantly improved; e.g. six sigma vssignificantly improved; e.g. six sigma vsthree sigmathree sigma

Good quality results within expected tolerancesGood quality results within expected tolerancesmost of the time; poorest individual performers most of the time; poorest individual performers improve towards best performers; more leverageimprove towards best performers; more leverageachieved for best performersachieved for best performers

Variable quality with some predictability; best Variable quality with some predictability; best individual performers assigned to business criticalindividual performers assigned to business criticalprojects to reduce risk and improve resultsprojects to reduce risk and improve results

Organization depends entirely upon individuals; Organization depends entirely upon individuals; little or no corporate visibility into DM cost or little or no corporate visibility into DM cost or performance; variable quality, low results performance; variable quality, low results predictability, little to no repeatability. predictability, little to no repeatability.

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Quality, Predictability of ResultsQuality, Predictability of Results

Page 17: Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

Value Determination FactorsValue Determination Factors

5 5 Fully OptimizedFully Optimized

4 4 Predictable RiskPredictable Risk

3 3 Corporate CompetencyCorporate Competency

2 2 Managed Managed

1 1 BaselineBaseline

Model LevelModel Level Value Determination CharacteristicsValue Determination Characteristics

Obvious value for services received; risk reduced,Obvious value for services received; risk reduced,

unnecessary costs avoided, clear best practices unnecessary costs avoided, clear best practices & sector leadership& sector leadership

Lower ROI in investments in DM are accepted in Lower ROI in investments in DM are accepted in exchange for reduced risksexchange for reduced risks

Measurable, able to recognize costs and benefits, Measurable, able to recognize costs and benefits, perform cost/benefits analyses, maximize ROI, perform cost/benefits analyses, maximize ROI, good results faster, better trained workforcegood results faster, better trained workforce

Anecdotal, based on individual performers’ Anecdotal, based on individual performers’ capabilities and specific memorable eventscapabilities and specific memorable events

Subjective, gut feel for performance, benefit, costs, Subjective, gut feel for performance, benefit, costs, and value receivedand value received

Gains: Consistency, Repeatability, Cost & Business Model AwarenessGains: Consistency, Repeatability, Cost & Business Model Awareness

Page 18: Cynthia C. Hauer Millennium Data Management, Incorporated Huntsville, Alabama

SummarySummary

• Maturity Models have potential for successMaturity Models have potential for success– To be successful, they must be understood at - and mapped To be successful, they must be understood at - and mapped

to - the application level of the enterprise processesto - the application level of the enterprise processes

• DM and CM have the capability to integrate their DM and CM have the capability to integrate their areas of expertise to address most organizational areas of expertise to address most organizational challenges, as they touch the enterprise everywherechallenges, as they touch the enterprise everywhere

• DM is making a contribution to the CMM/CMMI DM is making a contribution to the CMM/CMMI • Discussion: How can we improve and leverage the Discussion: How can we improve and leverage the

CMMI opportunity to benefit DM, CM, and our CMMI opportunity to benefit DM, CM, and our organizations?organizations?