Recruitment is All About Data. Here’s Why

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Years after Moneyball was published, recruiting is finally adopting a numerical model for assessing talent.

Coupled with the new wave of recruiting technology which also runs on numbers, no firm will be able to escape data-based recruiting decisions. Dynamic, rapid change is not something we traditionally associate with corporate recruiting, but buckle your seat-belt, because it’s happening.

Market cap leading firms like Apple, Google, Microsoft, Amazon, and Facebook continue to be the examples to which every CEO aspires. But while other firms try to follow their lead to become digital innovators, the average corporate recruiting process actually scares away the most forward-thinking and ground-breaking candidates.

Technology and robotics will begin eliminating many jobs at all levels. This will obviously reduce the need for many recruiters, while at the same time, require any remaining recruiters to focus on attracting hard-to-find and hard-to-sell technologists in every business function.


The shift to a data-based decision-making model takes off faster than ever before. Google’s success with harnessing candidate data to become the number one employer brand has led other corporations, like Sodexo, to join the analytically driven world of business.

Among the many weaknesses, this data has revealed is the failure rate of our hiring systems, which can often reach 50 percent. College degrees, the school you attended and your grades are not the accurate predictors of success we thought they were. Data has also revealed poor hiring assessments can lead to up to 80 percent of employee turnover, according to the Society for Human Resources Management (SHRM).


Recruit-tech software and hardware eclipse tradition – Software algorithms are about to take over recruiting. Most of the new recruit-tech innovations will involve the use of software algorithms to find, attract, maximize diversity, sort, match and assess candidates. Recruit-tech hardware in the neuroscience area will improve interview assessments and it can already show us how to improve the readability and attractiveness of posted materials. All these systems are data-driven, so they will not only be more accurate initially but continually improve as they learn from each and every error.

Prove your results or your approach will be dropped – Under traditional corporate recruiting, programs could remain operational for years without being challenged. However, under the new data-driven model, approaches and tools (e.g. sources, screening criteria, interviews, reference checks and brainteaser questions) with a questionable validity will simply be stopped. They won’t be reinstated until they can prove that they have a positive impact on the performance level of new hires.

Quantify your business impacts in $ – The language of business is dollars, so existing recruiting programs will no longer be fully budgeted unless they can show that their direct dollar impact on strategic business goals (i.e. new hire performance, revenue, innovation etc.). This also means that recruiting results will have to be reported in their traditional numbers but also in their dollar impact on corporate revenue.

Focus on innovators – The extremely high market valuation placed on serial innovation firms like Apple, Google and Amazon show the value of innovation over efficiency and productivity. The value of a single innovator may be two-and-a-half to 30-times higher than a high performer, so firms need to develop data-driven processes that are designed specifically to identify, recruit and retain them.

Concrete, prescriptive solutions are here to stay – Currently when there is a major recruiting problem, recruiters, and hiring managers are forced to utilize intuition and guesswork to find the best solution. This often causes delays and potentially, the application of the wrong solution. The new model will require providing prescriptive solutions that tell managers what to do next with some reasonable degree of certainty that the selected solution will work.

Look to the horizon — Managers want crystal ball metrics – 100 percent of traditional recruiting metrics are historical but executives want to know about the future, not the past. Newly developed metrics in recruiting will be predictive, from the career trajectory of new-hires to the positions they will need to be filling.This is the age of the algorithm: harnessing data and drawing strong conclusions from it is the future of the industry. As we shift our focus to more predictive and prescriptive models, be supported by strong data and analysis, lest you’re left in the dark ages.

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About the author

John Zacharakis
By John Zacharakis
Director of Data Products at Censia. "Information Management Architecture, in all its many disciplines, is my passion."