When organizations fail, our first reaction is typically to fall into "control mode": One person, or at most a small, coherent group of people, should decide what the current goals of the organization are, and everyone else should then efficiently and effectively execute those goals. Intuitively, control mode sounds like nothing so much as common sense. It fits perfectly with our deeply rooted notions of cause and effect ("I order, you deliver"), so it feels good philosophically. It also satisfies our desire to have someone made accountable for everything that happens, so it feels good morally as well.
But when a failure is one of imagination, creativity, or coordination—all major shortcomings of the various intelligence branches in recent years—introducing additional control, whether by tightening protocols or adding new layers of oversight, can serve only to make the problem worse.

To understand this, we need to (…) take a look at the world of industrial organization, which has had some valuable experience in recovering from major mistakes.

In 1997, the Toyota group suffered what seemed like a catastrophic failure in its production system when a key factory—the sole source of a particular kind of valve essential to the braking systems of all Toyota vehicles—burned to the ground overnight. Because of their much-vaunted just-in-time inventory system, the company maintained only three days of stock, while a new factory would take six months to build. In the meantime Toyota's production of over 15,000 cars a day would grind to an absolute halt. This was the kind of disaster with the potential to wreck not just the company itself, but the entire Japanese automotive industry. Clearly, then, Toyota, along with the more than 200 other companies that are members of the extended Toyota group, had ample incentives to find a solution.

The big question was : How? How does one rapidly regenerate large quantities of a complex component, in several different varieties, without any specialized tools, gauges, and manufacturing lines (almost all of which were lost), with barely any relevant experience (the company that made them was highly specialized), with very little direction from the original company (which was quickly overwhelmed), and without compromising any of their other production tasks? Well, actually it's not clear that one could do it at all, nor was it clear at the time to any of the senior managers of the Toyota group. After all, if this was the kind of disaster that their risk management executives had considered, they would never have left themselves vulnerable to it in the first place.

Nevertheless, they succeeded, but not in the way one might have expected. Rather than relying on the guidance and coordination of an inspired leader (control mode), the response was a bewildering display of truly decentralized problem solving : More than 200 companies reorganized themselves and each other to develop at least six entirely different production processes, each using different tools, different engineering approaches, and different organizational arrangements. Virtually every aspect of the recovery effort had to be designed and executed on the fly, with engineers and managers sharing their successes and failures alike across departmental boundaries, and even between firms that in normal times would be direct competitors.

Within three days, production of the critical valves was in full swing, and within a week, production levels had regained their pre-disaster levels. The kind of coordination this activity required had not been consciously designed, nor could it have been developed in the drastically short time frame required. The surprising fact was that it was already there, lying dormant in the network of informal relations that had been built up between the firms through years of cooperation and information sharing over routine problem-solving tasks. No one could have predicted precisely how this network would come in handy for this particular problem, but they didn't need to—by giving individual workers fast access to information and resources as they discovered their need for them, the network did its job anyway.

(...)

Creative intelligence analysis has a lot in common with other kinds of problem-solving activities: thinking outside the box, challenging deeply held assumptions, and combining different, often seemingly unrelated, kinds of expertise and knowledge.
By understanding how innovative and successful organizations have been able to solve large-scale, complex problems, without anyone "at the top" having to micromanage the process, the intelligence community could learn some valuable lessons that might help it escape the mistakes of the past.