“EMPIRICAL MODEL of DATA GOVERNANCEin EDUCATIONAL INSTITUTE”

Ms. Sunita Bangal #1 , Ms. Sumangala Dandavatimath *2

#Indira Institute of Management (MCA), Pune, India

* Indira Institute of Management (MCA), Pune, India1. sunitabangal06@gmail.com# 2. sumadmath@gmail.com*

Abstract :- In this knowledge economy “Data andInformation” is vital components of any organization. It isindeed an integral part of any organization. But study saysthat because of poor understanding [2] of necessity of data interms of quality, availability, security, consistency & privacythe enterprises are loosing winning advantage. To achievecorporate intelligence which is need of coming eraorganizations must be very strong in field of “DataGovernance” or “DG “. Data Governance field which wouldcertainly the area where different pillars in database domainare addressed. Fields like Master data management, Datamining, Data security, Business intelligence etc. are majoraspects and handled in this process of governance. Peoplemust be involved and certain privileges should be given so asto improve performance of organizations at large. In thisstudy model is suggested for Educational Institutes so as toimplement data governance practices and Institute can mapIndustry expectation.

Keywords— Data Governance, Corporate Intelligence, DataStewards,

(I) DATA GOVERNANCE

Since Data Governance is emerging conceptmost of the people are not acquainted with it. Solet us understand what is DG or DataGovernance in brief in simple terms. Then wewill look at corporate intelligence. Datagovernance is an emerging discipline with anevolving definition. The discipline embodies aconvergence of data quality, data management,business process management, and riskmanagement surrounding the handling of data inan organization. Through data governance,organizations are looking to exercise positivecontrol over the processes and methods used bytheir data stewards to handle data.” [1]

Data governance is indeed very new toindustry and it is defined as per need andfunctionality of institute. It is cross functional innature. It requires technology as well as businesspeople to formulate policies and procedure ofgovernance along with IT systems.

Following is the definition that covers almost allthe components and goals of data governance:

“Data governance (DG) is usuallymanifested as an executive-level data governanceboard, committee, or other organizationalstructure that creates and enforces policies andprocedures for the business use and technicalmanagement of data across the entireorganization. Common goals of data governanceare to improve data’s quality; remediate itsinconsistencies; share it broadly; leverage itsaggregate for competitive advantage; managechange relative to data usage; and comply withinternal and external regulations and standardsfor data usage. In a nutshell, data governance isan organizational structure that oversees thebroad use and usability of data as an enterpriseasset.”[2]

In accordance with the definition DG isnothing but controlling of data usage, dataintegration, and data filtering at different levels.It defines content and structure of data.

The survey made by IBM organizationunderstand that data governance is crucial and itmust be focused & so became emerging trend.Survey done by IBM of 50+ Global 5000 Sizebusinesses regarding their investments in “datagovernance” and the challenges they arefacing.[3]

I. 84% believe that poor data governancecan cause: limited user acceptance,lower productivity, reduced businessdecision accuracy, and higher total costof ownership

II. Only 27% have centralized dataownership

III. Fully 66% have not documented orcommunicated their program, and

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IV. 50% have no KPIs or measurements ofsuccess

Data governance cater to software tools likeMetadata management, Master data management,Data quality etc. (Fig. 1)In other terms these are the disciplines which areemerging along with DG.

[2]

Fig 1 DG and various emerging disciplines.

(II) DATA GOVERNANCE PRACTICES &CORPORATE INTELLIGENCE

Intelligence is an umbrella term used to describea property of the mind that encompasses manyrelated abilities, such as the capacities to reason,to plan, to solve problems, to think abstractly, tocomprehend ideas, to use language, and to learn.[7]

The definition is so apt which any personcould experience it in day to day life. In the eraof globalization organizations are highlycompetitive and world is changing so fast thatone should understand need of overallintelligence in corporate life (both individual aswell as organizational).

Now let us understand what corporateintelligence is.“Corporate Intelligence be the overall umbrellato advise on global, national and localenvironments, political and legislativeatmospheres, and competitive forces thatinfluence the marketplace, and the sales of thecompanies products or services. “ [4]

Let us study the examples of CI (CorporateIntelligence) which is emerging in thegovernment as well as industry.

