We're More Productive Than We Think

(Bloomberg View) -- Earlier this year I suggested that there was a problem with the tools we use to measure economic productivity:

The way we capture formal productivity data hasn't kept up with modern ways of doing business. As a result, I believe economists underestimate productivity increases.

I have since refined that conclusion: Productivity models don't properly capture gains created by the application of new technology. Furthermore, without a revamp of Bureau of Labor Statistics' productivity models, this distortion is going to become greater because of the latest iterations of mobile-technology apps. This is important because productivity is a crucial driver of economic growth, which by conventional measures hasn't been very impressive since the financial crisis.

When studying any subject, the place to start is with facts and data. Consider the following technologies:

• Slack: Using an app such as Slack to communicate with an entire company, including task-specific groups, management teams and subgroups is a big productivity enhancer. Having the ability to securely share documents and messages as opposed to e-mailing multiple parties is a huge benefit to any business that handles confidential material. Oh, and it's searchable and can be archived for future audits.

• Soundcloud: Imagine having a 90-minute conversation with an investment firm chief, or a Nobel prize winner or a top grad school professor, then being able to share that with as many people as you care to, who in turn can listen at the time of their choosing. We now take for granted that this is an ordinary thing, but it wasn't possible without a full radio or television studio just a few years ago.

• Google docs: The full suite of Microsoft tools for business costs $400 a year on a subscription basis for a single user. How do you capture the productivity gains of putting all of that computing horsepower in everyone's hands at no charge, as Google has done? Or try to imagine what it would have taken in time, personnel and money to do the same things just a few short years ago. How do you measure that obvious improvement in productivity?

You can probably name dozens of similarly indispensable technologies that make you, your co-workers or your employees more productive as well.

Now consider the newest technologies in the sharing economy. Unproductive assets -- from spare rooms to unused equipment to parked cars -- are being transformed into revenue generators. What is the impact of Airbnb, Rent the Runway, Uber and dozens or hundreds of others on productivity and how is the Bureau of Labor Statistics capturing these gains in the formal data?

Arun Sundararajan, professor at New York University's Stern School of Business and author of “The Sharing Economy: The End of Employment and the Rise of Crowd-Based Capitalism,” makes the point with a few specific examples: There are 80 million power drills in the U.S. and on average each is used just 13 minutes during its lifetime; there are 250 million cars in the country and most do nothing more than take up parking spaces or fill garages; millions of dwellings have spare rooms that sit empty; unworn clothing fills closets.

The economic impact of using these assets when they normally would sit idle is potentially enormous. It isn't hard to see that some industries, such as retail, might be hurt if more people are sharing. By the same token, manufacturing might gain if things like tools and cars are used more often and need to be replaced more frequently.

We are overdue for a comprehensive overhaul of productivity models in the modern era. There really should little doubt at this point that the way we measure productivity today, which captured the output of the economy in the last century, isn't up to the task in this century.

This column does not necessarily reflect the opinion of the editorial board or Bloomberg LP and its owners.

To contact the author of this story: Barry Ritholtz at britholtz3@bloomberg.net.

To contact the editor responsible for this story: James Greiff at jgreiff@bloomberg.net.