Fleets that used the insights provided by FleetRisk Advisors’ predictive models to remediate with at least the top ten percent of their most “at risk” drivers, as identified by FleetRisk Advisors, achieved an average 87% reduction in preventable accidents per million miles and an 80% reduction in driver turnover rate, according to the report. The data was normalized for group size across the customer base.
Among the top 10% of drivers identified as most at risk of an accident, the company can now predict 20% to 30% of the accidents, according to FleetRisk Advisors. Broaden the pool to the top 20% of most at-risk drivers and the number jumps to an average of about 35%, with a best-case of 50%.
FleetRisk Advisors enables fleets to anticipate and manage risk by analyzing an organization’s historical data to identify patterns that have a high correlation with preventable accidents or with drivers voluntarily leaving a fleet within the next 28 days. Equally important, FleetRisk Advisors also pinpoints the reason for the increased risk along with a remediation plan designed to help prevent it. The remediation plan includes a guided and positive conversation with each driver in question. These conversations are also intended to help foster a culture where managers encourage, reward and support drivers.
“We have a new level of insights, a deeper understanding of our business,” Vikas Jain, vice president and general manager of FleetRisk Advisors and vice president of Omnitracs product and program management, told the audience. You have to challenge yourself to think differently about paradigms. We tend to think of drivers as “safe or unsafe,” but they are really safe and unsafe. We all are like that. We all have more productive days and days that are less so.
“An accident is actually the effect of something,” he explained. “A stress causes a behavior change which results in an accident. That change in behavior on the part of the driver is reflected in the data and that is what we are harvesting. All the predictive models do is look at behavior changes that correlate with events.”
Keynote speaker, Rich Holada, vice president, BI/AA, for IBM’s Software Group, underscored the critical importance of taking action in response to the insights predictive analytics can provide. “Remember, you have to act at the point of impact,” he said. “If I can predict the winning lottery number, but I don’t buy a lottery ticket, it does not matter… Predictive analytics is all about taking a business problem [and addressing it.]..We pick a point in a process flow where, if we could be predictive, it would make a lot of difference.”
“The trucking industry is at a crossroads and we must re-evaluate our conventional thinking that events are random and that a driver’s behavior needs to be controlled to achieve great results. Instead, we believe a fleet’s success hinges on a more holistic approach that combines effective driver training and collaboration, proactive remediation, business intelligence and technology to improve driver safety, productivity and satisfaction,” noted Jain. “While our predictive analytics models provide key insights to help fleets transform their management approach, the key is helping fleets remediate successfully to prevent driver accidents or turnover.”The company also chose their annual meeting to share a new “infographic”designed to illustrate the impact of predictive analytics technology on fleets’ operational performance, as well as across a variety of other industries.