KPMG Forensic Company is a leadingprovider of professional services including audit,

tax, financial and risk advisory. The CorporateIntelligence team of KPMG gathers business-critical information to help companies reducerisk, enter new markets, solve corporateproblems and enhance business opportunities.[5]

Companies are dependent onconsultancies for strategic decisions and theythemselves don’t understand or rather giveimportance to their own strengths andweaknesses.

In India also government and relatedsectors are prone to use consultancy services incase of planning and taking strategic decision.For example Lancers is India's leading RiskConsulting Corporation has it’s corporateintelligence services which anticipates pre jointventure due diligence, vendor verifications,political analysis, geo location risk analysis,SWOT analysis of the market and competitor’sprospects, etc to users. [6] By looking at surveys[8] Technology and manufacturing industriesappeared in the middle of the pack, as far asmanagement commitment, budget allocation, andage and maturity of their corporate intelligenceprograms. by Fuld & Company Inc. Fuld &Company Inc. (www.fuld.com) is the world'spreeminent research and consulting firm in thefield of business and competitive intelligence. Ithas offices in Cambridge, MA, and London.

Survey done by society of corporateprofessionals’ state that 25 % of the hundreds oflargest corporate says that the spending oncorporate intelligence is about 14% of totalcompany spending of $500,000 [9]

Society of Competitive IntelligenceProfessionals (SCIP) says that CI is continuousprocess which involves ethical as well as legalinformation collection, monitoring and analysisof it. It enables senior management to takeinformed decision about marketing, research,investment tactics and development to long termstrategies.

To achieve the freedom in case of passingintelligence at all levels in the organization,company must understand that CI should not berestricted to upper management level. The era isfrom dictatorial to empowerment people from allthe levels must be involved so with properamalgamation and congruent environment willlet company get winning advantage.

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The examples of corporate intelligenceare endless. By looking at world’s companies’performance it is indeed identified that CI isdefinitely emerging but it is mostly ignored.Why it is ignored? One of the reasons might beit’s cost. Most of the applications of CI revolvearound IT (Information Technology). IT is oneof the costliest industries since it depends uponknowledge workers and there is lacuna in case ofdevelopment of knowledge workers. Estimatesays that Industry needs / demands more ITprofessionals but the professionals developed arevery less as workable product hence cost.

To have winning advantage companymust model the policy which will leads tocorporate intelligence by involving all thepersonnel according to the need of functionalityand need based study.

Also in the survey “Corporate DataGovernance Best Practices” conducted by IBMtalks about business drivers for DG and we canobserve influence of those parameters throughFig 2.

The parameters are certainly essential forcorporate intelligence. IBM suggested hierarchywhich is shown in

Fig 2 [3]

The above parameters are certainly essential forcorporate intelligence. IBM suggested hierarchywhich is shown in Fig 3

Fig 3[3]

Certainly above bodies are very much importantin case of Corporate Intelligence. So we can getthe inference that good data governance practicewill lead to smooth functioning of companiespolicies and it will add to corporate intelligence

Corporate Intelligence is equallyimportant in educational institutes.To understand this we need to first we will lookat the current scenario.

(III) EDUCATIONAL INSTITUTESSCENARIO

There are no formal Data Governancepractices adopted by Education Institutes.Institutes in higher education always strive hardfor improvement in quality of the students, inturn quality of Institute. For this, institutesconduct surveys which identify need of theindustry. Also by observing market scenariocertain quality input is given. Institutes usesexpertise of corporate or individual experience ofhigher management lead to identification ofgrooming input. Institute also maintainstransactional data on ad-hoc basis. There aremany trials happen which lead to qualityenhancement up to certain extend.

The shortfall of such practices is Instituteshardly observe data at operational level, andsuccess of the input. Also availability and dataaccess i.e. governance of data is lacking. Atoperational level data stewards keeps onchanging and hence every new data steward needtime to understand system which is implementedand followed. Management of Institute is alsolearns from different trials and new systems.Hence there is no formal data governance.Management hardly understands need andimportance of data. It do not maintains itssecurity and it proper utilization. Data is notproperly collected ,organized and utilized.

