IBM Analytics and Race Across America

By | 4 minute read | June 20, 2016

IBM and Race Across America

The Race Across America (RAAM) is a bicycle race like no other. Called “the toughest test of endurance in the world” by Outside magazine, RAAM spans North America, starting at the Pacific Ocean and ending at the Atlantic. Finishers spend eight to ten sleep-deprived days and nights on the road under conditions both extreme and unpredictable.

But, like any endeavor, successful execution begins with a plan, thoughtful preparation and execution that adapts to changing circumstances.

Ultracyclist Dave Haase has teamed up with IBM to gain the insight and foresight he and his crew will need to prepare for and execute his perfect race. Haase described his grueling race schedule this way: “The whole race is 3,000 miles long. I’m racing pretty much nonstop. So, the game plan is to race 30 hours without any sleep, stop for two hours and sleep, and then continue at that same pace.”

Haase and his crew have to make real-time decisions regarding heat, wind, rest times, nutrition and performance during the race. How will IBM help him race his perfect race? “IBM has built what they’re calling the ‘Internet of Dave,’” Haase said. “We’re collecting all this data in devices and then we’re going to use it to make me race faster.” IBM and Haase will combine analytical foresight and human experience to put together what we hope will be an epic performance.

Averages lie and intuition fools us

Haase is the four-time top American finisher in this test of fitness and grit. In 2015, he took second place overall. For 2016, his goal is to come in first. Like many of us, Haase has been maturing in his own use of instrumentation, measurement and analytics to build his fitness through better training and recovery. He has learned to trust analytics as a more reliable guide to his effort than simple averages and intuition, thereby coaxing more out of his training and building a stronger engine for the sustained effort.

In the video, “Going the distance with IBM Analytics,” I explain how analytics can make an impact. Analytics allow us to evaluate choices more effectively. There is no doubt there are going to be lots of decisions that have to be made, but some will undoubtedly weigh more heavily than others, and there can be a big difference in the decision quality that ultimately impacts the race itself.

Performance planning

Any big event in life needs planning for it to be successful. Consider when planning a major event such as a wedding, graduation party or vacation. Preparations involve a wide range of tasks, and you’ll make forecasts and predictions about the future and make decisions about each: dates, invitee list, clothing, average food consumption, contingency plans for bad weather and more. If you’re experienced at planning these events, you likely already know what to consider, which may be called insight.

Now, imagine that you could look into the future and see what lies ahead. This would be foresight. Together, insight and foresight offer the best chance at an optimum outcome. Businesses are also using insight and foresight to deliver the best possible outcomes for their organizations. But rather than relying on intuition alone or simple averages, they are leveraging predictive analytics to enhance their decision making.

A recent Forbes article covers several use cases for industry-specific analytics solutions, such as banking, retail, media and entertainment, oil and gas, and wealth management. For example, analytics can help banks “analyze customers’ spending patterns to predict their financial and life events and deliver more relevant offers.” That capability translates into increased offer uptake, increased revenue and fewer wasted resources. Analytics is truly providing a competitive advantage, whether the playing field spans thousands of miles of roads across the US, or thousands of branch offices or retail stores around the globe.

How hard can it be?

For 2016, Haase will combine his fitness training, insight and foresight using data and analytics from IBM to put together his perfect race. IBM’s deep experience enables it to marry the sensor data from Haase’s bicycle, biometric data from Garmin wearable technology, and forward-looking data on weather conditions— think wind speed, direction and temperature — from The Weather Company, an IBM Business. Haase and his crew then have the best information to make decisions about racing — and about resting — on this race across the continent.

Haase admits that during his first race he was quite naive and relied heavily on his natural intuition. He’s very experienced at long-distance cycling, so how hard can it be? Unfortunately, Haase wasn’t able to keep up with the demands of this extreme event and ended up in the hospital before he was able to complete the race. Not finishing is a common outcome for many ultracyclists. In some years, more than half of the starters do not finish, and ending up in the hospital is also a common occurrence. Haase participated in the race four more times and eventually finished as the top American finisher. Competing in RAAM takes strength of body and mind. “You’re constantly running into a brick wall, getting back up and [then continuing to go] across the country,” Haase said candidly, when he described his experience at the Vision conference in 2015.

The analytics advantage

Haase now uses the hard-won lessons from each previous race and his performance metrics to fine-tune his planning, training and racing strategy. IBM will be there again this year to help with one of the most challenging aspects of race execution decision making on the multiday event: knowing when to rest.

Together, Haase, his crew, Garmin and IBM are bringing together human intuition and high-speed, high-powered analytics and optimization to demonstrate how man-machine collaboration can make better choices than either might make independently.

Ride along with us, and you’ll learn about Haase, his crew, IBM Analytics and the Internet of Things. And hear directly from Haase and me as we discuss going the distance with IBM Analytics.