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EWSolutions

Strategic Partner & Systems IntegratorIntelligent Business Intelligencesm

Lean Data GovernanceWorkshopBy Anne Marie Smith, Ph.D.

Principal Consultant, Director of EducationEWSolutions

[email protected]



EWSolutions’ BackgroundEWSolutions is a Chicago-headquartered strategic partner and full life-cyclesystems integrator providing both award winning strategic consulting and full-service implementation services. This combination affords our clients a fullrange of services for any size enterprise information management, meta datamanagement, data governance and data warehouse/business intelligenceinitiative. Our notable client projects have been featured in the Chicago Tribune,Federal Computer Weekly, Journal of the American Medical InformaticsAssociation (JAMIA), Crain’s Chicago Business, and won the 2004 IntelligentEnterprise’s RealWare award, 2007 Excellence in Information Integrity Awardnomination and DM Review’s 2005 World Class Solutions award.

For more information on our Strategic Consulting Services, Implementation Services,or World-Class Training, email us at [email protected] or call at 630.920.0005

Best Business Intelligence ApplicationInformation Integration

Client: Department of Defense

World ClassSolutions Award

Data Management

2007 Excellence in InformationIntegrity Award Nomination



EWSolutions’ Partial Client List

For more information on our Strategic Consulting Services,Implementation Services, or World-Class Training email us [email protected]

AFLACArizona Supreme CourtBank of MontrealBankUnitedBasic American FoodsBecton, Dickinson and CompanyBlue Cross Blue Shield companiesBooz Allen HamiltonBranch Banking & Trust (BB&T)British Petroleum (BP)California DMVCalifornia State FundCanadian National RailwayCapella UniversityCignaCollege BoardComcastCorning Cable SystemsCountrywide FinancialDefense Logistics Agency (DLA)Delta DentalDepartment of Defense (DoD)Driehaus Capital ManagementEli Lilly and CompanyEnvironment Protection AgencyFarmers Insurance Group

Federal Aviation AdministrationFederal Bureau of Investigation (FBI)Fidelity Information ServicesFord Motor CompanyGlaxoSmithKlineHarbor FundsHarris BankThe HartfordHarvard Pilgrim HealthCareHealth Care Services CorporationHewitt AssociatesHP (Hewlett-Packard)Information Resources Inc.International PaperJanus Mutual FundsJohnson ControlsKey BankLiquidNetLoyola Medical CenterManulife FinancialMayo ClinicMcDonaldsMicrosoftMoneyGramNASANational City BankNationwideNeighborhood Health PlanNORC

Physicians Mutual InsurancePillsburyQuintilesSallie MaeSchneider NationalSecretary of Defense/LogisticsSingapore Defense Science & TechnologyAgencySocial Security AdministrationSouth Orange County Community CollegeSunTrust BankTarget CorporationThe Regence GroupThomson Multimedia (RCA)United Health GroupUnited NationsUnited States Air ForceUnited States ArmyUnited States Department of StateUnited States NavyUnited States Transportation CommandUniversity of MichiganUniversity of Wisconsin HealthUSAAUS CellularWaste ManagementWells FargoWisconsin Department of TransportationZurich Cantonal Bank



Anne Marie Smith – Professional Profile Internationally recognized expert and speaker in the fields of

enterprise information management, data modeling, meta datamanagement and data warehousing, one of the top industryexperts in data governance and information management strategyand planning

Published numerous articles that have been featured in some ofthe industry’s most prestigious magazines and newsletters

Contributing author to the DAMA Data Management Body ofKnowledge (DAMA-DMBoK©)

Contributing columnist – The Data Administration Newsletter –http://www.tdan.com

Has taught at several institutions of higher learning includingLaSalle University and Southern New Hampshire University

Holds certifications in CDMP / CBIP and has earned a Ph.D. inManagement Information Systems



Agenda

Introduction to LEAN Short overview of data governance Aligning LEAN concepts to data

governance Fundamentals of implementing a LEAN

data governance approach Challenges to successful LEAN data

governance – and how to overcome them Conclusion, resources for additional

study


Introduction to LeanConcepts




What is LEAN? Lean is an operational excellence strategy

that enables organizational improvement inany function Cultural improvement as well as functional

methodology In Japanese, the term often used is

“Kaizen” – describing incrementalimprovements

LEAN principles include processes andpeople, in any environment or industry


LEAN Mission

LEAN mission: Creating more value with less work –performing the right type of work and the right amountof work to achieve the desired purpose while respectingthe people performing the work

“LEAN is a systematic approach to identifying andeliminating waste (non-value added activities) throughcontinuous improvement by flowing the product at thepull of the customer in pursuit of perfection.”

Lean Thinking, Womack and Jones,1996


LEAN Goals Lean goals:

• Increasing efficiency and effectiveness ofany process–Efficiency – doing something with less effort–Effectiveness - the degree to which

something is successful in producing adesired result

• Decreasing waste (time, resources, effort,money, etc.)

