Guillaume Lerouge’s blog

What failed wasn’t the vision but the timing and the absence of a refinement process. Technologies which succeed commercially are not “moonshots.” They come from a grinding, laborious process of iteration and discovery long after the technology is invented.

The technology is one part of the problem to be solved, the other is how to get people to use it. And that problem is rooted in understanding the jobs people have to get done and how the technology can be used defensibly. That’s where the rub is. An unused technology is a tragic failure.

Companies that set up so-called "skunk works" operations tend to forget that the original Skunk Works had customers and worked closely with those customers. When it operated as a mere technology incubator it tended to produce duds. Its major successes were produced for the CIA and the Air Force.

Apple is really the moonshot idea turned on its head. It has the "skunk works" at the top and treats traditional operations as part of the product being created. [...] Product development should be "C-level", including prototyping, and the process of turning out millions of those products, marketing them and selling them, etc, should be assumed. It should also be headless and hence killable once the market for the product dries up, regardless of how long that takes.

At McKinsey, we were taught three approaches to making decisions under uncertainty:

1. Day One Hypothesis
   
2. Directionally Right, Same Order of Magnitude
   
3. What Do You Have to Believe?
   

These three tools have been immensely helpful to me in my own career, especially when I’m asked to make a decision about a future business opportunity where there are some key unknowns.

If you think about what you are trying to accomplish in a meeting with someone you are managing and you plot the following:

Dick's point is you want to optimize for the x axis, clear and crisp communication, and not worry too much about the y axis.

The important dynamic here is that a combination of very cheap off-the-shelf chips and free off-the-shelf software means that Android/ARM has become a new de facto platform for any piece of smart connected electronics. It might have a screen and it might connect to the internet, but it’s really a little computer doing something useful and specialised, and it probably has nothing to do with Google.

Now, stop thinking about it as a phone. How do the economics of product design and consumer electronics change when you can deliver a real computer running a real Unix operating system with an internet connection and a colour touch screen for $35? How about when that price falls further? Today, anyone who can make a pocket calculator can make something like this, and for not far off the same cost. The cost of putting a real computer with an internet connection into a product is collapsing. What does that set of economics enable? 

One of the great descriptions of what real testing looks like comes from Valve software, in a piece detailing the making of its game Half-Life. After designing a game that was only sort of good, the team at Valve revamped its process, including constant testing:

This [testing] was also a sure way to settle any design arguments. It became obvious that any personal opinion you had given really didn’t mean anything, at least not until the next test. Just because you were sure something was going to be fun didn’t make it so; the testers could still show up and demonstrate just how wrong you really were.

“Any personal opinion you had given really didn’t mean anything.” So it is in the government; an insistence that something must work is worthless if it actually doesn’t.

An effective test is an exercise in humility; it’s only useful in a culture where desirability is not confused with likelihood. For a test to change things, everyone has to understand that their opinion, and their boss’s opinion, matters less than what actually works and what doesn’t. (An organization that isn’t learning from its users decided it doesn’t want to learn from its users.)