If you worked for Ford in 1914, chances are at some stage in your career a private investigator was hired to follow you home.
If you stopped for a drink, or squabbled with your spouse, or did something that might make you less of a competent worker the following day, your boss would soon know about it.
This sleuthing was partly because Ford’s workers earned a better salary than the competition. The car manufacturer raised pay from $2.39 a day to $5 a day, the equivalent of $124 (£88) today. But you had to be a model citizen to qualify.
This ‘Big Brother’ operation was run by the Ford Sociological Department, a team of inspectors that arrived unannounced on employees’ doorsteps
Your house needed to be clean, your children attending school, your savings account had to be in good shape. If someone at the factory believed you were on the wrong path, you might not only miss out on a promotion, your job was on the line.
This ‘Big Brother’ operation was run by the Ford Sociological Department, a team of inspectors that arrived unannounced on employees’ doorsteps. Its aim was to “promote the health, safety and comfort of workers”, as an internal document put it. And, to be fair, it also offered everything from medical services to housekeeping courses.
The programme lasted eight years. It was expensive, and many workers resented its paternalism and intrusion. Today, most of us would find it unacceptable – what does my work have to do with my laundry, bank account or relationships?
Yet, the idea of employers trying to control workers’ lives beyond the workplace has persisted, and digital tools have made it easier than ever. Chances are, you use several technologies that could create a detailed profile of your activities and habits, both in the office and out of it. But what can (and can’t) employers do with this data? And, where do we draw the line?
What’s my worker score?
We’re all being graded every day. The expensive plane tickets I bought recently have already popped up in my credit score. The fact that I‘ve stopped jogging every morning has been noted by my fitness app – and, if it were connected with an insurance company, this change might push up my premiums.
From my online activity, Facebook knows I love beer, and believes my screen is a good spot for hipster brewery adverts. One website recently claimed that I am Colombia’s 1,410 th most influential Twitter user – something that could improve my credit score, it seems. And, yes, my desirability and efficiency as a worker is also up for evaluation and can be given a number.
And we’re not just talking the ‘rate-a-trader’ style online review process used on freelancer platforms or gig-economy services. A scoring system of sorts has lodged itself in the corporate world.
HR departments are crunching increasing volumes of data to measure employees in a more granular way
HR departments are crunching increasing volumes of data to measure employees in a more granular way. From software that records every keystroke, or the ‘smart’ coffee machines that will only give you a hot drink if you tap it with your work ID badge there are more opportunities than ever for bosses to measure behaviour.
Some analysts think this industry could be worth more than $1 billion by 2022.
One big aim of data collection is to make “predictions about how long an employee will stay, and it may influence hiring, firing, or retention of people,” says Phoebe Moore, Associate Professor of Political Economy and Technology at Leicester University in the UK and author of the book The Quantified Self in Precarity: Work, Technology and What Counts.
Data collection is “changing employment relationships, the way people work and what the expectations can be”, says Moore.
One problem with this approach is that it’s blind to some of the non-quantifiable aspects of work. Some of the subtler things I do in order to be a better writer, for instance, are not quantifiable: having a drink with someone who tells me a great story, or imagining a piece on my commute. None of these things would show up in my ‘job score’. “A lot of the qualitative aspects of work are being written out,” says Moore, “because if you can’t measure them, they don’t exist”.
The dilemma of data
A healthy, physically active person is a better worker, right? Research consistently suggests activity decreases absenteeism and increases productivity. This has spawned a thriving health and wellness industry with programmes worth billions.
Employees value these health initiatives not only because their bosses might allow them time off to participate but also because if they track exercise via their phone, smartwatch or fitness wristband they can earn rewards.
“I can just wear this device, and I get points and buy stuff for doing things I would already (be) doing anyway without it,” says Lauren Hoffman, a former salesperson for one of the programmes in the US, who was also enrolled in it herself.
Furthermore, the workplace offers an environment that can help people to reach their health goals. Research suggests that fitness programmes work better when they are combined with social encouragement, collaboration and competition. Offices can foster all that: they can organise running clubs, weekly fitness classes or competitions to help workers thrive.
There are several good business reasons to collect data on employees – from doing better risk management to examining if social behaviours in the workplace can lead to gender discrimination. “Companies fundamentally don't understand how people interact and collaborate at work,”, says Ben Waber, president and CEO of Humanyze, an American company which gathers and analyses data about the workplace. He says that he can show them.
Humanyze gathers data from two sources. The first is the metadata from employees’ communications: their email, phone or corporate messaging service. The company says analysing this metadata doesn’t include reading the content of these messages, nor the individual identities of the people involved, but involves crunching the more general information i.e. duration, frequency and general localisation so, will tell them which department an employee belongs to.
The second area is data gathered from gadgets like Bluetooth infrared sensors which detect how many people are working in one particular part of an office and how they move around. They also use ‘supercharged’ ID badges that, as Waber says, are beefed up with “microphones which don't record what you say, but do voice-processing in real time.” This allows measurement of the proportion of time you speak, or how often people interrupt you.
After six weeks of research, the employer gets a ‘big picture’ of the problem it wants to solve, based on the analysed data. If the aim, for instance, is to boost sales, they can analyse what their best salespeople do that others don’t. Or if they want to measure productivity, they can infer that the more efficient workers talk more often with their managers.
Waber sees it as “a lens of very large work issues, like diversity, inclusion, workload assessment, workspace planning, or regulatory risk”. His business case is that these tools will help companies save millions of dollars and even years of time.
