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DATA GOVERNANCE – A PRIMERDr. Braden J. HoschAssociate Vice President for Institutional Research, Planning & EffectivenessNovember 3, 20191

OverviewData governance concepts and major aspectsSelling data governance to senior leadershipCharacteristics of a data governance systemMaturity modelsChange management in a college or universityTechnological “solutions”2

Outcomes for workshop participantsDefine data governanceas an activity that centerson human behavior morethan dataDescribe majorcomponents of datagovernance activitiesArticulate challenges ontheir campus and howdata governance willaddress these challengesAssess their campusculture and organizationwith a data governancematurity model; selectand modify a datagovernance maturitymodel for their campusIdentify characteristics ofa data governancesystem; analyze wheretheir own institution hasgaps; and create anoutline for how datagovernance could fit intoexisting organizationalstructuresDiscuss how technologymay assist but notperform datagovernance; describemajor functions of datagovernance softwareapplications or “solutions”Explain principles ofchange management inhigher educationinstitutions and how theywill enable developmentof data governance ontheir campusesConstruct an action planfor next steps on theirown campus to advancedata governanceactivities3

What this workshop will not do Design your data governance system for you Promote specific technological solutions Prescribe specific functions, operations, or organization Identify how much money to spend4

WHAT IS DATA GOVERNANCE?5

Data Governance Definitions (Generic) “the execution and enforcement of authority over the management ofdata and data-related assets” - R. Seiner (2014) “specification of decision rights and an accountability framework toensure appropriate behavior in the valuation, creation, storage, use,archiving and deletion of information” - Gartner IT Glossary “a system of decision rights and accountabilities for information-relatedprocesses, executed according to agreed-upon models which describe whocan take what actions with what information, and when, under whatcircumstances, using what methods” – Data Governance Institute (2014)6

Data Governance Definitions from Universities “formalizes behavior around how data are defined, produced, used,stored, and destroyed in order to enable and enhance organizationaleffectiveness” – Stony Brook University (2016) “adds value to our administrative and academic data systems by theestablishment of standards that that promote data integrity and enablesstrategic integrations of information systems” – Vanderbilt University “the discipline which provides all data management practices with thenecessary structure, strategy, and support needed to ensure that data aremanaged and used as a critical University asset” – U of Rochester7

The 5-second elevator definitionDatagovernanceis a set of guidelinesfor how peoplebehave and makedecisions about data8

Master data management is often confused with datagovernanceMaster Data Management (MDM)Data Governance Comprehensive method to linkall critical data to a commonpoint of reference Example: All screens, documents andsystems showing a student’saddress derive from a commonlocation. Formalized system for howpeople make decisions aboutacquisition, production, storage,distribution, and analysis of data Example: Group decides on a definitionfor home address and agreeson a common source field9

Important characteristics of DG definitionsData governance ISData Governance IS NOT More about people andbehavior than data IT’s responsibility Solved by technology Equally applied across alldata assets A system that requires andpromotes shared agreement Formal (i.e. written down) Adds value by supportinginstitutional mission/goals10

Activity 1 – What data governance features do you have? List formal and informal structures you have for promotingdata lesResponsibilities11

WHY DO WE NEED DATA GOVERNANCE?12

Data governance is a strategic priorityProliferationof data andapplicationsPrivacyexpectations/ regulationsCloud datamobilityFair andethical use13

Justifications for Data GovernanceJustify data governance on your campusbased on:Value CostRisk14

Justifications for Data Governance - ValueEDUCAUSE identifies significant institutional value tohigher education institutions from data governance: Official vs. ad hoc data definitionsClear responsibilitiesCapacity for analyticsCompetitive advantageEDUCAUSE (2015). “The compelling case for data governance,” retrieved October 15, 2018 fromhttps://library.educause.edu/ /media/files/library/2015/3/ewg1501-pdf.pdf15

Justifications for Data Governance – Cost (1)A third of Fortune 100organizations will experience“an information crisis, due totheir inability to effectivelyvalue, govern and trust theirenterprise information.”Gartner. (2014). “Why data governance matters to your online business,” retrieved August 1, 2016from ta-governance-matters-to-your-online-business/16

Justifications for Data Governance – Cost (2)Poor data qualitycosts the USeconomy 3.1trillion every year 3.1TrillionIBM. (n.d.). “Extracting business value from the 4 V's of big data,” retrieved October 1, 2018 acting-business-value-4-vs-big-data17

Justifications for Data Governance – Cost (3)The average financial impact of poor data qualityon a typical businesses is 9.7 million per year.Opportunity costs, loss of reputation and lowconfidence in data may push these costs higher.Forbes (2017). “Poor-quality data imposes costs and risks on businesses,” retrievedOctober 22, 2018 from ses-says-new-forbes-insights-report18

