The Hundred Mile Hypothesis

Screen Shot 2017-04-05 at 12.55.54 PMToday’s tech entrepreneurs succeed by “iterating fast and releasing often”. The competitive environment is so fierce and technology evolves so rapidly that falling behind could spell doom for any venture. But speed isn’t enough. Success favors the teams that not only innovate rapidly but also innovate wisely. That balancing act is difficult for most any team.

The tension between rapid innovation and wise innovation can be excruciatingly challenging for a team. Innovate too hastily and risk making bad decisions with too little information. Try to innovate too wisely and find yourself slowing your team in analysis paralysis.

I believe that the team cultures that thrive in that sweet spot – that innovation zone – between acting on impulse and analysis paralysis are the successful ones. Those teams innovate well because they are are
a) Comfortable throwing themselves wholeheartedly into uncertain circumstances
b) Able to maintain an analytical detachment and curiosity that allows them to not only succeed or fail quickly, but to always seek to understand why

A few years back, I decided to run a 100 mile race. A decision like this is similar to a launching a new venture or business strategy. I couldn’t know entirely what I was in for. But I had some knowledge about what I thought it would take to succeed. And I was ready to innovate rapidly to get there in terms of training and personal knowledge.

There was going to be nearly 20,000 feet of climbing, and temperatures that approached 100. I knew there would be highs and lows and a lot more things that I couldn’t ever know that would impact my performance that I couldn’t really anticipate or control. A friend had told me that “A hundred mile race is really an eating a drinking contest.” I thought that was sage advice – at least it felt like something I could control.

But really, I was throwing myself wholeheartedly into a very uncomfortable unknown and I was ready to give it everything I could.

As for the analytical detachment, I had a folded piece of paper in my shorts. On it were the times between aid stations (splits) I had compiled from three previous experienced runners of three different profiles (fast, medium and slow). With it, I hoped to be able to gauge my anticipated finish time during the run.

The run went well. I didn’t get 1st – but I got fourth place, a time under 24 hours and a cool bronze rhino trophy. Turns out that my friend’s advice about an eating a drinking contest had been important and I had done well in that area. But I learned that even more important was keeping track of those in front of me as they either dropped out or I passed them.

After I finished the race, I was ready for another. I also wanted to better understand what drove success and failure in such a long race so that I could innovate for the next run.

So I took the race data and with a little coding developed a web application to visualize every runner’s times for each segment over the elevation profile and against each other.

Check it out here

Screen Shot 2017-04-05 at 12.35.39 PM

What i learned from visualizing the data is that the key to success with running a 100 mile race is managing the lows. You can clearly see runners in the visualization where one section destroys their overall time. You can see the seasoned runners who maintain consistency. I could even see how I lost third place with 30 miles to go when a low for me left me hobbling, and the runner behind used the opportunity to speed past.

Since then, I’ve run many more 100 mile races. And while I continue to iterate and improve from what I learn in each run, that initial lesson about managing the lows has remained as a central strategy for all of my running. The exact way to manage the lows? Well that is a pretty rich topic. But, the skills there are pretty applicable to just about everything.

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