Supposedly when asked how long it took to prepare his speeches, President Woodrow Wilson said:

“That depends on the length of the speech. If it is a 10-minute speech, it takes me all of two weeks to prepare it. If it is a half hour speech, it takes me a week. If I can talk as long as I want to, it requires no preparation at all. I am ready now.”

It's rather like the saying: "If I had more time, I would have written a shorter letter."

It's easy to think that a longer document, report, or talk would be more difficult. So it's a nice thought that it can actually be harder to do something short and well than it is do to something long. It's rather like Edward De Bono's observation that things get more complex before they get simple.

If you want to make something simple, you have to do the work.

QI has good articles on shorter speeches and letters.

Short speeches

Perhaps the most important curve of our times, Charles Keeling’s  curve shows the change in concentration of CO2 in the air with measurements taken every year for over 60 years. Taken at the top of Mauna Loa volcano in Hawaii because of its high altitude and relative isolation in the Pacific, Charles Keeling’s measurements show that the monthly average CO2 concentration in the air has risen from around 310 ppm (parts per million) to around 410 ppm in 2020. As a greenhouse gas this change in CO2 concentration is one of the critical causes of climate change.

The concentration varies seasonally as plants bloom in Spring and Summer reducing the concentration from its high around May as the CO2 has built up over the Norhern Hemisphere Winter.

The Scripps CO2 program is now overseen by Charles’ son Ralph Keeling.

The Keeling curve

You might think that adding more of a good thing would make things better. And, yes, that’s often true, up to a point. However, the law of diminishing returns suggests that as you add more of a single factor, you are likely to yield progressively lower benefits.

It’s like the old adage, “Too many cooks spoil the broth.” Another cook or two might help, but beyond that, they’ll probably start getting in each other’s way. Aside from cooking broth, you might see the law play out in spending on advertisements, quality improvements in production or your wealth.

And we should also never forget that “more is different”.

The sketchplanation is a homage to perhaps my favourite comedy sketch with an early-career Simon Pegg in the series Big Train: the cake factory (video). Well worth two and a half minutes.

Law of diminishing returns

For almost all mammals, 1.5 billion heartbeats, more or less, is how much you’ve got. From the teeniest, tiniest shrew weighing just a few grams to the largest whale — passing through animals as diverse as robins, monkeys, sea lions, and giraffes — each mammal has broadly in the region of 1.5 billion heartbeats.

Beyond just heart rate, knowing a mammal’s weight can help predict several other fundamental aspects of its life. A tiny mammal will likely have a heart that goes like crazy, live only briefly, and reach maturity quickly. A large animal, in contrast, will have a slow heart rate, a long life, and take its time to adulthood.

The most significant outlier is us, mainly because, in recent years, we’ve significantly extended our lifetime from what would be expected from Nature.

This gem, and many other fascinating insights about size, scale, Nature and physics, I learned once again from the book Scale by Geoffrey West.

1.5 billion heartbeats in a lifetime

If you took all the taxes a country pays each year on one hand, and all the money that people earn on the other, tax freedom day represents the day after which the country’s taxes would be paid by its citizens and the remaining earnings free to spend as they wish. It’s a national average as each individual’s tax freedom day would be different, though in principle you can calculate your own.

Given taxes vary between countries, each country has a different tax freedom day — though it’s not easy to compare as calculations tend to differ. In the US it’s calculated by the Tax Foundation.

Tax freedom day

I grew up with the idea that there are developed countries and developing countries. There was the ‘rich’ world and the ‘poor’ world. I didn’t actively consider it. It’s just always been there. And it’s wrong.

In his excellent book Factfulness, Hans Rosling shows that wealthier countries tend to have smaller families and a low child mortality rate. In contrast, poorer countries are more likely to have larger families and a high child mortality rate. Plotting the spread of countries in 1965 gives a reasonable approximation of a cluster of ‘developed’ countries with small families where most children survive and a cluster of ‘developing’ countries with larger families where more children die. But that was in 1965.

The world has changed a lot since then, and that model of dividing the world into two buckets no longer holds true with the data. Most people in the world are somewhere in the middle.

