1 to 40 Trillion, those are large numbers!

Somewhere over a trillion gallons of water fell from Hurricane Irene.  I even heard numbers quoted as large as 40 trillion. So, how are we doing in the aftermath of Irene, and how did we do leading up to the storm?  Let’s start with SCM (supply chain management), since it was non-existent.  I went looking for D-cell batteries one night several days before the storm, none in stock. 

Two weeks before the storm hit, they knew it would hit somewhere on the east coast.  Battery companies at that point should have been sending stock to mid-eastern seaboard warehouses.  A week before the storm those batteries should have been shipped to retailers from NC to Maine. 

I would like to say we need a Big Data solution to solve this issue, but we really do not.  We need improved SCM and common sense.  It is very easy to figure out what people need before and after a storm, here is the short list:  Batteries (D-cell in particular), bottled water, first aid kits, generators and chain saws.   Secondary items: ice, MRE’s, sump pumps, wet vacs, inflatable rubber rafts, etc. 

I was speaking with Billy Bosworth the CEO of DataStax yesterday and we both agreed companies need to study the military to really understand provisioning/SCM.  Having lived through Hurricane Andrew back in 1992, where wind speed was recorded at 220 miles per hour at Turkey Point, I was able to see what the military can do and how fast.  Tent cities set up over night, roads cleared in a blink of an eye, looting stopped on a dime (army rangers with M-16s never had to say a word), food and water distributed to those in need.   

With the right IT solutions, common sense, and help from the National Guard/Army we should be able to do a much better job pre/post hurricanes in the future. 

Now, where does Big Data come in?  The storm itself, although we had good warning and it was tracked fairly well, there were two areas that fell short.  First, the areas they thought would get the most damage did not.  Many of the coastal areas had minimal damage, ditto with places like Manhattan (NYC). However many places in land got hammered,Vermont, rural NY, Connecticut, etc.  

The second area they missed was the wind tail of the storm.  The storm was supposedly gone from my area (CT) by late afternoon; however we had high winds on Sunday from 5pm to 11pm, even though the storm was “gone”.  These winds cause a lot of extra damage.  Big Data can help in predictive modeling, with more data points analyzed; maybe those two misses above would not have happened.  

In the mean time I am in the dark both at home and figuratively. Still no power at the house and still wondering why we can not handle these hurricanes in a more effective manner.   

“Everybody lives for something better to come.” – Anonymous