Sweat, grit and analytics to get to the finish line first
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 Ocean. Finishers will 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 at the IBM Vision 2015 conference: “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 that same pace.”
Haase and his crew will have to make real-time decisions regarding heat, wind, rest times, nutrition and performance during the race. How will IBM help Haase race his perfect race? “IBM has built what they’re calling the ‘Internet of Dave,’” Haase said. “And so we’re collecting all this data in devices and then what we’re going to do with that is use it to make me race faster.” IBM and Haase will combine analytical foresight and human experience to put together an epic performance.
Averages lie and intuition fools us
Haase is the three-time top American finisher in this grueling test of fitness and grit. Like many of us, Haase has been maturing 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. I think one of the things that analytics allows us is actually to evaluate choices more effectively. There is no doubt there are going to be lots of decisions that are made, but some weigh more heavily than others, and there can be a big difference in the decision quality that ultimately impacts the race itself.
Any big event in life needs some planning for it to be successful. Consider when planning a wedding, baby shower, graduation party or vacation. You need to consider a wide range of tasks, and you’ll make forecasts and predictions about the future and make decisions on each: dates, invitee list, clothing, average food consumption, rain gear and more. If you’re experienced at planning events, you likely have built-in intuition for what to consider, which may also be called insight.
Now, imagine that you could look into the future and see what lies ahead. This ability would offer foresight. Together, these abilities offer the best chance at well-suited outcomes. Businesses are also using insight and foresight to deliver the best outcomes for their organization. But rather than relying on intuition alone or simple averages, they are leveraging predictive analytics for enhanced 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 is helping banks “analyze customers’ spending patterns to predict their financial and life events and deliver more relevant offers.” Banks are able to provide the most relevant offers at the right time. 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 across the globe.
How hard can it be?
Haase will combine his fitness, 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 bike, biometrics and forward-looking weather conditions—think wind speed, direction and temperature. Haase and his crew then have the best information to make decisions about racing—and about resting—on this eight-to-ten day race across the continent.
Haase admits he was quite naive and relied heavily on his natural intuition during his first race. He’s experienced at long-distance cycling, so how hard can it be? Well, unfortunately, Haase wasn’t able to keep up with the demands of the race 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 three more times and 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 at the Vision conference.
The analytics advantage
Haase now uses hard-won lessons from each previous race and his performance metrics to fine-tune his planning, training and racing strategy. IBM will be helping with one of the most challenging aspects of race execution decision making: knowing when to rest on the multiday event. Together, Haase, his crew, and IBM are bringing together human intuition and high-speed, high-powered analytics and optimization to the race to demonstrate how the 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.
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