"Our goal is to continually improve management of state government information and knowledge assets." -- Oregon CIO Dugan Petty, co-chair of the NASCIO Enterprise Architecture and Governance Committee (pictured)
The National Association of State Chief Information Officers (NASCIO) yesterday announced the release of its new research brief, "Data Governance Part II: Maturity Models -- A Path to Progress."
In characterizing the various levels of data governance maturity, maturity models outline the path or the journey toward effective data governance, and management of state government knowledge assets.
"We've outlined a number of maturity models -- each one brings perspectives, characteristics and issues that can be anticipated as state government addresses data governance," said Oregon CIO Dugan Petty, Co-Chair of the NASCIO Enterprise Architecture & Governance Committee. "Our goal is to continually improve management of state government information and knowledge assets. We believe proper management of these assets has a huge impact on the effectiveness of state government in serving citizens. Effective management of information and knowledge assets requires proper governance to ensure the quality of that information. Further, we need to ensure that information assets are properly valued and protected. That is our role as stewards of citizen information."
"We're continuing to build on our theme of Enterprise Governance as a critical ingredient for making state government work effectively," said Steve Fletcher, CIO for the state of Utah. Steve Fletcher is Vice President of NASCIO and also Co-Chair of the NASCIO Enterprise Architecture & Governance Committee. "The citizen must be able to experience a collaborative, integrated government - one state government. So how do you make that happen? Part of the answer is to proactively manage state government information as an enterprise asset - a resource that is shared across government to ensure government agencies are working in concert to benefit the citizen. That information must be maintained to ensure it is accurate. More and more decision making and service delivery requires cross agency collaboration. The information used by multiple agencies should be accurate, complete and not conflict. Data governance is a discipline for bringing together the right people, the right processes and the right technology to make that happen. Maturity models contribute to that end by presented the milestones we're after, the journey we need take to reach the higher levels of data governance."