Data rich, information poor: Fuel Card Analytics

To shift from ‘information poor’ to ‘information rich’, organisations cannot just scrape through reports of data ‘row by row’ to find the needle in the haystack. Instead, organisations are more commonly employing the use of modern tools, techniques and people who can immediately highlight the data insights needed to lower costs or spot fraudulent activity.

Fuel card analytics
A basic example of how organisations can convert their data into information is fuel card analytics. Fuel card data is arguably one of the most simple and boring datasets, but by applying some analytical techniques we can extract some very interesting insights. 

A client approached us recently to run analytics over their fuel cards due to their concerns around employee spending.

This graph sits on tens of thousands of rows of data and shows the fuel purchased for each person and car. The blue bar represents petrol purchased while the green represents diesel purchased. Visually, we are able to quite easily see if any employee is trying to use their fuel card to purchase more than one type of fuel for their vehicle.

On the back of our analysis, the business pulled surveillance footage from petrol stations and found that an employee had been lining up his friends and giving them “free” petrol on his company fuel card.

The odds of this fraudulent activity being picked up through reports and spreadsheets is very low due to the volume of data present in fuel cards, but by leveraging some basic analytics we were able to highlight these insights and help this business get some actual information out of their data.

If you would like to discuss how we can assist you to transform data to information or fuel cards, please do not hesitate to contact Jason Weir or Lisa Tai.