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How predictive analytics power up fleet shop efficiency

Jan. 19, 2022
Predictive analytics uses AI and data to help fleets avoid getting behind in work by allowing them to look ahead.

For fleet or maintenance managers in today’s age, fleet management software solutions are becoming familiar tools for the job to increase productivity and transparency across the shop. And they are fueled by predictive analytics, the method of using various algorithms, machine learning, and real-time and historical data to forecast future outcomes. Combining artificial intelligence and data off the trucks and from the shop, fleet maintenance platforms can filter oceans of data and find pearls of wisdom to help you make smart decisions. Alongside telematics, they use data to provide new opportunities across various business functions. But beyond impacting a company’s bottom line, the right fleet technology can effectively streamline and increase efficiencies on the day-to-day operations of fleets of many sizes.

The primary ways in which they do this are by leveraging predictive intelligence/analytics for asset management and failure analysis. Predictive analytics is so crucial to the operations of a fleet that the market is estimated to grow on a global scale to $28.1 billion by 2026. In this piece, you’ll learn the key fundamental values of implementing an intelligent predictive analytics platform that won’t just make your job easier, but also increase uptime, driver retention, and overall savings.

Impact on maintenance strategies

The most common form of predictive analytics in the fleet industry is predictive maintenance. This maintenance strategy can help servicers with several different approaches, whether they are focused on time-based maintenance (TbM), an expert in preventive maintenance and spread sheets, or devoted to run-to-failure. However, above all, implementing predictive maintenance can drastically improve a fleet’s overall operations and cost.

Where run-to-failure and time-based strategies require a lot of parts to be ready at hand and focus on speed of maintenance, having predictive analytics ensures you know well in advance the potential failures that will occur, allowing you ample time to notify the repair shop. This helps avoid missing parts or increased shipping fees for a shorter turnaround.

Preventative maintenance can also be enhanced by the future-forward intelligence of predictive maintenance. Instead of clockwork periodic inspections that require a large investment of time and resources, a shops can turn to the data for a more customized PM schedule, taking into account the unique driving patterns or use-cases of each vehicle at hand. With a powerful predictive analytics platform such as Pitstop, the user can see predictive insights on which vehicles to prioritize in the shop and which to keep on the road, ensuring the maintenance schedule is optimized to save time and money. The average user of Pitstop’s platform have seen a 20% reduction in downtime and savings of $2,000 per vehicle.

Impact on overall operations

Running and managing a fleet of vehicles entails managing a large number of stakeholders such as drivers, contractors, owner-operators, HR, and regulators. The proper running of operations, depending on scale, is looking at well over 50+ metrics on a monthly basis to stay compliant with regulators, internal policies and practices and ensure productivity and safety for the organizations. Data overload becomes the new challenge, as management and employees all can lose sight of the numbers that will drive the business forward, and those that are irrelevant and waste time. Even with intimate knowledge of the metrics, personnel, and stakeholders, a business can be vulnerable to idling data; in other words, having so much you don’t know what to do with it.

Fortunately, the AI can be trained to know what to do. Implementing a predictive analytics solution allows users to streamline billions of data points in order to receive insightful, easy to understand and actionable insights across a business’s organization.

With a shortage of driver supply, driving experience has become critical to the retention and tenure of drivers with a carrier. Advancing predictive analytics technology will make the lives of drivers a lot easier, driving experience better and ensure a safer work environment. Drivers will be able to pick better routes, know and plan for weather conditions ahead of time, and identify potential vehicle performance issues. Some predictive analytics solutions, including Pitstop, have a chat feature for fleet managers and operators to communicate challenges better and provide valuable feedback. This all leads to a smoother, more efficient operation as well as experience.

Conclusion

New technologies, such as predictive analytics, don’t have to be intimidating or overwhelming. Software solutions through the power of scalable web, cloud, and mobile technologies have become very intuitive over the years. Predictive analytics will uncover rich and new information about businesses across industries and can significantly decrease downtime, costs and overall inefficiencies in your operations. Companies who are already leveraging predictive analytics within their fleets now have a competitive advantage.

This piece was co-authored by Jessica Kim, marketing manager at Pitstop, and Rakean Zakir, customer success manager at Pitstop. To learn more, visit pitstopconnect.com or email [email protected].

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