(IV) PROBLEMS FACED at VARIOUSLEVELS

There is lack of knowledge about dataavailability among Personnel. They have nounderstanding about importance and relevance ofdata. Lots of data is generated unnecessarily.People adopt adhoc data processing and hence

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data duplication. This leads to confusion forutilization of data. User does not guarantee ofauthentic information for decision making. Datamay not be reliable if not maintained properly.Every data steward maintains data as per hisunderstanding, formats, and requirements. Hemay not be able to accommodate all dimensionsneeded in future. Data may not be timelyavailable if there is more turnover.

(V) RELEVANCE of DATA GOVERNANCE

The need for governance exists anytime a groupof people comes together to accomplish an end.When it comes to the centre of excellence (COE),the only thing simple about governance is theimperative that it exists. Without governance, theCOE can become aimless and ineffective. Withgovernance, the COE can establish authority, canbe positioned to efficiently and effectively carryout its mandate, and can facilitate a collaborativeenvironment. Governance will allow the COE tohelp the organization reap the benefits from itsdata assets, minimize total cost of ownership [10]

If shortfall of educational institutes would beremoved by formal technical method thencertainly institute will get need based relevant,reliable, authentic and timely data.This study will lead to introduce formal DGmodel. Objectives behind this study and modelare:[11]

a. To achieve clarityb. Ensure value from effortsc. Create clear missiond. Maintain scope and focuse. Establish accountabilitiesf. Better decision making.g. Reduce operational frictionh. Protect needs of data stakeholdersi. Build standard and repeatable processj. Reduce costs and increase effectiveness

through coordination of effortsk. Ensure transparency of process

Study includes following components:i. Process

ii. Framework for DGiii. Conduct of DGiv. Stakeholders

1. Process: DG formation decides about devisingnew policies, rules & regulations. Also it formsand organizes components. It decides Norms forreview, follow up of data governance. For settingup the rules and policies DG must mainly focuson standards, Data quality, privacy, security andintegration of data. Make decision makingmeasures and control polices depending on theearlier outcome or success rate. This also decidesabout metrics and measuring techniques. Thesetechniques would be refined based on thefeedback from DG conduct. Mission and Visionare not a part of formation process they aredecided by the organizing body and followed inDG.2. Framework for DG: Data governanceframework is a logical structure for classifying,organizing, and communicating complexactivities involved in making decisions about andtaking action on data. Following additionalcomponents apart from those already defined inprocess could be observed in Fig 4.

i. Data Steward: Data stewards cometogether and make decisions about data,policies, and rules of governance of data.They may craft recommendations forhigher level management.

ii. Stakeholders: All direct and indirecthuman resources involved in DGconduct are called stakeholders

iii. Execution of DG: DG conductimplements process and framework, alsoit executes as per norms defined.

iv. Decision making: Based on data accessedas per governance, rules, accessibility ofdata, decision making will take place.This could be at top level, middle level aswell as operational level.

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v. Advantage of right decision making atright time will lead to corporateintelligence.

(VI) CONDUCT of DG

Data Governance is the activity whichgives quality, timely, correct data also itmaintains integrity of data.

While implementing data organizationalcommittee adhere to mission & vision oforganization. They should have their ownmission & vision for data governance. Based onDG mission vision, rules, regulations will beformulated. Once all policy matters are discussedwith consent of all others committee members,they must get approval of final authority.Committee must understand hierarchy ororganization chart. In context with DG,committee must identify different componentsand their organization. After this organizationchart they must identify data stewards’. This willgive understanding about data stewards’ workprofile, accountability, permissions & rights.Data stewards may be divided into separatedepartment or units.

Conduct of DG includes reviews, followups and brain storming meetings. These will helpcommittee members to take certain strategicdecision. In this component, data stewardsprepare road maps, they design programs, applythese in case of governance of data. Datastewards monitors and measure all activitiesagainst norms set. Feedback is given forenhancement, refinement of policy matters.

(VII) ACADEMIC ENHANCEMENT

Data governance practices will certainly resultinto academic enhancement. Since operationallevel data which is following all parameters ofquality will be maintained and monitored by datastewards.Formats of data are predefined and defined/redefined by consent of all other data stewards /committee members and approval is taken fromconcern authority. Later this data will bemaintained by all concern operators / datastewards at central repository. This repositorywill be accessible by other with proper privileges.

