The engineers at Fatigue Science, a Vancouver firm that tracks and optimizes workers’ sleep schedules, chose a vivid way of framing the effects of fatigue on its subjects. Instead of displaying an essentially arbitrary unit of fatigue on graphs, it expresses its in a far more familiar context: Blood-alcohol level.
After all, as CEO Sean Kerklaan explains, the effects of fatigue are actually very comparable to the effects of alcohol.
“You and I understand that drinking two or three beers and getting in the car is dangerous. Your decision-making is compromised and responses are delayed,” he says. The same applies to a fatigued brain. “When you’re tired, you’re going to be slower to swerve and slower to respond.”
Fatigue Science specializes in first measuring a company’s employees’ sleep habits, and then using algorithms to bend their schedules so that workers spend as much time as possible in an alert state.
And it’s not just a matter of telling everyone to get more sleep: Not all hours of sleep are created equal. For instance, in one of Mr. Kerklaan’s demonstrations, shifting a given oil-sand employee’s wake-up time from 3 am to 4 am – and adding an extra hour onto the end of his day – can make the difference between an employee who is alert all day long, and one who spends much of the day effectively impaired.
The algorithms the company uses were originally developed by the US Air Force, and then licensed to Fatigue Science to commercialize; the firm pays royalties back to the American military, which is looking for the returns on the $20-million it spent on the research.
The company works with organizations where employees are under stress and alertness matters: Air-traffic controllers, where every routine shift holds lives in the balance; oil-sand workers, who work long hours in remote locations where industrial accidents can have dire consequences; or major-league hockey and basketball franchises, where millions of dollars ride on peak performance.
But for the size and scope of these organizations, Mr. Kerklaan says that all too often, the tools their administrators use to actually schedule shifts are totally rudimentary. “They’re mostly using Excel,” he says, frequently doing a simple arrangement of who wants which shifts when.
The company takes a three-step approach to a new corporate client. First, they input the company’s existing schedule, and perform a software analysis to flag potential trouble spots. Then, they gather first-hand data, by fitting employees with a “Readiband” – a motion-detecting bracelet. By analyzing the data from the Readiband’s accelerometers, the company’s software can track employees’ levels of exertion and restfulness – and, when they’re resting, just what kind of rest they’re getting.
The measurement period can be as short as a few days, but a typical cycle is 21 days, since it allows the software to track a worker through a full schedule rotation, complete with weekends, to see how off-time affects a sleep schedule. Typically, employees fall into three buckets: People with no sleep problems; people who have a sleep condition that’s keeping them from getting a good rest; and people who have “sleep hygiene” issues, which is a polite way of saying they’re lousy at going to bed when they should.
With this data in hand, Fatigue Science is in a position to recommend schedule changes, and help clients implement a training program – where the challenge has as much to do with corporate culture as sleep science. The company often follows up three to four months later, with the same individuals on their new schedules.
The very passage of time, also, can have deleterious effects. Companies that start with young teams have to adapt as their employees age. “As your staff get older and gain weight, it can have an impact on how you sleep,” says Mr. Kerklaan.
But, he says, a company that’s willing to take a holistic look at its employees’ schedules, factoring in things like commute times, schedule consistency, and a willingness to get employees to buy into the scheme, will see consistently positive results: Productivity goes up, and risk goes down.
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