The future of workplace analytics

As the field of workplace analytics advances with new approaches, new technology and the introduction of machine learning, we’re left wondering: What does the future look like?
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As our work becomes increasingly digital, will employers track employees’ every move?

Or, can we use this proliferation of data to empower employees?

future of workplace analytics

To get a sense of where we are going, it’s helpful to take a step back and remember where we came from.  

We used to learn by observing, with some unintended consequences.
Dating as far back as the early 1900’s, earlier scholars in management and organizational sciences studied work by observing people actually doing their work — building widgets, working an assembly line, etc. Through these initial studies, they were able to help drive efficiencies at work by optimizing various elements of the work environment so that workers could get more work done. But doing so didn’t come without an expense: employees felt like the widgets themselves. 

The introduction of surveys (to be less creepy).
To better understand how not to make employees feel like widgets, researchers began to focus on the non-physical aspects of work—such as the physical workplace, and job and workplace satisfaction. To study these phenomena, researchers had to ask employees how they felt about their workplace, jobs, and employers. This gave way to the first workplace surveys, first conducted in person, then by paper and pencil, Interactive Voice Response (IVR) and ultimately via web surveys. I would argue we’re now at a place where—thanks to the advent of more affordable and easy to use web-based technology—there’s a dizzying frequency of surveys at work such that the world of work (and the world in general) is over-surveyed. This can lead to lower response rates and sometimes lower quality responses — and ultimately lower confidence in their accuracy and validity.

Using workplace digital footprints to empower employees.
There’s a better way to understand the world of work—especially for knowledge workers. And this is largely due to how we now get our work done.  

Think about your average workday and all of the tools you use to communicate and complete your projects. From communication and collaboration tools such as Slack and Teams to project management tools like Trello, Jira, Asana and Calendars, employees have plenty of options from which to choose. Additionally, most of these tools are hosted in the cloud and automatically backup the data from their usage. And with privacy regulations like GDPR and the California Consumer Privacy Act, the data in these tools are now easily accessible and exportable. This leaves organizational researchers with a huge data source to analyze what drives effectiveness at work. 

Rather than ask people who they are collaborating with, how burnt out they might be feeling, or whether the projects they are working on are on track to be successful, we can now analyze the data. We can stop asking and start looking. And to avoid earlier problems where employees felt like widgets, we can now empower employees to leverage the data and insights themselves. 

Present state of work analytics
This brings us to the present state of work analytics. 

The way we are focusing on how to understand effectiveness at work is evolving. We can now use machine learning on their digital footprint to better understand and enable employees to do their best work. 

Why is this a better approach?

1. We can now help employees understand their own habits better than they can themselves. By analyzing disparate sources of data and looking for connections and relationships to important outcomes, we can share those “ah ha” moments that an employee may have never known and help them improve their effectiveness. When employees feel effective, they are more likely to be engaged.

2. Anticipate problems before they happen. Survey data is always a look back in time and at best a point in time measurement. If we can analyze data daily and use machine learning to look for pattern recognition, we can start to share predictions for the future and make recommendations to avoid missing a deadline, feeling burnt out or being spread too thin. 

3. We aren’t getting in the way. With all of the distractions an employee faces in a day, a survey is just one more thing to get someone out of their flow and then hope that their manager does something with the results. There will always be a time and a place to survey your employees, but we now have the technology to get similar insights in an unobtrusive way.

Responsibility on employers and vendors to consider privacy
As we move into this new area of digitally ambient data, there is a huge responsibility on vendors and employers to consider how they leverage this data. Employee trust will be paramount. Are you using the data to stack rank employees or are you giving your employees their own data to analyze? Are you pulling meta-data or are you analyzing private conversations? If we have any hope of leveraging powerful technology in this space, we need to safeguard employee trust and follow a strong standard of ethics at every step of the way. 

What’s next?
Not everyone has caught onto this approach. The survey business is still lucrative and likely will continue to surge in the near future. But as the war for talent proliferates, companies will be forced to consider new and innovative ways to empower their employees to be as effective as possible and ultimately more engaged. And to do that we will need to stop asking so much and start observing again.

This post was written by David Youssefnia, PhD, co-founder and Chief Strategy Officer at Uplevel.