Truck OEMs proactively harness potential of big data for efficient systems, processes
Mountain View, Calif.—Big data is driving significant cost efficiencies in several aspects of the global trucking industry, from manufacturing of trucks and vehicle systems, to their operation and maintenance.
Several leading OEMs and tier-1 suppliers have already started incorporating big data analytics to develop effective and efficient systems, processes and services targeted at specific customer groups. Big data analytics is offering industry stakeholder groups, in developing tailored solutions, the ability to attract specific market segments, enhance service quality, reduce warranty costs, and deliver time and mission critical solutions.
The evolution of several new technologies and business models, such as prognostics, autonomous driving, mobile freight brokering, mobile resource management, among others, is not only relying on big data analytics, but also enriching its ability to induce meaningful efficiencies in freight mobility and delivering economic benefits to all stake holding groups in the process.
New analysis from Frost & Sullivan, “Executive Impact Analysis of Big Data in the Trucking Industry,” finds that big data analytics in the trucking industry generated revenues of $93.9 million in 2014 and estimates it will reach $1.6 billion by 2022. More than 65 percent of OEMs in the trucking industry are expected to adopt big data in the next four to five years.
OEMs’ big data strategies are currently focused on enhancing quality and cutting costs in areas such as design, manufacturing and warranty management. For example, employing advanced data analytics tools with early detection capabilities will avoid large warranty claims.
“In the future, OEMs will use big data analytics to deliver cost reduction benefits to fleets,” said Frost & Sullivan Automotive and Transportation Research Analyst Sundar Shankarnarayanan. “Although the present advantages of big data analytics are enjoyed by research and development, product planning, production and supply-chain functions of OEMs and tier-1 companies, marketing and sales will benefit from the most profit when vehicle and systems manufacturers embrace big data analytics.”
Given the privacy issues surrounding the big data revolution, stakeholders are exploring secure ways to share and monetize data. Therefore, companies need to offer an incentive for data sharing to tap into the full potential of big data.
In addition, OEMs and tier-1 companies must collaborate with IT suppliers to build a sustainable big data platform. Heavy-duty truck OEMs, in particular, will rely on IT companies for deploying big data analytics, as well as, securing vehicular systems and developing customizable design and service offerings.
“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,” Shankarnarayanan said. “Furthermore, the integration of telematics and predictive analytics with the latest generation fleet automation solutions will considerably increase fleet productivity, generate faster returns, and underline the business case for big data in the trucking industry.”