The Importance of Failure

This segment from CBS Sunday Morning isn’t particularly groundbreaking or profound (and perhaps a bit hokey), but is a helpful reminder on the importance of failure. (Nevermind the failure to post anything new for two weeks.)

Duke University professor Henry Petroski has made a career studying design failures, which he says are far more interesting than successes.

“Successes teach us very little,” Petroski said.

Petroski’s talking about bridges, but it holds true for any creative endeavor.

Also cited are J.K. Rowling bottoming out before her later success, van Gogh who sold just one painting before his death, Michael Jordan not making his high school basketball team, and others. (You’ve heard of these, but like I said, it’s about the reminder.)

It also notes that the important part is also how you handle failure, citing Chipper Jones, who leads baseball with a .369 batting average, which is impressive but also means that he’s only getting a hit one in three times he has a chance:

“Well, most of the time it’s not [going your way] and that’s why you have to be able to accept failure,” Jones said. “[…] a lot of work […] here in the big league is how you accept failure.”

Which is another important reminder: the standout difference in “making it” has to do with bouncing back from failure.

And if nothing else, watch it for footage of the collapse of the Tacoma Narrows Bridge in 1940. Such a beautiful (if terrifying) picture of cement and metal oscillating in the wind. Also linked from the Wikipedia article are a collection of still photographs (including the collapse) and links to newsreel footage from the Internet Archive.

Friday, August 15, 2008 | failure  

Visualizing Data Book CoverVisualizing Data is my book about computational information design. It covers the path from raw data to how we understand it, detailing how to begin with a set of numbers and produce images or software that lets you view and interact with information. Unlike nearly all books in this field, it is a hands-on guide intended for people who want to learn how to actually build a data visualization.

The text was published by O’Reilly in December 2007 and can be found at Amazon and elsewhere. Amazon also has an edition for the Kindle, for people who aren’t into the dead tree thing. (Proceeds from Amazon links found on this page are used to pay my web hosting bill.)

Examples for the book can be found here.

The book covers ideas found in my Ph.D. dissertation, which is basis for Chapter 1. The next chapter is an extremely brief introduction to Processing, which is used for the examples. Next is (chapter 3) is a simple mapping project to place data points on a map of the United States. Of course, the idea is not that lots of people want to visualize data for each of 50 states. Instead, it’s a jumping off point for learning how to lay out data spatially.

The chapters that follow cover six more projects, such as salary vs. performance (Chapter 5), zipdecode (Chapter 6), followed by more advanced topics dealing with trees, treemaps, hierarchies, and recursion (Chapter 7), plus graphs and networks (Chapter 8).

This site is used for follow-up code and writing about related topics.