At swim practice, three-time Olympic gold medalist Nathan Adrian torpedoes down the pool in his signature freestyle – peculiarly – with dots pasted all over his body.
Before diving in, Adrian straps LED sensors to his body. After his swim, he uses the data they amass to analyze his form.
It’s brand-new technology, designed exclusively for the US National Swim Team, that takes root in autonomous vehicles. Video software uses the sensors on Adrian’s body to track his every movement (down to the angle of his toes) and renders them into two-dimensional images.
These highly detailed images allow swimmers to spot even the smallest of irregularities in their form. And for professionals like Adrian, correcting them can shave off a crucial millisecond of swim time.
The advantage of this stretches far beyond just his individual time. Because when he executes a move perfectly, trainers are able to pinpoint exactly what was right with the technique and teach other swimmers to replicate it. This way, all members of the US National Swim Team benefit from Adrian’s data collection, seeing the strengths of some being made available to all. What can this teach us about sales intelligence?
According to Andrew Small, High Performance Advisor for the John McEnroe Tennis Academy, data is not optional, it’s a way of life. “Before I take on a client, no matter how high profile, no matter what their past record shows, I look for data combined with analytical technology to find my opportunity. Data, the individual, combined with team data or in the context of where the sport is going, analyzed by machines guides my interventions. Time after time, the results are astounding.”
Small’s approach was on display at the 2016 Rio De Janeiro Olympics where the world watched with awe as a seemingly unstoppable US Swim team lay waste to the competition. 19-year-old Katie Ledecky won 4 gold medals and is now known as the “greatest female athlete alive.” Michael Phelps, thought of as a has-been, silenced critics after winning 5 golds. The US dominated the medals tables, amassing 16 golds. 13 more, by the way, than Australia’s team which ranked second.
This suggests that data, whether sports or sales intelligence, can be an incredibly powerful tool when in the right hands. And such a nuanced slant on team building is what Tad Martin, CEO of Collective[i], envisions for the future of B2B sales. The buying process has changed, he explained, and it is now down to sales organizations to adapt alongside it.
“It isn’t just about leveraging the individual contributor,” he says, “but rather, picking the strengths that help you perform better as a team.”
This has to be the case, especially with the huge number of platforms and content avenues available to prospective buyers that have made their journey anything but predictable. It means you really have to think about what channels, which format and for which phase of the buyer’s journey it is suitable to deploy a certain individual’s skills or expertise.
Either way, gaining that deeper understanding of the buyers you are serving and their journey to final purchase, described as a ‘circular journey’, could be the key to maximizing the impact of a sales organization.
There are four primary phases representing potential battlegrounds to either win or lose: initial consideration; active evaluation, or the process of researching potential purchases, and finally, closure and post-purchase.
Really understanding which stage buyers are at on specific devices makes a palpable difference.
New technology is facilitating the implementation of this strategy, for capturing both sales intelligence and sports performance data. Technology is more widely available to managers than ever before, not only as incredibly complex customized solutions but also as finished applications that are ready to use right out of the box.
Compiling and analyzing sales intelligence among team members benefits the team as a whole. In sports, not only does data allow team members to learn from their teammates’ best techniques, but also allows coaches to identify and capitalize on players’ individual strengths.
Take the German National Soccer Team, for example, in the 2014 FIFA World Cup. SAP arguably had a part to play in their lifting of the trophy. Players were exposed to new big data applications that aided in determining the strengths and weaknesses of opponents.
In the locker room, the German players and coaches could use the applications to learn how their opponents would line up, and then switch up their own lineup to better combat their opponents.
This analytical approach to team building is being applied across a lot of sports now, says Martin. Increasingly, the attitude is “let’s put together a team of people who may or may not have that star power, but together can win.”
This is true not only in sports but in B2B sales too. In a landscape where 88% of missed sales opportunities are caused by a failure to leverage resources such as internal sales intelligence, this strategic tailoring could be revolutionary.
Improving team selling makes a lot of sense to people philosophically, says Martin, “but without the information and analytics and the data to help them understand what they should do, it’s still an uphill battle.” Thus new sales platforms like Collective[i]’s provide crucial help to sales teams, just as new analytical tools provide such crucial help in sports.
The popularity of this strategy really all started with the true-life story of Moneyball, which depicts impoverished baseball team the Oakland Athletics in 2002. After having star players poached by wealthier teams, General Manager Billy Beane hired an Economics major straight out of Yale, Bill James, who happened to be a disciple of sabermetrics – the empirical analysis of baseball.
Because of James, Beane put data and analytics at the core of his game plan. There was no physical bias against the players brought in, from the seemingly lesser young to “washed-up sluggers”. As long as they espoused strong sabermetric values, they were in. And it paid off: the Oakland A’s went 20 games without losing. For baseball at least, this had never been done before.
This analytical approach has since spread to top-notch athletes like Nathan Adrian and Manuel Neuer (the German men’s soccer team goalkeeper) who, when equipped with this data, can collaborate with their teammates in a way that allows them to achieve more together.
In sports, star players – individual contributors – can only do so much. And this sentiment also holds true for great salespeople. Martin explains, “The best salespeople almost always have the best networks. What they do is leverage these networks in order to help them to succeed. They reach out to those they know within the company to find out more information, and better prepare themselves, which ultimately will lead to greater success.” Evidently, ‘collective’ sales intelligence lies at the heart of Collective[i]’s philosophy.
For a sales manager, leveraging great networks magnifies the possibilities. As Martin says, in knowing “who is great at developing relationships, who is best at explaining the product and its value, and who is great at negotiating,” a sales manager can curate the ideal sales force for a particular task at hand.
Such a collaborative environment, as shown by the Oakland A’s, Team USA and the German national soccer team, increases the chances of success.
Seeing sales as a team sport just require a paradigmatic shift. A move away from individual numbers, metrics, and quotas – things traditionally billed as the beacons of success – and replacing them instead with an amalgamation of all the best attributes of teammates.
By asking the question “Who can best help us achieve that goal?” you can start applying analysis not just of individual success but of teams as a whole.