• Using empirical methods to decide whatmatters and why


LEAN Waste Waste is anything—time, cost or work that adds no

value in the eyes of the customer Identifying “customer” for any effort is essential Customers will vary for projects, activities within

projects, etc.• Waste perception varies with customer – waste analysis should become part of

business requirements discovery

Waste exists at all levels and in all activities LEAN practices support recognition of wasteful

activities LEAN practices can identify new, less wasteful ways

to perform an action Not accept something as the “way work is done around

here”


The Seven Deadly Wastes

The ultimate lean target is the total elimination of waste.Waste, or muda, is anything that adds cost or time withoutadding value. Seven deadly wastes have been identified overthe years. Recently an eighth waste has been identified —underutilization of people.


Examples of LEAN WastesLEAN 7 Wastes

Waste ExampleInventory Unneeded files, extra supplies, unnecessary copies, excessive unread emails,

etc.Overproduction Producing reports before they are needed, performing more analysis than

requiredTransportation Filing/saving documents that will never be used again, updating customer

records in different or multiple systemsMotion Selecting additional keystrokes and fields to retrieve previous information,

searching for misplaced or duplicate files or dataWaiting Delays in getting feedback/approvals/decisions from peers, management or

leadershipDefects - Rework Incorrect/missing information on a form, handling a report numerous timesUnderutilization ofPeople

Assigning an employee to two jobs due to understaffing, having employeesperform a task that is politically motivated, not cross training employees


Understanding Waste

What would you be willing to pay for when ordering ahamburger?

___ Meat

___ Dough

___ Ketchup

___ Electricity to run ovens

___ Electricity to run outdoorlights left on accidentally

___ Person paid to inspect take-out orders

___ Cost of hamburgers notsold

___ Distribution center

___ Cost of radio, TV, webads

___ Cost of delivery trucksigns

___ Cost of store manager

___ Cost of cleaning

___ Cost of menus

___ Employee training

___ Profit


LEAN Continuous Improvement

Three basic principles: Challenge : Vision of the challenges one

needs to face to realize one's ambition – dailychallenge.

Kaizen : Processes must be improvedcontinuously, striving for innovation andevolution.

Genchi Genbutsu : Going to the source tosee the facts for oneself and make the rightdecisions, create consensus, and make suregoals are attained.


LEAN People Management

LEAN principles include attention to people as well asprocesses LEAN is not “mean” to people at any level

LEAN people management starts with personalmanagement Respect for individual’s commitment to continuous

improvement Respect for individual’s desire to work within a well-

performing team LEAN people management includes respect for others

Building mutual trust – attention to customer’s needs Continual attention to needs and results of team – team

work and performance


LEAN Approach LEAN emphasizes the prevention of waste: any extra

time, labor or material spent producing a product orservice that doesn’t add value to it

LEAN’s unique tools, techniques, and methods canhelp any organization reduce costs, achieve fasterdelivery and shorten most lead / planning times

LEAN fosters a culture in which all employeescontinually improve their skill levels and theorganization improves its processes, therebyincreasing morale


Implementing Lean Approach - 1

Senior management from business and IT agrees totheir vision of a LEAN organization

Management identifies project leader and sets projectobjectives

Project leader and management communicate plan andvision to the workforce

Ask for volunteers to form the LEAN Implementationteam (5-7 works best, all from different departments)

Appoint members of the LEAN Process ImplementationTeam from the list of volunteers and others

Train the Implementation Team in the various conceptsand tools; develop, implement and sustain education /professional development in skills


Implementing Lean Approach - 2 Select a pilot project to implement the LEAN approach:

scope, plans, budget, etc. All using the LEANapproach.

Run the pilot for 2–3 months - evaluate, review,document, and learn from your mistakes

Collect results based on accepted measures Evaluate results, encourage honest and constructive

feedback Stabilize the positive results by teaching supervisors

how to train the new standards and processes Reduce and eliminate the negative results with focus on

constructive action Roll out pilot to other organization areas to implement

LEAN across the enterprise


Introduction to DataGovernance


DAMA-DMBOK Framework

EIM Administrative Services© DAMA 2008


DAMA-DMBOK Framework

Environmental Elements

Goals &Principles

Activities

Deliverables

Roles &Responsibilities

Technology

Practices &Techniques

Organization &Culture

Data Management Functions

Document& Content

Management

DataWarehousing& BusinessIntelligence

Management

Reference &Master DataManagement

DataSecurity

Management

DataDevelopment

metadataManagement

DataQuality

Management

DataArchitectureManagement

DatabaseOperations

ManagementDataGovernance

© DAMA 2008


Data Governance

Data is one of the most important assets in acorporation

Data has value when it is delivered quickly,properly formatted, concise, accurate andunderstood

Business ownership of the data and activeparticipation are critical

Data governance is the foundational componentof functions of the DAMA-DMBOK © framework

Data stewards and data governance professionalsperform the activities of data governance


What is Data Governance? Data governance is the practice of making strategic and effective decisions

regarding an organization’s information assets Data governance includes:

Determination of valid data sources Management of master and reference data Responsibilities for data integrity Meta data management practices Data quality policies and procedures Establishing and/or enforcing meta data standards