And more helpful than dismantling my worldview was providing a new model to replace it: a model with 4 income levels instead of 2 and the number of billions of people living at each level. It’s a model with most people somewhere in the middle.

For more, check out the Factfulness book, or Gapminder. And you could do much worse than watch Hans’ entertaining TED talk: the best stats you’ve ever seen.

A world of 4 income levels

I like this simple idea that evidently illustrates that anything that is able to improve, learn, and grow at a faster rate than something else stands a decent chance of making up lost ground pretty quickly. Consider this when you’re hiring, or when you’re worried that some other person or company has got a headstart on knowledge. Position yourself always as the fastest and most persistent ‘improver’ and you’ll stand a chance whatever you’re doing.

Read the full story of Stanford Professor John Ousterhout’s thought for the weekend: a little bit of slope. 

A little bit of slope makes up for a lot of y-intercept.

The value of a telecommunications network is proportional to the square of the number of users of the system.
— Robert Metcalfe

This law explains a little of the remarkable power of a growing network. Each time you add a user, or node, to the network, the number of connections increase in proportion to the square of the number of users. So, in this simple example where every new node gets a connection to each of the existing nodes, you can see that, say, adding a single node to an 11 node network creates 11 new connections.

It’s a simplified example because in most networks the value is not directly proportional to the number of connections as some connections or users may be more valuable than others, and usually adding a new user wouldn’t create a connection to all existing users — say if it was in a different country, or people spoke a different language, or just cared about different things. But nevertheless, you can see how a network quickly becomes valuable as users join.

So, Facebook has about 2 billion users…

Metcalfe was talking about telecommunications networks and the basic proposition has been modified since it was formulated including by Metcalfe himself.

Once again, just because something is called a law doesn’t mean it is one. See Fitt’s Law

Metcalfe’s Law

How the expectations of new technologies often evolves.

The Gartner Hype cycle

Smaller software releases generally means fewer bugs, and bugs that are easier to fix. The number of bugs created typically increases with the complexity of interactions of code, which in turn increases with the size of release. This means that a number of smaller releases can hopefully get you to a large change in a safer way with less bugs, and less problematic bugs, created along the way than a single release with the whole lot. There’s probably a somewhat more general relationship with amount of unexpected problems created and the size of any change.

Bugs and releases

This is an adapted version of the Kubler-Ross model for the stages of grief from her work with terminally ill patients. I should caveat that this is overly simplified in several respects and people don’t necessarily go through all these stages, nor necessarily in this order. Though, when you look at it, it’s hard not to have the feeling that it could provide some value in understanding that complex and difficult situation. I find it interesting as a more generally applicable model of how people deal with change. I think it’s possible to relate to some of these stages at some points in life which have experienced major change.

Stages of grief

The data vary, but for a medium-sized adult you can probably expect half of the caffeine from that 3pm cup of coffee to still be doing half of its thing about 7pm, 4 hours later. Apparently smokers deal with caffeine quicker and caffeine sticks around in children much longer.

You can expect about 10 minutes before it first kicks-in which, I suppose, is why if you’re feeling tired while driving it’s a decent plan to take a break and drink a coffee, then have a 15 minute nap. See tiredness can kill, take a break. Once it starts to kick-in you might hit peak caffeine any time from 45 minutes to 2 hours later.

Caveat: that chart visualisation is extrapolated from reported data, so the shape is approximate only.

Some references say longer, and some say, from 3-9 hours or so. My source which seemed pretty comprehensive was:

Bertil B. Fredholm, Karl Bättig, Janet Holmén, Astrid Nehlig and Edwin E. Zvartau, Actions of Caffeine in the Brain with Special Reference to Factors That Contribute to Its Widespread Use, Pharmacological Reviews March 1999, 51 (1) 83-133;

The half-life of caffeine.

It’s a funny thing, when you think about it, that if you owned a stock in the market and the value went up 50%, and then went down 50%, that it wouldn’t end up at what it started.

Another way to look at it, is if you owned something worth 100 and it lost 50%, it’d be worth 50. To get back to being worth 100 you’d then need a 100% gain. 