Justifications for Data Governance - RisksFines Imposed by Federal Student AidFiscal YearClery/Part 86 Imposed FinesIPEDS Imposed FinesOther Imposed FinesTotal Imposed Fines2010 42,000 225,000 48,653,500 48,920,5002011 195,000 144,500 4,868,500 5,208,0002012 212,500 158,500 624,000 995,0002013 812,000 56,000 5,204,137 6,072,1372014 438,000 111,250 6,750 556,0002015 500,000 39,250 14,130,000 14,669,2502016 307,500 57,000 79,462,500 79,827,0002017 2,542,500 1,500 382,500 2,926,5002018 988,250 67,500 20,000 1,075,750Source: Postsecondary Education Participants System (PEPS)19

Data as an Asset By 2020, Gartner predicts that 10% of organizations will have ahighly profitable business unit specifically for productizing andcommercializing their information assets. By 2021 companies will be valued on their informationportfolios: “Those in the business of valuing corporateinvestments, including equity analysts, will be compelled toconsider a company’s wealth of information in properly valuingthe company itself.”20

Data as an Asset for UniversitiesGeneric ExampleAt Colleges & Universitiesweb sites grant access in exchange forpersonal data (email address, etc.) –these data have value and can beleveraged or even soldData are purchasedNames of prospective studentsLibrary databasesVarious datasets (U.S. News,Academic Analytics, etc.)Data are soldTo vendors for discounts or servicesLost data carry costsData breaches21

Who owns the data? Consider carefully use of the word “ownership” with data Often represents assignment of responsibility Connotes individual control and property vs. caretaking of sharedresource Institutions own the data Individuals provide stewardship22

Activity 2 - Why do we need data governance? Identify institution-specific examples that help make the casefor data governance Value – what could you do that you can’t do now? Costs – what costs are you incurring because data are not wellgoverned? Risks – what risks are you taking because data are not well governed?23

FEATURES OF DATA GOVERNANCE24

Key features of data governance systemsDocumentsGroups Charter / framework Principles & values Purpose & scope Roles & responsibilities Senior leadership[buy-in] Written & published policies Data dictionaries Communication strategies Data steward council(s)Individual roles Data stewards Data custodians/ caretakers Policy council Data users Information securitycouncil/program Positions/office tosupport DG25

Principles and valuesEstablishing principles and values for datagovernance assists with:Initial focusNavigatingdifficultsituations26

Principles of Data Governance (Generic)Consistency of data in itssourcing and in itsvocabulary, definitions,and taxonomiesQuality which isproactively assessed andstandards appliedResponsibility andaccountability definedacross the data lifecycleand recorded in theinformation asset registerBusiness alignment whichensures that data isregarded and treated as akey business assetAccess to relevant users,kept secure throughaccess controlProviding trusted insightSource: Carruthers, C. & Jackson, P. (2018). The chief data officer’s playbook, London: Facet, p. 14527

Principles and Values – ExampleUniversity of Wisconsin - MadisonAccountabilityDetermining who is responsible for the management of data at UW Madison as well asholding them to our outlined standards.AgilityAll of our processes should adapt when necessaryChange ManagementNew processes demand new and changing staff at UW. We’re committed to ensuringsmooth transitions and well informed decisions.ConsistencyAll decisions made will be applied consistently across campus.Metrics DrivenWe monitor ourselves against measurable goals on a regular basis and use the resultsto determine courses of action.StewardshipDetermine formal roles for those in charge of data. This does not mean that everyone oncampus is not responsible despite formal roles.TransparencyWe will make it clear how and when decisions are made and when processes arecreated. We also strive to ensure that decisions and processes are audited to supportcompliance based requirements.Source: 8

Principles and Values – ExampleStony Brook UniversityValuesShared AssetsStewardshipQualityData and informationare sharedorganizationalresources thatconstitute valuableassets.Employees of Stony Brook Universityhave a responsibility for the curationof data. They serve as caretakers ofdata to ensure data are collected,stored, and maintained under thepremise that others will access anduse them over timeTo ensure dataretain value,quality of datais activelymonitored andmaintainedPrivacy &ConfidentialityMaintenance of individualprivacy and confidentiality ofeducational and personalrecords represent not onlylegal requirements but alsoprimary outcomes of datamanagement.Principles for Data abilityStandardsSource: https://www.stonybrook.edu/commcms/irpe/about/ files/DataGovFramework.pdf29

Principles and Values – ExampleMesa Community CollegeAccessibility Users have roleappropriate access todata needed to makeinformed decisions. Data is available acrossplatforms, on-site andremotely.IntegritySecurityEthics Data should becollected andmaintained withreasonable assurancesof its consistency,reliability, timelinessand accuracy. Individuals shareresponsibility and areaccountable for theirentry, use and access ofthe College’s datarepository, requiringongoing training on thepart of those who enter,use, and care for it. Sensitive data isprotected fromunauthorized accessand improperdisclosure. The integrity of data isprotected frommalicious or accidentalalteration. Data is available withaccess grantedaccording to the role ofthe user. Processes are in placeto ensure training andawareness. Data is used inaccordance with ethicalprinciples, acceptedbest practices, and legalrequirements. Data is used to improvepractices and furtherthe College mission.Source: vernance/introduction-data-governance-brown30

Connect Data Governance to Mission Data governance is a system to improve the effectiveness of theorganization, not an activity for its own sake Anchor data governance to mission when justifying need orpresenting structure31