Effective Data Utilization Begins with Governance — Here’s How Courts Agencies Should Begin
Posted on March 4, 2022 by Shay Cleary
A previous blog explored the advantages that can be gained by justice organizations via “big data” approaches that leverage artificial intelligence (AI) and machine learning (ML). This blog examines the importance of data governance. The amount of data that courts receive, provide, and ultimately are responsible for has increased exponentially over the last decade, with no signs of slowing down. While this abundance of data presents opportunities to improve operations and better serve the public, it must be managed appropriately, from both a business and information technology (IT) perspective. The effective implementation and application of big data tools that leverage AI and ML require oversight and planning from a data governance group.
Data governance is a framework that can be used to develop short-term and long-term strategies for collecting, using, and disposing data. The framework also can be used to reach and communicate decisions pertaining to data use, and to ensure that the organization’s data management and business practices are aligned. Simply put, data governance means having an essential organizational focus on data and how it can be used to improve outcomes. Leveraging AI and ML starts with having conversations about data.
As might be expected, numerous steps are required to develop data governance within a justice organization. One of the most important is the maturity model, which identifies where the organization is today regarding data and where it wants to go. On the low end of the model, every decision is ad hoc and on an individual system level, with little thought given to how those decisions affect other aspects of the organization’s data collection and utilization effort. On the high end, data is viewed from an enterprise-wide perspective, with consistent elements across the entire organization. The maturity model defines the way that the organization’s data strategy evolves — it is relatively simple in the beginning and then gets more complex over time. Until it is developed, an organization cannot identify the specific tactics that will inform its data strategy.
The following are a few tips for establishing data governance:
- Determine the organization’s data culture, i.e., is the culture data aware? Do personnel talk about data? Do they know what types exist? Do they know how advantageous data can be?
- Utilize existing organizational structures whenever possible
- Formalize the data governance strategy within your organization
- Develop a data governance committee/group and include representatives from all functional areas of the organization (everyone has data)
- After the committee/group is onboarded, start by piloting processes and tools with a single domain/line of business
- Focus internally first (but keep collaboration with partners on the radar screen)
The subject-matter experts within MCP’s data integration services team would welcome the opportunity to work with your organization to develop a data governance strategy — please reach out.