Leading Effective Data Conversations

Updated: Jul 16

Welcome to #BeyondTheMean! Check out this post to see what this blog is all about.

The phrase data-driven decision making has become ubiquitous in education. You find it on job descriptions, embedded in strategic plans, and copied into faculty meeting minutes. But do we, as an education profession, really have a good grip on what that phrase even means? I don’t think we do. In this post, I want to provide some guidance for the next time you gather your continuous school improvement team around the conference room table.

Develop a Data Analysis Approach

The first step to having a meaningful data discussion with your team is to develop a consistent data analysis approach. Consider the myriad of ways that you can manipulate data – there are dozens of methods. Your team should select an approach to deploy consistently throughout the year. This ensures that your meetings are efficient and everyone knows what they’re looking at and for when they open the data reports.

I am a big fan of open ended exploratory data analysis processes. I like that they are replicable, focused on simple mathematical principles, and are cyclical and iterative. Your school or district may have access to additional tools, such as standardized dashboards or reports that come out of your student information system, that may expedite your data review. Your team could also opt to develop their own data analysis protocols. The key is to agree on a process, train everyone on that process, and stick to it.

Review, Ask Questions, Review Again

Once you have agreed upon a data analysis protocol, you need to develop a routine or rhythm for your data meetings. I recommend that you start with a simple review of the data. Throw your dashboard, report, or other analysis tool up on a big screen and take some time to walk through it from top to bottom. As you do so, allow team members to document their questions along the way. When you have completed your initial review, open the floor for team members to pose their questions and facilitate some discussion.

It is important to make sure that you complete your full review of your analysis before opening the floor for discussion. This ensures that every data point in your agreed upon approach is highlighted and your limited time together doesn’t get eaten up by the first two findings while leaving the next eight on the screen for later (later will never come).

As your team discusses the data, allow the data to provide answers to questions. Turn back to the data and apply your data skills to dig deeper and better understand nuances or abnormalities.

If you get stuck…

It is likely that your team will get stuck early on in the process as you build both routines and confidence. You should have a back-up protocol in place for those days when thoughtful questions from the data simply aren’t flowing. I like the to start with the six data questions by Edie Halcomb:

1. What question/s are we trying to answer with the data?

2. What does the data tell us?

3. What does the data not tell us?

4. What are the causes to celebrate?

5. What is the need for improvement?

6. What are our next steps?

Have these questions printed up on a poster and hung in your conference room for easy reference. They will get you unstuck every time.

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