Workforce analytics, productivity tracking, employee monitoring software: Whatever you want to call it, worker surveillance tech is trending way, way up.
Pre-pandemic, just three in 10 companies with 1,000+ workers used tech to measure employee productivity, but by the end of 2021, six in 10 reported doing so, according to a Gartner survey reported by HR Brew. And as of August 2022, eight of the 10 largest private US employers used these technologies, according to a NYT examination.
And that growth is reflected in funding, too: Despite overall VC funding being down by as much as 53% year over year as of Q3 by some estimates, funding for remote employee-monitoring tech is surging.
VCs invested a total of $180.5 million in the space in 2020, and in 2021, VCs invested more than $243 million, according to PitchBook data pulled for Emerging Tech Brew. In the first three quarters of 2022, the sector’s total VC investment has surpassed $394 million—62% more than 2021’s full-year total, even though the year is not yet over.
The sector’s growth in usage and funding comes alongside the rise of fully or semi-remote work, which could make employers more nervous about workforce productivity. It also comes despite misgivings from some privacy experts and from workers themselves.
“Employers see this as a treasure trove, like… ‘There are so many technologies now for me to capture all of this data about my workers, and it’s going to help me make better decisions, increase productivity, [and] have that ideal worker,” Jessica Vitak, an associate professor at the University of Maryland’s College of Information Studies, said. “It’s so much more complicated than that.”
Productivity problems
ActivTrak, a workforce analytics software company with more than $77 million in funding, recently ranked on Deloitte Technology’s list of fastest-growing companies in North America for the third consecutive year. The company has achieved “485% growth over the last three years,” according to a press release.
Prodoscore, another productivity monitoring company, has had 300% YoY revenue growth for the past 3 years, CEO Sam Naficy told us—and the same growth rate for the number of employees on the platform, which is currently at about 20,000.
The company uses machine learning and natural language processing to offer clients “visibility into employee productivity in the form of one simple score,” according to its Google Workspace listing.
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The tech’s popularity is now coinciding with a period of layoffs and recession fears, during which companies—in particular, tech companies and startups—have announced a push to focus on productivity and “doing more with less.”
“We have seen kind of unbelievable growth year over year for the last three years…and especially the last six to 12 months,” Naficy said. “I’m not sure if it’s directly because of layoffs and/or recession fears or, I think, just the adoption of productivity tools becoming more and more accepted and, frankly, ubiquitous as part of the corporate tech stack.”
In a research paper shared with Emerging Tech Brew, which is currently under review at an academic journal, Vitak and her co-authors showed 645 US workers who worked from home during early 2020 examples of workplace monitoring tech. Participants tended to have concerns about data collection used to assist in making promotion decisions or to track monthly performance metrics. They also “strongly disapproved” of reasons for collecting data that went “beyond expected goals” like productivity or information security (e.g., healthy behavior monitoring).
And in May, a separate survey by Morning Consult found that more than half of tech workers would resign if their employer used audio or video computer surveillance or productivity-monitoring facial recognition software. Just under half said they’d resign over the use of keystroke monitoring tech or tech that takes screenshots of their computer screens. And more than half of respondents said they would decline a new job at a company that uses productivity monitoring tech.
Employers’ perceived benefits of the tech include more access to data and, in theory, the ability to make better decisions about workers, Vitak said. But, she added, the societal risks include longer-term data aggregation that could be used for purposes beyond the original intent, as well as the potential development of predictive algorithms focused on what it means to be productive.
“What makes somebody a ‘good worker’ cannot…be boiled down to a mathematical equation,” Vitak said. “The concern is about putting so much faith in the data—and not recognizing what the data can’t tell us, and not recognizing the way in which the data can misportray people.”