• Both internal and external Stakeholder arbitration mechanism Development of stewardship role for selected business subject matter experts

in all business domains

Data Governance is a fundamental componentof an effective enterprise informationmanagement program


Data Governance in Data Management

Provide an enterprise wide metadata management environment that provides accessto data semantics, format and source information – ensures semantic uniformity,correlation of format from all sources

Provide and govern a set of processes that ensure data quality – ensure that dataquality processes are comprehensive and applied consistently

Provide and govern a set of processes that measure data value – ensure that datavaluation processes are comprehensive and applied consistently

Provide and govern a set of processes that ensure appropriate security – determinesecurity levels and approve application/data security approach

Provide and govern a set of well-documented processes and interfaces for accessingdata which eliminates the proliferation of redundant and inconsistent data – approvesand then ensures adherence to processes

Provide standards and governance of processes for the definition/design, creation andmaintenance of data – approves and then ensures adherence to processes

Enable data sharing for both ad hoc inquires and new application systems therebyreducing storage of redundant data – ensure that data stewards provide access asrequired for data sharing

Provide an enterprise-level data dictionary and appropriate data stores that enable thereuse of data – provide mechanism for enterprise dissemination of meta data

Provide a framework and standardized set of data storage requirements that enableappropriate capacity planning activities – ensures that all data is compliant with thedefined data infrastructure


Objectives of Data Governance

Reduce data redundancy

Data Accessibility Data availability

Data flexibility Data reuse

Systematically improve:

Address and synchronize data collection processes


Data Governance Benefits

Enables the organization to produce high-qualityinformation which is useful, appropriate, andtimely by: Providing one point of accountability for data

management Reducing data duplication Increasing confidence in data for business and IT Improving timeliness and usability of data Establishing a common vocabulary of data to ensure

access to the right information Defining enterprise-wide (or site / project wide)

values for common reference data Providing information and guidance to assist in

compliance and regulatory efforts concerning data


Data Stewards in Data Governance

Data Stewards: selected subject matter experts whoserve as the first line resources for many activitiesin a data governance program: Metadata definition Data quality standards development Data quality profiling and analysis Data model content expertise Master data management content Data governance policy implementation Etc…

A successful, coordinated data stewardshipprogram is an essential component of anysuccessful data governance initiative


Key Attributes: Successful Data Governance

Successful Data Governance requires: Adoption of Enterprise Data / Information Management methodology and

standards throughout the organization• Use of data governance professionals as specialists to manage development of

policies, standards and methodology for the program within established guidelinesand best practices

Strong, continued management support of the approach – authoritygiven to data stewards to enact and to enforce proper standards andpolicies

Continued focus on improving data and information quality, throughvigilant data and information management

Successful, continual interaction across the organization for sharing ofcommon goals and objectives, common processes, etc.

Establishment of measures to chart progress of the data governance andstewardship program and the use of data and information managementstandards

Continued, sustained and active executive support from all levels andfrom both business and IT leadership


Measuring Program Success

Business Value Measures - attribute business value to implementation of the data governance program data standardization improved data management discipline across the enterprise and in

projects Acceptability and Compliance Measures - ways to

directly evaluate and measure the level of adoption of enterprise data standards data governance program performance of the stewards and the stewardship teams


Mission for Data Governance“A specific task with which a person or a group is charged; a pre-

established and often self-imposed objective or purpose”

Development of objectives “Call to action” Clear, dynamic statement that demonstrates how the mission will

be achieved

SAMPLE: The mission of the CLIENT Data Governance Program is to elevate the

status of data as an asset in our organization through proper governance

practices and management, methodologies and implementation techniques.

Our community will work together in a collaborative, open and honest

fashion to improve the value of data and its management across the

enterprise.


Vision for Data Governance

“A thought, concept, or object formed by the imagination; unusual discernment orforesight; the act or power of seeing”

State to be achieved View of the future Describes how data governance will support reaching that end-

state

SAMPLE: To enable the generation of business value from the

information assets CLIENT owns and has access to so that the

organization, and its customers and partners can achieve their

business objectives.


Benefits of Mission and Vision Statements

Strengthen culture through a unified sense of purpose Improve decision making with clarity about "big picture”

and the details to achieve Enhance cross-functional relationships through a shared

understanding of priorities

Mission and vision are NOT synonymous, they arecomplementary, especially to governance Clearly established Vision encourages people to focus on

what's important Clearly defined Mission statement also helps employees

better understand the organization and itsapproaches/changes


Data Governance Goals

Reduce overall business cost through the reductionin redundant data and elimination of re-workrequired through poor data definitions and lack ofcoordination for data knowledge among businessunits

Improve business capability: Consistent data experience for customers, clients,

partners, and vendors Privacy and compliance Mergers and Acquisitions Customer loyalty Efficient business transactions with external parties

Customer data safety / privacy


Data Governance Success Factors

Define your program's objectives, mission and vision with identified methods forachievement.

