Trucking companies around the world are turning to Big Data and analytics in order to save money and operate more efficiently according to a new analysis from Frost & Sullivan.
In fact, Big Data analytics in the trucking industry generated revenues of $93.9 million in 2014 and is set to reach $1.6 billion by 2022, according to the study, “Executive Impact Analysis of Big Data in the Trucking Industry.” And more than 65 percent of trucking industry OEMs (original equipment manufacturers) are expected to adopt Big Data in the next four to five years, the study notes.
A few leading OEMs and tier-one suppliers are already using Big Data analytics to develop more effective and efficient systems, processes, and services aimed at specific customers. With these customized solutions, companies are able to offer better service to their customers, according to the study.
OEMs are using Big Data and analytics to improve the quality of their products as well as reduce their design, manufacturing, and warranty management costs. For example, using advanced data analytics with early detection capabilities will help OEMs avoid large warranty claims.
“In the future, OEMs will use Big Data analytics to deliver cost reduction benefits to fleets,” says Frost & Sullivan Automotive and Transportation Research Analyst Sundar Shankarnarayanan.
Currently, research and development, product planning, production, and supply-chain functions of OEMs and tier-1 companies are using Big Data and analytics, Shankarnarayanan notes. However, when vehicle and systems manufacturers go all-in on Big Data analytics, marketing and sales departments will realize the most profit.
But to make the most of Big Data analytics, OEMs and tier-one companies can’t do it alone. They have to collaborate with IT suppliers to build workable Big Data platforms, according to the study. Heavy-duty truck OEMs will also turn to IT firms for help deploying Big Data analytics, as well as securing vehicular systems and developing design and service offerings that can be customized.
“The real differentiating factors for OEMs will be a Big Data framework, a clear connectivity strategy with the ability to handle large volumes of data, and most importantly, partners to help harness the true power of this data,” notes Shankarnarayanan.
Additionally, integrating telematics and predictive analytics with the next-gen fleet automation solutions will significantly increase fleet productivity, generate faster returns, and highlight how Big Data can help the trucking industry, he says.