Sunday Reads #105: How to think like an Epidemiologist
And Business Success Stories, a Negotiation Masterclass, and more.
|Jitha Thathachari||Sep 6|
Hope you and yours are keeping safe (and sane).
I'm back again with the most thought-provoking articles I've read in the week.
If you’re new here, don’t forget to check out the compilation of my best articles: The best of Jitha.me. I’m sure you’ll find something you like.
This week, we first start with an introduction to Bayesian reasoning - the #1 tool for being rational in life and business.
Next, a couple of fascinating business success stories from the Twitterverse. How Joe Rogan became the world’s #1 podcaster “overnight”, and how Kanye West overcame $53M of debt, to become a millionaire. In just four years.
And third, the best book I’ve read on negotiation. A masterclass by a top FBI hostage negotiator.
Here's the deal - Dive as deep as you want. Read my thoughts first. If you find them intriguing, read the main article. If you want to learn more, check out the related articles and books.
[PS. If you like what you see, do forward to your friends. They can sign up with the button below.]
1. How to think like an Epidemiologist (OR, the way of the Bayesians).
I came across this excellent NYT article this week, How to Think Like an Epidemiologist.
While it is ostensibly an article about COVID-19, it's a great introduction to Bayesian thinking.
What is Bayesian thinking?
Based on Bayes's Theorem of Probability, Bayesian thinking is the right way to update your beliefs about the world as you get more information.
Quoting from the article:
As Marc Lipsitch, an infectious disease epidemiologist at Harvard, noted on Twitter, Bayesian reasoning comes awfully close to his working definition of Rationality.
“As we learn more, our beliefs should change,” Dr. Lipsitch said in an interview. “One extreme is to decide what you think and be impervious to new information. Another extreme is to over-privilege the last thing you learned. In rough terms, Bayesian reasoning is a principled way to integrate what you previously thought with what you have learned and come to a conclusion that incorporates them both, giving them appropriate weights.”
The basic formula for the Bayes Theorem is pretty simple:
Prior Odds * Relative Likelihoods = Posterior odds
I won't go into a detailed introduction to Bayesian thinking here (I’d need an additional 5K words 😄), but this is a great introductory article .
Why is Bayesian thinking important?
Because our intuitions are lousy statisticians.
Take this example from Bayes’ Theorem and the Deathly Hallows, a good primer on Bayesian Thinking in medical testing.
A patient goes to see a doctor. The doctor performs a test with 99 percent reliability—that is, 99 percent of people who are sick test positive and 99 percent of the healthy people test negative. The doctor knows that only one percent of the people in the country are sick. Now the question is: if the patient tests positive, what are the chances the patient is sick?
The intuitive answer is 99 percent, but the correct answer is 50 percent…
Surprised by the answer? Read the article to understand why you got it wrong.
Here's another example of how un-intuitive all this is, this time from the COVID world.
And here's the Scientific American, talking about the fallacy of the “antibody passport”, back in April.
What would happen if we used the FDA-approved Cellex test to issue COVID-19 passports in a hypothetical society with 10,000 people where the prevalence is 1 percent? If all 100 people who had COVID-19 also had antibodies, passports would be correctly issued to 94 (94 percent of 100) of them who test positive. Of the 9,900 uninfected, 9,504 (96 percent of 9,900) would correctly test negative. However, the remaining 396 (4 percent of 9,900) would falsely test positive and get passports incorrectly.
Thus, 396 out of the 490 (94 plus 396) passports issued (four out of every five) would be illegitimate!
And this is important in business too!
Bayesian thinking is the #1 tool for being rational in life and business.
I've found three primary insights from Bayesian thinking, applicable to business.
#1: When you know almost nothing, even a little information teaches you a lot.
On any problem with an uncertain outcome (e.g., a high-intensity M&A negotiation), it's vital to learn as much as we can from every interaction.
And we need to be nimble with our beliefs. Going into a negotiation discussion with a certain set of assumptions (e.g., the opposite party will never trade away a certain right), we need to be able to update our beliefs based on what we hear.
On a similar note, the Rule of Five is particularly useful when you’re doing a survey to understand a population. You learn a surprising amount by just taking a dipstick sample of 5 respondents.
There is a 93.75% chance that the median of a population is between the smallest and largest values in any random sample of five from that population.
