Analytics and disaster recovery

While 2012 has been a very active hurricane season in terms of total storms, the effects on life and property have been relatively small and the need for disaster recovery less than many years. Let's all be thankful for that. Right now, Tropical Storm Sandy is threatening Jamaica and the Caribbean but is forecast to head out to the Atlantic like many of its relatively harmless brothers and sisters this year. [10/25 UPDATE: Looks like I spoke to soon regarding Sandy. If forecasts keep trending the way they are, there could be a substantial disaster recovery effort in the mid-Atlantic and/or Northeast. Let's hope she stays out to sea.] One of the few exceptions was Hurricane Isaac, which blew through the gulf region in late August, devastating parts of the coast.  Many areas experienced more flooding than during Hurricane Katrina, almost exactly seven years earlier.

Disasters have strange impacts sometimes.  For instance, thousands of dead nutria (think giant rats) washing up on the gulf shores after the flooding.  Levees built to protect from flooding having to be destroyed to relieve areas from flooding.  And of course, Jim Cantore of the Weather Channel standing in a hurricane never ceases to amaze.  But, what most of us don’t think about is that long after the wind stops, and soon after the flooding has dissipated, the disaster is just beginning for the government entities that have to start over the process of rebuilding infrastructure, people rebuilding lives, and communities restoring a sense of normalcy.  Post event, whether hurricane, earthquake, fire, etc., the disaster recovery process begins to return life to (hopefully) at least what it was before, or, maybe just a little better than before.

How does this occur and how long does it take?  Well, we all know about FEMA as an emergency response entity.  Really, they are a long term recovery team as well, designed to help state and local governments and their citizens recreate their lives after a disaster.  Money is assigned to projects and the rebuilding begins. Disaster  recovery is a process that takes years.  Not weeks, not days: Years.

Think about it.  Schools destroyed, bridges washed away, houses completely flooded or lifted off of their foundations and washed downstream.  Rebuilding them in a better and more sustainable manner takes time, money, and effort.  There are rules and laws that govern the disaster recovery process.  Data is collected on all of these projects, potentially thousands of them.  What does it all cost?  Who provides the information on costs for projects that will take years to complete?  Is the current system accurately accounting for changes in labor and material costs over time?  And, are all of the insurance regulations, environmental requirements, and government rules and regulations accounted for in the estimates for these projects?

The answer is yes, and yet, those estimates are historically inaccurate across the disaster.  This occurs due to unseen damage that is discovered as the project unfolds.  It occurs due to length of approval time and construction time.  Changes occur due to inflation and other economic factors. The question becomes, how do we accurately predict overall disaster recovery project costs and account for time value, new damage, rising labor and material costs?  Is it even relevant or important?

Katrina had approximately 17,000 projects in infrastructure recovery.  There are still a number of them that are not completed.  Many of them are incomplete due to all the factors talked about above.  Analytics can play a critical role in every major event or presidential disaster declaration.  Imagine a solution that allowed the local, state and federal government to be as accurate as possible at the beginning of an event in predicting total costs from the event throughout the entire recovery and mitigation process.  Taking into account all the factors, insurance, environmental regulations, business rules, time, labor, etc., a series of models can be established that will accurately forecast the costs of each project.  This will allow for FEMA to accurately forecast their needed budget at the beginning of the disaster, allow for states to predict there budgetary needs based on cost share and allow for locals to more quickly be able to rebuild the infrastructure that supports their community more quickly and efficiently.  As we have more and more events focused in a particular area, such as the Gulf, we can begin to look at patterns that will help model those exact costs right from the beginning.  Ultimately, setting accurate budgets during initial phases of a disaster will help every level of government be able to tell their citizens when they can get back to normal, and how much it is going to cost.

 

tags: analytics, disaster recovery, hurricane isaac, infrastructure, natural disaster, SAS

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  1. [...] > State and Local Connection > Baseball, disaster planning and unintended consequences « Analytics and disaster recovery Baseball, disaster planning and unintended consequences Chuck Ellstrom|October 25, 2012 [...]

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