As my day job is in strategic marketing, I often have to deal with numeric data, such as market size, market shares, revenue forecasts, etc. That’s maybe the reason I stopped believing in naked figures. Particularly when presented in isolation, without any information about their source, logic or meaning.
Take this example. A few months ago I was preparing a presentation about disruptive market trends in telecom. While crafting a slide about the massive potential of the Internet of Things, I got confronted with growth forecasts ranging from “26 billion units by 2020” to “212 billion things in 2020.” Yes, that’s a difference of a factor of almost ten. One would expect a bit more alignment between respected industry analysts like Gartner and IDC. It was even impossible to tell which estimate was the most accurate one, because it wasn’t also very clear what “units” or “things” they actually counted…
Here’s my point: numbers are meaningless without context or without a good explanation. There’s a quote attributed to Winston Churchill, saying that:
“The only statistics you can trust are those you falsified yourself.”
Although sources claim that Sir Winston never made such statement at all – which means that you should be as cautious when citing quotes as when showing numbers – there’s certainly some truth in it:
- Most presenters use figures either to prove their point or to persuade their audience (of a point they aren’t able to prove.) Both may of course be honorable causes, but still, as a member of the audience this often gives me an uncomfortable feeling of being manipulated.
- Even when facts and figures are not intentionally misleading, they still may be massaged to invoke more (or less) emotion (see e.g. Garr Reynolds’ example about the usage or tables and charts in my previous post.) And of course, the same numbers can mean different things to different people.
- You can prove anything you want with numbers, statistics and correlations. From a 2011 BusinessWeek article I learned that Facebook ignited the Greek debt crisis, and that Global Warming is caused by scientific research… If you (or the people listening to you) have no idea of what’s behind a correlation, you may claim any fact you like.
Another more recent case of such correlation equals causation thinking – also known as the cum hoc ergo propter hoc fallacy – is a Princeton study saying that Facebook would lose 80% of its users by 2017. The numbers generated a row between the Princeton University researchers and the Menlo Park social networking giant, as the latter on its turn “proved” that the renowned university would lose all of its students by 2021.
As a conclusion, if you want to include numbers, statistics and correlations in your presentation, use them scarcely, carefully and wisely. Always mention their source(s), present them with the necessary reservation, and in the right context.
For what it’s worth: last week, Google announced a new tool that should help data analysts distinguish cause from correlation, when e.g.measuring sales generated by a web banner, or estimating the impact of a new feature on app downloads.
- Make Numbers Work for You (by the Executive Communications Group)
- The only statistics you can trust are those you falsified yourself (by Ingmar Weber)
- “Trau keiner Statistik…” (by Joe Wein)
- 10 famous quotes commonly misattributed (by Shannon George)
- Correlation or Causation? (by Vali Chandrasekaran)
- Facebook Hilariously Debunks Princeton Study Saying It Will Lose 80% Of Users (by Josh Constine)
- Liking curly fries might not mean you’re smart: When mere data isn’t enough (by Derrick Harris)
- Google has open sourced a tool for inferring cause from correlations (by Derrick Harris)
- The duck and the rabbit (by me)
- Living by numbers (by me)
- Principles of persuasion (by me)