The Pareto Principle article on Wikipedia is a really valuable read.
Unless you’ve been living under a rock and not reading the hundreds (thousands, perhaps?) of articles online that over-apply the idea of the Pareto Principle, you already get the main idea.
20% of something is responsible for 80% of something else.
That’s the core idea, expressed in the most general possible terms.
Here’s the actual principle as described by Wikipedia:
“The Pareto principle (also known as the 80/20 rule, the law of the vital few, or the principle of factor sparsity) states that, for many events, roughly 80% of the effects come from 20% of the causes.”
The critical caveat there is: “for many events”. Not for all events. Not for all phenomena.
That said, the Pareto Principle is impressively explanatory. It fits lots of phenomena, and in so doing provides a reassuringly simple sense of order to the world.
It, however, does not explain why 80% of the effects come from 20% of the causes. And it does not predict causation; meaning it does not predict which causes will have that outsized contribution to effects.
The Pareto Principle is not truly universal either. You can’t just pick any pair of cause and effect and say 20% of this cause will be responsible for 80% of this other effect. I mean you could say that, but you would often be wrong. 🙂
If you read the Wikipedia article (and I think you should), you’ll see lots of examples of situations where the Pareto Principle does and does not apply. Here is one interesting place where it does not:
“However, it is important to note that while there have been associations of such with meritocracy, the principle should not be confused with farther reaching implications. As Alessandro Pluchino at the University of Catania in Italy points out, other attributes do not necessarily correlate. Using talent as an example, he and other researchers state, “The maximum success never coincides with the maximum talent, and vice-versa.”, and that such factors are the result of chance.”
Digging deeper into Pluchino’s research is fascinating, and we find this helpful summary of their research from the MIT Technology Review.
Quick aside: it was amusingly ironic to me that the abovelinked MIT Tech review article was published in early 2018, around the same time that one of the biggest recent “black swan” events involving complex systems was kicking the crap out of the world economy. The Pluchino paper’s authors talk about how luck is the determining factor in success, and they were doing so at a time when something like luck was an outsized factor in the health of the world economy, but in a negative–rather than positive–direction.
From the MIT Tech Review summary:
“The results are something of an eye-opener. Their simulations accurately reproduce the wealth distribution in the real world. But the wealthiest individuals are not the most talented (although they must have a certain level of talent). They are the luckiest. And this has significant implications for the way societies can optimize the returns they get for investments in everything from business to science.”
Just like with the Pareto principle, there’s a certain sense of comfort we get from ideas that are simple to express, but in this case the explanation is: “They’re wealthy because they’re lucky”, not “They’re getting outsized results because they know what 20% of inputs to focus on”. Both ideas suggest a simple correlation between inputs and results.
Here’s the actual paper Pluchino and his team published, BTW. The MIT Tech Review summary (necessarily, I imagine) omits lots of juicy, interesting detail from the source paper. For example, the following:
“In fact, from the micro point of view, following the dynamical rules of the TvL model, a talented individual has a greater a priori probability to reach a high level of success than a moderately gifted one, since she has a greater ability to grasp any opportunity will come. Of course, luck has to help her in yielding those opportunities. Therefore, from the point of view of a single individual, we should therefore conclude that, being impossible (by deﬁnition) to control the occurrence of lucky events, the best strategy to increase the probability of success (at any talent level) is to broaden the personal activity, the production of ideas, the communication with other people, seeking for diversity and mutual enrichment. In other words, to be an openminded person, ready to be in contact with others, exposes to the highest probability of lucky events (to be exploited by means of the personal talent).”
There’s a whole series of articles begging to elaborate on just that one paragraph! And there are echos of the widely distributed quote: “The harder I work, the luckier I get.”
What’s our bottom line here?
I hope you’re a little less quick to apply the Pareto Principle to any ole situation, and more thoughtful about it when you do. Going forward, I certainly will be.
There’s a deeper question I’m grappling with here:
If you’re curious what contributes to success, who do you model?
I mean sure, you can just throw up your hands and say: “Luck matters. So…. good luck! See ya!”
But if you’re in the business of advising clients, surely you’re interested in more systematic ways of helping them improve their condition, right? Surely they’d like to get a little more for their money than an elaborately fashioned statement of: “Good luck, kid!”.
So that raises the question: who do you study and attempt to model as you’re looking for the patterns that contribute to success?
I don’t mean who specifically do you look at to understand what contributes to success. I mean where in the distribution of outcomes do you look?
Let’s think in Pareto terms, and let’s think about 3 layers of an “onion”:
- In the outer layer of the “onion”, 80% of the effects come from 20% of the causes. Ex: 80% of dollars of global wealth come from 20% of people.
- In the middle layer of this onion, we apply the same 80/20 distribution to the top 20% from the previous layer of the onion. Ex: 64% of global wealth comes from 4% of people.
- In the innermost layer of this onion, we go again with the 80/20 applied to the previous layer and get: 41% of the global wealth comes from 1% of the people (and in this we hear echoes of Occupy Wallstreet’s “the 1%”).
If you’re wanting to understand what contributes to success in some endeavor, which layer of this onion do you look at to discover patterns?
It’s tempting to look at the innermost layer–the 41/1 distribution. It’s tempting because this is the smallest group, so, questions of access and transparency aside, it should be the easiest to study. It’s also the group with the most emotionally impressive ratio between inputs and outcomes. After all, these people have the same 24 hours in a day and many of the same fundamental constraints we all do. If they need to fly from New York to London for business, they can’t do it 10 times faster on a $50 million Learjet than someone who buys a $500 coach ticket on Norwegian Air. Other aspects of their experience might be 10 or 100 times better, but they won’t get there 10x faster. Yet despite sharing many constraints with the rest of us, they get such outsized results!
This innermost layer of the Pareto Onion is a seductive place to look for patterns that contribute to success, but I am unconvinced that it’s the best place for such lessons.
My hunch is that, like Pluchino’s team claims, idiosyncratic factors like luck–but not limited to luck–play an outsized role in what gets you to that inner layer of the Pareto Onion.
I am respectful of the role that idiosyncratic factors play in your life and career. And like the Pluchino paper says, you can (and should!) do things that increase the chances that these idiosyncratic factors work in your favor.
But I’m more interested in understanding systematic factors that contribute to success for small expertise-driven businesses. And that means I’m not looking at the inner layer of the Pareto Onion. In fact, I’m not sure I’m even looking at any layer of this onion. In other words, the best lessons for systematic success might not lie in the top 20% at all!
I hope this is at least a little bit shocking to you.
I can’t prove this yet. It’s just a hunch.
But stay tuned as I follow this thread. I think it’s important.
On a personal note, is anyone else psyched that Apple is adding mouse support to iPaDoS 13 or whatever they’re calling it? When my wife and I hit the road 2 months ago I committed to using an iPad as my primary work computer (and quickly upgraded to the larger size iPad Pro).
Working primarily on an iPad has added productive friction that I’ve appreciated. And I’ve been surprised how quickly I’ve habituated to touching the screen. Even when I pull out my laptop for some thing I can only do there, I find myself instinctively reaching to touch the screen.
And yet, I’ll be super happy to have mouse support on the upgraded iPad this fall. I hope it supports this SwiftpointGT mouse I have.