Fighting hiring bias with data to build better leadership teams

Checking functional knowledge, work experience, and qualifications of candidates are all relatively easy to do when hiring, but the tricky part is making sure that people work well together.

Ott Niggulis

In essence, leaders must marry the functional knowledge of candidates with the existing or newly created team to make sure that competent people fit into the team.

The problem is that as humans, we’re all guilty of biases that affect our everyday lives in ways that we can’t even imagine. The same is true for hiring. When we choose between otherwise comparable candidates, we’ll often choose the one we like more, e.g., the most like us.

While it comes naturally, choosing people you’ll be working with based on personal feelings is dangerous. Just because someone is competent and you like them personally does not mean that they’ll be a good fit for the team.

A team consists of people, plural, and it’s essential to make sure that they all get along.

Fighting biases with data

More and more forward-thinking companies are turning to talent analytics and talent data to get around hiring bias. They are turning generic job descriptions and free-flowing candidate interviews into a strategic tool used to attract the right candidates and compare and score each of them without biases getting in the way.

The process starts by mapping out the position in terms of key objectives, competencies needed to distinguish superior performers, and a list of required experiences, qualifications, and skills.

While this creates some extra work up front, it makes for better decision making later down the line. “It forces you to be crystal clear on what and who you’re looking for. It brings more clarity and objectivity to the hiring process,” adds Tim from a major global manufacturing company.

Next, reliably assessing candidate values, personality, and competencies individually and in a team setting. The key for this lies in using academic frameworks and not random personality tests that a candidate has taken years back.

At Teamscope, we use assessments based on proven academic frameworks, which have demonstrated high accuracy and strong predictive power in various settings and cultures to bring data into understanding person and team fit.

Achieving team fit

Teams come in all shapes and sizes. Some have been working together for years. Some are just starting. And then there are brand new companies looking for their first team members. Talent analytics can and should be used by all as the advantages are the same.

With a newly established company, the question is not about finding team-fit (as there is no team yet) but finding people who work well together with the team leader.

In the beginning, it’s hard to imagine, apart from the functional roles and responsibilities, what the personality and other traits of the people should be.

On this, Tim added, “we initially hired three people and built a team profile around that. We then analysed the profile together with the team and understood in which ways the team is lacking and hired two more people to fill those gaps to make the overall team perform better.”

The same approach works for established teams. It’s never too late to bring data and talent analytics into teams and analyse it to discover what might be holding the team back and how to remedy the situation.

Indeed, this is what Karma Ventures did. They already had an established leadership team that was working well together and was bringing results. Still, after going through data-based team analysis with Teamscope, they discovered aspects of the team that could be improved upon.

Conclusions

As with any other product or solution, team-based talent analytics only works when everyone involved understands what it is, how it’s used, and perhaps most importantly, why it’s used.

Tim agrees. “As with any tool, it’s only as useful as you know how to use it to get the maximum benefit from and people who understand, and appreciate the process value it highly.”

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