>>The Ultimate Recruiter’s Guide to the People Analytics Debate (And How You Should Use Them)

The Ultimate Recruiter’s Guide to the People Analytics Debate (And How You Should Use Them)

People analytics has been a big term in human resources (HR) and recruitment circles lately, but it’s kind of hard to define. Turning people into numbers, and then claiming to be able to predict their behavior based on those numbers, is a practice that has a tendency to seem unreliable.

VoloMetrix provides a definition of people analytics that explains how expansive the term really is:

People Analytics is the use of people-related data to optimize business outcomes (and solve business problems) at the individual, team or organizational levels. This is a pretty expansive definition, but we think People Analytics is a real ‘category,’ with applications across all parts of the modern enterprise.”

The term envelops any type of analytics that are related to your people. For recruiters, this means people analytics can cover a variety of topics such as skills testing, personality assessments, performance benchmarks, source of hire, cost of hire, and any other metric that is related to a hire’s potential success.

These analytics can be as expansive as tracking organizational wide happiness with a monthly survey to the size of the plates your employees eat from – Google famously tracks this metric, along with other granular decisions to keep their ‘happiness’ metric as high as possible.

If you don’t have the computing power that Google does, whether or not this data is reliable is a bit controversial. The reality is that it depends on the data you’re actually crunching.

This disparity between whether or not people analytics “really work” becomes clear when you start to ask professionals whether or not they’re talking about cognitive ability and skills as opposed to demographics and culture fit.

We can predict some employee behavior, but not all of it. Crunching cognitive and skills datais easypredicting happiness, retention rate and personality fit is not so easy.

Good recruiters leverage people analytics successfully, and they do it because they know where to look, what to track, and what the numbers actually mean.

We’re taking a dive into people analytics from the recruiter’s perspective: what’s the state of people analytics today, what should and shouldn’t you rely on people analytics for, and what’s the number one most important people metric for recruiters to know.

The State of People Analytics in the HR world Right Now.


HR departments aren’t using the data they have available to them, but they want to be – people analytics methods just haven’t been very widely adapted to their full potential yet.

Deloitte University Press released enlightening statistics on the state of HR analytics in their report,Global Human Capital Trends 2015.

The report summed up three major points:

  • Not enough people are using people analytics, and it’s hurting their bottom line.
  • 75 percent of the industry believes that people analytics are important, but only 8 percent think they’re leveraging them well enough.
  • Companies that use people analytics knock out the competition in quality of hire, retention, leader capabilities and employer brand.

For HR in general, people analytics is their largest overall capability gap, meaning there is a lot of unused potential sitting in people analytics.

The chart below shows the capability gap by country. The score is computed with two metrics – how “ready” a country is to use these analytics and how “important” they are to that country. The importance score is subtracted from the readiness score to reveal the region’s capability gap.


The U.S. in particular is pretty behind, with Deloitte University Press reporting a capability gap of -34.

This could be in part because HR departments that are currently using people analytics don’t think they’re doing a very good job – there is an overall feeling that the data isn’t used to it’s full potential.

The chart below is an internal evaluation of respondent’s own performance using data across different HR categories. They rate themselves from not applicable to excellent, with the majority claiming their use of data was weak across all categories.


The consensus among the recruiting watercooler seems to be that this is because people analytics are rather new. Because they’re new, recruiters have to wait for the right technology to be implemented or until enough data is collected to gain valuable insights.

This is true – for the most part.

Myth Buster: People Analytics Aren’t New

Using metrics for recruiting purposes is essentially the practice of taking data on current employees, and using that information to make determinations about a prospective hire’s possible performance.

The idea that we can use information on current employees to make predictions about candidates is not new – it’s the mass amount of data and accuracy that’s new.

“People analytics have been around for over a century,” Harold Kaufman, a professor at the NYU Tandon School of Engineering said. “The big difference is the emergence of powerful computers that can churn out results very quickly and our ability to use text information.”

Kaufman has extensive experience working with, studying and teaching people analytics – he’s Professor of Management in NYU’s Department of Technology Management and Innovation as well as the Academic Director of the Organizational Behavior, Systems and Analytics Program.

“We’re essentially talking about algorithms versus equations,” Kaufman said.We’re all talking about the same team – quantitative techniques to find the best person for a particular position.” 

Kaufman told me that predictive analytics go back to biographical data, or bio-data. This is an assessment of who performs best based on biographical data – information collected in most cases from a questionnaire.

Now we use computers and massive amounts of data to track and learn this information – but what exactly are we tracking?

