When+Connecting+Intelligences+Fails

As this is an exploration of "connected intelligence", what we can learn from high profile failures?
1. Hurricane Katrina

2. Pre 9/11 U.S. Intelligence Operations

3. Long Term Capital Management
In "Network theory's new math" 2003 Michael Schrage writes:

//"Executives interested in the possible impact of network mathematics on their businesses and industries have a superb analogy from financial innovation, the Nobel Prize-winning Black-Merton-Scholes option-pricing equations. The mathematics was as much a machine tool for creating options as a diagnostic tool for analyzing them."

Surprizingly what Schrage doesn't mention is these same Nobel prize winners were involved with Long Term Capital Management, the hedge fund that applied their equations and was bailed out by a group of banks contributing a//bout $300 million each to raise a $3.65 billion loan fund in the fall of 1998 after market conditions changed and the Federal Reserve feared disruption to the financial markets. at risk. ([|Thayer Watkins,] [|Dowd 1999].

Authors list a range of reasons for the failure including an outside event, Russia revaluing the ruble, and internal, top traders In addition to the losses caused by the turmoil in the financial markets there was also the problem that top traders "with almost pathological overconfidence began to take unhedged positions in the market, effectively betting hugh sums on the direction changes in financial variables would take" (Watkins) and lack of real diversification to reduce risk.

In thinking about "learning through connected intelligence" we are conscious of appropriate applications.