Asymmetry of returns

"The only mistake you can make when it comes to financial planning, is doing nothing."
— Carl Richards

If you haven’t seen them before, you might enjoy Carl Richard’s Behavior Gap sketches. This was an attempt at Carl Richard’s style. Only when I finished it did I notice this one. Worried about making a hash of something? Don’t worry. The first draft is always perfect.

Benefits to you from getting started

Translation: The energy efficiency of computers doubles roughly every 18 months.

In a new twist beyond Moore’s Law, which shows signs of reaching it’s limits, there’s Koomey’s Law. In his own words, the idea is:

“…at a fixed computing load, the amount of battery you need will fall by a factor of two every year and a half.”

Why does this matter? It means we can fit more more computing power into smaller and smaller devices. Which is much of the reason the phone in your pocket is probably more powerful than the EDVAC there in the chart.

Koomey’s Law

This chart is from the original he published - just the five data points. Pretty simple huh? The “observation, originally made in 1965, that the number of transistors on an integrated circuit would continue to double every year. Although this increase has slowed to a doubling in eighteen to twenty four months, Moore’s law has held true for nearly fifty years and is the foundation for the astounding Information Technology revolution we see around us.”

For those interested in Moore’s law, remarkably, I think the best information is my Dad’s book, The Computing Universe, which is also the source of the quote.

Moore’s Law

I’ll understand if this hasn’t been a burning question for you. But I’ve always struggled to identify correctly when one is put in front of me. Turns out, after sleuthing, they do have separating characteristics along, colour, the tightness of skin and the amount of seeds. I had to go 3D, but I think this should allow you to identify the next small orangey thing that you eat.

Mandarin Has seeds, loose skin and is orange

Clementine Seedless, tight skin and orangey-red in colour

Tangerine Has seeds, loose skin and is orangey-red

PS I promise no more mandarin-related sketchplanations in a hurry

What’s the difference between mandarins, clementines, satsumas and tangerines?

We sleep for around one third of our lives. If you live until you're 90 years old you will have slept for a remarkable 32 years.

If you live ‘til you’re 90 you will have slept for 32 years

I very often find myself reflecting on what ought to be an improvement to the caveman-esque communication method that is the horn. But it’s harder than it seems I think to make something that supports helpful behaviour, provides safety and avoids lawsuits. Surely can’t be that hard though…

Use of the car horn

Travel and new foods

Data graphics can lie in many ways, but the most common, I expect, is the error of using area or volume objects to represent one-dimensional data.

More data visualisation principles from Edward Tufte.

Watch for the lie factor

Normal (the weight of apples, measurement errors, IQ…), skewed (Number of children in a household, age at retirement…) and Pareto (80/20 rules, long-tails, size of meteorites).

Common distributions: normal, skewed, pareto

From the video Wealth Inequality in America

Wealth inequality in America

Principles from Edward Tufte. Remove chart junk. Erase redundant and non-data-ink. Above all else show the data.

Of course the present infographic trend laughs in the face of these principles in the interests of trying to encourage people to actually look at the data in the first place. But, assuming you actually want people to seriously infer some meaning from the data, these are not bad principles to follow when constructing your data graphics. Some basic Excel templates could do with a clean up for example.

Maximise data-ink

The law of lockers

This helpful framework is an enhancement of regular adoption theory with the different approaches to design for each stage. Canada, Mortensen, Patnaik, 2007 (pdf). Some great examples of each stage in the paper.

Designing for adoption

I think there may be a counter trend at some point too, but generally I think this has some validity.

The wedding bar goes up the more weddings you attend

London dog size is roughly proportional to the distance from central London

I love Bill Buxton’s Long Nose of Innovation theory that basically a ton of small incremental work precedes what feels like a wow innovation moment. Computer mice, touchscreens, robotics, CNC machining, haptics etc were all around for decades before they hit the big time.

The Long Nose of Innovation

I regularly make half-caf coffee. I think there’s a gap in the market. Why is coffee so binary?

Adjust your daily caffeine intake

On productivity and temperature

Getting beyond the getting stuck taught me by Dev Patnaik. The first 50 are the same as everyone else’s via Emily Ford.

Sketchplanations tagged with chart