Sunday Morning Disruptive Technology – The Fermi Problem

20130511-201011.jpgThis dude was around a while ago, but with the increase of Big Data his theory around approximation becomes more and more important.

His name was Enrico Fermi, born in Italy in 1901, passing away in 1954. He did quite a lot within his lifetime but to me in what I do, his legacy of the ‘Fermi Problem’ is what I’ll remember him for.

The Fermi Problem was most famously used in his University teachings in the US to challenge his students to estimate how many piano tuners there are in Chicago. A daunting task if you didn’t work with approximations.

From wikipedia
“A typical solution to this problem involves multiplying a series of estimates that yield the correct answer if the estimates are correct. For example, we might make the following assumptions:
There are approximately 5,000,000 people living in Chicago.
On average, there are two persons in each household in Chicago.
Roughly one household in twenty has a piano that is tuned regularly.
Pianos that are tuned regularly are tuned on average about once per year.
It takes a piano tuner about two hours to tune a piano, including travel time.
Each piano tuner works eight hours in a day, five days in a week, and 50 weeks in a year.
From these assumptions, we can compute that the number of piano tunings in a single year in Chicago is
(5,000,000 persons in Chicago) / (2 persons/household) × (1 piano/20 households) × (1 piano tuning per piano per year) = 125,000 piano tunings per year in Chicago.
We can similarly calculate that the average piano tuner performs
(50 weeks/year)×(5 days/week)×(8 hours/day)/(2 hours to tune a piano) = 1000 piano tunings per year per piano tuner.
Dividing gives
(125,000 piano tunings per year in Chicago) / (1000 piano tunings per year per piano tuner) = 125 piano tuners in Chicago.”

So basically the Fermi Method is to identify a series of assumptions, use these assumptions to obtain answers that seem impossible to calculate given the limited amount of information or data.

I use this method a lot in calculating energy savings, predicting energy consumption and providing a better context of our choices for a more sustainable life – for example water savings from showers versus red meat.

The disruption? Well, we are in real danger that Big Data will stall progress, deer in the headlights style.

Don’t over think the data, break it down into base assumptions and calculate an accurate approximation – use the Fermi Method.

1 Comments on “Sunday Morning Disruptive Technology – The Fermi Problem”

  1. Pingback: Don’t make it until you’ve sold it – common mistake of entrepreneurs « SIMON WILD

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