Leverage a Data Governance methodology/framework DAMA’s DMBOK – vendor neutral, collaborative effort by industry experts

Data Governance industry best practices and methods (e.g., DGPO, consulting methodology, books,etc.).

Define the program components to enable your Data Governance initiative basedon your organization’s structure and culture.

Formalize a multiple tier structure of committees and teams comprised of bothbusiness and technical resources. Utilize subject matter experts (SMEs) asneeded on the various committees and teams.

Executive sponsors, or executive stewards, should be drawn from the businessexecutive side of the organization. They own the data.

Educate, communicate, and collaborate about Data Governance across theentire organization.


Lean DataGovernance Steps


Lean Data Governance

How does a Data Governance program align with these Leanpractices?


Where Do I Start?

Mission, vision, goals – essential for LEAN focus Start with a brief / not lengthy assessment of the

organization’s current state of enterprise data /information management Current State Future State Gap Analysis Roadmap for Implementation

Assessment results will dictate business cases forprojects and for each subject area to beimplemented iteratively


LEAN Data Governance Mission

Exercise: Take LEAN mission and Data Governance

sample mission and create your LEAN DataGovernance Mission


LEAN Data Governance Vision

Exercise: Take LEAN vision and Data Governance

sample vision and create your LEAN DataGovernance Vision


LEAN Data Governance Goals

Exercise: Take LEAN Goals and Data Governance

sample goals and create your LEAN DataGovernance Goals


LEAN Data Governance Success Factors

Exercise: Take LEAN Goals and Data Governance

sample success factors and create your LEANData Governance Success Factors


Assess Data Management Current State

Components Data Governance Data Quality Data Architecture Data Warehousing and

Business Intelligence Master Data

Management Metadata Management Unstructured Data

Management Data and Information

Security

Environmental Factors General Environment Sponsorship and Goals Principles, Attitudes and

Beliefs Cultural Readiness and

Adoption Metrics and Business Value Practices and Processes Roles and Organizational

Structures Technology Skills, Experience and

Training


Assessment Process

Assess current state and describe future state:Diagnostic assessment of: Key business goals and drivers Current state and key challenges to enterprise information management

(EIM) and each component / function, especially for data governance Current data management efforts and milestones (successful and

unsuccessful) Assess each DMBOK function and strategic view of EIM EIM evaluation based on industry standards and a maturity model

Develop high-level business case for data governanceDefine solution approach and prioritize component implementations

according to business case / needsDevelop roadmap and data governance implementation plan - iterative


LEAN Approach to Assessment

LEAN approach to assessment incorporates following principles: Waste reduction – focus on reducing or eliminating any activity

that does not contribute value to the final product• Only critical components are assessed – each organization

decides what is “critical”• Level of assessment is determined by organization needs

– Assessment may be deep if needs require it Small, experienced team – assessment team consists of senior

level personnel only Assessment report delivers only desired level of detail – focus on

constructive feedback, recommendations and implementation


Survey Current Situation

Conduct an assessment of the current datamanagement situation at the enterpriselevel

Identify areas of strength, areas wheresome improvement is needed and areaswhere significant improvement is needed

Choose initial focus area for governanceactivities based on survey results


LEAN Data Management Assessment

Exercise Using the list of enterprise data management

components, and remembering the LEANprinciple of waste reduction, choose the four(4) most critical components for yourorganization to assess – and write a shortexplanation for each of your choices


Choose Initial Focus

Focus on policy, standards, and strategy Focus on data quality and meta data

quality Focus on privacy, compliance, and security Focus on architecture and integration Focus on data warehouses and business

intelligenceWhat will be the focus of your LEAN datagovernance program?


Business Cases for Data Governance

Essential for securing and retaining support for adata governance initiative

Creating business cases by subject or functionalarea can increase support – and re-focus effortsif project stalls

Each business case should identify a problemthat could be solved with involvement from a datagovernance program

Business case can include possible solutions forthe proposed data governance program


LEAN Business Case Points Make the business case interesting; remember

many people may read it Keep it clear, factual and concise; minimize jargon

and conjecture Communicate the essential facts as part of the

overall story – a LEAN business case is completeand succinct

Remember the LEAN principles of continuousimprovement, reduction of waste, and effectivemanagement of resources in developing thebusiness case

Demonstrate the value the data governanceinitiative brings to the organization and to thesituation in the business case


Lean Data Governance Steps - 1 Senior management from business and IT agrees to their vision of a LEAN

organization Management identifies project leader and sets project objectives Project leader and management communicate plan and vision to the workforceLean Data Governance: Organization performs LEAN data management assessment and

receives recommendations to develop a data governance program Senior management develops LEAN data governance vision with

assistance from leaders in business, IT and Enterprise DataManagement

Management chooses Data Governance Program Officer, responsiblefor program design and implementation – may need to recruit fromoutside organization for this role

Senior management and Program Officer solicit members for the DataGovernance Council

Data Governance Council creates basic Data Governance ProgramCharter (3 pages maximum) as initial documentation of program’svision for LEAN data governance


LEAN Data Governance Council Senior representatives from across the organization

Council membership should be limited to expectedcontributors

Cross-functional representation Broad representation for business and IT is essential

