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.

Efficiency innovations provide return on investment in 12-18 months. Empowering innovations take 5-10 years to yield a return. We have ample capital - oceans of capital - that is being reinvested into efficiency innovation.

It is when the product is not good enough that proprietary integration gives you a competitive edge. You cannot outsource and be competitively successful in this situation. But at the other end, where standard components assembled in standard ways can yield acceptable performance, you must outsource.

The whole enterprise of teaching managers is steeped in the ethic of data-driven analytical support. The problem is, the data is only available about the past. So the way weve taught managers to make decisions and consultants to analyze problems condemns them to taking action when its too late.

The transformation at the corporate level was achieved by selling off business units in old markets and by creating new business units to pursue the new opportunities. But the individual business units themselves within those transformed corporations were almost inert to change.

One of the factors that make great companies so great is that they have processes that allow them to solve difficult problems again and again. These processes have developed over time as teams have successfully wrestled with a certain type of challenge. Eventually, people begin to say, "This is just how we do something around here." The problem develops when that team then has to solve a very different set of challenges. The processes that are such strengths can be crushing liabilities.

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.