Oceans of Data

Recently, I found my way to a businessinsider.com piece relating to ‘mechanistic” theory of the world, and the article states in part that ‘we are afloat on a hidden ocean of equations.”   

It brought to mind the visualizations from the movie The Matrix, with ones and zeroes behind the scenes ostensibly making the Matrix work, but the scientist in question puts forth the notion that essentially everything in the world can be attributed to ‘ or explained by – seven mathematical equations.

Whether you subscribe to a broad mechanistic view of the world where, for the purpose of this article, you believe that math can pretty much explain everything, lean entirely the other way, or come down somewhere in the middle,  it’s clear that we fuel industry types are swimming in data”Oceans of data.”

A long time ago in a marketing area far away, a company sought an incentive program for their heating oil delivery staff.   The desire was to quantify a baseline level of delivery staff efficiency that could be measured, and with which delivery staff could be paid for superior performance. 

In an attempt to isolate the parameters they could measure directly, including miles driven, hours worked, time spent actually pumping fuel to customers, time spent loading trucks, the company postulated that what remained was essentially the time spent doing everything else.  

The theory was that the delivery staff had control over certain aspects of the delivery process, and that drivers were in a position to hasten the delivery of fuel.  In simple terms, the company was measuring how well their delivery people were moving when they were not loading, not pumping, and not driving.

The company went about it a different way, but it all boiled down to measuring what could be measured directly to get to what could not be measured directly.  For the delivery of fuel, it involved measuring productive time, non-productive time, miles driven, average drops, stops made, gallons pumped, payroll and benefit dollars, and so on.

Depending on what software you happen to be using for your fuel delivery and dispatching, you may already track miles driven, hours worked, hours actually delivering fuel, number of stops, and gallons delivered.

Provided that you are already collecting the information noted above, you have the basics necessary to arrive at a number of very useful calculations, including but not limited to stops per hour, average drop, miles per stop, productive vs. non-productive time, and  so on.

It’s remarkable how versatile and revealing analysis of this information can be, particularly when collected over time and used in a historical context.  If your data collection is consistent and you are diligent as to the accuracy of the collected data, you can arrive at baselines for delivery efficiency, create a model for your month-to-month delivery staffing needs, improve your budgeting aptitude, and get a quantitative handle on how many physical trucks you really need to get the job done.

Though it takes time and effort to collect, process and analyze data from your operation, it is a prudent investment that will provide you with new insight on your operation, how all those ones and zeros fit together, and last but not least, allow you to make informed decisions.



Shane Sweet is in management with a major Northeast marketer of heating oil, propane and motor fuels.  From 1993 to 2007 he served as Executive VP and Lobbyist for the Vermont Fuel Dealers Association and from 2007 thru 2010 was President & CEO of the New England Fuel Institute.  He lives in Shaftsbury, Vermont and can be reached at shanemsweet@gmail.com or 802-558-6101 cell.   Suggestions by readers for future column content are welcome.


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