We have just witnessed one of the fastest digital transformations of a business function in our history with that of the employee experience. While many big enterprises have been digitally transforming functions like the back-of-house or consumer-facing functions (think of the move to online shopping), those projects have often taken years or even decades. And then, seemingly in the blink of an eye, those same global enterprises underwent a digital transformation of their most important function: employee experience. The ramifications will be years in the making. But one of them is already here and could be moving rapidly to negatively impact the bottom line: the impact of cognitive load on health and productivity. Organizations that are able to successfully measure and improve this new metric could reap the business benefits that will define the winners and losers of this new digitally transformed workplace.
“Cognitive load” is a 30-plus-year-old theory from instructional design that says people have trouble performing tasks and learning new things if they are trying to process too much information at once. For example, in a 2013 study, college students who multitasked on laptops during class (and students who sat next to them) had lower GPAs. A 2009 review of information overload research suggested that too much information can actually be harmful to performance. Employees with a high cognitive load could be less productive in the workplace. Research from the University of North Carolina published in 2010 found that workers who felt overloaded with digital communications were less productive, and this decrease was especially strong for workers who depended on technology. We were likely already losing productivity to cognitive load before this rapid digital transformation, and this problem could be getting worse.
Now that companies are announcing that all or certain functions can work remotely on a permanent basis (Twitter, Square, Facebook and Shopify, among others, have jumped on board) and the demands of a global, always-on marketplace are apparent, the need for employees to process digital communication data will likely only increase. In fact, my company’s recent data on 3,000 relationships between managers and their direct reports showed that employees sent significantly more messages after hours while working from home, and rates of digital behaviors, such as asking for feedback via email or chat, also increased.
While anecdotes and research suggest that the impact of processing all that data is burning us all out, the details are hard to measure. What is the cost if an employee is 10% less productive? What is the impact if my brain shuts down my ability to think strategically at 4 p.m. instead of 5 p.m.? Reduced strategic thought due to issues like email overload could have a profound impact on the ability to lead other people, but how much lost revenue does this translate to?
This measurement of cognitive load on business performance may be the new frontier of people analytics. As the cofounder and CEO of a leadership development platform that utilizes artificial intelligence and machine learning, people analytics is a function that I’ve seen gain huge momentum in the last decade. Back in 2017, Bersin by Deloitte (via Forbes) found that 69% of companies were integrating data to build a people analytics database.
The goal of people analytics is to build and understand metrics that tie employee experience to business results. But what happens now that the employee experience just underwent what may be the most rapid change we have ever seen? Old key performance indicators (KPIs) may no longer be strong measures of productivity. For example, research suggests workers are less productive when they have long commutes and work long stretches in the office. But when everyone is working from home, are these factors still as relevant? New factors such as too many Zoom calls or Slack messages may be what affect workers’ productivity now. If companies want to increase productivity, they should look to this new data and develop new metrics, and I believe the king of those metrics is cognitive load.
Cognitive load is not just a measure of productivity for the business, but also a measure of well-being for the individual. If I hit my maximum cognitive load at work, how am I experiencing life at home, after hours or on the weekends? Too much cognitive load could impact other aspects of human life, and we see that evidence in reports (paywall) of employee stress and anxiety. Keeping cognitive load in check is a win for both organizations and their employees. But how do we do it?
The answer lies in the problem. Technology creates the bits of data we have to process that stresses our brain, but technology can also help us harness it. Artificial intelligence and machine learning technology could measure the amount and type of digital communications and find patterns in it. The technology that is giving us constant reminders about those unread chat messages could be the same technology that notifies us when we have reached a threshold for cognitive load above which productivity drops. In the future, new technology may not only remind us about cognitive load, but also help to automatically reduce it for us.
In the future of work, I believe we will develop ways to measure cognitive load for the individual and connect organizational cognitive load to productivity and revenue. This could be the KPI that organizations will use to understand and improve the employee experience. The organizations that can do that will reap the benefits, and the organizations that ignore it will see a steady drain on their business and the well-being of their people.
As Co-founder and CEO of Cultivate, Joe is focused on building leadership development and future-of-work technology for the digital workforce. In addition to leading Cultivate, Joe enjoys writing about workplace trends, teaching about startups and product management at UC Berkeley Extension, and occasionally running a marathon.