Analyzing data to uncover new insight into a carrier’s performance is nothing new – think plotting revenue and profit over time on a graph. What has changed in recent years is the ability to analyze larger and larger amounts of data from more and more sources to unlock insights.
OEMs are no different, according to a study by Frost & Sullivan, a consultancy and research group based in Mountain View, Calif. The company announced June 4 the release of a new study, "Executive Impact Analysis of Big Data in the Trucking Industry," which indicated big data analysis has helped several OEMs and their suppliers improve their business processes and service offerings.
The company found that the data analytics generated $93.9 million in revenue in the trucking industry in 2014 and projected that amount would grow to $1.6 billion by 2022.
According to the report, this type of data analysis allows OEMs to:
Plus, the big data has aided in the development of new technologies such as prognostics, autonomous driving and mobile freight brokering, among others.
Frost & Sullivan said that OEM’s main focus is using big data analytics to improve quality and cutting costs, while in the future, OEM’s will use it to help reduce costs to fleets.
In order for OEMs to realize the full potential of big data analytics, there will have to be incentives for data sharing and companies will need to develop “big data platforms,” most likely working with third-party IT providers, Frost & Sullivan said.
“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," said Sundar Shankarnarayanan, an automotive and transportation research analysts with Frost & Sullivan, in a statement announcing the report.
