Cómo una estrella de la Copa del Mundo fue descubierta usando datos y lo que significa para los reclutadores
Bruce Anderson / Linkedin Talent
El Mundial de Fútbol 2018 ya es historia y Francia es el campeón. Un jugador clave que posibilitó este logro para el cuadro Galo fue el mediocampista, N’Golo Kanté. Lo interesante de su caso, es que fue un jugador que durante mucho tiempo fue invisible para los grandes clubes. Su altura (1,68 mts) era un factor que le jugaba en contra (el promedio de altura de los jugadores top de la ligas europeas es 1,82 mts). Sin embargo, el equipo de Talent Analytics del Club Leicester de Inglaterra se dio cuenta, al analizar los datos de miles de jugadores, que el pequeño volante tenía una impresionante combinación de velocidad, resistencia y anticipación en comparación con otros jugadores. Su desempeño ahora sí está a la vista, tanto así que el ex-jugador Francés y campeón del mundo en Francia 1998, Marcel Desailly, tuiteó hace algunas semanas: «El 71% de la tierra está cubierta por agua. El resto está cubierto por N’Golo Kanté». Un caso real que muestra el impacto que puede tener el análisis de datos aplicado al reclutamiento & selección de personas.
As you and nearly a billion other people settle in to watch Sunday’s World Cup final, pay particular attention to No. 13 for the favored French. He shouldn’t be hard to spot: He will be everywhere at once.
Three years ago, N’Golo Kanté was playing midfield for Caen, a lightly considered team in France’s Ligue 1. He was 24 and his name was on nobody’s lips.
Today, everyone seems to be talking about Kanté, who is an astonishing example for recruiters everywhere of the importance of measuring the right things and the power of using data analytics to recruit.
Why Kanté was overlooked–and how a little data showed he shouldn’t be
In the past, Kanté was overlooked because, frankly, it was so easy to do—he is only 5’6” (168 cm), while the average height of top European male soccer players is just under 6”(182.1 cm). On top of that, he hardly ever scores.
But in 2015, Steve Walsh, a legendary scout and then the assistant manager for Leicester City in England’s Premier League, asked the club’s analytics squad to scour the metrics of all the top European leagues. Specifically, The Independent reported, he wanted see players’ interceptions, tackles, and forward passes per 90 minutes. The analytics group also looked at other statistics that were relevant to Leicester’s style of play. “Kanté’s name just kept cropping up,” The Independent said.
Kanté, it turns out, has a breathtaking combination of speed, stamina, and anticipation that creates the illusion that there are actually two of him on the pitch. Marcel Desailly, the former captain of the French team, tweeted: “71% of the earth is covered by water. The rest is covered by N’Golo Kanté.” And today he has France on the cusp of winning the World Cup. Les Bleus head into the championship match as the odds-on favorite over tiny Croatia.
What this means for recruiters
International soccer may seem completely unconnected to your industry or line of work. But there is a lesson for talent acquisition teams of all kinds in how the the sport has successfully used talent analytics to recruit. What works in soccer, works in business: companies that use people analytics to support business decisions see an 82% higher three-year average profit than their counterparts, according to a study byBersin by Deloitte.
In the same way that a soccer club can benefit from looking at data that goes beyond just goals and assists, talent acquisition teams can benefit from looking at metrics that go beyond time to fill and quality of hire. Dr. John Sullivan recommends seven metrics, including employer brand strength and the performance differential of innovators and top performers, that many data-savvy recruiting teams are already using.
It is critical to measure the right things rather than just the easy things. Fortunately for corporate recruiters, a growing array of tools can help them measure hard skills, such as coding and graphic design, as well as hard-to-screen for soft skills, such as collaboration, grit, and curiosity. This includes tools like Koru and Pymetrics, which provide companies with insights into candidates’ soft-skill strengths and weaknesses.
Tools like this are a game-changer, as our survey of 9,000 recruiters and hiring managers revealed that 63% of them say their biggest issue with existing interview formats is their inability to assess soft skills.
Even after pulling all the advanced statistics together, Walsh found that Kanté wasn’t an easy sell. Leicester manager Claudio Ranieri kept telling Walsh, “He’s not big enough. Why do I want Kanté?”
But Walsh had data that actually explained the young Frenchman’s je ne sais quoi. The Foxes signed Kanté and he led them to their first-ever Premier League championship in what some hailed as “the greatest miracle in sports history.”
The following season, Kanté moved to Chelsea, led the Blues to the Premier League title, and was named 2017 PFA Player of the Year. “Now,” writes an ESPN correspondent, “he is king of the World Cup and a strong contender for best player of the tournament.”
Of course, not all data and not all analytics are created equal. Rory Campbell, a soccer analyst for West Ham United in the Premier League, told The Telegraph: “You can measure everything. The hard bit is working out what’s important.”
By determining what skills matter most for your business and measuring for them, your talent team may be able to find an all-star too.