#50: Problem solving: Peer networks

18th century Europe was a particularly exciting time if you were in the seafaring business. There were multiple ventures, several with vast capital investment attempting some very bold goals (most of these ventures would be outright illegal or egregious by today’s standards or ethical standards of any age – colonial ambitions, slave trade et al.... Continue Reading →

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Update your priors!

The other day, I saw a t-shirt slogan – ‘Update your priors!’ These nerdy t-shirt slogans are not uncommon in the Silicon Valley. This one caught my eye – to me, it has never been more relevant given the current swirl of data and analysis around Covid-19, now that epidemiologists and statisticians are in a... Continue Reading →

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Complex Systems: Limits to our understanding

Over the last several weeks, I have been writing about decision making, with the focus being how to get better at navigating VUCA environments. This has been rooted in the paradigm of reasoning and a deterministic view of the world. Which to be sure, works pretty well in most situations. And then we got hit... Continue Reading →

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Problem Solving: Learning from other disciplines

Richard Feynman Richard Feynman (he doesn’t need an introduction) was a consummate problem solver. When asked about his problem-solving techniques, his colleague Murray Gell-Mann (a Nobel Laureate himself) defined the ‘Feynman Problem Solving Algorithm’: Write down the problemThink very hardWrite down the answer While this was partly in jest, this to me captures why it... Continue Reading →

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Navigating extreme events with small data

Here’s a thought experiment: Fred and Bay want to run a coin toss experiment. They want to make sure that the coin is completely unbiased – so they go to the US Mint and get a quarter that has passed all its tests (i.e. there is no manufacturing defect[1]); toss the coin 100 times. They... Continue Reading →

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Designing a Learning System

In 1651, Thomas Hobbes wrote, “reason … is nothing but reckoning (that is, Adding and Subtracting) of the Consequences of generall names agreed upon.” It is widely accepted that with this, he laid the foundation for the Computational theory of the mind. And as often happens in science, one thing led to the other and... Continue Reading →

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#60 – Rediscovering the maker mindset

You have probably heard of the growth mindset (Carol Dweck’s seminal work in development psychology). This is the recognition that the brain is a muscle – with practice, effort and nurturing, it can continue to grow and develop, a clear departure from the more fixed mindset of intelligence being an innate trait (you either have... Continue Reading →

#58 – Learning Systems

In my last post, I had made a case for expertise – and why it is important to have the necessary domain expertise in high performing teams. And not surprisingly, I got several responses arguing that experts are over-rated. Which I tend to agree with – experts are over-rated, but expertise is definitely not. The... Continue Reading →

#57 – What is expertise?

In one of the more obscure corners of the internet, there is a raging debate going on in the chess world ('A bird-seed seller beat a chess master online. And then it got ugly') Well worth a read – here’s the nub of the issue: on chess.com, an obscure player from Indonesia rose rapidly in... Continue Reading →

#56 – Problem Solving: Insights

The bright Data Scientist in your team has spent several intense days with a problem statement and comes to you with a bunch of Analysis and charts. She is all excited with her work – and your first question, ‘Where are the insights?’ I find some managers use this almost reflexively as a way to... Continue Reading →

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