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4 Companies Using Machine Learning to Keep a Close Eye On Employees

Matt Wujciak


Using machine learning and artificial intelligence to keep a close eye on employees can help organizations monitor employee performance metrics and increase efficiency. A recent Gallup study says 25% chunk of Americans work between 45-59 hours per week (between 9 and 11.8 a day), yet the average salaried U.S. worker only gets about 3 hours of work completed each day. When the majority of employees spend well under half their work day actually working, it’s no wonder larger enterprises are investing in technology-driven performance metrics. But when predictive analytics, AI based algorithms, and even surveillance cameras are recording employees’ every move, it can begin to feel invasive. 



Microsoft has been patenting different technologies recently to understand employee relationships and monitor employee productivity. Using AI to deliver KPIs is a great way to enhance employee efficiency. Microsoft’s Workplace Analytics lets employers monitor an individual’s data such as time spent on certain websites, writing emails, email response rates, and time spent working after they leave the office. 

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Several enterprises, including Freddie Mac, Macy’s and CBRE are using Microsoft’s system to monitor employee behavior. According to the WSJ, managers using Microsoft’s software’s data analytics and predictive algorithms are able to look at groups of five or more workers and analyze various employees’ activity, like easily measurable email behavior. They can then study the sender, recipient, and timing to receive workplace intelligence on employees’ relationships with one another and personal priorities. 

 As another potential example, organizations may use similar technology to track the time you spend reading articles like this one. Leveraging machine-learning, the tool can develop an algorithm for predicting work engagement or likelihood to quit for another company.

While reaping the efficiency and employee engagement benefits of this technology, it is of course important to consider boundaries. Is there a point at which diving deep into employee behavior becomes more invasive than productive?



According to NBC, “Walmart last year patented a system that lets the retail giant listen in on workers and customers. The system can track employee “performance metrics” and ensure that employees are performing their jobs efficiently and correctly by listening for sounds such as rustling of bags or beeps of scanners at the checkout line and can determine the number of items placed in bags and number of bags. Sensors can also capture sounds from guests talking while in line and determine whether employees are greeting guests.” 

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However, some states outlaw recording audio of people without their consent, which would make this technology illegal in 12 states that Walmart operates in. "Shoppers aren't going to expect their conversations will be recorded," Sam Lester, consumer privacy counsel of the Electronic Privacy Information Center told CBS News, adding that such recordings would raise "a ton of concerns" about privacy. You don’t say.



Using smart devices to measure a person’s physical movements and track performance is by no means a new technology in various industries, like fitness for example. But Amazon has patented a new retail automation that does exactly that. Their employee wristband that emits ultrasonic sound pulses and radio transmissions can accurately track where warehouse employees are placing their hands on packages and use vibrations to nudge them in certain directions. The proposed wristbands would identify the precise location of a worker’s hands as they retrieve items and essentially steer them towards the right direction. The patent, which was filed in 2016 and won last year, outlines a haptic feedback system that would vibrate against the wearer’s skin to point their hand in the right direction. 

Max Crawford, a former Amazon warehouse worker in Britain, said in a phone interview with the New York Times, “After a year working on the floor, I felt like I had become a version of the robots I was working with.” He described having to process hundreds of items in an hour, and one day, he fell over from dizziness. “There was no time to go to the loo,” he said, using the British slang for toilet. “You had to process the items in seconds and then move on. If you didn’t meet targets, you were fired.”



Domino’s recently introduced the Dom Pizza Checker to its Australia and New Zealand locations, a new tool that utilizes in-store cameras to “use advanced machine learning, artificial intelligence and sensor technology to identify pizza type, even topping distribution and correct toppings.” If employees do not execute the order correctly, they are instructed to make it again.

The Dom Pizza Checker is spurring a debate about the grey area between performance optimization and corporate ethics.. In reflecting on the Dom Pizza Checker, as well as other employee monitoring systems, A Guardian columnist Arwa Mahdawi +said  employers “may be taking remote screenshots of your computer. It may be logging your keystrokes or recording your Google searches. It may be tracking the time you are spending reading this… It may even be monitoring your facial expressions or tone of voice and gauging your mood.”  

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As technology innovations continue to evolve at a seemingly uncontrollable pace, staying ahead of the game in future corporate technology capabilities have never been more imperative. When it comes to performance monitoring, employee efficiency, and customer centricity, learning proper practices to optimize consumer value from an ethical and productive standpoint is becoming increasingly relevant, for so many reasons. Tune in to our live event, The Contact Center of 2025, on December 3rd and 4th to introduce yourself to analysts’ predictions and upcoming cutting-edge technology trends at our complimentary online summit. Everyone knows the right questions to ask in customer centricity, but fewer analysts know the answers than CCW’s world-class experts and contributors.