People Analytics is the organizational discipline of applying scientific and statistical methods to behavioral data. In other words, it’s the science of turning data into action at work. People Analytics plays a critical role in the business performance and health of an organization–even more so when the stakes are high, like achieving company objectives or transformational change.
As humans, we habitually make decisions based on intuition, also known as mental “shortcuts” or heuristics, rather than evidence. This is a highly adaptive skill we developed to manage high cognitive loads, and not a result of laziness. Unfortunately, heuristic thinking often leads to incorrect conclusions due to insufficient data, especially when dealing with the complexities of human behavior.
People Analytics helps separate signals from noise to pinpoint exactly where opportunities or challenges exist within an organization, with the scientific rigor and technical capabilities business leaders rely on to determine and target their talent management approach. You could also say People Analytics is dedicated to demystifying the connection between human behavior and business outcomes with data.
The case for People Analytics and data-driven decisions
Take this example: A leader receives low scores on their latest employee engagement survey. They want employees to feel appreciated and jump to the conclusion that a short term fix, like a party, will boost engagement long term.
Eye rolling ensues.
Unfortunately, inadequate measures like these pose a risk to more than the leader’s reputation. As our co-founder Laszlo Bock, former CHRO of Google and author of “Work Rules!” says, “left unaddressed, people problems always become business problems.”
People Analytics helps leaders like these understand what the data actually means, and what to do about it, so low employee engagement, for instance, doesn’t become a business problem.
The work of People Analytics doesn’t actually start with data though; it begins with the right question. What is the challenge the business needs to solve? What information does the business already have? What information is needed to make a better decision?
The answers to these questions form the basis for developing a clear hypothesis, choosing relevant metrics, gathering sufficient evidence, and making inferences with statistics, known as insights, to appropriately act on data.
People Analytics is best supported by a full suite of behavioral and data science capabilities, which are most effective when integrated as part of a company’s overall data function. People Analytics operations include:
- Data engineering and sourcing enables data creation and quality control so People Analytics can rapidly test and iterate with high quality data. Data should be sourced from CRM, finance, sales, etc. and then linked to HRIS and other HR data.
- Survey development based on psychometrically sound employee listening surveys that are valid, reliable, and fair and can be used as a key data source.
- Business application happens when results are interpreted through data and behavioral science and applied to business challenges. People Analytics is then in a position to make science-backed recommendations on employee behavior change to business leaders
How People Analytics developed over 100 years to meet changing business needs
People Analytics traces its origin toThe Principles of Scientific Management by Frederick Taylor published in 1911. According to famed management consultant Peter Drucker, Taylor was the first who “deemed work deserving of systematic observation and study.”
As a mechanical engineer turned businessman, Taylor applied the scientific method to management to increase industrial efficiency, later known as organizational effectiveness. “Taylorism” was adopted by industrialists like Henry Ford, who revolutionized production at scale, and carried his principles through the post-WWII mass production era.
In the 1970’s, the Business Administration function took on greater prominence as companies navigated a challenging economy and rapidly globalizing market. The increased computing power of the 1980’s and 1990’s enabled people processes to be effectively managed and measured across the workforce, which created the Human Resources departments we recognize today.
Then came the Internet Revolution. The ability to collect quantitative and qualitative data in large volumes, now known as Big Data, sparked demand for a new business skill: analytics. Analytics academic Thomas Davenport observed in 2006 that companies effectively competing in a saturated market were “armed with the best evidence and the best quantitative tools” and repeatedly made the best decisions “big and small.”
After the Global Financial Crisis of 2008, business functions were eager to leverage analytics in decision-making to gain a competitive advantage. This began a widespread practice of predictive modeling and optimization to forecast and monitor everything from customer targeting to risk assessment.
But what about talent management? While CHRO at Google, Humu’s co-founder Laszlo Bock and his team invented the term “People Analytics” and pioneered practice that are widely adopted today. Inspired by the workplace culture and performance at Google, People Analytics functions began cropping up among other leading-edge enterprise HR departments and realizing the business impact of better workplace practices.
Best Buy, for instance, discovered the value of a 0.1% increase in employee engagement at a particular store was $100,000. Similarly, Google found that shortening the onboarding process by three months saved them $400 million in productivity. This insight was the beginning of the People Analytics capabilities Google would ultimately build.
How People Analytics empowered Google to pinpoint what makes a manager great
In 2008, Laszlo’s team of researchers at Google had a simple question: do managers matter? Their investigation, known as Project Oxygen, was inspired by many executives’ deeply held belief that middle management was “at best, a necessary evil.”
Researchers started by trying to prove the anti-management bias correct. However, manager performance ratings and feedback from Google’s annual employee survey quickly showed that teams with great managers were happier and more productive.
This raised the natural next question: what makes a great manager? The researchers conducted double blind interviews with the best and worst managers as rated by employees, and found that only two of the ten attributes of a great manager were technical. Eight of the ten attributes were interpersonal, starting with “is a good coach.” These behaviors were predictive of team outcomes like turnover, satisfaction, and performance.
Project Oxygen successfully improved 75% of the worst performing managers. By the end of the initiative, 83% of managers were rated as “highly effective.” This had a material impact on the business as the most effective managers were found to drive 36% more revenue than least effective ones.
Elevating the importance of HR with People Analytics post-pandemic
The organizational pressures of the pandemic radically elevated the role of the CHRO, along with People Analytics. With senior leadership fascinated en masse by workforce dynamics (i.e. remote work, high attrition), People Analytics was positioned to influence core business strategy and enlisted to help reinvent how companies work.
A year before the pandemic, 70% of companies had a People Analytics function. A year into the pandemic, 52% of companies reported plans to invest in tools for people-data collection and analysis. In the last year, a survey of 100 CHROs showed that 9 in 10 CHROs report People Analytics to be a core component of their strategy.
While People Analytics has more support, only 29% of HR functions say they effectively make organizational changes based on data. By expanding beyond the HR function, People Analytics can close the evidence-based decision-making gap and drive significant impact for the business analytics value chain.
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Why People Analytics matters now more than ever
After three years of compounded economic uncertainty, global crisis, and social turbulence, employees and leaders alike are exhausted. However, we face new mounting pressures and no clear playbook on the future of work.
To ensure we can chart a path forward, organizations need to take on less–not more–by taking stock of what they do know and leaning into what they’ve already learned. In the words of tennis player Arthur Ashe, “Start where you are. Use what you have. Do what you can.” People Analytics is an invitation for organizations to do just that.
Check out our latest ebook for guidance on how to turn data-driven insights into action to help your organization navigate uncertainty.
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