How data can support start ups and alpine cycling

79 miles. 4 mountain passes. Over 6,000 feet in elevation. I took on the challenge of completing the Copper Triangle road bike ride last summer. When I said yes to the challenge, I was feeling daunted and nervous about the endeavor.  The feelings of trepidation were vaguely familiar as I remembered my experience working in a start-up environment—excitement about the challenge, worry about my own readiness, and fear that I might not reach my goal.

In both cases, one of the greatest tools I had to address my lack of readiness was my ability to use data to help break down the challenge into manageable pieces, to track my growth by celebrating small successes, and to help uncover strategic moves to help me progress.

In start ups, the data points are often measured in time, money, and impact. In the bike race I would be measuring data related to elevation gain, endurance over multiple mountain passes, and overall mileage. I knew the big picture goals of the race would be so satisfying if I met them, but starting on my training on day 1, I knew that I had to break those numbers down to not become overwhelming. I knew the big buckets that I was striving for—elevation gain and endurance. When I planned for my training rides, I could identify them as either elevation rides or endurance rides, so I began to plot out how to start small with elevation gains (adding 100 feet to each climb) or endurance gains (10 more miles each ride). This allowed me to see the smaller improvements over time.

Similarly, start ups often know where they want to go. They may have annual goals set around how many people they want to serve, how much money they need to pull off their programming, and what gains they hope to see. But annual goals can be too far away and too big to see in the day-to-day work. By breaking it down into smaller increments, those larger measures of success can be seen on a monthly or quarterly basis. Instead of focusing on how many clients start ups want to serve in a year, set goals around how many people are needed initially to launch the work and set a two-month goal. Then invest in the recruitment, structures, and marketing to hit that first milestone.

After breaking down the data, I needed to use the data to track progress towards the end point. In cycling, I found myself using data apps to track my rides. When I rode the same course, I would look for improvement in my overall time to show how I was improving my endurance. As I rode hills, I looked for how often I could set personal records for speed. Over time I saw how my work paid off—and on days where I didn’t get the gains I was seeking, I would know to push myself more the next time.

In the start up world, we track progress along the way. We evaluate our data on an ongoing basis, from quarterly budget checks, to analyzing our programming on a regular basis. We are able to see our successes and address our challenges on a smaller scale that would help us meet our annual goals. By using data on an ongoing basis, we not only could see if we were on track, and we can more nimbly respond to the needs of our clients and make changes that result in greater long term success.

In the end, I crossed the finish line and completed  the Copper Triangle. The months of training and using data to support me, helped me accomplish what I wasn’t sure was possible.

In both cycling and start ups, the data offers a roadmap for what long term success can look like and breaks it into smaller and more timely data sets. This allows for celebrations or adjustments along the way to ensure that long term goals are met.

If you are interested in helping your team set long term goals, or engaging in shorter cycle data work to help you meet your goals (or to discuss Copper Triangle training), contact .