Combining data with human insight to build the best team

What can businesses learn from how The British & Irish Lions have combined statistical data with expert insight in the official app?

British and Irish Lions rugby team huddling together on the pitch

One of the key features of The British & Irish Lions app is the My Lions function. Users select from a roster of every player from England, Ireland, Scotland and Wales to build their perfect team. 

What makes My Lions different from other sports management sims is that together with EY, the Lions have drawn on more than two years of comprehensive match performance data on every player (refreshed after every game), and combined it with input from some of the world’s top coaches to develop an algorithm that lets you know just how good a team that is, and how good a coach you could make.

In other words, it’s a bit like a sports-based HR simulator — not just comparing individuals’ past performance histories, but also their attitudes, ways of working and how they operate with other team members. Get the balance right, and it should help you to pick a high-performing team. But, as any manager will tell you, picking the best people isn’t just a question of data. 

Building a perfect digital talent picker

The player data collected covers around 150 different points of performance, from speed to number of tackles to average number of points scored per match. This data was weighted to account for certain factors — it shouldn’t be surprising that a prop is more involved in scrums than a player on the wing, or that tries scored in an international match would count for more than those achieved in a club game. Putting data in context was just as important as collecting it. 

Of course, there are some data points that are harder to capture. Player A might be the fastest runner in the world and player B might be the top scorer, but if they personally do not get along, then their performance on the same side is going to be less than the sum of its parts. 

To counter this, EY consulted with two of rugby’s top pickers: Scotland’s Sir Ian McGeechan, previous head coach of the Lions, and Tim Horan, who was part of two Rugby World Cup winning Australia squads. With their expert input, the development team could further weight the algorithm to take into account these less quantifiable factors.

The algorithm can then be used to give users a score on how good their selection is when measured against the data. But while it can certainly teach you how to pick a better squad, can data turn your average Joe into a world-class manager? Well, not exactly.

Why managing people needs a human touch

The development of the My Lions function offers a crucial insight about applying data to the art of people management. There are huge swathes of human behavior and interaction that cannot be quantified and turned into data points. Although data can certainly help, sometimes it takes human intuition to understand other humans. 

Perhaps, in the future, biometric sensors that capture increases in heart rate when two particularly antagonistic colleagues talk to one another will provide a statistical foundation for analyzing interpersonal relations. Psychological tools, such as Myers-Briggs tests, already do this in a limited way. One day, perhaps ever more sophisticated tests will show the way toward ever more refined ways of modeling interpersonal dynamics. But, for now, aspects of work, such as team spirit and ability to cooperate, lie beyond the reach of pure number crunching. 

Of course, even with measurable data, there’s always the danger of this driving performance rather than the other way round. Everyone is familiar with underperforming colleagues choosing favorable metrics while ignoring meaningful KPIs. An overreliance on data and algorithms can encourage this.

Data can also push leadership into applying the wrong solutions to a problem. Growing your social media team may seem a good way to manage an influx of negative social listening data, but risks ignoring underlying causes of customer discontent. Perverse incentives abound when handing too much control over to decontextualized facts and figures.

Of course, this isn’t to say data tools aren’t incredibly powerful in the right hands. But this is what’s meant when people talk about data and machine learning augmenting, rather than replacing human expertise. A world of entirely robotic HR managers (or coaches) would be one of warped, myopic business strategies (and locker rooms full of punch-ups rather than planning). You still need humans behind the wheel. 

This is why effective people-managers often first use their intuition and expertise to make the decision, and then let the data support or refine it, to question and challenge their assumptions, rather than the other way around.

Data is a powerful tool, but only by pairing it with human insight can it truly deliver on its promises.

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