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Predicting the future is fashionable, even though evidence suggests that most people are rather bad at it. Much of what is written is either completely obvious or complete guesswork. Given that set up, I thought I would take a stab at futurism myself! I’m very capable of both guesswork and observing the obvious, so I feel uniquely qualified for the task. I will start with three predictions about the future of work based on real technology that has either already been developed or that looks likely. Let me be clear – the technical capability to do these things already exists, more or less. What I’m contemplating is how the technology will be used and what it will mean for people at work.
I’d also like to address a topic that is often sorely missing in the conversation about jobs, work and technology – that is, the idea that technology will teach us something about ourselves that we do not already know. While others ponder automation and the impending irrelevance of human beings to many areas of work, I believe a more noble pursuit is to consider what HR technology will enable us to do for people and for employers of people. So, here are three ways life at work could change based on the emergence of increasingly powerful HR technology.
There are 1.2 billion Facebook users, 500 million LinkedIn members and 3.5 billion Google searches a day. As a result, many professionals have online data footprints that are large and growing.
This vast array of data provides a unique window into humanity. A growing body of research shows that this data can be highly predictive of what a person is really like, especially at work. The language that people use, how often they share, the type of content they interact with are direct indications of personality; what people “like” online and how they perform in problem-solving games are predictive of their cognitive ability.
These connections have not gone unnoticed, and tools are emerging that can turn this data into quite accurate talent profiles and predict your chance of success in certain jobs. While some tools are still asking you to “do something” to know you better (like MercerMatch and Hogan-X), others are using available public data without any additional input.
The natural progression is that organizations of the future will consider it necessary and responsible to use the available data to assess and understand candidate fit before offering someone a job – particularly a managerial or professional role. In the same way that a lender scrutinizes your credit history (as a route to understanding how reliable and capable you are) when you ask for a loan, employers will use your digital footprint to understand if you are the right person for the role without even needing to speak to you. The data they can get online would be far more valid and reliable than anything you could say.
Of course, the crucial prerequisite is that you have a social media profile. Without it you are an unknown quantity – a black box. Indeed, some tools have responded to the black box quandry by estimating their accuracy according to the amount of information they can find about you.
The point is that the employer of the future might not even consider you as an employee for a professional position without being able to see a substantial data footprint from your online life. As the science and research around this improves, the links between your online social footprint and your potential at work are likely to strengthen and become even more valid. If you have a problem with this concept, consider whether it is worse than online marketers using the same information to advertise products to you, directly to your inbox or Facebook feed (which already happens).
As an increasing number of organizations move to more distributed work teams (that is, teams that are not in the same place at the same time) and onto cloud-based communications systems (like Office 365) the amount of unstructured communication data that is available for organizations to analyze increases rapidly. The asynchronous nature of many virtual teams means that this data is often written or text-based. While most people think of their work email or instant messaging chat conversations as private, it’s common for employers to make it very clear that written communications at work can be scrutinized for any business purpose—a vast data set of employee insight.
The availability of this data set leads us to emerging technologies that can analyze what employees are writing about at work – mostly from email or internal chat data, but also internal social media posts or responses to open questions from pulse surveys. While this tech started life as a way to understand how people communicate (e.g., Volometrix), the internal relationships they have (e.g., Trustsphere) or what their biggest concerns are (e.g., Kanjoya), it is evolving quickly. Just see the recent Harvard Business Review articles looking at the connections between employee engagement survey responses and the email behavior of employees and their bosses.
While in its early stages, the analysis and predictive opportunities are significant. As natural language processing algorithms improve and HR analytics data sets become larger, it’s possible that companies can soon forget about surveying employees for their opinions and just run analytics on their internal communications instead. For example, researchers like Rob Cross have already shown that people who are experiencing collaborative overload are less happy in their roles and burn out faster as a result. It’s only a short leap of imagination to create a scenario where your email warns you that you’re burning out and need to decompress.
The way you communicate with others has already been shown to give away many signals about who you are (see point 1 above). On top of that, it can also provide a lot of information about the experience you’re having – e.g., Are you getting on with your colleagues and your boss? Do you work longer hours than others? Are you feeling frustrated or disconnected? All of these questions might be answered by looking at how you are expressing yourself to colleagues and clients.
The main consideration then is about how this information could be used. Imagine if the early warning signs of disengagement could be detected by your email, with advice sent to you and, at your request, your boss. Wouldn’t that be much better than getting to the point of wanting to quit without anyone knowing or being able to help?
Many of us feel increasingly comfortable rating our experience of a service or person that we have just dealt with, mostly because it’s become easy to do so via our mobile phones. It started with sites like TripAdvisor for hotels and restaurants and has made its way to taxi drivers via Uber. The universal 5-star scale seems to be the weapon of choice. The more immediate the feedback the better.
While many people complain about ratings data, there is an important reality to consider: in most cases your performance at work is what people perceive it to be rather than some tangible metric. It is your reputation for performance that defines you. The notable exception is often at the most senior levels of leadership, where people can be (but rarely are) judged based on organizational output. This means that more frequent and more diversified ratings data is actually likely to be useful—it can create a more valid picture of your performance from a wider range of sources. This picture of performance would expose those who “manage up” well, but “manage down” poorly, and help those who are actually getting work done (pleasing customers and colleagues).
Performance metrics of the future are probably real-time and app-based, making it easy to get faster access to more fluid ratings of your reputation and making it much more transparent and direct to connect your reputation at work with the way your performance is measured. Transparency would also have the positive effect of changing the role of your boss from someone who is rating and approving your performance feedback to someone who is coaching you on how to respond to it, which is a very different conversation.
So what?
It matters. The way we secure work and how we are evaluated for our contribution is changing. These changes will shift our relationship with our employers and our jobs. The emerging HR technology industry is deploying the data we generate online and using it to make many more inferences about us to enable better decision making.
The question will be whether individual employees resist these changes or embrace them. My view is that the quicker we embrace them, the more control we will have over how technology influences careers, jobs and work in general.
Africa
