Recently, I started playing around with some numbers. My first question was actually the one you find in the title —you will find an answer to this question lower down in the text. The result is quite surprising and made me think about scale.

Scales are notoriously hard to understand. That is why we usually break down large numbers and explain them by using smaller numbers in other categories. In this article, I will do the same by breaking down very large numbers of hours into “lifetime equivalents”, or the average number of hours a human lives or works. Let’s start!

Have you ever wondered how much time is wasted? And how much time is used productively? As an example: How much time do you think is wasted just by reading a boring news article? Let’s say that article takes 10 min of your time. But of course, you’re not the only one reading it, maybe it reached 100 million people all across the planet. 100 million people spending ten minutes to read an article. That’s an astonishing 16.7 million hours wasted. And that is, incredibly, the average lifespan of 24 human beings (79 years, which I will use as average lifespan of a human is 692,040 hours).

Before continuing let’s define another metric. The average productivity of a person is roughly 1/3 of their lifespan, as we tend to be productive for about 8 or more hours a day. We should choose the lower number, because at very young and at very old age, we can’t really count the time as productive in an economic sense. An average productive lifespan therefore has about 230.680 hours.

These calculations are illustrative and make a lot of assumptions. But all give examples of how to visualize scales. Scales are an incredible thing. We are very bad at perceiving small or large scales correctly. Even mathematically minded and trained people tend to short out when they need to envision orders of magnitude. Sometimes mathematics lends a helping hand and we figure out that a change in order of magnitude (a change of scale) doesn’t actually change the behavior of a system. Such scale-invariant systems are useful in physics, where they help theorists get a better grip on the dynamics without having to worry too much about what happens when we scale up or down. But as we know, the real world doesn’t work like that — there is a difference between an atom and a planet. And of course there is a difference between 5 people working and 5 million people working.

Let’s do the exercise promised in the title of this article. And let’s start with you. How much of your time are you wasting? If your spend about an hour every day killing time (browsing aimlessly, reading articles that you can’t remember 30 min later, doing things that don’t really benefit you in terms of productivity OR relaxation), you are wasting about 7 hours a week. That’s almost a full working day. Over the course of one year, that becomes 364 hours.

At least that is time you have control over. What happens when you think on larger scales (there we are again)? What happens when the board of a multinational company (say 5000 affected employees) makes a decision that requires everybody to work one more hour, or makes everybody do non-productive work for an hour? Every day, these people collectively lose 5000 hours of productive time. Either this time is wasted on company hours — i.e. people still work their scheduled times, but their work is non-productive — which generates a net loss in productivity for the company. Or this time is wasted on an affected employee’s time — this happens when everybody does a single hour of overtime filled with non-productive work. We get to the implications a little while later.

Either way, we are losing about 25000 hours of time every week assuming a standard five-day workweek. Over the course of a year (220 workdays), this adds up to an astonishing 1.1 million hours. Or one and a half lifetimes (defined as 692,040 hours). This puts inefficiency and scale into perspective. The larger the scale, the more important become efficiency and good decisions. Using the above description of productive time, i.e. assuming that a person does about 8 hours of truly productive things every day (by which I mean everything from working to reading a book to playing with children to having a glass of wine with a couple of friends), 1.1 million hours is the productive equivalent of about 5 people. Thus, this board’s decision destroys the productive lifetime equivalent of 5 people.

Not only is this a shocking result, I believe it’s a severe underestimation. And since such non-productive work isn’t usually “part of the job description”, it’s work done after-hours, meaning it’s going off your time, not the company’s time. It is the hallmark of bad decision makers everywhere and is literally costing lives.

Here is what I understood when I played around with these numbers:

1. Scale makes things hard to understand, and not thinking about scale means not having perspective.
2. A life is actually a very short amount of time. After just 700,000 hours it’s expected to be over. We should all be more conscious of the short amount of time we have. An hour seems so much more important when you know that there is a finite amount of them.
3. If something feels wasteful of your time… don’t do it. If that applies to your work — be smart, find a way around it or instigate change to how you and your colleagues work. Should you, dear reader, be a board member, be more mindful of your employee’s time and the value you are not creating.
4. Being a mindful author means to say: I’m sorry if I wasted your time. But if your derived value from this change of perspective I’d be happy for comments or a discussion.

# # Disclaimer

This article states the author’s views and does not reflect the views of his employer.

Dr. Burkhard Schwab is a theoretical physicist with a Doctor of Science from ETH Zurich and an MASt. from Cambridge University. He has worked in active research positions at Brown University and Harvard University and is currently a business and strategy consultant in Germany.

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Ph.D. in theoretical physics — Data Scientist — technology enthusiast — voracious reader — staunch citizen of the world (with a European bias…)

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Ph.D. in theoretical physics — Data Scientist — technology enthusiast — voracious reader — staunch citizen of the world (with a European bias…)