Analytics and Big Data Drive Olympic Success

Analytics and Big Data Drive Olympic Success

Last week, while watching the Olympics, I read a very interesting article in Forbes about the success of the British rowing team—a team that has won at least one gold medal in every Olympics since 1984, including three golds and two silvers in Rio—and how they use data and analytics to drive success.

For starters, they collect “every bit of data available” on each athlete, current and historic, to look for patterns that can point to better training regimens and greater competitive success. They look at past data on workouts and performance gains to figure out the optimal balance of strength and endurance training. And in the process, they’re also reducing the number of injuries and the length of recovery times. In all, they’re turning to data to find out exactly what works, what doesn’t, and why.

Does this sound familiar?

Great Britain’s rowing program, with its emphasis on figuring out which effort triggers which result, sounds very much like the marketing attribution analyses that I see our customers doing today. Given hundreds of marketing “touches” or activities, which activities contributed the most to closing the sale?

And there’s a predictive element as well. The rowing team is trying to determine which elements of a training program will take an athlete to the next level of performance. A typical corporate data initiative might try to figure out how to motivate your next purchase. For the rowing program, it’s how to enable the athletes to make the boats go faster.

Does this sound even more familiar?

Here’s line that had me nodding as I read:

“We found ourselves working silos,” says Sir David Tanner, who has lead the Paralympic rowing programs since 1996.

This is probably the main problem all of our enterprise customers face today, often on an Olympic scale. I’ve written about that challenge at length, and the need for enterprise-wide integration, so this time I’ll let Forbes lead the charge:

“In common with businesses trying to get to grips with the potential that analytics can unlock, sports teams are finding that a holistic approach to data management and strategy is likely to pay off.”

On data that’s broad, not big

It doesn’t sound like the British rowing team is dealing with huge data sets—certainly not on the order of a multinational corporation or a regional healthcare provider. What makes a “big data approach” work for the rowing team is more that they’re dealing with so many different data sources: training, nutrition, performance on the water, medical, biomechanical ….  Big data technologies are very well-suited for enormous data sets, but they’re also great for very large numbers of data sources. The advantages of a big data analytics approach include:

  • You don’t have to spend the time up front creating a data model for all of these data sources. You can ingest data into a data lake with minimal or no preparation up front.
  • You don’t have to worry up front about what questions will be asked. With a data warehouse, you generally need to create a design to answer a question. Big Data provides far more flexibility in that regard. You can create a model view of the data that is specific to the analysis you are running.

But despite the “dump it without prep” hype, to really get value out of a data lake, you have to have a plan for tagging, modeling, and providing meaning and context to your data to make it usable. Much of that rowing data would do little good if you couldn’t attribute it to a specific athlete, for instance. In a business environment, failure to contextualize data could render the data lake all but useless, or at least contribute to the common situation where analysts spend 50 percent to 80 percent of their time doing data prep instead of deriving useful business insights.

Let’s bust a myth:  Data lakes do not remove the need for data management.  In fact they might require even more data management.  But they do let you do just the data management you need to do for your specific initiative.  The advantage is flexibility and speed.

Data Lakes Are Proving Their Worth

At first, a story of analytics at the Olympics may not seem directly relevant to business, but on taking a closer look, it has very similar challenges and opportunities to what we see successful enterprise customers doing with Big Data and analytics today. It’s another proof point (or rather, three gold and two silver proof points) of what you can do when you integrate silo-ed data and manage it to deliver useful business or sports insights.

For more on the power of a well-managed data lake in the business realm, download our extensive ebook, “The Marketing Data Lake.” At just over 200 pages, it delivers real insight into using data to focus marketing spend and drive record-setting results.