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Governing a data-driven organization (4/24/2014)

Governing a data-driven organization (4/24/2014). Define governance within organizations. Understand the general activities of governance. Define relative levels of governance “maturity”. Identify key aspects of data governance Discuss how an organization governs data.

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Governing a data-driven organization (4/24/2014)

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  1. Governing a data-driven organization (4/24/2014) • Define governance within organizations. • Understand the general activities of governance. • Define relative levels of governance “maturity”. • Identify key aspects of data governance • Discuss how an organization governs data.

  2. Data-driven decision making is relative • Organizations are in various stages of using data to support organizational decision making. • Spans from standard accounting reports to competing on analytics. • Organizations vary in data availability. • Internal silos to integrated data. • Internal only to integrated external and internal. • Organizations vary in data understanding. • We have data??? to Data is an asset. • Organizations vary in analytical capability.

  3. What does it mean “to govern”? • gov·ern v.gov·erned, gov·ern·ing, gov·erns • To make and administer public policy and affairs • To exercise sovereign authority • To control the speed or magnitude • To regulate • To control actions or behavior • To keep under control;to restrain • To exercise a deciding or determining influence • To exercise political authority • To have or exercise a determining influence

  4. Corporate Governance IT Governance Data Governance

  5. Governance Activities • What are the key activities in corporate governance? • What are the key activities in IT governance?

  6. Governance Artifacts Standards A standard sets a requirement and/or creates a baseline Policy Policy defines “what” the organization must do or not do. They are the principles/rules of an organization. Drives Guidelines A guideline describes a preferred approach with practical directions. What do we need policies about? What is the goal of a given policy? What level of standards are necessary? How detailed should a standard be? What guidelines would be helpful?

  7. IT Governance Project Short term goals People Staff skills Process Ongoing work Facilities Network, servers Technology DBMS, multimedia Applications ERP, app software Data Internal, external, structured, unstructured, purchased, free

  8. IT Governance Frameworks • Information Technology Infrastructure Library (ITIL) • Control Objectives for Information and Related Technology (COBIT). • Commonalities: • Align IT objectives with business goals. • Provide list of general processes that must be accomplished by IT organizations. • Provide metrics to evaluate efficacy of processes. • Use maturity models to evaluate relative formality of processes.

  9. Evaluating governance based on maturity level • “Maturity” evaluates the degree of formality and optimization of a policy/standard/guideline structure. • A maturity model: • Defines high and low levels of maturity. • Categorizes degree of maturity based on key characteristics. • Describes steps that move an organization from one level of maturity to another.

  10. Why use a maturity model? Maturity Model • Assessment • Describe the overall environment. • Evaluate current state of capabilities. • Consistently compare evaluations over time. • Compare organization to other organizations. • Improvement • Define and create a path for progression. • Direct the potential next steps. • Target priorities and resources necessary for action.

  11. Capability Maturity Model Integration (Carnegie Mellon Software Engineering Institute)

  12. What are the key aspects of data governance? • Protect and Control: • Improve data quality. • Protect and safeguard data. • Assign ownership. • Understand the value of data and impact of loss. • Control change. • Make Useful : • Define data across the organization. • Integrate data from a variety of different sources. • Ensure data availability. • Enhance data accessibility. • Adapt and Change: • Encourage data use. • Facilitate ongoing data evolution and acquisition.

  13. How to govern data? • Governance artifacts: Policies, standards, guidelines. • IT is all about the people. Organizational structure issues: • Who is responsible for data governance? • Who will establish the policies, standards, guidelines? • Who will encourage the policies, standards, guidelines? • Who will enforce the policies, standards, guidelines? • How should data be managed across the enterprise? • Should “protect and control”, “make useful”, “adapt and change” activities be handled separately?

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