We live in a time when almost all facts can be expressed in data. This enables us to create vast amounts of links and to recognize correlations with corresponding underlying assumptions. Without a doubt, data is a crucial source of input for decision-making. This, of course, includes data in executive search.
The use of data in the field of HR has many facets. One example: profiles on social job boards like LinkedIn are constant companions to our careers. Here, many data points in a candidate profile help us to find relevant candidates as quickly as possible.
Most users, however, stick to the minimum details like employer, title, and location. Other helpful data – such as an exact role description with keywords, a personal summary, details about customers and projects – is not necessarily always mentioned.
Yet, these are all factors that are highly relevant in executive search – especially when job titles are becoming increasingly individualized and difficult to interpret.
In what way is data useful in executive search?
Data offers insight into dynamics and links that might otherwise remain abstract. In a world with the increasing availability of data, it’s essential to understand, select, interpret, and analyze it.
On the organization's side, data helps to make better, more transparent decisions that are easier to justify and understand. Data also allows to react to trends in HR as well as to get a clearer sense of the skills that are needed in potential candidates.
On the candidate’s side, using data is an opportunity to improve employability and strengthen their negotiating position – since mapping out special skills and qualifications can create or increase personal branding.
Data can also be a useful control mechanism for a phenomenon known as 'confirmation bias'. Successful decision-makers often presume that they are right – after all, their success confirms it. While their careers advance, their environment reinforces this assumption. As a result, leaders may value their instincts more than external information when looking for a suitable candidate. This is where data comes into play.
What are the limitations of data-driven executive search?
Data only adds value when it is put into context. Otherwise, you are looking for the literal needle in a haystack.
The candidates who stand out are often the ones who share the most about themselves. The issue with this, however, is that they are relatively easy for anyone to find and thus very likely to receive many requests from headhunters.
But just because a candidate makes it very easy to find them – with lots of pictures, keywords, and reviews – it can't immediately be concluded that they are the best candidate for the job.
What is frequently overlooked is that some potential candidates deliberately give only minimal information in their profiles or use unusual abbreviations for titles. This means that they are rarely contacted. Finding and considering them requires well-thought-out search strategies, supported by comprehensive data models.
How can a data-driven executive search be implemented?
To use a data-driven approach to executive search, the first step is to define a clear goal before collecting data. This is typically a derivation of the requirements for the candidate we are looking for. Here, the emphasis could be on professional stages and fields of activity, which allows to specifically address people who match this search pattern. Keep in mind that many employees want to move ahead and therefore want to be found for the next career step, not the current one.
An indispensable factor is the expertise of our team, which provides decisive clues for the right characteristics and keywords. These can then be translated into specific search requirements that are systematically processed.
Then, handling large sets of Boolean string operators is part of the execution – but it takes a lot of experience to phrase these strings correctly so that you don't overlook any relevant candidates.
Generally, basic knowledge about the possibilities of processing data and which criteria must be used for the data are, in my opinion, important skills for managers so that the overall strategy is coherent. After all, data is not an aim in itself and cannot do without informed, experienced human interpretation.
Samuel is a structured and strategic Executive Search consultant at Nordic Minds with key skills in knowledge management and experience from two Global 500 companies. You can contact him via mail here .