The Role Of Politics In Data Governance

By Anne Smith

As the United States (USA) selects a new president and chooses from candidates for other offices, many thoughts may turn to the role of politics in data governance.

Politics is the process by which groups of people make decisions. Generally, the term is applied to behavior within civil governments, but politics has been observed in all human group interactions, including corporate, academic and religious institutions.  Politics consists of “social relations involving authority or power” and refers to the regulation of a political unit, and to the methods and tactics used to formulate policy and influence behaviors.

The connotation of the word “politics” has become negative, especially where it concerns activities in corporations or other non-governmental entities, but politics is not inherently negative; mis-application of political skills gives that unsavory flavor.  Data governance is a function performed by people in a group to provide order for the use of data and information across internal organizational boundaries.   Whenever a business activity crosses an organizational fence (functional area, division, etc.) there will be political issues, and all organizations are “political”.  It is best to recognize this fact and address the need to understand and manage the political nature of each organization.  Conflict is inevitable, but good politics allows for the healthy resolution of conflict and the continued development of a functional organization.

In exploring the political landscape of an organization, some points to consider and document may include:

  • What is the current organizational arrangement?  Know the levels on the organizational chart and how each interacts (collaboratively, authoritatively, decentralized, etc.).  Is the organization fragmented and is each portion operating independently for the capture and use of data and information?  How do the leaders at each level interact (up, down, across)?  What are their attitudes toward each other and how are those attitudes affecting the organization?  How are decisions made, communicated and enforced?
  • Is there social synergy in the organization? Are things arranged so that individuals and groups add to (rather than subtract from) the long-term evolutionary potential of the organization?
  • How can the governance organization be arranged to support and maintain the charter, sense and values of data governance?
  • How can the communities in the organization increase collective intelligence?  Reflect on the historical collection and use of data; problems and opportunities to be explored for improved data definition and cross-organizational usage; and develop methods to learn from its experiences to create appropriate activities and relationships with data and information throughout the organization.
  • How can the organization’s governance system maintain an evolving, coherent approach to data management, rather than drifting into social incoherence (misnamed “anarchy”) or into some rigid and dysfunctional status quo?
  • What feedback systems are missing, blocked or dysfunctional which, if present in healthy forms, would allow the organization to regulate data management consistently? (Examples of social feedback systems: success criteria, economic indicators, accurate information about organizational conditions, institutionalized collective self-reflection, acquisition of externally generated perspectives, etc.)
  • Is the governance system capable of generating and revising shared vision and culture as the need arises?   If not, why not and what can be done to correct this “bad political climate”?
  • What is the quantity and quality of organizational dialogue? Are all relevant viewpoints and stakeholders involved and is dialogue conducted in the spirit of contribution? (Dialogue is defined as multi-directional communication to enhance shared understanding — as contrasted with debate [communication to win], and all forms of one-way communication.)

Thanks to Tom Atlee, “Thinking Holistically Beyond Politics and Governance”.

There are three critical components to the political view of data governance: objective high quality analysis, publicly visible forums for the management of the data governance and stewardship functions, and organizational engagement about data issues.  Each contributes to the application of “good” politics to influence the acceptance and practice of data governance, and the absence of any of these components can cause the demise of a governance effort.

Good, healthy politics exist and can contribute to successful data governance and data management.  Attributes of healthy politics for data governance are deft and engaging leadership from the Governance Council and leading data stewards, appropriate management of the line / business area stewards’ responsibilities and challenges, coordination of cross-functional data issues, active information sharing and encouragement of all management to participate in information sharing, principled use of internal social networks to accomplish the goals of data governance, continued and objective evaluation of the successes and failures of the data governance program.

Someone once said that “Politics is the art of the possible” and data governance needs healthy politics to achieve its mission of managing the availability, usability, integrity, and security of the organization’s data


About the Author

Anne Marie Smith is a leading consultant in Information Management and is a frequent contributor to various IS publications. Anne Marie has over 20 years experience in information management for several corporate entities and has successfully led the development of data resource management departments within corporations and consulting organizations. Anne Marie is active in the local chapter of DAMA and serves on the board of directors of DAMA International, and is an advisor to the DM Forum. She has been an instructor of Management Information Systems (MIS) with Philadelphia, PA area colleges and universities. Anne Marie has taught topics such as: data stewardship and governance, data warehousing, business requirements gathering and analysis, metadata management and metadata strategy, information systems and data warehouse project management. Anne Marie’s areas of consulting expertise include metadata management including data stewardship and governance, information systems planning, systems analysis and design, project management, data warehouse systems assessment and development, information systems process improvement and information resource management/data resource management. Anne Marie holds the degrees Bachelor of Arts and a Master's of Business Administration in Management Information Systems from La Salle University; she has earned a PhD in MIS at Northcentral University. She is a certified logical data and process modeler and holds project management certification. Anne Marie can be reached at [email protected]

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