When faced with a possible change, we often want to see data that shows our transition is a good idea. Sometimes that data exists and sometimes it doesn’t. What data can you discover to see if the change is a good idea? How can we get feedback early to see if the change is useful?
I’m not talking about involuntary changes. We see our reality for those. I can’t ignore my vertigo—that would be stupid and reckless. In a real sense, my reality is my data. My feedback loop is quite short.
Voluntary changes are different. Maybe an app suggests an alternative way for your drive. Maybe you’re considering changing the way you eat for better health. In my consulting, organizations, managers and teams think about moving to an agile approach.
It would be nice if we had data to support our potential change.
Data Can Support Potential Changes
For alternative drives, we assume the app is traffic-aware, that the app has the data. We decide—often based on past experience—that it’s fine to trust this app. That’s because we get fast-enough feedback as we drive.
If you’re thinking about changing something about the way you eat, you might do some research on the changes. One thing all diets agree on is that people need more vegetables. You could take that first small step while you investigate other data. You might see if incorporating more veggies is enough of a change. That’s a short feedback loop.
And, what about changing the way you work? That’s a lot more difficult. We often don’t have easily comparable data from other people, teams, or organizations. That’s because we need time to define the problem and time to assess the results.
Who Sees Progress?
In software, we often cannot fully define the problem until we show the customer some progress. Some construction projects are like that, too. Our feedback loops are much longer.
When we change the way we eat, we might also need time to assess the results. The feedback loop from behavior change to results is longer than we might want.
That feedback loop duration challenges our ability to gather data. What data makes sense to gather? When do you need the data?
Many years ago, I wrote an article. When I asked for feedback, the reviewer said, “I know about three points to make a line or form a conclusion. You managed to do this with one point.”
That reviewer offered me a tremendous gift. I had not made my case with the data I presented. I needed to offer more data and explain the feedback loops.
Consider Thinking About Data This Way
Here are some ways to think about the data you might gather:
- What’s the smallest change you might make, to provide some data? That data shortens the feedback loop.
- Is there interim data that would help you see where the experiment is going? That also shortens the feedback loop.
- How often can you gather the data? That frequency might shorten the feedback loop.
In terms of the Satir Change Model, the image at the top of this post, shortening the feedback loops helps us know if the Transforming Idea will work.
I find that the more I want to experiment or adapt, the shorter my feedback loops have to be. I see much more data with short feedback loops.
Adaptable leaders, that is the question this week: Can short feedback loops offer data?