The People Analytics that Really Matter Effect Your Bottom Line

Data that matters is data that effects the organization-wide bottom line –  and it’s generally a CEO-level issue. Below are a few that stick out across the industry:

These high level metrics act as frameworks for HR departments so they can best track performance on a high level. With this new focus on big data, the actual metrics themselves get a bit more granular.

Metrics Description
Understanding and Predicting Retention The practice of tracking how and why people either choose to leave or stay with a company.

This is top priority as companies struggle to retain top talent.

Boosting Employee Engagement Tracking employee happiness and performance.

Changing behavior among mangers is a little bit harder to predict.

Sales and Customer Service Using top sales and customer service employees as benchmarks for which to compare candidates.

This helps recruiters better decide who to hire.

Expand Sources of Talent and Improve Quality of Hires Organizations want to better understand the hiring process to prepare themselves for the future.

This metric is why no one conducts more than four interviews anymore, but it goes deeper than that.

*General information from the People and HR Analytics and Human Capital Trends 2015 report by Deloitte University Press. 

Now is the time to focus on talent analytics,” Josh Bersin, Founder of Bersin by Deloitte wrote in Forbes. Our clients are working on many high-return applications which apply to nearly every business

Some of those applications include a deeper dive into the metrics described by the Deloitte University Press. Bersin described those metrics in his article as follows:

  • Employee retention – what creates high levels of engagement and retention?
  • Sales performance – what factors drive high-performing sales professionals?
  • Accident claims – what factors and which people are likely to create accidents and submit claims?
  • Leadership pipeline – who are the most successful leaders and why are some being developed and others are not?
  • Loss analysis – why are some locations more prone to theft and loss and what causes the variation?
  • Customer retention – what talent factors drive high levels of customer satisfaction and retention?
  • Expected leadership and talent gaps – where are our current talent gaps in the organization and what gaps can we predict in coming years?
  • Candidate pipeline – what is the quality of our candidate pipeline and how do we better attract and select people who we know will succeed in our organization?”

Does tracking these analytics actually work? Data always allows us to see trends and informational patterns, but it’s more effective in some areas than in others.

Recruiting Has Gotten Better: We Can Predict a Candidate’s Success with Relevant People Analytics


We can predict candidate’s performance based on their cognitive abilities and skills – and possibly other factors to a candidate’s success that are easily testable.

Ivan Casanova, VP of Marketing and Product at Jibe says that people analytics are an algorithm issue, but that we can predict employee actions based on those of the best performing employees.

“Predicting the success or failure of a hire is completely in the realm of the technology we have,” Casanova said. “A higher percentage of employees nowhave performance reviews, and they’re not just anecdotal. These can help us predict fairly well what good performance will look like.”

Some of this information comes from past performance reviews, others from skills tests in the hiring process, but we know that this information can reach the highest level of value for an organization – a category called predictive analytics.

Josh Bersin of Bersin by Deloitte shares his Talent Analytics and Maturity Model on Forbes:


If we can predict the performance of candidates coming in through the funnel, then we can project the impact those specific candidates will have on an organization’s bottom line.

Ilya Breyman, Managing Director of Talent Equity Ventures specializing in HR Technology supports the power of predictive analytics in anticipating employee actions:

“We are in the world of big data,” Breyman said. We can predict how a specific employee will perform – it’s a matter of collecting and leveraging the right types of data and ensuring data integrity.”

The “right” depends on your organization. One of the ways recruiters are collecting data is by testing the skills and cognitive abilities of possible candidates against those benchmarks – and it’s effective.

 “Cognitive ability and knowledge are the most common skills test,” Kaufman said. “This goes along with a general mental ability test. These have a pretty high validity for predicting high-level complex problems. 

According to Kaufman, the more complex the problem or position, the better the use recruiters can get out of skills testing. With these insights, they can determine who is going to stay with their organization and who won’t.

Case Studies: People Analytics are Already Improving Recruiting

Analytics are already changing the business landscape in a big way, both for individual corporations and for the industry as a whole.

On an individual corporate level, analytical data has helped a major Russian corporation scale their recruitment at very fast speeds using a common recruiting metric – source of hire.

Breyman often notes a successful Russian company – Knopka – in the people analytics course he teaches on Coursera. Knopka was outsourcing accounting and administration support for companies – they were growing fast and needed a lot of accountants to support their clients.

They were originally using the traditional recruiting funnel which included posting ads on recruiting sites, conducting interviews and then onboarding candidates, but they were not filling positions fast enough.

