Guide to People Analytics

The Definitive Guide to People Analytics

What is People Analytics

Since 2012, HireRoad Co-Founder and CEO, John Pensom, has been defining people analytics as:

Using both people data and business outcomes data to make smarter people and business decisions.

Let’s break that definition down into 3 components.

First, people data might come from any or all of the following.

Second, business outcomes data will also come from a variety of forms like:

Third, this combination of people and business outcomes data must be applied and continuously used for making decisions in the business.

People Analytics will help companies:

  • Make smarter hiring decisions
  • Identify and retain key talent and
  • Drive ROI and invest the most impactful HR and talent programs


See how People Analytics helps HR focus on Value

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People analytics, HR analytics, talent analytics or workforce analytics?

People analytics was and is sometimes referred to as HR analytics, talent analytics or workforce analytics.

Up until about 2014, these various terms were somewhat interchangeable – used by early vendors trying to mark space and name the segment. It was at this time industry analyst heavyweight and long-term proponent of data-driven HR, Josh Bersin, weighed in and colloquially anointed the space People analytics.

While the people analytics category of HR tech was emerging in the 2012-2015 period, data-driven HR had been around for a while but having a people analytics function was still pretty much an anomaly within most organizations. During these early days, when people analytics was part of HR it was typically played out as a niche (and often one-off) activity by individuals with technical skills and an interest in data. People analytics was growing but it was not yet a widely practiced discipline.

What was happening during this time however, was the coming together of a number of influences that helped make people analytics an imperative for HR:

  • People data was starting to be considered of much higher value in organizations given the war for talent, the high proportions that we spend on “human resources”, and that CEOs were becoming more and more convinced and vocal that people were/are their most crucial asset.
  • Sources of people data (candidate and employee) were rapidly expanding and this data was more accessible due to cloud-based apps being bought by HR, in addition to more advanced data management, integrations and APIs.
  • HR tech vendors jumping on the bandwagon of analytics claiming they offered people analytics solutions.
  • Nearly every HR tech vendor started to claim they had people analytics, big data and predictive in an effort to pump valuations and ride the marketing wave but caused tremendous noise and marketplace confusion. In reality, most of them didn’t have anything beyond single dimension reporting on the data which their transactional system generated – a far cry from people analytics. All but a few of these claimants were transactional HR systems and therefore, did not employ one of the most crucial components of any people analytics technology – an HR-specific data warehouse for optimizing the complex structure of multi-sourced HR data.

The result is that HR started to have more data and more systems – but they weren’t able to move beyond single-dimension reporting on the data isolated in their transactional systems.

This leads us to what we call the universal problem in HR.

The Universal Problem Related to People Analytics

Deeper Dive into the Universal Problem

  • HR and people data are everywhere – largely stuck on islands (i.e. your transactional HR tech). 
  • Not only is that HR tech landscape continually being expanded with new systems and additional sources of rich data, there’s no real plan to have a bridge across these islands – or unifying the data into one single view of the truth. Essentially, these islands of HR data are accelerating in their disparity and in the volume of historical data they are collecting.
  • This disparate HR data could and should be used to make better people and business decisions.
  • There is an emerging, yet still limited understanding of the people-side of business outcomes and how to most effectively use your people data to create new value.
  • The value of your data increases dramatically when you combine and connect multiple sources – resulting in your data having multiple dimensions.
  • Managing, connecting and combining HR data for business intelligence is extremely complex and can be considered somewhat of a dark-art (if you disagree with this, have you ever done it – with HR data, at scale with continuously refreshed data?)
  • Enabling information delivery of a company’s most sensitive data (people data) to the right person at the right time, while ensuring confidentiality, privacy and information security is not only really complex, but absolutely mission critical from many angles. A data breach of this type could sink any company.
  • HR reporting and analytics needs have traditionally been considered by IT teams as lower in priority than other corporate requirements.

These challenges often result in HR reporting being executed in its most simple, single dimension fashion, with spreadsheets being manually created time-and-time-again.

Needless to say, spreadsheet-based HR reporting introduces many risks including data integrity, limited access management controls, limited data management capabilities, and raw data being downloaded from systems with little governance or internal control.

Don’t get me wrong, spreadsheets are great for getting going and prototyping, but they tap out very quickly and should not play a key role in enterprise-grade HR reporting and people analytics.