The quantified self movement has gained significant momentum over the last few years as more and more people have sought ways to collect data on all aspects of their life.

Similarly, as most of the world worked from home last year, many companies looked for ways to assess the productivity of their employees.

The question is – does it help make us more productive to track our work in a quantified way or not? In this Science of Productivity episode, Matt Plummer shares what the research’s answer. 

Prefer to read? Here’s the transcript:

The science of productivity segment brings you scientific insights you can trust into how accomplish your goals faster. In this week’s segment, I want to share research that unpacks whether tracking data on yourself will boost your productivity.

People began tracking data on themselves using large, unwieldly computers as early as the 1970s in the hopes of “gaining knowledge through numbers.” In the last 15 years, this trend has exploded, popularized by the technology magazine Wire beginning in 2007. Today, we can track an incredible amount of data on our lives from health data using devices like the FitBit to how we spend our time, using applications like RescueTime.

While the ability to collect and analyze such data has increased, the question remains: does it make us better and more productive, particularly in the work context?

Researchers from Stanford set out to answer this question by placing RFID tracking technology on workers in a garment factory in India. To remove the effect of incentives on performance, the researchers instituted the RFID tags without linking them to any performance-based incentives for the workers. They simply tracked the data and made it visible to the employees themselves.

And just tracking the data in this way increased the productivity of the workers by over 8%, but only for some workers. Productivity rose by this margin for workers completing simple tasks. However, for workers completing complex tasks, productivity dropped by 5%.

Quantification works when the task is simple because we are convinced that the data meaningfully represents the goal we are trying to achieve. However, for complex tasks, the data doesn’t represent the true goal, causing the tracking and displaying of such data to be distracting and ultimately, demotivating.

The key takeaway is that if you want to quantify the output of your work, be sure that the work is simple enough that one or a few data points will accurately represent it. Otherwise, it will likely have the opposite effect.

Sources:

Ranganathan, Aruna, and Alan Benson. “A numbers game: Quantification of work, auto-gamification, and worker productivity.” American Sociological Review 85.4 (2020): 573-609.