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Hierarchically Structured thinking and Communication for Data Scientists using Minto Pyramid Princip

One of the challenges that data scientists as well as consultants face is finding the most efficient way to communicate the results of your meticulous analysis to your heterogeneous audience. The audience whom are usually under a lot of pressure to drive results and are particularly pressed with time.

McKinsey hired Barbara Minto specifically to solve their communication problems and her work has been highly adapted by consultants globally. I found this method to be useful, particularly for data scientists who are coming from years of academic lifestyle and the ones who are working for non-tech companies.

Conclusion first:

Imagine if people have to leave the meeting early what do you want them to know, that should go first.


The current situation (relevant stats, plots, descriptive analysis) is presented first. If there is not an agreement about the current situation with the stakeholders, you can't get enough buy in for your results and proposed strategies.

Next, is to mention the complications and ask the relevant questions that your analysis and model will answer. Finally, answer the question!

Structured thinking:

A data scientists doesn't have a magic orb, what they usually have is clarity while facing tremendous amount of uncertainty. One way to get that clarity is by following the SCQA framework and next grouping issues based on the most relevant criteria (chronological, departments,...).

As a data scientist you have to think about all the possible components of a problem and then methodically try to zoom in onto a solution.

But this is just the beginning. You then have a responsibility as a scientist to show your integrity by trying to break your solution (cross-validation). As Feynman says:

"I would like to add something that's not essential to the science, but something I kind of believe, which is that you should not fool the laymen when you're talking as a scientist. . . . I'm talking about a specific, extra type of integrity that is not lying, but bending over backwards to show how you're maybe wrong, [an integrity] that you ought to have when acting as a scientist. And this is our responsibility as scientists, certainly to other scientists, and I think to laymen."

So what!

After creating your deck of slides,it's time to look back at each of them and ask yourself so what? Does this help the stakeholders in any way? If the answer is negative that slide has no business in being there.