Concerned with executive, high-level, data-orienteddecisions Leadership for data governance and for general

information management Attention to LEAN principles, data management and

data governance


Data Governance Program Charter

A short document that outlines the businesspurposes that necessitated creating the datagovernance program Target the specific concerns and opportunities of the

organization concerning data governance

LEAN Best Practice: Data governance chartershould fit on no more than three (3) single-spacedpages. Anything longer is likely too long

Charter is a business document and not atechnical document – used for executivecommunication

Charter is not a scope document – scope isseparate


LEAN Data Governance Program Charter

Exercise: Take LEAN Data Governance Mission, Vision,

Initial Focus Area and Business case, and theProgram Charter guidelines, and create yourLEAN Data Governance Program Charter


Lean Data Governance Steps - 2 Ask for volunteers to form the Lean Process Implementation team (5-7

works best, all from different departments) Appoint members of the Lean Process Implementation Team – official

team creation Train the Implementation Team in the various lean tools and processes,

and connect with other organizations that have implemented LEANLean Data Governance: Data Governance Council solicits members of the initial Data Stewardship

team Initial Data Stewards and the Data Governance Council attend basic

training in data governance concepts with LEAN focus, usually given bythe Program Officer

Program Officer should connect with data governance professionals atother organizations to share experiences and learn from their operations– Communities of Practice

Data Governance Council reviews Program Charter to revise it ifnecessary, based on selection of initial data stewardship team orimplementation focus area


Lean Data Governance Steps – 3a

Select a pilot project to implement: focus, scope, plans, budget, etc. Run the pilot for 2–3 months - evaluate, review and learn from your mistakes

Lean Data Governance: Data Governance Council selects the initial subject area for data

governance – data stewardship team selected based on this choice Remember to maintain focus on LEAN principles in selecting subject

area (increasing efficiency, decreasing waste, adding demonstratedvalue, etc.)

Program Officer and Data Stewards select one or more datamanagement functions to implement in this subject area: Data quality review and enhancement Data definitions creation and refinement (business and technical) Data mapping – source to targets used for integration and

conversions


Data Governance Project Scope

Scope documents are project-based Each project has a scope document Identifies and describes all work necessary for that project Critical for setting good requirements All activities should be based on the scope document Use to prevent “scope creep” Being too detailed can be as bothersome as not

providing enough detail Reinforces the LEAN principle of waste reduction –

elimination of anything that does not contribute value Do NOT skip this document


LEAN Scope Document – Major Sections

Short project description Project scope description Short list of project’s critical success factors (3-5) Major risk factors Major project assumptions Major project issues List of required resources (roles, number needed) High-level project plan

Remember LEAN documentation principle: clear,concise materials – not too much information and

not too little information


LEAN Data Governance Project Scope

Exercise: Take LEAN Principles, the Data Governance

Program Charter, Business Case, your chosenfocus area, and the Project Scope guidelines,and create your LEAN Data GovernanceProject Scope document


Lean Data Governance Steps – 3b

Select a Pilot Project to implement Run the pilot for 2–3 months - evaluate, review and learn from your

mistakes

Lean Data Governance: Implement data stewardship meetings to perform the activities

chosen for the selected subject area – stewardship team meetingsat least weekly, program officer tracks results against determinedmeasures Using processes, practices, standards developed by data

management department Activities supported by data management team and Data

Governance Program Office Connect stewardship team leader with Data Governance Council

for periodic meetings and coordination between stewards andcouncil (vision, communication, etc.)


LEAN Data Stewardship LEAN data stewardship focuses on following

points: One implementation at a time – single point of focus

• Metadata definition, data quality for a specific subject area, source-to-target mapping, etc.

Daily challenge• Stewards work on data stewardship activities as part of normal tasks

Continuous improvement• Data stewards must be given time to learn about data governance,

data stewardship and other areas of enterprise data management Going to the source

• Data stewards must be able to consult with other subject matterexperts and other resources in the organization to resolve any data-related issue


LEAN Data Governance Documentation

LEAN data governance documentation principles: Document what is required to the necessary level of detail Do not document what is not required, do not over-document Create standard documentation whenever practical

• Teams should not create their own documentation unlessabsolutely necessary

Create document libraries and encourage their use• New documents should be included in the library after

validation• Publish document library listings periodically

Rely on industry standards whenever practical• Refine / adapt standards only where necessary

Refine and update existing documentation appropriately


Some Data Governance Documents

Many documents can be appropriate for usein governance and stewardship

Your organization may have some or all ofthese documents, some may need revision

• Meeting Agenda• Meeting Minutes / Notes• Change Request / Change Management Report• Status Report• Governance and Stewardship Handbook• …..


