The Data Didn't Tell Me What to Do. It Helped Me Decide.
I spend a lot of my professional life thinking about how organizations use data to make better decisions. I didn't expect an Achilles injury to give me one of the clearest examples of that thinking in my own life.
When I injured my Achilles, I realized that I needed to apply the same approach to my own recovery. I didn't want to simply run a few miles without pain. I wanted to get back to long-distance trail running and ultramarathons. Specifically, I had three mountain races in mind: a 108K in June, a 100K in July and a 100-miler in September.
So I started with the outcome I wanted and worked backward:
What would I need to be able to do to get there?
What could I measure along the way?
And, most importantly, how could I use that information to decide what to do next?
That was much more useful than simply asking myself every morning: “Does it hurt?”
The problem with collecting data
One thing that has always bothered me about data work is the idea that collecting more data automatically makes us more data-driven. It doesn't.
You can have an enormous amount of data and still have no idea what decision to make. We do this in business all the time. We build dashboards, add metrics and integrate another data source—and then someone asks, “So what are we supposed to do with this?”
My Achilles recovery gave me a personal reminder: I could track everything, but unless it helped me make a better decision, what was the point?
I needed some governance around my own data
Pain is subjective, but that doesn't mean it can't be measured. I developed a simple, consistent way to track my recovery: what I did that day, daily steps, how my Achilles responded during activity, what happened later that day and how it felt the next morning. And since pain can also be very subjective, I put definitions around those pain scores. I wasn't looking for one magic number. I was looking for patterns.
That is essentially governance:
Define what you are measuring.
Measure it consistently.
Know what the data actually represents.
Then use it in context.
The pain score by itself wasn't the answer. It was one input into the decision.
Data didn't tell me what to do. It helped me decide.
This was probably the most important part. I wasn't collecting information so I could have a really good Achilles spreadsheet. I was collecting it because I needed to make decisions.
Do I progress?
Stay where I am?
Modify the workout?
Back off?
And then I had to see what happened after I made that decision.
That created a simple feedback loop:
Measure → assess → decide → act → measure changes → adjust.
Not every data point carried the same weight. A single pain score didn't tell me whether I was ready to increase my running. The trend—and especially how my Achilles responded to increasing load over the following 24 hours, while looking at my total load across seven days—was more useful.
The data also helped keep me on track mentally. There were plenty of days when my brain was telling me, “This is going nowhere.” But the trends often told a different story. The progress was too gradual to feel day to day, but it was there when I looked across weeks.
The goal wasn't to eliminate uncertainty. It was to make better decisions despite it.
Start with the outcome
I knew where I wanted to end up, so I worked backward.
For those races, I eventually needed to tolerate a long time on my feet and have the strength and durability to handle it. I knew my current state and future state. The data helped me understand the gap and decide whether I was ready for the next step.
It wasn't about hitting an arbitrary number and declaring myself “healed.” It was about building capacity and watching how my body responded to increasing load.
I eventually completed the 108K, 100K and 100-mile race I had set out to do.
The bigger lesson
I think this is why I continue to be so interested in data and analytics. The interesting part isn't the data itself. It's what happens after you have it. Good governance makes data more trustworthy and usable. Good analytics helps turn it into information. But the real value comes when that information changes a decision—and that decision moves you closer to an outcome.
My Achilles happened to be the system I was trying to improve. The outcome happened to be getting back to running.
Know what you're trying to accomplish.
Work backward from the outcome.
Collect the data that actually matters.
Make sure you can trust it.
Measure the result.
Adjust and keep moving.
Because collecting data is not the goal. Getting somewhere better is.
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