Lessons from a Triathlete: Chasing Down Data and Stronger Performance

Editor’s Note: This is the fifth article in a 10 part series on how an elite athlete applies the lessons she’s learned from Triathalon training to her role as a Fortune 100 marketing executive. Read the first, second, third and fourth article in this series.

In 2008, I saved the little bit of energy I had left in my tank to unleash a huge smile as I crossed the finish line of Ironman Lake Placid. I was overjoyed to have completed racing 140.6 miles — which included my first marathon. For six months, I followed a classic endurance training approach: Base, Build, Peak.

Five years and three Ironman races later, I discovered the difference of power. Threshold tests, max aerobic tests, and sprint tests became a regular part of my Tuesday and Thursday mornings at M2 Revolution Cycling in San Francisco. I knew my average watts. I relished if I could break 330 watts in the sprint test. I talked watts with my friends. And this attention to data paid off. Back on the same cycling course for Ironman Lake Placid in 2013, I finished the bike portion 23 minutes faster. The following year on a flat course at Ironman Maryland, I cut 29 minutes off my cycling time across 112 miles.

I was finally learning to embrace data to drive my performance.

Optimal performance driven by data

IBM recently worked on a project with US Cycling Women’s Team Pursuit to use real-time data collection and wearable devices to feed live performance. While many cyclists (like me) focus on speed, cadence, and power, new data capture mechanisms — like BSXinsight — are allowing the team coaches to collect muscle oxygen information and soon, psychology. They are feeding information back to the cyclists immediately after a workout and in real time during a race through smart glasses.

“They put in what kind of power do we need to produce… it is very simple color coded on whether you are in the red or you are in the green. Did you go too hard? Did you go too easy?” Sarah Hammer, USA Cyclist.

This data and real-time feedback improves the cyclists’ efficiency, guides them on when to push more, and helps them avoid the dreaded “bonk” when your tank just runs out of fuel. The results are impressive so far for Team USA: They took home the gold at the World Championships in 2016 and the silver medal at the 2016 Olympics in Rio.

Applying data driven training to weekend warriors

USA Cycling Coach Neal Henderson believes that most athletes train in the middle range of their actual intensity capacity. With all the data we have now from Garmin watches, fitness apps, wearable devices, and power meters, how could we athletes break out of our rut? How can we focus on the right data and break out of the middle to see real impacts on our performance?

Whether you’re a weekend warrior, a 10k enthusiast, an aspiring Ironman, or a regular podium finisher, there are a few essential tips we can all put into practice thanks to what I learned from IBM and USA Cycling:

• Focus on what’s critical: “Sport always evolves, sport always changes. That is why records are always being broken. It is not necessarily that you have better athletes. It is that people are learning different methods. And if you are not up on that technology, then you know you are going to fall behind,” says Sarah Hammer, Olympic cyclist. Businesses must react the same way. You can’t be afraid to try a new software or even new vendor just because you’ve grown accustomed to something.

• Inspect at your individual response: While you can compare your results across communities like Strava, Runkeeper, and Fitbit, you’ll gain the most improvement by focusing on your own response and output. Imagine if we could all have dashboards like the one of USA Cycling — or feedback from our treadmill at the gym to help us meet our targets? Speaking of dashboards – you likely are using Tableau, Looker, Chart.io, Amplitude to monitor your sales, marketing, or product usage.  How could you use those tools to dig deeper into your own impact?

• Be willing to abandon old models, use data to drive results: According to Sarah Hammer from Team USA, “When you feel like you have the tools that you need it just makes you that much sharper.” I gave up on the traditional “Base, Build, Peak” Ironman training model to focus on improving my cycling watts. At work, I’m just about ready to walk away from measuring leads and building scoring models to examine engagement and conversion.

• Look for tools that improve your training and racing psychology: Neal Henderson believes that psychology can be trained. Can you become more motivated or more competitive? How can we infuse that mental training into our apps and get actionable insights from the data delivered? At the office, what does it really take to shift your organization’s mentality?  What kind of investments would be needed to adopt a challenger mindset?

I’m more excited than ever to map out my training plan for Ironman Lake Placid 2018 – and work with my team at IBM to find new ways to measure and improve prospect engagement. I can’t wait to see the results 10 years after my first race — once I’ve applied real-time analytics and individual responses to my training program.  And, I can’t wait to see how IBM evolves as we monitor site heat maps and do correlation analysis to determine the overlaps between content viewed and trial conversions.