Let’s start by saying that, much to my Welsh parent’s dismay, I’m not much of a sports fan! I’m a technologist who has little interest in watching a ball being kicked or tossed around a field and would much rather view strings of code working together in unison to form the perfect programming gameplay. I do however see a synergy between technology and sports and am both intrigued and excited by the way this relationship is steadily evolving. After all, for athletes competing at the highest level, the smallest factor can spell the difference between victory and mediocrity. That’s why Olympic swimmers began wearing friction-free swimsuits to gain milliseconds on their lap times (until they were banned), and why football boot manufacturers keep pushing the limits of how light and flexible a shoe can be.
But, let’s face facts! If one swimmer can wear a ludicrous spandex one-piece, their competitors can as well. The same applies in football – if one team invests in 20 pairs of 100 gram boots so can every other team.
Optimising individual performance
And then there’s professional cycling, which is where technology comes into play. At this year’s Tour de France, the bikes were equipped with Internet of Things (IoT) GPS sensors that generate live-tracking data such as individual riders’ speed, position within the peloton and distances between riders throughout each stage. The data can then be analysed and served up to cycling fans, broadcasters and commentators, around the world – enhancing the viewing experience and giving fans a closer view of the action.
For the teams themselves, data can also be used to help understand how the above factors are affected by environmental conditions, such as gradient and weather. This allows each rider’s race plan to be adjusted in order to optimise their individual performance (take a look here for the lowdown on the technology used).
So, what does this have to do with running a business?
Today’s leading companies are in a similar position to professional athletes in that the market has become increasingly crowded and competition is so fierce that differentiation is difficult to achieve. Crickey, the cost of even the smallest misstep can be dramatic.
In response, businesses are turning to IoT data and analytics to gain a better understanding of their operations, uncover inefficiencies, and find ways of working smarter to better serve their customers. For example, retailers are pushing for end-to-end visibility of their supply chains so they can better manage a growing number of purchases and returns and meet rising shopper expectations.
Competing with the big boys!
Similar to the way cycling teams combine rider and GPS data to improve performance, this drive for process automation extends to the rest of the business. It offers companies the ability to collectively analyse data from a large range of sources – everything in fact from customer devices to market performance. This, in turn, provides companies the context they need to make sound strategic decisions based on qualitative judgments, rather than just on static numbers.
We’ve also seen that sensor technology and access to information helps small companies compete with the “big boys”. Proactivity is the hallmark of an excellent customer experience, which is why young disruptive start-ups that have built their business models on data access and pre-emptive services are taking market share away from established players who continue to follow more reactive business models.
No one size fits all!
The next frontier for sensor data is machine learning, a form of Artificial Intelligence (AI) that helps companies find new connections and insights in their data so they can incrementally improve the way they work and serve customers. Researchers at Carnegie Mellon University recently displayed how this machine learning might look in a company’s factory floor and earlier this year, Google revealed how one physical sensor – a smartphone camera – can actually serve as a million different software sensors to provide users with a treasure trove of valuable insight.
Machine leaning and AI show enormous promise but, unlike a footballer who can simply lace up his new boots and get back to playing the game more quickly, businesses need to adapt their way of working from the inside out to take advantage of these technologies. There is no one size fits all when it comes to data collection and certainly not with regards to how companies should use the information at their disposal. This is what makes data the ultimate differentiator, and it will be those companies that do their homework and uncover its potential that will set themselves apart.
Originally published in Dimension Data.
