How data analytics can make hiking easier and biking greener
Leisure activities, such as hiking, and cycling benefit from big data
In its now famous report, Big data: The next frontier for innovation, competition, and productivity, the McKinsey Global Institute (MGI) looked at numerous business sectors to determine their big data environments and potential. According to the consulting company's research, the sector that includes "recreation" has the lowest amount of stored data at 150 terabytes per employee among the 17 markets analyzed. (Not surprisingly, financial services tops the list at 3.8 petabytes per employee.) This situation seemingly would make enterprises in the leisure business unlikely candidates for big data solutions.
However, in MGI's heat map analysis of those markets, customer intensity in the recreation segment is ranked higher than in financial services, giving it the highest potential for value. Recreation consumers, it seems, want the potential benefits big data-based services offer. The good news is they're already getting them.
One leisure activity that is definitely benefiting from big data is one of the simplest recreational activities possible: hiking. While a few austere explorers venture like John Muir into the wilderness with monk-like gear, provisions and information, most hikers are outfitted with plenty of durable lightweight modern equipment for their treks. Perhaps most important, they now apply big data tools for their outings.
When Google released version 5.2 of Google Earth, nature enthusiasts came to call it the Hikers Edition because of all the tools it gave to wilderness backpackers in helping them prepare for their hikes. And it offered them the ability to input data after their hike to recreate their adventure for friends. The Sierra Club offers online lessons on how to use Google Earth to create a trail map.
Cyclists also consume data in big ways. They, too, plot rides on Google Earth. But because of the value of cycling in maintaining air quality and easing road traffic, governments use data to encourage more people to ride to work as well as to cycle for pleasure and health. In the United Kingdom, an independent organization called Cyclescheme promotes data on everything from the daily CO2 saved from using a bike to the amount of calories UK citizens burn each day while pedaling.
Even consumers who enjoy their leisure while watching sports on television are being exposed to the benefits of big data. In the U.S., baseball is a game loaded with data. Every pitch and its result is charted. That information is being used in new and daring ways.
Indeed, during a recent telecast, the game's announcers were marveling at how one team, the Tampa Bay Rays, had elevated the use of data "to a new level." The Rays manager has fully embraced the use of big data and uses it to position his defense in the field for ground balls not based on tradition or his "gut" feeling like most managers. Instead, the Rays apply a defense-deployment model based on how a given batter will likely hit the ball in a given baseball park against a particular pitcher in certain weather conditions with or without runners on base while facing a range of balls and strikes, etc. The complexity of the model impressed the announcers. More important, the Rays have had the best defense for ground balls in the America League since they embraced the new strategy.
While analytics may not be widely considered "fun" among those seeking recreation, it is quickly becoming a part of our good times. And we should enjoy it.
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