Big Data and the C-suite: What it Means for Fleet Executives

by Frank Bussone and Tom Toton

Frank Bussone is vice president of technology and data analytics for Corcentric Fleet Solutions. He has spent more than 25 years providing business analytics and business intelligence to the transportation and real estate industries. For the past nine years, he has helped Corcentric customers find lower cost solutions for their truck fleets by working through the big data broadcasted from trucks. Bussone is a certified transportation professional and received a master’s degree in urban and regional planning from Florida Atlantic University. He has also received a data science with SQL and tableau certificate from Cornell University and a certificate of achievement in six sigma green belt from Villanova University.

Tom Toton, vice president of Sales, Capital Equipment Solutions, brings nearly 40 years of extensive experience in the transportation industry to his role at Corcentric. He works with companies to determine a flexible, data-driven solution that is based on their operational and financial needs in order to optimize every asset.

With an ocean of data available to help fleet executives make decisions, it is important that the right data reaches the C-suite. Frank Bussone and Tom Toton of AmeriQuest Transportation Services explain the importance of crystalizing data and the role executives can play in ensuring the correct data is gathered.

The problem with Big Data is that it’s too big. This is especially true as you get higher up in an organization. C-suite executives are expected to make decisions on hundreds — sometimes thousands — of issues and don’t have time to pore over spreadsheet after spreadsheet. It’s no different for fleet executives, whether they operate a for-hire fleet or a private one.

There are so many moving pieces that need to mesh together to keep a fleet operating efficiently. This includes inputs from the maintenance side, the fuel side and the insurance side, just to name a few.

Total cost of ownership (TCO) has become a defining metric for many fleets. They have to consider not only the purchase price of a vehicle, but also anything that preceded it, the whole warranty analysis piece, all of the maintenance inputs and how the equipment is being used.

Each fleet needs to determine which factors to include in its TCO equation. In addition, there is a sweet spot for when a fleet should replace equipment. To find that, all operating data needs to be factored in.

Additionally, information needs to be included from external sources. Consider all the technological changes that continue to be introduced into the trucking industry and all the new features that improve safety, driver comfort and fuel efficiency. A fleet’s TCO could rise dramatically if it delays retiring an old asset and purchasing a new one.

Unfortunately, no matter which metrics are measured, the information is not always housed in the same database, making the analysis that much more difficult. One of the challenging things for folks in the C-suite is to get the pertinent data compiled into a usable format. That takes time, especially when the information is going to be used to prognosticate or determine budgets for the coming years.

Although compilation of critical data can be time-consuming, effective decisions cannot be made without it. Fleets need tools that expedite the management of the data that is already available to them.

Recently, there has been a move toward cloud-based dashboards, particularly ones that are “drill-downable.” But a usable dashboard has to include information from disparate sources that can be analyzed. Someone has to be dedicated to doing that.

Providing crystalized data — something that is easy to read, easy to see and easy to figure out — takes a concerted effort among a variety of people within an organization.

It actually starts at the top, with C-suite executives — or whoever is making the ultimate decision on how funds will be spent — who can provide guidance about the type of information needed. Ultimately, what you are looking for are reliable results that aid in real-world decision making.

It is important to note that Big Data analytics can’t work in a vacuum with only IT folks controlling the process. Data management scientists need leadership guidance, but they should also seek input from the fleet manager, maintenance manager and others involved in the day-to-day operation of the fleet. This is especially true for private fleets, where trucking is not a core competency and the people in the C-suite may not have a background in trucking.

Fleet management has to bring together people who have studied very disparate disciplines. This team approach to understanding the issues will provide fleet solutions based on the correct management of all the data.

Data analytics help to crystalize the information through algorithms. This leads to a decision tree that is designed to inform the executive team about actions that need to be taken or not.

There is no in between. You either do something or don’t. The C-suite wants analytics to improve the chances of making the right decision.

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Terry Mulreany
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