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Using Math and Big Data to Save Lives – Maybe
December 11, 2015 Blog big data

This article was originally published by and can be viewed in full here

The Air Force’s Air Mobility Command has been able to save money on fuel costs by crunching numbers and using big data to be more efficient, but the command may have saved more than funds.

Assistant Director of Analysis for Air Force Air Mobility Command Don Anderson said a matrix used by the military to track fuel costs may also be saving lives.

Air Mobility Command (AMC) noticed that C-17 airplanes departing from Oman and Kuwait were very inefficient when flying into Afghanistan compared to other parts of the world.

Here is where big data really comes into play.

The average flight time for a C-17 from Kuwait to Kabul is almost four hours, burning 9,968 gallons of fuel. To get back to Kuwait the plane will need to refuel with another 10,000 gallons of fuel.

Each truck convoy from Pakistan to Kabul holds 6,000 gallons of fuel. Each C-17 that tankers fuel into Afghanistan removes 1.6 fuel trucks from our convoys.

AMC created a matrix for plane commanders’ origins and destinations to find out if it’s better or worse to carry fuel.

Since  the program started,  5,858 C-17s and C-5 have tankered fuel into Afghanistan. There are now 597 less convoys on the road than before this program started. The Army casualty factor per convoy is .042 deaths per convoy and when you multiply that out, 597 convoys off the road equates to approximately 25 lives that were saved because of this program.

Of course there is no hard evidence that 25 lives were saved, but the use of big data is making convoys less dangerous and planes more efficient.