Collection and protection
But not everyone is convinced of the usefulness of these techniques, or whether such personally intrusive technology can be justified. A PwC survey from 2015 reveals that 56% of employees would use a wearable device given by their employer if it was aimed at improving their wellbeing at work. “There should be some payback from something like this, some benefit in terms of their workplace conditions, or advantages,” says Raj Mody, an analyst from the firm. And Hoffman remembers that these programmes were not always an easy sell. “You’re going to get the data and you're going to use it against me,” she was often told by sceptical workers.
There is a fundamental problem: these measurements are often inaccurate
And there is a fundamental problem: these fitness tracking measurements are often inaccurate. People are very bad at self-reporting and fitness trackers and smartphones are not exactly precise. A recent evidence review shows that different models and techniques gather different results and it is very difficult to draw trustworthy comparisons between them.
It is also unclear if counting steps, for instance, is actually a good way of measuring activity, both because this measurement doesn’t take intensity into account – a step made while running counts just as much as a step made walking at home – and walking is more difficult for some than others.
Another issue is the amount of data these programmes can collect. They not only track your daily activity, but also often offer health screenings for participants, which allows them to register things that don’t seem like your boss’s business: your cholesterol level, your weight, or even your DNA.
In most cases, it is illegal in the US and Europe for companies to discriminate against workers based on their health data or any genetic test results, but there are some grey areas. In 2010, Pamela Fink, the PR manager of an energy firm in the US, sued her employer because she claimed she was sacked due to a double mastectomy to reduce her probability of developing cancer. While the company didn’t have access to her DNA results, she contended that they knew about the risk because the surgery showed up on her insurance bills. The case was settled out of court.
Wellness programme providers say that employers only see aggregated and anonymised data, so they can’t target specific employees based on their wellness results. Humanyze ensures its clients are not forcing their employees to be monitored, but instead give them the chance to opt in. In a similar fashion to wellness programmes, they anonymise and collate the information that they share with employers. Waber is emphatic that his company never sells the data on to third parties, and emphasises transparency throughout the process.
But this kind of data could be used in more controversial ways, and the goodwill of the companies involved doesn’t eliminate all the risks. Data could be stolen in a cyberattack, for instance, or it could be used in ways that are not transparent for users. It “could be sold to basically anyone, for whatever purpose, and recirculated in other ways,” says Ifeoma Awunja, a sociologist at Cornell University who researches the use of health data in the workplace.
Taking a short-term profit on user data would damage your company’s reputation - Scott Montgomery
There are reports that some providers are doing just that already – even if they data they sell is anonymous, they could be cross-referenced with other anonymous data to identify people. Not all these companies do it, and some say it is not smart business to do so. “Taking a short-term profit on user data would damage your company’s reputation, causing user volume to plummet and thus your value to clients to diminish” says Scott Montgomery, CEO of Wellteq, a corporate wellness provider based in Singapore.
But even if all the companies did the right thing and acted only in their costumers’ best interest, people in some places are still only protected by their wellness programme’s goodwill. The US law is “significantly behind” the European Union and other parts of the world in protecting users, says Awunja.
In the EU, a new General Data Protection Regulation (GDRP) will come into force thisMay, which will outlaw any use of personal data to which the user didn’t explicitly consent. In the US, the legislation varies between states. In some of them, sharing some health information with third parties is not illegal as long as the data doesn’t identify the person. Furthermore, according to Gary Phelan, a lawyer at Mitchell & Sheridan in the US, since this data is generally not considered medical data, it does not have the privacy restrictions as medical data.
Human beings are evaluated in terms of the risk that they pose to the firm - Awunja
There is also the question of return on investment for the employers. Do they actually save businesses money? These programmes are meant to lower health insurance premiums both for companies and employees, since they are supposed to decrease health risk, sick days, and hospital costs. But it is not clear if this actually happens. A 2013 study by the Rand Corporation claims that, while these programmes save companies enough money to pay for themselves, they “are having little if any immediate effects on the amount employers spend on health care.”
With all these tools, “human beings are evaluated in terms of the risk that they pose to the firm,” says Awunja. Still, it’s a complicated balance: dealing with the everyday habits of employees as if they were just another hit to the bottom line sounds a lot like the old days of the Sociological Department. Whatever benefits these technologies can bring, they have to balance with the privacy rights and expectations of workers.
There is an episode from TV show Black Mirror that offers a chilling warning. In it, every person is given a score based on their interactions on a social platform that looks strikingly like Instagram. This score defines almost every opportunity they have in life: what jobs they can get, where they live, which plane tickets they can buy or who can they date. In fact, in 2020 China will roll a mandatory Citizen Score calculated from a number of data sources, from your purchase history to the books you read.
Although not quite as sinister, this illustrates the technological, legal and ethical limitations of doing something similar elsewhere. In most parts of the world, the law prevents your HR department from sharing or requesting data about you from your credit card provider, your healthcare provider, or your favourite online dating site, unless you explicitly consent that it can do so.
This should keep the most cynical temptations at bay for now, but how to reap the benefits of data in an acceptable way? There is a strong case for finding this balance: as Waber says, data can give you evidence-based advice for advancing your career, or for enhancing your effectivity at work. Having a space for taking care of your health at work might improve your happiness at your job, and some studies suggest that this also translates into a productivity push.
Part of the answer seems to be to agree to certain ethical standards. In a paper, Awunja proposes some practices like informing employees of the potential risks for discrimination with the data, not penalising those who decline to take part in these programmes, and setting a clear ‘expiration date’ to the collected data.
This is an important conversation to have, even if you are of those with nothing to hide. As it turns out, it is very likely that giving away our data is going to be part of the everyday experience of work in the near future, at least in the corporate world.