Faced with limited budgets and growing responsibilities, companies are turning to data as the driver of their business objectives today. Data governance is therefore more critical than ever. It sets the overall framework by which information is managed and utilized. As such, data governance is less about data infrastructure and more about the stewardship of data use and integrity.
For public sector organizations, data governance is a growing focal point on many fronts. Compliance, financial transparency and public accountability have become central to operations. The ongoing digitization and openness of data further requires government entities to utilize rigorous data standards.
In the private sector, it is important for organizations looking to improve their data governance to familiarize themselves with best practices. To get started, it’s worth considering the foundational steps necessary to obtain data stewardship.
Setting Organizational and Enterprise Objectives
As with any strategic planning process, a key step in establishing a data governance framework is to identify key business and organizational goals. This will help to define which enterprise processes are central to an organization—such as data analytics, capital planning, information security or regulatory compliance. Data governance often focuses on the quality and functionality of data, as well as its accessibility.
All too commonly, organizations set out to improve their data practices without truly understanding what they want to achieve. This occurs when too much emphasis is placed on data production and management instead of the more important overarching enterprise strategies.
Developing a Data Leadership Structure and Hierarchy
A defining aspect of data governance is the establishment of data “stewards” within an organization. These leader have the authority to manage data processes and maintain data quality. They also hold themselves (and an organization) accountable from a data management perspective.
Because of the growing technical requirements in data governance, many organizations assign this responsibility to the Chief Information Officer. It is the CIO who is then responsible for defining a data governance hierarchy of data stewards, managers and coordinators. Many organizations will also establish a data governance committee—typically comprising internal stakeholders and information technology experts—as a way to account for the cross-department nature of enterprise data.
Building a Data Governance Strategic Plan
Developing a data governance strategic plan is critical to ensuring the long term success of the program. A strategic plan is often comprised of the following tasks:
- Building context and rationale for a data governance program
- Setting key goals and deciding how to measure these goals in the future
- Understanding key users and providers of data
- Developing data roles, hierarchies and leaders
- Establishing action plans
- Setting funding and technology commitments
Vanderbilt University’s Strategic Data Governance plan is a strong example of how data governance focuses on the assignment of organizational data leadership, action plans and processes.
Data Governance and 4tell Solutions™
For commercial real estate organizations, data governance policies have become critical. You cannot make decisions based on real estate data with confidence without these procedures in place. Similar to financial reporting, poor data governance will result in poor-quality, unreliable reports that impact strategic planning and capital processes. Organizations simply cannot afford to get it wrong.
4tell Solutions™ has helped many organizations understand their internal data requirements. Please contact us for more information on how we can help you enhance or establish your data governance processes.
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