If you’re like me, you enjoy hearing about novel ways companies are using big data and analytics to drive business decisions.
I’ve read about entertainment companies using the tool to script on-demand TV programming that matches the interests of the “Twitterverse.”
I’ve seen case studies of HR using big data to drive hiring decisions and make sure the right jobs are being filled with the right people.
And one of my fellow bloggers reported earlier this year on a fascinating use of analytics to choose the ingredients for a craft beer. Really!
It seems nearly every business in every industry is finding ways to use the incredible amount of data generated by customers, partners, suppliers, employees and the general public every day.
And the fuel card industry is no different.
Fuel card providers now have a wealth of data at their fingertips – and that amount will only grow as Internet of Things (IoT) and connected cars become more pervasive.
Customer info – contact information, demographics, purchase patterns, frequency of visits, communication preferences – can be derived from every driver with every transaction. Social media analytics can add an authentic, birds’-eye view of customer sentiment. Wi-Fi and beacon-enabled location data mix in rich, on-the-ground info about users, vehicles, points of purchase and more.
Add in the connected car, which drives data about vehicle wear and tear, route optimization and fuel efficiency, as well as IoT, which automates the collection of sensor- and entry-based data, and fuel card providers might just find themselves neck-deep in a vast data lake.
Which can be a good thing – as long as your company’s ready to swim.
The challenge, in this environment, is not just to collect data, but to collect the right kind of data, to ensure its quality and then harness it in a way that allows the building of predictive models that can lead to business insights.
At CSC, we recommend companies consider these questions when doing data dives:
- Is it domain specific? Only data related to the problem is of interest. Tables, members and files need to be easily identifiable and relatable to the whole system.
- Does the data have a time range? A sufficient amount of historical data needs to be available. It’s best if data can be compared across different time intervals.
- Is it well documented? This applies to individual entities.
- Is the event frequency of sufficient size? Predictive models depend on a large number of observations.
With these items in place (and partners, including CSC, are available to help or provide as a service), fuel card providers can reap the benefits: improved customer service, optimized operations, innovative product development, fraud detection and prevention, regulatory compliance and so much more.
Maybe even a pint of Big Data Brew on the house. 😉
How is your company using big data to drive business decisions?
In this series of posts, I’m discussing transformations in the fuel card industry, drawing from my years of experience working with the industry and watching it change and shift. I’ll discuss the fundamental drivers and hopefully put to rest any fears that challenges are insurmountable. Far from it, they’re driving innovations that will open companies to a bright future. Join me in the discussion here or connect with me on LinkedIn. I look forward to engaging with you.
Neil Brownlie has been at CSC since 2005 when he joined the company to head up sales for Cards and Payments in Asia, Middle East and Africa. He worked to introduce mobile payment solutions across the region, then in 2012, moved to Austria to lead the Fuel Card group and International sales. In 2014, he was appointed General Manager for Bulgaria. Outside of the office, he enjoys an active outdoor lifestyle, attending concerts and indulging in the good life – and wine – of Austria.