Tag Archives: Tim Ferriss

The Problem with Big Data: Lies, Damn Lies, and Statistics

I’ve used the subtitle in a previous post and I think the application to the content of this post also makes it worthwhile to use again. I was reading a post from Tim Ferriss the other day and it made me think of statistics. The post is about alternative medicine, but understanding that isn’t entirely necessary for the point I’m making. Here’s some context:

Imagine you catch a cold or get the flu. It’s going to get worse and worse, then better and better until you are back to normal. The severity of symptoms, as is true with many injuries, will probably look something like a bell curve.

The bottom flat line, representing normalcy, is the mean. When are you most likely to try the quackiest shit you can get your hands on? That miracle duck extract Aunt Susie swears by? The crystals your roommate uses to open his heart chakra? Naturally, when your symptoms are the worst and nothing seems to help. This is the very top of the bell curve, at the peak of the roller coaster before you head back down. Naturally heading back down is regression toward the mean.

If you are a fallible human, as we all are, you might misattribute getting better to the duck extract, but it was just coincidental timing.

The body had healed itself, as could be predicted from the bell curve–like timeline of symptoms. Mistaking correlation for causation is very common, even among smart people.

And the important part of the quote [Emphasis Added]:

In the world of “big data,” this mistake will become even more common, particularly if researchers seek to “let the data speak for themselves” rather than test hypotheses.

Spurious connections galore–that’s what the data will say, among other things.  Caveat emptor.

This analogy reminded me of the first time I learned about correlation and causation in my first psychology class as an undergraduate. It had to do with ice cream, hot summer days, and swimming pools. In fact, here’s a quick summary from wiki:

An example of a spurious relationship can be illuminated by examining a city’s ice cream sales. These sales are highest when the rate of drownings in city swimming pools is highest. To allege that ice cream sales cause drowning, or vice-versa, would be to imply a spurious relationship between the two. In reality, a heat wave may have caused both. The heat wave is an example of a hidden or unseen variable, also known as a confounding variable.

Getting back to what Ferriss was saying near the end of his quote: as “Big Data” grows in popularity (and use), there may be an increased likelihood of making errors in the form of spurious relationships. One way to mitigate this error is education. That is, if the people who are handling Big Data know and understand things like correlation vs. causation and spurious relationships, these errors may be less likely to occur.

I suppose it’s also possible that some, knowing about these kinds of errors and how little the average person might know when it comes to statistics, could maliciously report statistics based on numbers. I’d like to think that people aren’t doing this and it just has more to do with confirmation bias.

Regardless, one way to guard against this inaccurate reporting would be to use hypotheses. That is, before you look at the data, make a prediction about what you’ll find in the data. It’s certainly not going to solve all the issues, but it’ll go a long way towards doing so.

Macro Goals and Micro Quotas: How to Beat Procrastination

A few months ago, I saw a YouTube video from Tim Ferriss answering a question on a Reddit AMA (Ask Me Anything). If you’re unfamiliar with AMA’s, they’ve become a rather common way for famous (and sometimes anonymous because of where they work or what they do for a living) people to answer questions from fans. Even Barack Obama did one.

Anyway, Ferriss did one of these a while back and for at least one of the questions, he did a video response. The question boiled down to procrastination. People look at Tim Ferriss and think that he mustn’t have to fight procrastination given that he’s just turned 36, but he’s published 3 best-sellers, is a polyglot, has travelled the world, and is an angel investor or advisor to Facebook, Twitter, Evernote, Uber, etc. Apparently, these people would be wrong. Tim Ferriss has to battle with procrastination just the same as you or I. In the video below, he offers some really important tips for dealing with procrastination.

A couple things I want to highlight: he’s just like you or I, as I’m sure many people you’d think were “other-worldly.” As the saying goes, he puts his pants on one leg at a time.

The second is the idea of macro goals and micro quotas. He absolutely hits the nail on the head that many people are paralyzed with anxiety in the face of an extraordinary goal (write a bestseller, climb Mount Everest, play professional sports, etc.). The key to hitting these macro goals is to set micro quotas. Ferriss shares the anecdote from a friend of his who has ghost written 60 (!) books:

“Two crappy pages. That is my quota. Everyday, I have to write two crappy pages. That’s it. If I write two crappy work pages, that day is a win.”

You can make your dreams come true. You’ve just got to know the mechanism, first.

You Waste a lot of Time at Work

… or at least so says this infographic from Atlassian. I wanted to embed the infographic here, but the infographic is not presented in a way that makes it easy to share (other than giving you the URL, which I’ve already done). So, I’ll just go over some of the key statistics from the inforgraphic. Though, I highly recommend checking out the infographic because the information presented in that fashion might make it more memorable.

They name three main culprits of wasting time at work: email, pointless meetings, and constant interruptions. I think these are probably all things that most people would agree on. Let’s look at some of the costs associated with these “culprits.”

Email

Annual Productivity Costs per Employee:

Spam: $1250

Unnecessary emails: $1800

Poorly written communications: $2100 to $4100

Meetings

U.S. Business lose $37 billion in salary because of the cost of unnecessary meetings

Interruptions

Interruptions a day for the average employee: 56

Minutes spent working before the average employee switches tasks: 3

Hours spent recovering from distractions per day: 2

~~

If all of this is true, it kind of makes it hard to ignore the costs associated with these three major time-wasters. Of course, Atlassian’s motive isn’t entirely pure. At the bottom of the infographic, they’d like you to sign-up to learn how their business solution (Confluence)* can help your team work more efficiently.

The information provided in the infographic is certainly compelling, isn’t it? The point about email seems particularly poignant, especially the note about poorly written communication. It seems that a team leader would want to host a workshop or hire some help to ensure that the team is communicating at its optimal capacity.

Seeing this infographic also makes me want to revisit Tim Ferriss’ 4-Hour Work Week. There are lots of important productivity tools in there for making your team more efficient. More than that, be sure to check out Ferriss’ blog, where he continues to talk about ways to improve efficiency (in many different aspects of life: he’s just finishing up a book on cooking and he’s also published a book on dieting/working out).

*Note: Please don’t consider this an endorsement of Atlassian or Confluence. I hadn’t heard of the company (or the product) until I came across this infographic and I have no experience using Confluence.