How we work, who we work with, and even what we define as work is rapidly changing, but the most transformational change—at least for our professional lives—may be occurring at the intersection of data, sensors, and artificial intelligence. Companies in all fields are beginning to dive into the world of big data in order to increase the health and happiness of their employees, along with boosting productivity and overall output. Using a variety of methodologies including workplace wearables, employers now have more information than ever about their employees. But what to do with that information?
Employers are beginning to take on more interest and responsibility in their employees’ mental and physical health. There are a variety of reasons for this. One of them is growing acknowledgment of the link between happy employees and better business performance. As a result of this link, many companies are employing a range of approaches to assess the mood and well-being of its staff. For example, manufacturing company John Deere is testing a new, comprehensive, bi-weekly review system for measuring their employees using a “happiness metric.”
Beyond surveys, employers are now beginning to use technological methods to gauge employee well-being. Consider Hitachi, whose employees wear happiness-measuring sensors that are housed in badges. The sensor collects data on employee movements 50 times a second throughout the day, including employee time spent sitting, walking, nodding, typing, and talking. Using these metrics, Hitachi has invented an algorithm that measures happiness; they’ve dubbed the whole system Human Big Data. We’re still waiting to hear the first round of conclusive results from the device, which debuted in February 2015, but Hitachi isn’t alone in pursuing the use of sensors to gauge and improve employee satisfaction.
Bank of America wanted to study how group dynamics impacted performance, so they tested a similar badge-based sensor on 90 call center employees. The resulting data revealed that it was important for the company to allow group breaks, as employees would often troubleshoot their workplace problems and also created “a cohesiveness shared between the coworkers.” Based on their research, Bank of America made a few adjustments to their culture policies and reported a 10 percent improvement in productivity.
There are other ways to apply data in the workplace beyond assessing employee health, of course. The pairing of personal data—people’s skills or assets, productivity, preferences, and availability—with intelligent systems is also influencing employment models and job roles. As a basic example of this model, the on-demand economy consists of technology platforms pairing people and their assets or skills with predefined tasks. “Find me a taxi to take me to location X.” “I need a graphic designer to complete project Y.” “Locate a housecleaner to visit my apartment on date Z.”
Now consider a much more sophisticated version of this process that will enable organizations to provide real-time assessments and recommendations on employees and job roles. By using workplace wearables that generate data linked to job performance, productivity, and professional satisfaction, employers will also be able to better connect their employees with the work they are best suited for and is meaningful to them. In their recent report in 2014, Pricewaterhouse Coopers states that “metrics and data used to drive business performance through…strategies that identify thousands of skills sets will help create precision around sourcing the right candidates for the right tasks.”
Imagine a business executive has just been given a huge project with multiple deliverables. In the future, she will be abel to use an intelligent system to analyze the project, break it into smaller tasks, generate job roles, and recommend team members who are best suited to tackle certain portions of the project based on insights stemming from their personal data.
The same PWC research predicts similar applications for health care. “Periodic health screening will give way to real-time monitoring of health, with proactive health guidance and treatment to enable staff to perform more efficiently and reduce sick leave,” the authors note. For example, if an employee’s data reveals a blood pressure increase it will trigger an automated text or email with a suggestion to schedule a checkup, including contact information for their primary care physician.
Of course this all may sound fantastic, but let’s be realistic: This technology is still in its earliest stages. Only 7% of employers use data collected from sensors to assess employees, according to Springbuk Health Analytics. That said, now is the time to consider how the growing amount of personal data will require rigorous new policies.
How will employers define their opt-in policy around wearables? Who has access to the resulting data? If employers collect employee data that indicates the employee may have a serious health condition, should they notify the employee? How can employers provide transparency in regards to assigning job roles to avoid bias assumption? After an employee leaves an organization, what happens to their data? These kinds of questions barely scratch the surface on all the data privacy implications.
Technology is supposed to improve our work lives and business outcomes, but the ways companies are able to engage and educate employees about new technologies will ultimately determine their success. Proactive communications and full transparency will help shape a fair, more efficient workplace, and this relationship must be treated as a partnership between employer and employee.
The potential benefits of such innovations are vast, but they also require a critical eye. We’re entering a time where we may, in fact, be able to work less while doing more for ourselves—and society. It is a massive mind shift, but considering the progress already being made in certain areas, we’re on the precipice of a transformational change.