Harvard’s Brain-Bender

Sometimes I think that Harvard Business Review should have a coloring page.

The January/February 2012 issue is a “Special Double Issue” with 156 pages. (In comparison, the December 2011 issue was a regular one-month issue with 148 pages. I can’t find the November issue, but October’s one-month issue was also 156 pages.) So having a few more pages than the previous month and the same number of pages as a couple of months before that somehow makes this issue “double”. If this is the sort of math they teach at Harvard, it’s no wonder the world’s economy is in the shape it is…

Anyway, I opened up the current issue and my eyes were assaulted with this graph, ‘How Electricity Powers Well-Being‘.

In the text the author, Arun Majumdar, says, “Electricity does not cause well-being, of course. But it is a powerful enabler.” Well, Arun, if electricty does not cause well-being, then why do you say precisely the opposite in the title of the graph?

I’m not going to quibble with the text since the graph itself is such a train wreck: There are no axis lines, even though the vertical axis does not start at zero. The data points (one for each country) are all the same size, many that are similar colors overlap and there is no indication why certain ones are colored one way and others another way. (India, which has an enormous population, is the same size as Kuwait, which does not.)

There’s a text box on the graph with which I am willing to quibble. It says: “When annual energy consumptiton per capita reaches just 2,500 kilowatt hours [per person per year], countries move near the top of the human development index.”

Strangely, the consumption level of 2,500 kilowatt-hours seems to be depicted as a shaded range, rather than a single value. More importantly, though, consumption of electricity clearly from the graph exhibits diminishing marginal returns. A person with a smartphone can do more than the one with a regular phone, but the person with 10 smartphones cannot do 10 times more than the person who only has one. The biggest jump is from no phone to one phone. Phones #8, #9, and #10 add comparatively little value.

The same is true of many things: number of cars you own, number of flush toilets in your house, the number of cheeseburgers on your dinner plate tonight, and the number of kilowatt-hours of electricity you consume each year.

So the natural scale on which to plot the x-axis of this graph is logarithmic, not linear. I made the following graph using Gapminder, which has data available up to 2008, but since the Harvard Business Review article’s graph uses data from 2006, the graph I made below uses 2006 data as well. Gapminder’s data is from the International Energy Agency, but essentially the same as the source of the HBR data.

The size of each bubble is related to the country’s population and the color to which region of the world it is in.

We can see from that graph that there is nothing magical about the 2,500 kilowatt-hour value. A consumption level of 100 kilowatt-hours per person per year is correlated with an HDI of about 0.4. For consumption levels about 10 times higher the HDI is about 0.65. And ten times higher again is correlated with an HDI of about 0.9.

Of course, there are exceptions. Zimbabwe consumes about 1000 kilowatt-hours per person per year, but does not rank above 0.2 for HDI. I’m guessing the people who run that country must spend a lot of time reading Harvard Business Review.


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