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Data Governance Part II: Maturity Models – a Path to Progress

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Data Governance Part II: Maturity Models – a Path to Progress NASCIO: Representing Chief Information Officers of the States Data Governance Part II: Maturity Models – A Path to Progress Introduction When government can respond effectively and expeditiously to its constituents, it In the previous report on Data Governance1 gains credibility with citizens. The an overview of data governance was opposite is also true. When government presented describing the foundational can’t respond, or responds incorrectly, or issues that drive the necessity for state too slowly, based on inaccurate informa- government to pursue a deliberate effort tion, or a lack of data consistency across for managing its key information assets. agencies, government’s credibility suffers. Data governance or governance of data, information and knowledge assets resides This research brief will present a number within the greater umbrella of enterprise of data governance maturity models2 architecture and must be an enterprise- which have been developed by widely wide program.There is a significant cost to recognized thought leaders. These models March 2009 state government when data and informa- provide a foundational reference for tion are not properly managed. In an understanding data governance and for NASCIO Staff Contact: emergency situation, conflicts in informa- understanding the journey that must be Eric Sweden anticipated and planned for achieving Enterprise Architect tion can jeopardize the lives of citizens, [email protected] first responders, law enforcement officers, effective governance of data, information fire fighters, and medical personnel. and knowledge assets. This report contin- ues to build on the concepts presented in Redundant sources for data can lead to Data Governance Part I. It presents a conflicting data which can lead to ineffec- portfolio of data governance maturity tive decision making and costly models. Future publications will present investigative research. If data from differ- other important elements that comprise a ent sources conflicts, then the decision full data governance initiative. These other maker must research and analyze the elements include frameworks, organiza- NASCIO represents state chief various data and the sources for that data tion, delivery processes, and tools. information officers and infor- mation technology executives to determine or approximate what is true and managers from state and accurate. That exercise burns time Maturity models provide a means for governments across the United and resources. Accurate, complete, timely, seeing “what are we getting into?” The States. For more information visit www.nascio.org. secure, quality information will empower higher levels of maturity present a vision decision makers to be more effective and or future state toward which state govern- Copyright © 2009 NASCIO ment aspires and corresponds to not only All rights reserved expeditious. More effective decision making leads to higher levels of enterprise a mature data governance discipline, but 201 East Main Street, Suite 1405 also describe a mature enterprise architec- Lexington, KY 40507 performance. The ultimate outcome is Phone: (859) 514-9153 better service to citizens at a lower cost. ture discipline.The case has already been Fax: (859) 514-9166 Email: [email protected] Data Governance Part II: Maturity Models – A Path to Progress NASCIO: Representing Chief Information Officers of the States made in Data Governance Part I that state the State CIO” for further discussion of government will never be able to effec- organizational change management.3 tively respond to citizens without properly governing its information and knowledge The growing importance of properly assets. managing information and knowledge assets is demonstrated by a number of In early 2009, the states are under severe predictions regarding data and data economic stress—major revenue short- governance by the IBM Data Governance falls, growing deficits and reduced public Council.4 spending. State governments expect continued expenditure pressures from a variety of sources including Medicaid, IBM Data Governance Council employee pensions and infrastructure. Experts predict even more economic Predictions troubles for the states in fiscal year 2010 Data governance will become a regula- and beyond. A key ingredient for estab- tory requirement. lishing strategies for dealing with Information assets will be treated as an continuing fiscal crisis is the ability to asset and included on the balance sheet. effectively harvest existing knowledge Risk calculations will become more bases. Those knowledge bases must pervasive and automated. provide reliable, up to date information in The role of the CIO will include responsi- order to enable judgment, discernment bility for data quality. and intuition. These comprise what might Individual employees will be required to be termed wisdom. Even with perfect take responsibility for governance. information, wisdom is still required to make the right decisions and to execute on those decisions. State leaders will be As described in the previous issue brief on forced to make tough decisions in the this subject the delivery process must months ahead, certainly requiring wisdom. begin with an understanding of what the This research brief will focus on that first end result will look like, and what value a key ingredient—knowledge. So, state data governance initiative will deliver to government must make the commitment state government. Value is defined by to begin now to manage and govern its executive leadership and depends on the information and knowledge assets. vision, mission, goals and objectives Maturity models assist in helping state executive leadership has established for government prepare for the journey and the state government enterprise. The that is what this report is intended to value delivery process must also provide present. Governance will not happen methods and procedures for monitoring overnight—it will take sustained effort how well state government is currently and commitment from the entire enterprise. performing and the incremental steps for reaching the desired level of performance. As state government moves up the maturi- ty curve presented by these models, there The process for establishing and sustain- will be technological and business process ing an effective data governance program ramifications. However, nothing will will require employing the following compare to the organizational fallout. It enablers: will take commitment and leadership from executive management to bring the enter- Strategic Intent: describes WHY data prise along in a way so that it will be a governance is of value, the end state positive experience for government that government is trying to reach, and employees and citizens. See NASCIO’s the foundational policies that describe publication “Transforming Government the motivation of executive leadership. through Change Management: The Role of This strategic intent should be described in the enterprise business 2 Data Governance Part II: Maturity Models – A Path to Progress NASCIO: Representing Chief Information Officers of the States architecture. If state government does framework for data governance will co- not have quality data and information, exist with other frameworks that it will not achieve its objectives. describe other major components of Flawed data and information will lead the state government enterprise archi- to flawed decisions and poor service tecture. delivery to citizens. Methodology for Navigating the Data Governance Maturity Model: Framework: describes the methods describes the journey from the AS IS to and procedures for HOW to navigate the SHOULD BE regarding the manage- through the framework, create the ment of data, information and artifacts that describe the enterprise, knowledge assets. In parallel to this and sustain the effort over time. This journey regarding data governance is methodology will co-exist within the the journey that describes a maturing enterprise architecture methodology enterprise architecture operating disci- and touch on business architecture, pline. State government must process architecture, data architecture, understand where it is today and organizational governance, data / where it needs to go. This is an impor- knowledge management processes, tant step in planning the journey in and records management processes. managing information as an enterprise asset. Data governance maturity Performance Metrics: to measure and models provide the means for gauging evaluate progress and efficacy of the progress. By presenting intermediate initiative. These are traceable back to milestones as well as the desired end strategic intent and related maturity state, maturity models assist in models. These metrics need to be planning HOW state government will continually evaluated for relevancy. reach the next level of effectiveness, as Valuation and Security of State well as WHEN and WHERE within state Government Information Assets. As government. presented in the previous issue brief on data governance, proper valuation of Organizational Models, Roles and Responsibility Matrices (RASIC data and information will determine the level of investment to ensure quality and Charts)5: defines WHO should be involved in decision making, imple- appropriate security throughout the menting, monitoring and sustaining. information asset lifecycle. This is where Organizational models are a compo- the data architecture and security archi- nent of the enterprise business tecture domains
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