A century ago, Frederick Taylor’s Scientific Management laid the foundations for modern HR. His central premise was that organizations should turn their workplaces into real-world psychology labs, measuring and monitoring employees’ every move in order to boost their performance and reduce their stress levels. The paradigm was revolutionary, and led famous industrialists like Henry Ford to unprecedented innovations in human engineering, with the creation of the seminal assembly line, and a science-infused formula for optimizing roles, tasks, and job design to enhance employee productivity. Big companies, such as the Ford Motor Company, became a testing ground for applied psychology, and evidence-based HR was born.
Fast forward 100 years or so, and it is all footnotes to Taylor. Some of the largest, most successful corporations, such as Google and Microsoft, are ramping up on data science, recruiting an army of Ph.D.’s in Industrial/Organizational Psychology, and accelerating their digital transformation to deploy smart technologies around AI and big data to improve their talent management systems. The people analytics age is here to stay, and it was already well advanced before the pandemic. But in a world of work that is increasingly virtual (and perhaps even only virtual), the volume of data available to understand and predict employees’ behaviors will continue to grow exponentially, enabling more opportunities for managing through tech and data.
Broadly understood, people analytics is the HR function dedicated to the pursuit of data-driven insights about an organization’s workforce — yes, the geeky part of HR. Think of data as digital records of employees’ behaviors, and people analytics as the science that translates these data into actionable insights that improve the organization’s effectiveness. Most organizations sit on a wealth of data. We have repeatedly heard that “data is the new oil”, but data without insights are meaningless — just 0’s and 1’s. You need the right framework, model, or expertise to ensure that data acquires meaning, and the next stage of the process is to act on the basis of those insights to create data-driven decisions, changes, and a data-oriented culture, in an organization. As such, people analytics is a deliberate and systematic attempt to make organizations more evidence-based, talent-centric, and meritocratic, which, one would hope, should make them more effective.
Consider the employee experience, which has traditionally been evaluated via annual surveys focused on job satisfaction or employee engagement. Although these measures are positively linked to job performance, the correlation is typically small (suggesting less than 20% overlap between engagement and productivity), and conflated with irrelevant factors, such as employees’ personality. It is also unreasonable to wait for an entire year to evaluate whether morale has gone up or down, so why not monitor this more regularly?
This is where more regular “pulse surveys” and employee listening tools have started to gain popularity and can quickly be used to drive real action that benefits employees and businesses. Companies such as Glint, CultureAmp, Qualtrics, and Peakon are all able to help organizations to regularly “pulse” their employees to understand engagement and employee sentiment on a real-time basis. While employee listening has been around for a while, it has gained even more popularity in response to the Covid-19 crisis. Companies such as Rabobank, Merck, and National Australia Bank are all using employee listening to understand how their employees are coping with new remote working arrangements, how their needs for support are changing, and what their preferences are for returning to work. Using techniques such as stratified sampling (an alternative to random sampling that enables data scientists to partition a given sample into “strata” in order to make predictions about the population) and text analytics on free text comments (software that decodes words and word frequency into emotional sentiment or different psychological traits) and discussion boards, companies can gain valuable insights into what’s important to their employees in a rapidly changing environment, while avoiding survey fatigue and preserving anonymity at an individual level.
Another important issue, particularly in the current context, is whether new technologies could be used to keep people safe, monitoring their mental and physical well-being. With widespread discussions right now on how employers can make their workplaces safe and ensure a healthy reopening of their offices in the post lockdown phase, it is not just the usual measures, such as temperature checking or social distancing, that may help. There are many ways that companies are implementing new technology to support their employees. Wearables can now monitor stress and anxiety, if employees choose to share that data. Chatbots that can be deployed to ask about your e