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Going the distance with IBM Analytics

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Overview

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. IBM has teamed up with ultracyclist Dave Haase to provide 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.”

Learn more about how IBM is helping ultracyclist Dave Haase win RAAM 2015: a 3,000 mile race across the United States.

Transcript

0:00my 0:01I just enjoyed a ride my bike and I with that high 0:05challenge myself with someone crazy races that are out there to do in 0:10I find different ones to do in how the Race Across America is 0:14the hardest most challenging all the racists my initial plan for the 0:18races to I'm started California 0:21and ride 35 to 40 hours straight 0:24sleep for about two hours and then ride 0:27about 22 hours a day man do that 0:31to the finish line the overall idea of the racist a really race 0:35as many hours as you can in to sleep as little as you can 0:38constantly move forward Tom rates across america is probably challenging because 0:42new 0:43are going through the the battles on mentally 0:46physically I 0:48all the time just trying to continue moving forward as fast as you can 0:52in the desert areas can be 120 degrees now 0:55and then in the evening in the mountains it gets down to 32 degrees 0:59just all over the you know mother nature aspects of the event the heat 1:0350 what you're trying to eat put in your body so it's 1:06just doll to a challenge of trying to survived the race 1:10the thing that's been most remarkable is how dave is using analytics to build the 1:15best 1:15engine we got the best from the internet of things. we have experts that I build 1:19applications that use cloud data services and we're gonna stacked those 1:23talents and mix them into 1:24well just one good outcome here %uh we have to make sure that the system we're 1:29creating the internet and Dave as we call it 1:31rate is resilient to 3,000 mile bike race 1:34you know the idiosyncrasies in the internet if dave is really built on our 1:39blue mix platform 1:40we are working not closely with the decision optimization team 1:44predictive analytics and and Watson analytics 1:48given us new insight into this very large Saturday 1:52data that day brought to us and said you look there'd been here's my training 1:55records 1:56for the last five years right what can you help me learn about myself because 2:02knowing himself right 2:03can help them raise that engine and great speed I think one of the things 2:06that analytics 2:08allows is actually desi dumb to evaluate 2:11choice more are more effectively 2:15palm 2:17do there's no doubt there are going to be lotsa decisions that are made but 2:20some way more happily 2:22other than others and their computer a big difference in the decision quality 2:26that ultimately impacts the race itself 2:29I think everyone has technology that they're using whether it's by computers 2:32are heart rate monitors are power meters 2:34I'll bite finding ways to use it efficiently 2:38Tom an event like this and then knowing where your limitations are 2:42and how hard you can race I'll and staying at that below threshold level 2:48arm is very important I think the result a using 2:52that analytical date is that it does dumb 2:55allow me to be a little more oppressions on each day that a ride 2:58I think it's making me smarter and more aware of how I'm riding my bike 3:02from that standpoint I'm I know I'll have more confidence we have the 3:06Starlight as we have 3:07information that we've been using and now we can use during the race 3:12time 3:13do 3:21good