Knowledge is Power! Measure what Matters!
If our cliches are an indicator, we all know that data collection, review, analysis, and understanding is important. We all hear of data-driven decisions, and the importance of data in education and educational systems, but we are often challenged to incorporate data review and the next steps into our everyday lives. As we’ve been exploring the Essential Elements of a Data Culture, we’ve been considering how an organizational culture can shift from a culture in which data is in the periphery, pulled to the center for high stakes discussions and decisions, to one in which data is an integral part of every day, informing the small moves that reinforce the vision, clarify decisions, and advance progress.
This is where our love of habits comes in…
We’ve explored, researched, and utilized the introduction and examination of individual and team habits for every facet of what we do within our teams at Education Elements, and with our district partners as they make shifts in their districts. In our exploration of habits, one of the insights that has special relevance for leaders considering organizational change is the idea of the Keystone Habit. In his book The Power of Habits: Why We Do What We Do in Business and in Life, Charles Duhigg introduced the idea of a Keystone Habit. A Keystone Habit is a high-leverage move that, once practiced, will lead to much larger impacts on the organization than just the outcome of the move.
When we are considering shifting to Data Culture, finding and practicing a Keystone Habit can be an easily implemented first step that can get the ball rolling in the right direction. But how do you find your Keystone Habit? A Keystone Habit is characterized by the following:
-
It is aligned with your values
-
It offers small wins
-
It naturally leads you down a more productive path
-
It is as easy as possible to start
Practicing the habit will impact the data, and practicing data review will impact the culture.
A recent article in The 74 Million helps envision how this could work:
-
Gather Data: This article utilizes data about the rate of teacher performance improvement, and research that confirms the importance of teacher quality in student learning. In addition to this area of focus, a school or district would reflect on their organizational values--the specific habit might look different in an IB school versus one that is focused on Project Based Learning.
-
Identify/Implement the Habit: this will be one measurable focus. In the article, the example is increasing wait time after a teacher asks a question. To support this shift, teachers might write the answer on a post-it to share at the end of class rather than answer the question for students.
-
Review Data: The review of the data is what begins to shift the culture. If teachers count their post-it notes at the end of the day, and teams review the post-it notes at the end of the week, they are building a habit of regular data review and building toward a sustainable data culture.
-
Revise/Refine/Add to Habit: Once the teacher has built a habit of increasing wait time, there may be another practice to add to build toward a more student-centered classroom. This may involve identifying an additional or a different metric, and this reconsideration and revision is what builds a responsive data culture.
Organizational psychologists, business journalists, and entrepreneurs have documented the success of intentional habit-building as an agent of effective change management in groups from Alcoholics Anonymous and Alcoa to Zappos. This practice is a hallmark of a learning organization, so where better to perfect it than in school--the original learning organization?
Join our upcoming Data Culture Mini Conference to learn how to determine which information to collect and prioritize, and establishing norms and goals for data collection and usage.
More Data Culture reading
Blog: A Four Step Process for Developing Data Culture in School Districts
Blog: How Bias Affects Our Perceptions of Data: 3 ways to guard against unconscious bias
