...it's easier to hold to your principles 100% of the time than it is to hold to them 98% of the time.

If the theory accurately predicts what they [scientists] see, it confirms that it's a good theory. If they see something that the theory didn't lead them to believe, that's what Thomas Kuhn calls an anomaly. The anomaly requires a revised theory - and you just keep going through the cycle, making a better theory.

Capitalism has taught us that markets are always more efficient than hierarchical managerial coordination. But in a situation where those three conditions aren't met, I can't outsource or partner with you because markets don't function in the absence of sufficient information.

Disruption is, at its core, a really powerful idea, but everyone hijacks the idea to do whatever they want now.

Management is the most noble of professions if it's practiced well.

Disruptive technology is a theory. It says this will happen and this is why; it's a statement of cause and effect. In our teaching we have so exalted the virtues of data-driven decision making that in many ways we condemn managers only to be able to take action after the data is clear and the game is over. In many ways a good theory is more accurate than data. It allows you to see into the future more clearly.

I was lucky enough to build on the work of a number of people who had already run laps around this theory-building track. The original classification scheme, years ago, distinguished radical from incremental change. The theory said that established firms managed incremental change well, but would be expected to founder when their industry encountered a radical change.