A phrase that gets tossed around a lot is “big data.” On the face of it, big data has to be a good thing. More information is always better than less, right?
This statement made in the Harvard Business Review in 2012 enthusiastically supports that conclusion, “Because of big data, managers can measure, and hence know, radically more about their businesses, and directly translate that knowledge into improved decision making and performance.”
In its discussion of this topic, the Review helpfully defined what big data means, and it relates to more than merely a wealth of information. Its definition highlights three qualifying parameters:
Build Your Own Report Making Your Data Work for You
The sheer amount of input available today is staggering; more data are now loaded onto the internet every second than were stored on the entire World Wide Web 20 years ago, when tech types spoke in terms of megabytes. They now talk about petabytes, a measure of bytes in quadrillions. To visualize one quadrillion, imagine enough information that if it were on sheets of paper, it would fill 20 million filing cabinets.
Even that threshold has been crossed, and data managers use the word exabyte —one billion gigabytes. Several exabytes of information — it is difficult to quantify how much — are created every day.
To produce that much data, things are happening quickly. Processing speeds are light years ahead of where they were a few years ago; long gone is the era when downloading a file meant a coffee break. In homes as well as offices, we take high-speed data streaming for granted. And, when information is arriving that quickly, it has the potential to overwhelm any person or organization trying to make sense of it.
Big data comes from everywhere. We still receive information from the traditional sources—in person, audio and video broadcast, and the printed word — but most of that has rapidly been replaced by more targeted, specific communication. This includes everything from what we read on our cell phones to home appliances and motor vehicles that can tell us how they are doing. With words and numbers coming at us from so many places, the challenge is to make the best use of it: to filter out what we don’t need to know, and apply what is useful to us.
Some commenters on the big-data phenomenon add two more versus to the definition: variability and veracity. To perform an accurate analysis of information we need it to be consistent, and there has to be a way to determine which messages are accurate and which are based on input that is either faulty or misleading.
Making Use of Big Data
How does this information overload affect a business professional — specifically, a commercial fleet manager? Big data can be a solution instead of a problem when it can reveal ways to maximize productivity, reduce expenses, and point the way toward smart decisions affecting the future. Data analysis is key. As a recent Forbes magazine article on big data says, “Predicting outcomes is helpful, but explaining them — understanding their causes — is far more valuable, both from a theoretical and practical perspective.”
That applies to vehicle fleet management because GPS fleet tracking yields an increasing amount of data, far more than was available before fleet manager software. By itself, this information is a bunch of numbers, but looking at what those numbers tell us can pay real dividends. Fleet tracking reveals relevant patterns that help us understand what is going on, both with the driver and the vehicle. And this understanding is being used today to “support improved performance, safety, diagnostics and maintenance,” noted the online industry journal TruckingInfo.com.
Today’s competitive marketplace has made these telematics inputs essential in measuring driver activity, the condition of equipment, and the optimum use of resources. Trucking Info noted that typical business information uses past performance to create operating standards, in contrast to predictive analytics that process the data to construct a model of future events.
One example cited is driver behavior. Producing scorecards for drivers not only gives fleet managers an objective platform for deciding compensation and other rewards, it can also indicate possible issues — and suggest training that may head off problems before they develop.
Big data can be applied on a micro basis — using engine diagnostics to determine a maintenance schedule for an individual vehicle — or on a macro level, to identify industry trends or monitor international technical or regulatory developments. Either way it’s an increasingly indispensable tool. Big data tells us what we need to know, when we need to know it.