With over 20 years of experience in the Logistics space, the client’s leadership team was on a constant hunt to leverage digital technologies; in order to offer IoT logistics solutions and expands its customer base. Most logistics customers have four main business concerns; real-time tracking & monitoring of vehicles, understanding driving habits of workforce, tracking vehicle idling & fuel usage trends, and predicting vehicle failures. With the existing fleet tracking systems, they had no means to track their fleet of vehicles in real-time; to avoid any breakdown, failure, or delay in their supply chain operations. There were no insights for the companies to understand the driving habits of workforce like harsh braking, cornering, etc., due to which they were unable to put focus on improving the performance of inefficient & discourteous drivers through trainings. In addition, they had no means to identify unplanned stops of each vehicle, drive time versus customer service time and vehicle idle time. In addition, their existing system lacked capabilities to track vehicle idling & fuel usage trends to optimize fuel consumption, making it impossible to set up a cost-effective fleet optimization engine. Unexpected failure/breakdown of vehicles resulted in a huge loss in vehicle productivity and maintenance costs. Also, their existing manual process for vehicle repairs and maintenance was time-consuming.
Our client wanted to address all these impediments smartly with an efficient IoT fleet management solution that utilizes diagnostic data of the vehicles, drivers and history of unplanned events. And, such data needs to be obtained from installed GPS enabled devices (IoT assets) in the vehicles. These devices provide information such as vehicle speed, engine coolant temperature & RPM, trip mileage/fuel consumption, hard acceleration/brake, engine idle time etc. By analyzing the collected data, a complete picture of real-time operations can be made available. These insights would help them select the most appropriate route, maximize uptime, control costs, and reduce fuel; thereby boosting productivity, increasing operational efficiency, and optimizing fleet. However, to architect such a solution they required an integrated IoT & Data Analytics platform; which supports any kind of device and possesses an ability to perform analytics for critical insights. To create such a robust predictive analytics fleet management solution, they engaged Saviant as their IoT & Data Analytics consulting partner.