Data science for leaders

Written by Peter

As a leader, your only job is to eat information and pump out decisions. You don’t run the warehouse, you don’t answer the phone, and you don’t have to make the tea. But you will be measured, bonused, or moved along based on the quality of your decisions, as umpired by the P&L and the share price.

There are plenty of texts for business leaders. Taleb says: discard anything written by someone without skin in the game. Horowitz says, don’t take business advice from someone who hasn’t even run a fruit stand. Take advice from Sun Tzu, or Musk, or glance upward reverently at your Theo Paphitis motivational wall calendar. Whatever works for you. But you don’t instinctively take advice from some pimply nerd who pronounces that data is the new oil and he has a graph that proves you’ve been doing it wrong all this time.

Your job as the leader is to eat information and pump out decisions. So the stats bod, or the data scientist, is just one of the sources of information a modern leader must go to. And this is a fairly new development. You’re used to beating-up your suppliers to get closer to the truth of what they’re doing. You’re well practiced at foxing the FD and finding holes in next year’s budget. You have made a fine art out of flipping the script on the marketing director and sending their narrative back to the drafts folder. All in a day’s work.

But how do you poke holes in Bayes’ theorem when it tells you not to open a shop in Sudbury? How do you challenge-back the mathmo who tells you to divert the next quarter’s marketing budget into Pinterest? It’s hard to know what to say. In this case, ignoring the immediate problem will make it go away. But the nagging feeling you get at 11pm when you’re setting tomorrow’s agenda, that you’re missing a trick and the other guy is making money with this stuff, will stay.

So, if after much soul searching while sat on the back of an elephant on your tropical paradise retreat, you’ve decided to embrace the stats and enrich your decision making through this new-ish lens, then here’s where to start.

As CEO I lead with the ‘everybody gets input, and I make the final decision’ approach. It’s easier than getting tied up in committee for two years while everyone decides what radio station should play in the office (short answer: none).

So as part of your new approach to decision making, one of the people around the table at the ‘input’ stage needs to be a statistican or data analyst. Someone who’s not afraid to tell you ‘I don’t know, because there’s not enough data to decide right now’. And someone who is confident enough to tell you that the experiment they ran for you last month really didn’t work out. But that someone may also bring you a golden nugget of information a year from now that allows you to gobble up a competitor or quickly dominate in your marketing channel of choice. But they need a voice now, not later, or that nugget will never arrive.

Now, statistics can’t help if your current decision-making model is immature. Adding another perspective in that situation is like adding another raw egg to your fish finger and nutella sandwich. Eventually your gut feel will land you in A&E and a more competent replacement will be found.

Stats also can’t help if you don’t have a culture that supports open and frank input into key decisions. If everyone has been conditioned not to volunteer inconvenient information for fear of losing their job, then your statistician is likely in the same position and will draw you a beautiful visualisation in Tableau that supports your brother-in-law’s daft idea about how to spend last year’s retained income.

Those are bigger problems for another day.

But for now, please enjoy my recommended reading list for 2020. It will give you a head start on how to ask the right questions of your number crunchers, so you don’t have to feel brainwashed or bamboozled. I wish you every success in your next 365 decisions.

Peter

3 Good Data Reads for 2020

Algorithms to live by: The Computer Science of Human Decisions

Hiring and firing. Spending and saving. Advancing here, retreating there. Major life decisions like a marriage proposal and long-term issues like how to help a friend who is self-destructing.

Both of these examples are covered sensitively, in a book that cleverly exposes how computer science concepts work, while giving you some real help making your next set of life and business decisions.

The Art of Statistics: Learning from data

A bird’s eye view of just the important bits of Statistics.

“Statistics can be abused to promote an opinion or just attract attention” says the author. He’s out to empower people to question the numbers with confidence. There are no formulas in this book. Lucid and readable while not being clickbait and trite.

We all need someone who’s a great explainer, and the author is in a high-stakes game of saving the public from balderdash: he’s British Statistician Sir David John Spiegelhalter, Chair of the Centre for Risk and Evidence Communication at the University of Cambridge.

Information is Beautiful

Let the pictures do the talking.

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