Leveraging Formalized Data Teams to Build a Culture of Data Use
You may be wondering what a formalized data team is! And why does it matter if you are part of a formalized data team rather than different staff members completing analysis on an as-needed basis? Simply analyzing your data is not enough.
A formalized data team helps you operationalize your approach to data analysis. As data teams create a formalized analysis process, your ability to use data strategically in decisions about program operations, accountability, and program improvement increases.
Have you experienced the following?
Imagine if instead
- You had an internal data team bringing staff together and an external data team representing multiple diverse perspectives that each met on a regular basis and used a consistent process of data-informed inquiry that made looking at data a regular part of doing business. You probably already have existing structures that you can use to form your internal data team (such as staff meetings or professional learning communities) and external data team (such as an Interagency Coordinating Council or other existing workgroups).
- These internal and external data teams could analyze agreed-on priority areas and critical questions.
- The data teams could identify barriers to being able to answer other critical questions and make recommendations to leadership about next steps.
- The data teams could select and integrate a clear, consistent data-informed inquiry process, making data-informed decision making routine.
- The data teams could look at data for program improvement and follow through to see if the improvement strategies put into place actually are making a difference.
- When you formalize your data team and approach, you work toward building a culture of data use where data are truly used for multiple purposes and inform program operations and program improvement.
Do you really have time for this data team work?
- Yes, there is an up-front investment of time and energy to thoughtfully build a formalized data team. But once the team is built, it takes much less energy and effort to look at data and examine new questions or issues rather than having to pull together a group each time a new initiative or requirement arises. So, how do you build an effective data team?