Lean Data Governance Steps - 4 Collect results based on accepted measures Evaluate results, encourage honest and constructive feedback Stabilize the positive results by teaching supervisors how to train the new

standards and processes Reduce and eliminate the negative results with focus on constructive action

Lean Data Governance: Data Governance Council and Program Officer identify key performance

indicators to be measured Results of the data stewardship activities are measured and results are

collected by Governance Program Officer Program officer and selected management representatives evaluate

results Communicate results, institute training to correct negative results and

focus on constructive actions and communications Data Governance Council reviews Program Charter to determine if initial

effort was aligned with charter’s stated intentions. Project scope isreviewed against results


Lean Data Governance Steps – 5a

Roll out pilot to other organization areas to implement LEAN across theenterprise

Lean Data Governance: Once the initial subject area has implemented a level of data stewardship

under the guidance of the Data Governance Program: Initial data stewardship team expands focus from one data

management area (data quality, meta data, etc.) to another withintheir subject area

A second data stewardship team is created for another subject areaand a chosen data management focus:• Determined project scope – within Program Charter• Training for new data stewards – current data stewards serve as

mentors• Alignment with existing data stewardship teams• Incorporating new team into Data Governance Council activities


Lean Data Governance Steps – 5b

• Roll out pilot to other organization areas to implement LEAN across theenterprise

Lean Data Governance: Management evaluates need to expand Data Governance Program

Office, adding assistance for the Program Officer as program grows Program Officer continues communication of program’s results across

the enterprise, with revisions to Program Charter as necessary Expansion follows organization’s established LEAN data governance

principles and implements LEAN data governance incrementally yetconsistently throughout the enterprise: Daily challenge Continuous improvement Going to the source


LEAN Data Governance Expansion

Exercise: Take LEAN Principles, the Data Governance

Program Charter, and all that has beenpresented so far – determine how you wouldexpand your LEAN data governance programfor the next iteration. Write the scope of thenext iteration and be prepared to discuss it.


Lean DataGovernanceChallenges


Challenges to LEAN

Resistance to change Common to any new initiative

Failure to empower staff at all levels with LEAN approach Requires Plan-Do-Check-Act approach with guidance and support

LEAN cannot be learned only by study Demonstrated guidance is usually needed for implementation

LEAN is seen as applicable only to manufacturing Many non-manufacturing areas have adopted LEAN approaches

successfully LEAN is considered to be philosophical

Approach is a combination of philosophy, methodology,processes, tools, cultural change and empowerment

Fragmented departments across organization LEAN implementation requires cross-departmental, holistic

cooperation


Challenges to Lean Data Governance – 1

Resistance to change Data Governance requires many changes, and so does lean. Combination of

changes may be too much for some organizations without significantsocialization

Failure to empower staff at all levels Data stewardship role requires empowerment. Any data governance will fail

without accountability, responsibility and authority vested in the data stewards

Lean cannot be learned only by study Implementation is the only way to see if your approach works, and how to

correct the mistakes made. Continue to implement, incrementally

Lean is seen as applicable only tomanufacturing Data governance, and lean, can be applied in every organization, customized

for the environment, as long as certain principles are followed


Challenges to Lean Data Governance – 2

Lean is considered to be philosophical Lean is a combination of philosophy, tools and techniques and application to real-

world problems to yield solutions. Data governance is the same, since it includesan approach, essential best practices, tools and techniques and implementation tobe successful

Fragmented departments acrossorganization Many organizations operate as silos, and do not share data or processes. This

makes the use of any enterprise approach difficult and of little benefit. Like Lean,data governance must be integrated across the organization to provide value.


Discuss LEAN Challenges Exercise

Choose the three (3) most importantchallenges to implementing LEAN datagovernance in your organization

Examine the challenge Write reasons for the challenge and ways to

overcome it within your culture Engage in a short discussion with your

colleagues to share ideas


Socializing,Communicating, and

Marketing DataGovernance


Stakeholder Profiles

Stakeholders are individuals, groups, ororganizations that are actively involved in aproject, are affected by its outcome, or caninfluence its outcome.

The stakeholder profiles identify the customers forthis product and other stakeholders, and statestheir major interests in the product.

LEAN stakeholder profiles identify the critical rolesand business units affected by the effort, and thecontributions or challenges each stakeholder mayhave to the project.


Example – Stakeholder Profile

StakeholderMajorValue Attitudes Major Interests Constraints

Executives Increasedrevenue

See product asavenue to 25%increase inmarket share

Richer feature setthan competitors;time to market

Maximumbudget =$1.4m

EditorsFewererrors inwork

Highlyreceptive, butexpect highusability

Automatic errorcorrection; ease ofuse; high reliability

Must run onlow-endworkstations

Legal aidesQuickaccess todata

Resistantunless productis keystroke-compatible withcurrent system

Ability to handlemuch largerdatabase thancurrent system;easy to learn

No budgetfor retraining


Examples of Stakeholder Value

Improved productivity Reduced rework Cost savings Streamlined business processes Automation of previously manual tasks Ability to perform entirely new tasks or functions Conformance to current standards or regulations Improved usability or reduced frustration level

compared to current applications


LEAN Stakeholder Profiles

Exercise: Using the sample stakeholder profiles and

remembering LEAN values, create your LEANstakeholder profile


Governance Communication Plan LEAN approach strongly recommends continual communication,

formal and informal, to ensure that the practices are implementedand accepted Determine goal(s) – why do you want/need to communicate? Determine objective(s) – what do you want to communicate? Identify target audiences – each audience will have different

needs and expectations Determine strategies – how will you communicate to each

audience? Finalize key messages – what do you want to communicate to

each audience? Determine activities – what are the tasks to accomplish each of

the goals Determine evaluation mechanisms – how will you determine if

your communications are successful? Build communication plan from template using these points


LEAN Steps to Communicate Governance

Select project(s) for data governance and stewardshipcommunication – choose both completed and in-progress projectswhen possible

Explain how data governance and stewardship was / will beimplemented in the project(s)

Broadly broadcast communication – in various forms (portal, centraldocuments, meetings, etc.)

