The E-mail Productivity Curve

A Mixed Response

Late last year, Pew Research found that online workers identified e-mail as their most important tool, beating out both phones and the Internet by sizable margins. Almost half of the workers surveyed claimed that the technology made them “feel more productive.”

As Pew summarized: “[e-mail] continues to be the main digital artery that workers believe is important to their job.”

Around the same time this research was released, however, Sir Cary Cooper, a professor of organizational psychology, made waves at the British Psychological Society’s annual conference by identifying British workers’ “macho,” always-connected e-mail culture as a factor in the UK’s falling productivity (it now has the second-lowest productivity in the G7).

Cooper went so far as to advocate companies shutting down their e-mail servers after work hours and perhaps even banning all internal e-mail communication.

This bipolar reaction to e-mail — either it’s fundamental to success or terrible — extends beyond research circles and often characterizes popular conversations about the technology.

So what explains this oddly mixed reaction?

I propose that the productivity curve at the top of this post provides some answers…

The E-mail Productivity Curve

The above curve shows the rise and fall of productivity (y-axis) as e-mail use (x-axis) increases from a minimum of no e-mail to a theoretical maximum of non-stop e-mail use.

Notice, at the left most extreme (i.e., no e-mail use) productivity remains healthily above zero. This captures the obvious reality that even if e-mail (and similar digital communication tools) were banned, companies could still get stuff done, as they did in the many decades before such technologies were introduced.

As we begin to move to the right (increasing e-mail use) productivity increases. This point should also be obvious.  It’s hard to argue against the proposition that e-mail is an immensely useful technology: universal addressing, instant information transfer, asynchronous storage and retrieval — these are all hard communication problems that e-mail solves elegantly.

As we continue to move to the right, however,  things get interesting.

Eventually we will arrive at a theoretical maximum point on the x-axis where all workers ever do is check and send e-mails. At this point, no time is left for any actual work, so productivity would be zero.

If we step back, we see our three obvious observations from above tell us the following about any curve that describes a measure of productivity versus increasing e-mail use: the curve will start above zero; it will rise for a while; and it will eventually decrease all the way down to zero.

Any curve matching these criteria will, like the sample curve above, features two crucial points: one where the productivity produced by e-mail use hits a maximum point (marked by the first blue X above), and a break-even point after which  e-mail use makes users less productive than if they didn’t have e-mail at all (the second blue X).

I propose that the mixed reaction to e-mail summarized at the beginning of this post can be better understood with respect to the different regions of this curve.

In more detail…

Those who aggressively defend the e-mail (like the workers surveyed by Pew), are responding to the reality that much of this productivity curve is above the no e-mail level. That is, they’re reacting to the true observation that e-mail can make you more productive than no e-mail.

Those who decry e-mail (like Cary Cooper), are responding to the reality that an increasing number of organizations are to the right of the first blue X (and perhaps even to the right of the second X), and therefore their e-mail habits are making them less productive than they could be if they were more discerning about their use of this technology.

It’s possible, in other words, for your e-mail use to be both making you more productive (as compared to no e-mail) and less productive (as compared to its optimal use).

Holding both these thoughts in one’s head at the same time can be confusing — thus explaining, to some degree, the muddled polarization of e-mail rhetoric.

From Explanation to Opportunity

Once we understand this style of productivity curve, however, we can do more than simply demystify our confusion, we can also recognize a major management opportunity.

With few exceptions, e-mail use arose organically within organizations, with little thought applied to how digital communication might best serve the relevant objectives.

The result is that e-mail habits tend to fall somewhat haphazardly on the e-mail productivity curve, with a bias toward to the right-hand side (as increased connectivity tends to be more convenient for people in the moment, especially when unchecked by other metrics).

It’s important to note that there’s nothing fundamental about these current e-mail habits: an observation which leads to the conclusion that forward thinking organizations could consider exploring different regions of this curve in search of the optimal point.

By thinking in terms of a search for optimality, such organizations could escape the e-mail is either bad or good dichotomy that often cripples such initiatives before they get too far, and instead cast the efforts in terms of process optimization.

To reduce e-mail use, in other words, is not necessarily a repudiation of the technology, but can be instead an embrace of its full potential.