They used data from several different sources to help cut their recruiting funnel into three steps: post the job advertisements, invite candidates for a group interview or observation and then conduct final interviews before a hire.

They measured how many people they were getting from each channel and where they should spend their money most efficiently. This allowed them to scaled their operations and increase hiring at a velocity they needed.

On an industry-wide level, we can now make definitive statements about the application process.

With analytics taken from the candidate experience technology platform Jibe, we can now show a direct correlation between the time it takes to finish an application and its completion rate.

Customers of Jibe are comfortably told by representatives universally – the shorter an application is the better.

Skills and hard recruitment numbers are just a piece of the pie. Personality and company culture fit matter greatly for an employee’s success within a company, but these metrics are a bit harder to track.

Crunching Data Surrounding Culture Fit and Personality Just Isn’t Reliable (Yet).


The Harvard Business Review said it best – the fact of the matter is that the strongest predictor of a person’s future behavior is their past performance itself.

The best way to evaluate a person’s performance is with a person – a manager or co-worker who knows that person well and can evaluate their past performance within context of certain situations and a wider view of their responsibilities.

Sometimes this context includes factors that aren’t so easily able to be described by data. An employee’s personality, background, and personal life might affect his performance in certain cases – it’s always subjective.

Even some of the strongest supporters of the power of people analytics note the weakness of data in areas such as demographics, personality and emotion.

While Casanova clearly believes in the power of analytics, he noted their lack of development when it comes to demographics:

“Given the role HR and recruiting plays in an organization, I don’t think we want to parse demographics,” Casanova said. This is not what machine technologies are good at, and we shouldn’t even try.”

According to Kaufman, our analytics professor from NYU, the effectiveness of skills tests has been proven with cognitive abilities and skills, but not so much personality and company culture fit – and those are important factors.

The “soft” points of data about a particular candidate are hard to describe with data, but recruiters are coming up with different ways to account for this gap.

One popular recruitment technique is the use of company referrals. Happy employees that refer potential candidates have the best chance of finding a good culture fit, background and personality for their company.

According to Breyman, referrals are often a favorite because they bring in people that are a great fit for the company culture.

There are other sources of hire that can help close the gap between both a candidate’s cognitive skill set and his or her personality and culture fit for a particular role.

The Number One Metric for Recruiters: Source of Hire


Because it’s the one metric that allows these two sides of the people analytics coin to overlap, source of hire is one of the most important metrics for recruiters.

We’re not the only ones who think source of hire is the number one metric for recruiters – Casanova agrees. According to Casanova, this has to do with cost, and the fact that source of hire also effects the quality of hire metric.

“This is completely achievable with the technology out there,” Casanova said. “Recruiters will invest more money in any channel if it’s doing well, regardless of cost.

While we might not be able to analyze people down to numbers and data, we can use analytics to refine recruiting processes based on relevant insights.

What about one of the most costly channels out there – direct hire recruiting agencies? Even after many declarations that agencies would disappear, these recruiters are still doing very well. Recent data shows the marketplace flourishing as more and more recruiters join the scene.

Direct hire recruiting agencies do well because they provide quality and bandwidth that in-house recruiting teams don’t have the time to dedicate and track themselves.

Organizations are willing to spend more on them for higher-level positions critical to their organization, because they produce good quality hires, simply by bandwidth alone.

“Recruiting agencies do have a role to play, but they’re highly specialized,” Kaufman said. “They know their clients very well, and they often have a track record in effective placement.

You (recruiters) should still use the techniques you refine along with yourrecruiting companies. They go hand-in-hand – we need the people as well as the analytics.”

Whether we’re talking about referrals (according to  Kaufman, the most sought-after recruiting method), recruiting agencies, job boards or another source of hire – companies will use the channel that is most effective no matter what the cost.

But the source only matters because it’s the most effective one for you. In people analytics, source of hire is the most important metric for recruiters to track because it encompasses both side of a candidate – both their sift and hard skills.

While the use of people analytics is still not quite developed throughout the HR world, it’s clear they’re having a visible impact on both the industry as a whole, and individual corporations.

We can’t crunch number surrounding your entire organization’s employee population, but we can give you insights into how your agencies are working for you. If you’re interested in the insights we have to offer, check out our marketplace.


By |2017-07-28T16:37:54+00:00December 16th, 2015|Categories: Talent Acquisition Trends|Comments Off on The Ultimate Recruiter’s Guide to the People Analytics Debate (And How You Should Use Them)

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