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A Legacy Approach: Portfolio Management

Most organizations have instituted some form of formal or informal IT Governance / Portfolio Management processes. In this type of governance, leadership creates a vision for what types of issues and changes are to be addressed, along with an implementation budget.

A gatekeeper organization is put in place to administer the budget and to decide which specific requests for funding to approve. In this model, there are actually two funding buckets. The first belongs to Business and IT managers, who make independent and traditional “management decisions.” They all have a certain amount of discretionary funding to be used for maintenance and minor enhancements to software, data, and processes. They are empowered to authorize efforts that fall under a certain threshold for funding and resources.

The second funding bucket is for projects that fall over that threshold; these efforts require gatekeepers’ approval.

 

 

This approach – allowing gatekeepers to prioritize projects and to fund those that are ranked as high priority – may work well for software development projects. But this approach does not generally work well for data-related efforts that address boundary-spanning, foundational elements. This approach does not work well for efforts that – in themselves – do not have a high ROI, but are on the critical path for other high-value efforts. This approach does not always work well for data-related efforts that set the stage for initiatives that are being planned for, but have not yet been approved.

This approach does not work well in an environment that does not allow re-prioritization of efforts once a year’s budge has been established. And it can create ill-will and political problems for Data Governance sponsors and participants if the result of deciding to address a recently-discovered need means that another project will be canceled or delayed.

Organizations that attempt to push all Data Governance-identified projects through a Portfolio Management process generally discover that they are expending a large amount of energy “justifying” the projects to gatekeepers. This can be frustrating to Data Stewardship Councils that have already been through a prioritization process of their own.

 

Next:  A New Model: Combining Portfolio Management and Data Governance Recommendations

 

 Image courtesy of mapichai at FreeDigitalPhotos.net

About Gwen Thomas

Currently the Corporate Data Advocate at the World Bank Group's private sector arm (IFC, The International Finance Corporation), Gwen Thomas is the Founder of The Data Governance Institute and primary author of the DGI Data Governance Framework. Gwen has personally helped build Data Governance programs at the Federal Reserve System, Sallie Mae, Disney World, NDCHealth/Wolters Kluwer, American Express, Washington Mutual Bank (WaMu), Minnesota Pollution Control Agency, Wachovia Bank, Coors, and others. Gwen frequently presents at industry events and contributes to IT and business publications. She is the author of the book Alpha Males and Data Disasters: The Case for Data Governance.