This is our story of co-creating a solution with a global driver risk management company
As we know…
Many fleet operators are changing the ways they manage risks and losses arising from accidents and driver errors by leveraging technology to track and analyze the behavior of drivers in real-time.
Precision, timeliness and efficiency in reporting can reduce the risk profiles of fleet operators and help them provide appropriate training to their drivers. It can also contribute alongside a culture of safe driving behavior across the organization.
The challenge for the driver risk management company was…
Analyzing instances of unsafe driving behavior exhibited by drivers of fleet operators within 24 hours of the occurrence for timely and appropriate action. This had a direct impact on fleet insurance premiums since greater compliance with road safety meant lower premiums.
With fleet operators from 15 industries — such as chemical, automotive and military — spread across the globe, the company’s previous one-size-fits-all method of analyzing drivers and events was not yielding productive results. Recognizing the need for a more tailored approach, the company installed Electronic On-board Recorders (EOBR) to capture all driving-related events.
This video data had to be analyzed quickly across variables such as vehicle type, location and company specification to generate insights that could help the fleet operators coach the drivers and help ensure safe driving behavior.
Here’s what we co-created as a solution…
WNS segmented the 15 industries along four lines — trucking, waste, services (vehicles carrying passengers) and government vehicles. Resources were trained to identify events for each line. We introduced automation using a proprietary work allocation tool to assign video clips to the relevant resources. The in-house tool enabled quicker review and analysis by integrating with the client’s tool.
Our solution included:
Improving the efficiency and quality of reviewed events
Developing a training management tool with a gamification element to upskill new hires in a simulated learning environment
Hiring and training a team of 500 experts across various industries, resulting in improved speed of reviewing video clips at higher quality levels
Building a trial management framework to help us educate new customers, deliver excellent service and improve the conversion rate of trial customers
Deploying a specialized team, audit framework and rigorous transaction management geared towards handling priority customers on the basis of their revenues, fleet size and growth prospects
Reducing the cost of event reviews using innovative pricing methods
Building an innovation lab with highly skilled subject matter experts, consultants and Six Sigma resources to work on high-profile projects addressing key business requirements
Our learnings and outcomes from the process of co-creation are…
That we could transform driver behavior, together. Significant outcomes include:
Reducing cost of operations by 22 percent with the same quality of service, leveraging automation and process efficiencies
Reviewing all events within specified turnaround times ranging from four to 24 hours; delivering consistent and reliable output on quality
Reducing classroom training time by 50 percent and the learning curve of new hires by 74 percent — from 38 weeks to 10
Improving conversion rate of trial customers and increasing satisfaction among priority customers
Building a strong, robust IT infrastructure with zero downtime over the last four years
Managing events in multiple languages across three continents
Incorporating technology solutions that improve the event review program’s reliability and maturity
Providing continuous process improvement through the cutting-edge innovation lab
Interestingly, this case study does not end here…
The road ahead…
We are also developing an end-to-end training solution using 3D immersive experiential learning simulations and assessments, adaptive intelligence and data tracking.
By leveraging our analytics and technology capabilities, we are creating a prototype to automate behavior identification using machine learning and robotic process automation.