The dogmas of data science are harmless for data-led companies whose value mechanisms are a by-product of their data. But companies whose data are a by-product of their value mechanisms need a more flexible approach. — Modern data analytics is characterized by three mythical dogmas Data are the only natural starting point for all analysis The way to ensure objectivity is to suppress speculation and “simply” gather data — “the facts” — with righteous impartiality

The trouble that lurks in the parameterization and the properties of the PERT distribution — For many, the PERT distribution is now the go-to distribution for encoding quantitative insights from subject matter experts. But the PERT distribution is an ad hoc, belt-and-braces distribution determined far more by calculation convenience than any meaningful correspondence with the uncertainties we encounter. …

Black Swans call for a radical reappraisal of the way we model, but we are just as deluded about their significance as we are about our ability to explain and predict them. — According to Nassim Nicholas Taleb, the author of the highly influential book “The Black Swan”, a Black Swan event is characterized as follows: First, it is an outlier, as it lies outside the realm of regular expectations, because nothing in the past can convincingly point to its possibility. Second, it…

Thank you and thank you for your thought-provoking comment. Much appreciated You characterization of Popper is spot on, I think. And you're absolutely right that DS is inherently inductive. It doesn't get much more inductive than regression and a great deal of data science is basically regression on roller skates. …

The demystification of mathematical modelling is the first step to raising the level of mathematical literacy in public debate — Under COVID, our lives are dictated by the mandate of a handful of mathematical models. The public understanding of those models has never been more essential. Yet models are often discussed as if they were the exclusive province of a mystical caste of mathematician priests, while at the same time…

How high functioning in other intellectual disciplines can be an obstacle to learning mathematics — In a famous and controversial public lecture in 1959, the scientist and author C. P. Snow lamented the increasing polarization of western intellectual activity into two distinct “cultures”: science, engineering and mathematics on the one hand, and what he called literary humanities on the other. Snow argued that the phenomenon…

A layman’s look at the foundations of Frequentism and Bayesianism and how you can have the best of both. — What is probability? We often hear that there are two schools of thought, Bayesian and Frequentist; that Frequentists believe in an objective measure of probability, which we can only access through large numbers of repeated experiments; and that Bayesians, on the other hand, hold that there is no objective measure…

It’s not because you’re stupid or weren’t concentrating in school — In 1982, Kahnemann, Slovic and Tversky published “Judgement under uncertainty: Heuristics and biases” and shattered humanity’s collective self-delusion that we had any functional intuition for even the most rudimentary problems in probability theory. …

Only one of them is actually a book on leadership — The five books that taught me most about leadership are On Grand Strategy by John Lewis Gaddis War and Peace by Leo Tolstoy The Open Society and its Enemies by Karl Popper Talleyrand by Duff Cooper Middlemarch by George Eliot By leadership, I mean the act of forging and articulating…