Measure and report results – REWARD SUCCESS REGULARLY!! Include lessons learned and challenges – not everything will be

successful but lessons are learned on every effort Involve marketing department in communication plan development

and execution – LEAN practices recommend relying on experts ineach field


Socialization vs. Communication

Communication is the act of tellingsomeone something

Socialization is the act of integratingpractices and activities into a culture orgroup

They are complementary – notsynonymous!

LEAN requires continual multi-level coordinatedcommunication and socialization for success


LEAN Communication TemplateSituation Analysis

What is the need or problem that LEAN data governance can address? What are the issues to becommunicated? Describe business situation for governance and stewardship in the organization.Briefly describe any cultural concepts that apply to the organization and how the culture could affectLEAN data governance.

Goals andObjectives

What goals and objectives do you have for the communication and socialization of the program?Short-term goals, medium-term goals, and long-term goals for the LEAN data governance programand its socialization.

Audience AnalysisWho are you trying to reach and why? Define target audiences, there will be more than one. For eachaudience, describe the business need for these messages, and any unique characteristics that mayinfluence content and delivery. List major concerns each audience may have about the governanceprogram and identify a way to alleviate that concern.

VehiclesWhat tools will you use to disseminate your messages? With what frequency? Establish a timelinefor each vehicle. Consider those in your specific function or business group, as well as company-wideevents/vehicles. Vehicles are more specific than message strategies.

Overall KeyMessages

Three – five statements of what you’re communicating. These should support the business objectivesfor socializing LEAN data governance, for communicating the program’s objectives and plans andshould address the major concerns of the target audience(s).

Expected Outcome Describe what you want to happen with the intended audiences concerning LEAN and datagovernance and your messages. What would you like to see as a result of your efforts?

Metrics /Measurement

How will you know if you have succeeded in your communication and socialization? Develop metricsthat will be concrete and measurable, formal or informal. How will you measure success in socializingthe program?

Contacts Who are important people/groups for you to know and maintain contact with as you socialize the EANdata governance program?


LEAN Data Governance Communication

Exercise: Build a sample LEAN Data Governance

Communication plan for your organizationusing the documentation and all you havelearned to this point.


Engage BusinessSupport and

Participation for theData Governance

Program


Selling Data GovernanceQuestions to be answered by business and technology areas: Can you identify customers (products, inventory, vendors, etc.)

CONSISTENTLY across business units, applications, divisions, etc.? Can you measure the quality of data CONSISTENTLY across business

units, applications, divisions, etc. (accuracy, completeness, validity, integrity,etc.)?

Can you identify CONSISTENT quality definitions and metrics acrossbusiness units, applications, divisions, etc.?

Can you collect data from more than one source without requiring significantsearching and cleansing?

Can you define the key terms used across the organizationCONSISTENTLY?

Can you identify master / reference data CONSISTENTLY across businessunits, applications, divisions, etc.?

Can you point to owners of data and process for each subject area andfunction in the organization?

Can you identify those business people responsible for the quality andmanagement of the data in each subject area?

Can you describe the current condition of the data in each subject area?

If you cannot answer all of these questions confidently and consistently, your organizationneeds enterprise data governance!


Talking to BusinessBusiness Sponsorship & Involvement

Research & understandbusiness initiatives for

business area

Research & understandreal or potential data

challenges in businessarea

Do not talk about needfor Data Governance or

data management

Discuss howsponsorship and

participation will enabletheir business initiative

or business challenge tobe successful

Clearly identify time andresource commitment.

Identify cost savingsand/or increased

business capabilities orprocess efficienciesthrough sponsorship

Understand and speakthe language of the

business area

Has a similar businessinitiative been tried and

failed before?

As sponsor membershipgrows, leverage current

participants for newsponsors

Talking Points for LEAN Data Governance


Data Governance Opportunities Standards do not exist for common data

(e.g., customer) across lines of business,which inhibit attempts to integrate dataacross applications resulting in poorcustomer experience.

Guidance for release of data to 3rd partyvendors & partners leaving potentialexposure of intellectual property.

Product status codes and associatedtimestamp information have differentmeanings inhibiting data integration.

Consumption of customer data protectedby state and federal laws or by contracts.

Different data standards (e.g., US vs.European) used across lines of businesspreventing sharing of information aboutthe same customer or product.

