Race Across America with Analytics

Last week, I caught wind of a presentation being delivered at the Finance Forum in Melbourne, and was fascinated to hear how Doug Barton was going to make the link between Finance and cycling, or as he refers to it, “what Doug Barton does on his day off“.

I’ll be the first to admit – I know nothing about cycling.  I’m baffled why my father is happy to ride 100km with his crew just to “grab a coffee” and then ride back home.  But add sensors, weather predictions and analytics – and now you’ve got my interest!

Race Across America is an annual transcontinental bicycle race from the west to east coast of the USA. Athletes from around the world race almost 5,000kms from coast-to-coast in what is recognized as one of the world’s toughest endurance races.  With entrants from over 35 countries, winning takes more than just preparation and luck – everyone is looking for an edge over their competitors.

Doug shared his personal story working with Dave Haase, one such ultracyclist.  A five-time competitor in the Race Across America, Dave first rode the race back in 2004, and every year until 2008 where he reached his peak finishing in third place.  This year, seven years since his last race, Dave decided to take on the challenge yet again, and pushing well into his 40s, turned to analytics to help him get his competitive edge over the rest of the field.

In theory, to win an endurance race of this nature you need to spend as much time on the bike and as little time sleeping as possible.  In reality, it’s not that simple.  What’s to say taking an extra 30 minute nap won’t lead to better performance and faster speeds over the course of the day?  You have your resources: your body, your fuel and your bike.  You have your conditions.  And you have your goal – to get to the end of the race as quickly as possible.  So how do you optimise the use of your resources, within the constraints of the conditions, to complete the race as quickly as possible?

Dave worked with IBM to model his body, his bike and the race a lot like we model businesses.

They knew the velocity he needed to achieve on the bike is a factor of distance and time.  They knew four turns of a 27″ circumference wheel covers three yards on the road.  They knew 80 revolutions per minute would drive him 240 yards.  They knew the exact effort he had to exert and how far that would take him each day – and using sensors on the bike, how well he was tracking to those targets.

It wasn’t just the bike that was instrumented to monitor performance, Dave swallowed a pill every 24 hours to collect vital data about how his body was performing, sending the results to his phone and the crew’s iPad for analysis.

But it’s not just enough to predict where Dave would be on the road at a point in time.  They also had to use context and foresight to create their own luck.  It doesn’t matter what the weather is, you’ve just got to get up in the morning and ride against it, right?  Wrong!  We all know it’s easier to ride uphill not downhill.  But did you know that 60-70% energy expended riding a bike goes into pushing against the wind?  As nice as it would be to have a tail wind from the Pacific to the Atlantic, a route over 5,000km changes direction, as does the wind.

Combining data from The Weather Company, they were able to predict his location more accurately, and the wind he’ll experience at each point in the race.  “You can’t choose the weather, but you can choose when to ride it.”  With better insight, the team could see heavy winds ahead and predict whether it’s better for Dave to slow his pace to avoid them. With seven stops across the eight day race, the decision about when and where to rest can be critical to success.  The team estimated smarter decisions about when to rest saved Dave 12 hours over the course of the race – that’s 12 hours faster with no calories burned, zero watts required!

Of the 41 racers this year, only 18 finished due to heat exhaustion.  Dave was one of them, not only finishing the race, but coming in second place – just eight hours behind the leader.  In his fifth Race Across America, Dave Haase finished in an incredible 8 days, 20 hours and 6 minutes, with an average speed of 14.16mph.  That’s 2mph faster than his pace seven years ago when he finished in closer to 10 days.  Dave’s preparation and hard work paid off, with a little help from his crew at IBM – “I raced my perfect race with IBM Analytics.

Back to the original question – what does this have to do with Finance?  Doug summed it up as this:

At the core of the Office of Finance, is comprehensive planning, modelling and monitoring how an organisation manages one of it’s most vital assets – money.  Just like the world of ultracycling, it’s critical that you have a good understanding of the resources at your disposal, the conditions you’re working under (both internal and external), and the ultimate goal you are trying to achieve.  This puts you in the perfect position to be able to leverage analytics to better predict what is likely to impact the bottom line, and optimise the use of your resources, under those conditions, to meet your corporate financial objectives.

Organisations today model their businesses with external data and advanced analytics, because they know:

  • Weather is a leading indicator of future business trends such as retail demand or insurance loss;
  • Social sentiment can be used to predict customer adoption or churn;
  • Quota assignments can be improved with analytics used to model the potential across territories and sales rep types (hunter vs. farmer);
  • Advanced analytics offers predictive insight into maintenance requirements eliminating down time and catastrophic losses;
  • There is a direct link between economic activity and performance.

Next time you head out to take the wheels for a spin, spare a thought for how valuable it’d be to know what’s coming next in your business so you could adapt and optimise the outcome.  And take a moment to imagine what it’s like sitting on that seat for 8 days, 20 hours and 6 minutes.  Yeowch!

For more on Dave’s analytical Race Across America, check out the Analytics of Dave website.