Newer versions should be maintained accordingto year / batch, semesters, different domains anddisciplines. Newer formats will be refined ifnecessary and made available in standardtemplate.

(VIII) CORPORATE / INDUSTRYCOLLABORATION

To bridge the gap between academicindustries collaboration is the tool for whichdifferent stakeholders’ role is very crucial. Someof them are corporate, alumni and academicexperts / consultants. Data / informationextracted from them could be paramountimportance.

Like Corporate feedback about studentsregarding competencies, skills, attitude willresult in identification personality groomingrequirements. This data is short term and must bemaintained from time to time as per industryrequirements. For this some data stewards mustbe allotted for such data collection, compilation.After collection of data DS must organize it andthey should give feedback so as to take decisionabout personality grooming programs / contents.Same process could be applicable for technicalinputs required as per industry requirements.

Alumni feedback / interaction programswith students can help to change their mindset.Alumni feedback is crucial at micro leveloperations in educational institutes. This will letfaculties understand comprehensive trainingrequired. Also students get insight of corporateworld, need , work culture. Alumni related datais historic data and need to be maintainedperiodically.

Academic experts / consultants areidentified for upcoming trends, latesttechnologies so as to keep students competent tooutside world. Updated data is very muchnecessary for approaching such experts.

Regulatory bodies should includerenowned personalities from major relevantsectors. Such bodies meet regularly and makestrategic decisions. These decisions must befollowed in DG.

Staff of the organization must maintaindata regarding student background, continuousprogress, impact of training / workshop on

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overall development of each student. Such datais also timely; it must be maintained on regularbasis as per defined format. Newer formatsneeded for more analysis is defined by datastewards. All other must adhere to it.

All these stakeholders play veryimportant role in data collection, formation andanalysis. All their activities will result in strongrepository. This repository need to be updatedregularly. Data must be timely, correct andauthentic. Such practices will help in long runsuccess. Decision making will be smooth andcorrect. This is nothing but corporate intelligence.

( IX) CONCLUSION

If Privileges and rights are freely flowingthrough organization and proper comprehensivedata governance practices present among thegroups mentioned above will lead to centre ofexcellence in the organization. Which certainlyallow personnel to understand their roles Basedon data (available), information generatedthrough DG they can apply their intelligence andexperience. This could lead to competitiveadvantage for institute.

Through this institute can learn, experience,share, evolve and expertise in their own field.But since this field is emerging corporate worldand professionals should not ignore it.Involvement of personnel and some research onpolicies and practices will drive understandingabout data governance field and certainlyinstitute can take advantage of it.

REFERENCES

[1] http://en.wikipedia.org/wiki/Data_governance[2] TDWI best practices Report second quarter 2008 By Philip

Russom, Data Governance strategies, Helping yourOrganization Comply, Transform, and Integrate www.tdwi.

[3] Corporate Data Governance Best Practices 2006-07Scorecards for Data Governance in the Global 5000 A CDIInstitute MarketPulse™ In-Depth Report April 2006

[4] Article by Corporate Intelligence By Alan J Simpsonhttp://www.comlinks.com/pol/ci2.htm

[5] KPMG Forensic UK (KPMG in the UK is a leadingprovider of professional services),http://www.kpmg.co.uk/about/index.cfm

[6] Lancers is India's leading Risk Consulting Corporationhttp://www.lancerindia.com/index.htm

[7] Intelligence - From Wikipedia, the free encyclopediahttp://en.wikipedia.org/wiki/Intelligence

[8] “In Corporate Intelligence Programs, PharmaceuticalIndustry Scores Highest, Financial Services and LegalLowest -- First-Ever Global Benchmark Study by

Fuld & Company Inc.” http://www.marketwire.com/press-release/Fuld-and-Co-727921.html

[9] Book on A short course in international business ethics-By Charles Mitchell, Jeffrey E. Curry (Page 123.) [10].Governance: The Superglue of the Center of Excellence,Intelligent Solutions, ( Information Management Magazine,December 1, 2008 )

[11] http://www.datagovernance.com/fwk_dgi_data_governance_framework_components.html

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