As systems become more complex and interconnected, rare events can trigger costly outcomes that could have been prevented if attention were paid to the way those outcomes occur.  Instead, most analytic modeling is based on classic reliability theory, which is used to estimate reliability indices.  These indices measure system averages.  These averages never capture the extreme events.  But it is the extreme event that accounts for the catastrophic cost that one ought to be trying to prevent.

The basis of our approach is to identify those events that are both rare and consequential.

We replace the typical reliability model with VMN’s state-of-the-art system models.  We focus on the rare, but catastrophic events that are of most concern to the public.  (For electrical power systems, such events result in large-scale geographic blackouts.)  Our models are based on the recognition that the current approaches do not represent the true range of uncertainty of outcomes (which is a straightforward statistical consequence of measuring averages) and they do not optimize strategy.  We place the analysis of rare events into an optimal strategy analysis.

We recognize that catastrophicevents result from two fundamental causes:

1. added stress on subsystem components associated with failure of a subset of components in the same subsystem

2. linkages among subsystems that permit failure consequences to cascade—complex systems can fail in unanticipated ways. 

It follows that data is insufficient to characterize catastrophic event rates.  Therefore, our approach is based on scenario planning, using our proprietary tools to support such planning.  A fundamental claim we make is that policy failure in this area is a failure of the imagination

The outcome of the methodology is a strategy designed to prevent or reduce the likelihood of the rare events that result in catastrophes.

The methodology has been applied, only theoretically, to the electric power industry.  We are actively seeking candidates for this new approach, both within and without the electric power industry.