#2: Extraordinary claims require extraordinary evidence.
If an industry analyst tells you that he can predict exactly the contents of your competitor's big secret announcement in 7 days, that's an extraordinary claim.
If you don't really believe that predicting is possible (i.e., your prior probability of successful prediction is low), then he better have good reasons for making that claim. Does he have a past history of 50 successful predictions? Does he have an insider track into the competitor?
#3: Ordinary claims require only ordinary evidence.
Conversely, for things that are more likely, you don't need a mountain of evidence.
For instance, let’s say you’ve hired a new person in your team.
We know that 1 in 3 hires fail (and the ratio may be even higher for senior roles).
In this situation, you don't need 5 colleagues to come and complain about your new recruit's work quality, before you're moved to act. A couple of independent points of feedback are more than enough.
I’ll write more about Bayesian thinking in business soon.
But in the meantime, here's some further reading on the topic:
Guide to the Bayes’ Rule: This is a great summary introduction to Bayes' theorem and Bayesian thinking. Highly recommended.
Here's Robin Hanson applying Bayesian thinking to the recent UFO sightings. Given the puzzling sightings of Unidentified Flying Objects, how likely is it that we were really visited by aliens? (Spoiler: very unlikely).
And on a lighthearted note, here's a comic about a Bayesian Vampire 😊
2. Business Success Stories from the Twitterverse
Two great twitter threads, on recent business success stories.
Success Story #1: Joe Rogan, the world's most successful podcaster.
As Joe Rogan's $100M+ deal with Spotify starts, a good time to look at how he's succeeded overnight.
My key takeaways from the Twitter thread:
He worked hard (and for over 3 decades) at cultivating his niche.
He started from one area of expertise, and kept parlaying and extending into the next one.
Martial arts (retired at 21) → Comedy (financed by tons of odd jobs) → UFC commentator → Fear Factor → Podcast in 2009, when the sector was still so nascent.
He jumped on a new distribution channel (podcasting), right in its infancy. So he was able to ride the wave higher than anyone else.
And last, there's no such thing as overnight success.
That's the wonder of compounding. Things happen slowly, and then suddenly.
The below GIF (courtesy Mother Jones) is a great illustration of this. Watch how slowly the pond fills up (you barely see the water), and then suddenly it's full.
I wrote about compounding and exponential growth in Sunday Reads #104, with reference to Stan Lee and Marvel Comics:
In 1961, when Stan Lee first conceptualized Spiderman and Iron Man, he was already 39. He'd already been working in comics for TWENTY PLUS years!
And it was another few decades before Marvel’s fortunes soared skywards.
Morgan Housel has also written about the power of a freakishly strong base.
Success Story #2: Kanye West, a successful artist and an amazing negotiator.
Read the thread. It's an incredible negotiation story.
How Kanye played two competitors (Nike and Adidas) against each other.
How he asked for the moon, and got it. (Good reminder - you don't get what you don't ask for).
The power of creating scarcity and exclusivity around a brand.
If you want to read another remarkable negotiation story, read about how Microsoft got started on its journey to world dominance. It all began with a plucky 25 year old pushing IBM into a sweet, sweet deal - The Agreement that Catapulted Microsoft over IBM.
3. The World of Books
Speaking of amazing negotiations, Never Split the Difference is one of the best books I've read on the topic. It's written by an FBI negotiator, with tons of experience negotiating in high-pressure situations, with high stakes.
I've seen numerous examples (personal + anecdotal) of this book’s approach working in business negotiations as well.
I’ve summarized my notes from the book here.
The book has three Big Ideas.
Big Idea 1: Calibrated Questioning
Give your counterpart the illusion of control, but constrain them at the same time.
Big Idea 2: Tactical Empathy
In a negotiation, listening is the cheapest, yet most effective, concession we can make.
Big Idea 3: Controlling a Negotiation
By tapping into the power of framing, loss aversion and prospect theory, you can “bend your opponent’s reality”.
Check out my notes from the book here. (I'll also add a PDF soon, that you can download).
4. And last, just for fun...
I found this video hilarious!
Look at the moment when the Serbian President (sitting to Trump’s right in the video) realizes he's just signed up for something he didn't realize.
That's it for this week! Hope you liked the articles. Drop me a line (just hit reply or leave a comment through the button below) and let me know what you think.
See you next week!