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Reasons for Data Governance Program Failure

Reasons for Data Governance Program Failure

Many data governance programs fail for a variety of reasons, most of them are able to be corrected.  Review this list and ensure that your organization is avoiding these issues / challenges.

In reading many articles about the various data governance initiatives that have been started by organizations of all sizes and across all industries, one may sense that all such programs are immediately effective.  Unfortunately, this is not the case, as Gartner predicts that less than 10% of initial data governance programs succeed (Gartner, 2008 and later).  The reasons for these failures are as varied as the programs they represent, but there are some themes that can be identified to serve as warnings for new or existing programs.

Some Main Reasons for Data Governance Program Failure

 Cultural barriers: In many organizations, a culture of ignoring data issues has arisen, combined with the siloed approach to data acquisition and management.  These two aspects can create barriers to forming and sustaining a data governance program, since the organization must recognize that data quality issues will not be solved miraculously, nor will the brick walls between organizational sections disappear overnight.  Additional cultural barriers can include the reluctance of business management to accept ownership for their data by expecting the information technology department to solve all data management problems independently.  Socializing the program within the culture is an important aspect of a successful program.

Lack of sustained senior business sponsorship: Much has been written about the need for executive sponsorship for all enterprise initiatives.  However, the key to success is the sustainment of the sponsorship, which gives the organization a chance to recognize the permanent nature of a program such as data governance.  Initial sponsorship is essential, of course, but the sponsorship must be sustained through management / role changes to be truly effective.  Maintaining the executive support can involve periodic briefing on the program’s successes (see below for “Metrics”) and challenges, requesting executive assistance in removing cultural barriers where possible, and demonstrating the need for a broad and deep consensus for data improvement.

Lack of demonstrated success, small as well as large: Many programs are built with the view of “big results only, please”.  This is a key to program failure.  Just as Rome was not built in a day, a successful and sustained data governance program will not have major success quickly.  Waiting for the “big results” can doom a program, since these results may not occur quickly enough to satisfy management and recalcitrant departments.  Demonstrate any data management / data integration / data quality successes, no matter how small or contained.  Periodic, continual small successes can become larger victories when the program has developed traction and scope.  It is important to develop and maintain momentum for permanent initiatives.

Grandiose expectations: An organization cannot be transformed overnight, especially in a labor-intensive program such as data governance.  Expecting the change from no program to an enterprise-wide program in a few months is unrealistic.  Many organizations assume that the program will be comprehensive quickly.  However, research has shown that many successful data governance programs required 3+ years before demonstrating enterprise-level results.  Patience is necessary.

Underestimating the amount of work to be done: Planning, scoping and executing a data governance program are a challenging effort.  It can be done in stages, but some foundational planning and development is necessary to ensure that the actual work to be done is done properly.  Diving in to address data quality or data integration issues without a plan for execution and communication – and not identifying the right people for the work (data stewards) – is a recipe for failure.  Take the time to plan the program’s scope and objectives, identify the correct set of initial data stewards and define their activities at the start.

Planning too much, not doing the work: The tendency to simply “work” and not plan in some organizations is countered by the reverse tendency to plan and strategize and discuss without actually doing the work.  Just as insufficient planning and structure is a bad approach, so is the “planning paralysis” that can occur when organizations focus on complicated procedures, documentation and discussions without a goal to use them in the real work of governance and stewardship.

Lack of sustained line / business commitment: Without the continued active involvement of many business people (governance council and data stewards) the program will die.  Business people are the heart of a data governance program, and their daily commitment to the program’s goals and its regular activities is essential.

No metrics: To demonstrate success, to show value, to garner continued support from executives and staff, it is essential to know what is important, what are the measurements for each item, and the ability to track changes.  Spending, saving, changes to quality, changes to data reuse, changes to error ratios, etc… all these and more should be monitored and the results communicated to the organization regularly.  These metrics will help to maintain interest in the program and can lead to enabling the support that is so vital to the program’s continuation.

No data governance program staff / team: Expecting the data stewards and data governance council to do all the administrative work of a functioning data governance program is foolish.  The staff / office can be small or large, but it must exist.  At minimum, there must be a program director who manages the overall operation of the program and its components as their primary (only) responsibility.  Most programs without this dedicated managerial resource do not thrive.  Healthy and living programs have the director and a few staff members to support the communications, analysis and project activities of the data governance program.

Conclusion

These are a sample of the reasons data governance programs can fail.  Each can be turned into critical success factors and can put a program on the road to triumph.

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Anne Marie Smith, Ph.D.

Anne Marie Smith, Ph.D. is an internationally recognized expert in the fields of enterprise data management, data governance, enterprise data architecture and data warehousing. Dr. Smith is VP of Education and Chief Methodologist of Enterprise Warehousing Solutions, Inc. (EWS), a Chicago-based enterprise data management consultancy dedicated to providing clients with best-in-class solutions. Author of numerous articles and Fellow of the Institute for Information Management (IIM), Dr. Smith is also a well-known speaker in her areas of expertise at conferences and symposia.

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