Data-Driven Recruitment: Finding C-Level Candidates Without Looking At A Single Resume

I have widely covered how data and analytics are changing the recruitment landscape. So far, most of the focus has been on filling low and mid-tier vacancies – such as Xerox and their work to find the best candidates for call centre positions. But what about filling the most senior vacancies – the “C-suite” of CEOs, CFOs, CMOs and other chiefs in your organization?

These are the people who are going to guide the direction of the business. They carry a large amount of responsibility and in return often take home a sizeable chunk of a business’s earnings. When mistakes are made appointing people at this level, disaster is a distinct and clear likelihood. So of course it makes sense that filling these vacancies should be done with as little guesswork as possible. Many companies are already taking steps to make sure that the process is

Big Data headhunters

In this post I look at Corporate head-hunters Korn Ferry which have taken steps to ensure c-level recruitment is firmly rooted in data and analytics. The firm has specialized in finding candidates for the highest level jobs for almost 50 years. In recent years it has started to apply Big Data analytics to the wealth of data it has acquired, in order to find the best people for the best jobs.

This has allowed the firm to draw up detailed profiles of the competencies, traits and experiences needed to succeed at the top level. In partnership with data scientists at the University of Southern California the company began to build its analytics-based people placement platform (which they refer to it as the Korn Ferry 4 Dimensions of Leadership and Talent – or KF4D for short.)

Dana Landis, Korn Ferry’s vice president of global talent assessment and analytics, told me “The biggest discovery was that there are some real universals playing out – more than we expected would be the case.” The data revealed some strong patterns about the importance of traits and qualities required for C-level positions, including being a lifelong learner, higher levels of emotional intelligence (for example, empathy), communication skills and a tolerance for risk.

How relevant is experience?

Along with traits and competencies, experience is obviously a core necessity for success in many roles. This can be covered with Big Data analytics too. Comparative analytics can show what skills a person has picked up in previous positions, and which of those they will likely need to carry with them as they move up the career ladder.

Although Korn Ferry has almost 50 years of data gleaned from assessing candidates for high level positions, in order to continue gathering truly Big Data it was necessary to automate the process of data collection, to make gathering the required sample size viable.

This means compressing a complex assessment process often carried out over several days, under controlled conditions, into a 45-minute online test which can be completed anywhere in the world with internet access. Landis told me “When you’re talking about Big Data you’re talking about assessing millions of people all over the world, so you need self-assessment.”

With self-assessment of course come worries that candidates might try to “game the system”, providing the answers they think top hirers will see as desirable. But this is mitigated against by the psychological nature of the questioning – asking candidates to prioritize a number of seemingly equally valuable qualities they might possess.

Are you a good fit?

Another key element which the system is designed to assess is how well the candidate will fit within the culture of the organization. Mike Distefano, chief marketing officer and president of Korn Ferry’s research and analytics arm, the Korn Ferry Institute, told me “One thing I always say is that people get hired for what they know and fired for who they are. So we have spent a lot of time making sure we can check that the person is a good cultural fit.”

Clients looking to fill positions have the ability to choose whether they are happy with their organizational culture – in which case the system will find someone who is likely to fit in – or are looking to change it. If this is the case, then candidates will be suggested who are likely to be agents of change.

But is there one quality – or attribute – that stands out above all others as essential for leadership? Yes, according to Distefano. “If I had to pick one individual indicator of success, then it would be agility.” The data analysis has shown that candidates who score highly for agility also tend to deliver well on delivering increased profitability. His advice is therefore to ‘hire the agile, but check for fit.’

This analytical approach to c-suite recruitment wouldn’t be possible without the predictive modelling and statistical analytics, backed up with huge datasets, that we call Big Data. Korn Ferry uses Amazon Web Services Elastic Compute Cloud (EC2) and Simple Storage Service (S3) for distributed storage and processing. Algorithms are created in-house using open source technology such as R and Python.

Appointing a new CEO is undoubtedly one of the biggest challenges a business will ever face. Most companies wouldn’t make decisions about which products or services to offer without solid data analysis. Is it now time to bring the same in-depth, analytical approach to hiring for top level positions? The claim is that by making the move to evaluating top talent on quantifiable data, backed by comparative analysis, companies can make sure their leadership positions are filled by the people most likely to take the business – and everyone inside it – onward to bigger and better things.

I regularly write about management, technology as well as the mega-trend that is Big Data for LinkedIn and Forbes. If you would like to read my regular posts then please click 'Follow' and feel free to also connect via Twitter, Facebook and The Advanced Performance Institute.

Here are some other recent posts I have written:

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About : Bernard Marr is a globally recognized expert in big data, analytics and enterprise performance. He helps companies improve decision-making and performance using data. His new book is Data: Using Smart Big Data, Analytics and Metrics To Make Better Decisions and Improve Performance. You can read a free sample chapter here.