Various custom data exchange standardsused across various lines of business withexternal clients, partners, and vendorsresulting in increased business cost due tocomplex data mapping.

Data quality issues with address dataresults in delays with delivery of productsresulting in additional cost and poorcustomer experience.

Inconsistent product names across linesof business prevent consistentengagement and satisfaction withcustomer.

A common vocabulary for data usedwithin your organization does not existimpacting business decisions made acrosslines of business.


Targeting Business Needs

What areas are the current focus for business strategy? What is planned in the program/project portfolio for the

upcoming FY? What are the Tier 1 & 2 programs/projects for the

company (e.g., Project Portfolio)? What are the major business applications being

implemented (e.g., ERP, Claims, Billing, CDI, PIM, other)? What are your executive sponsors’ focus areas / areas of

interest? What business areas and/or applications have known

data management challenges?


Initial Data Governance Opportunities

What business areas and/or applications haveexisting or upcoming regulatory, governmentmandated, or other compliance challenges?

If Risk Management exits, what businessareas and/or applications are consideredexposed from a data managementperspective?

What groups or projects are considered to beat an enterprise level in the organization?

Target new critical business initiatives (e.g.,customer loyalty program).


Sustaining a LEAN DataGovernance Program


Sustaining LEAN Data GovernanceHow do we sustain the LEAN Data Governance

effort?Executive sponsorship

Commitment to LEAN principles – in organization and in datamanagementJob description alignment with implied responsibilitiesPerformance metrics and actionable measurementsRewards for performance of data governance duties

Communities of Practice (CoP)User understanding and communication of LEAN and datagovernanceFeedback loop for DG Council and data stewardsDrive future direction for data management and data governanceInternal and external communities

Marketing LEAN data governance efforts


Sustaining LEAN Data Governance

Exercise: Using the guidelines for sustaining LEAN data

governance and remembering LEAN values,describe how you will sustain yourorganization’s LEAN data governance program


Data Governance Program Maintenance

Include a system of necessary audits and checksimplemented to test and confirm adherence to policy

Control is re-defined from “monitoring results” to “makingthings happen according to approved processes”

Follow established procedures, refine procedures asappropriate – living the process

Include additional projects into governance approachand appoint stewards for new projects, provideneeded education and training at start and duringimplementation

Maintain governance approach until it is acrossenterprise – iterative refinement and implementation


Some Best Practices Clearly defined and communicated vision, objectives, processes, and metrics

of the Data Governance Program

Well defined, actionable roles and responsibilities for all data governanceroles

Functioning Data Governance Council with continued executive support

Sustained data stewardship teams and functioning data stewards and subjectmatter experts

Continued support for governance and stewardship from data / informationmanagement group (“support analysts”)

Continued data governance training and communication for all data stewards,custodians and business partners

Defined, approved and published data standards – communicated throughoutorganization

Managed and sustained metadata environment

Functioning internal Data Governance Community of Practice andparticipation in appropriate organizations (DAMA, DGPO, IAQDQ, etc.)

Data governance and stewardship socialized into the organization’s culture


Executive sponsors, or executive stewards, should be drawn from the businessexecutive side of the organization. They own the data – close to the source.

Establish enterprise data policies, standards, and processes, the most important points.

Leverage a basic Data Governance methodology/framework:

DAMA-DMBOK ©

Data Governance industry best practices and methods (e.g., DGPO, consultingmethodology, books, etc.) – continual development

Engage with business critical projects to utilize critical data governance practices.

Incorporate data governance practices and artifacts into SDLC and other enterpriseprocesses for continuous improvement.

Measure and monitor data governance metrics for business impact.

Provide business value early and continually, as prioritized by the business.

Pick and choose business areas of focus, concentrating on areas of strategic businesssignificance.

Perform continuous communication, socialization, and education efforts.

Achieving LEAN Data Governance Success


Conclusions


LEAN Applicability to Data Governance

LEAN concepts can be applied to any function Data governance is well-suited to be transformed

via adoption of LEAN principles Use of three principles can serve as foundation

for a LEAN data governance program Daily challenge Continuous improvement Going to the source

Reduction of wastes can lead to an effective andmore efficient use of data as an asset Data governance efficiency Data management effectiveness


LEAN data governance requires a conscious cultural change: To a unified acceptance and usage of data as the foundation of

information and knowledge

To acceptance and adherence to LEAN concepts and practices

Data governance requires that business units accept ownership oftheir data assets and understand they must manage data as anasset Data must be recognized as an asset at the business unit level and at

the enterprise level for data governance to be successful

Change is unsettling to all creatures - expectations and reactionsmust be anticipated, addressed and resolved - starting with seniormanagement through and across the organization

To be effective, cultural change must be managed in a spirit of co-operation and mutual accountability

Continuous process improvement and business ownershipincreases the value of data, aligned with the LEAN goal ofincreasing value across enterprise

Cultural Change Required


Questions



Contact Information


Anne Marie Smith, Ph.D.Principal Consultant andDirector of Education

EWSolutions, [email protected] (M)856-494-3722 (O)