There’s an awful lot of attention being paid these days to the role “Big Data” can play in freight transportation across a wide range of areas, from making trucks more fuel efficient to improving asset utilization.
Indeed, in the nearby story about the finding of the 18th annual State of Logistics Outsourcing study headed up by Penn State University, Big Data figures to play a very prominent role in helping third party logistics providers (3PLs) and shippers alike fine-tune their global supply chain operations.
Indeed, C. John Langley – professor of supply chain information systems and director of development for the center for supply chain research at Penn State and one of the main authors of this yearly report (seen above) – stressed that 3PLs and other supply chain service providers will need to tap into “Big Data” in order to stay competitive.
“Analysis of ‘Big Data’ though can’t be viewed as a solution for problems; it may actually play a more vital role in finding out where the ‘soft sports’ are in global supply chain networks,” he noted in a recent conference call with reporters.
[What exactly IS this “Big Data” everyone keeps babbling about? The video below helps explains what it is and how it came to be.]
Another recent report – dubbed Big data: its power and perils – compiled by the Association of Chartered Certified Accountants (ACCA) and the Institute of Management Accountants (IMA) found that 62% of respondents in the U.S. and around the world cited “Big Data” as hugely important to the future of business, potentially giving businesses an edge over their competitors.
“As the volume and variety of data available is increasing at an intense rate, the ability to organize, make sense and analyze data is at the core of substantial investments corporations are making,” noted Faye Chua, ACCA’s head of future research. “This means big data can offer professionals the possibility of reinvention – the chance to take a more strategic, ‘future-facing’ role in their organizations.”
[Kirk Borne, a multidisciplinary data scientist and professor of astrophysics and computational science at George Mason University, recently gave an interesting TEDx talk about how “Big Data” and the process of “data mining” influence the world every day.]
So how can “Big Data” affect the world of finance? ACCA’s Chua explained: “Using their analytical skills, finance professionals will be able to provide senior management with real-time updates on a wider set of variables, which will place them at the heart of business strategy,” she said. “It is not just the private sector where big data will prove invaluable. Big data will also make it easier for auditors and regulators to spot large-scale fraud.”
The ACCA/IMA report suggests three “imperatives” will be required to successfully take advantage of what “Big Data” offers over the next 10 years, including:
Of course, there are several “negatives” related to “Big Data” in the business world – not so much about the gathering and analyzing of data itself but how that analysis is put to use. Indeed, this is something trucking needs to be concerned about as more and more of trucking operations increasing rely on digital connections to move freight.
“While big data may provide huge opportunities for businesses, we must also bear in mind that privacy is high on the agenda of governments and individuals,” stressed Raef Lawson, IMA’s vice president of research. “We’ve seen high-profile protests about the amount of data that organizations are holding, and, in some cases, selling. It is vital that finance professionals steer their organizations carefully through this ethical and legal minefield.”
As a result, in order to use big data properly, Lawson believes a shift will be needed away from working in silos towards more cross-departmental cooperation. “Data and more importantly, the results of data analysis, must be shared for the company to make informed, evidence-based decisions and equally to manage future risks,” he said.
These are definitely things trucking firms should keep in mind as they wade ever more deeply into the “Big Data” pool.