7 Ways Fleet Managers Can Leverage Data to Improve the Supply Chain

7 Ways Fleet Managers Can Leverage Data to Improve the Supply Chain

“Data is the new oil” is a common catchphrase among business leaders today. It’s more than a string of buzzwords, too, as digital data’s value continues to skyrocket and unlock new possibilities. Still, data won’t provide any value by itself. Companies have to know how to apply it.

Fleet managers have much to gain from data if they leverage it correctly. Here are seven of the most impactful ways they can use data to improve the supply chain.

1. Planning More Efficient Routes

Route optimization is perhaps the most recognizable use case for data in fleet management. UPS has famously saved 100 million miles per year through ORION, its data-based route planning platform. Systems like ORION analyze real-time data to find the most efficient path, saving time, fuel, and money.

Fleets can gather data from GPS networks, transit authorities, weather systems, and other cars on the road. Analytics platforms can then use this data to provide a more accurate, timely picture of traffic and road conditions. Those insights help these systems find the best path forward, even when that’s not necessarily the shortest route by distance.

Real-time data lets fleets account for road closures, inclement weather, and traffic. Drivers can then follow the most efficient routes possible every time, minimizing travel time and costs.

2. Predicting Inventory and Demand Shifts

Supply chains are infamously fragile, largely because they’re prone to disruption but lack the insight to predict these challenges. Fleet managers can counter that by using data analytics to recognize potential disruptions as they arise, informing quicker responses.

Artificial intelligence (AI) can find connections between complex and seemingly disparate data points that humans often miss. In supply chain management, these insights can reveal demand and inventory trends. Analytics algorithms can alert managers when a demand spike may be coming so they can adjust their ordering accordingly and prevent shortages.

Amazon uses an anticipatory shipping system that predicts when customers will want an item, pushing them into the delivery network before users even purchase them. Some bakeries use weather analytics to indicate shifting demand because of the weather. Insights like this can help supply chains become more resilient.

3. Enabling Predictive Maintenance

Maintenance is crucial for efficient fleet operation, and data can improve these processes, too. Internet of things (IoT) sensors can gather data on engine vibrations, temperatures, and other maintenance factors. They can then alert workers when the vehicle will need repair in a practice called predictive maintenance.

Predictive maintenance helps catch vehicle health concerns before they become more costly and dangerous. It also improves on traditional, schedule-based preventive care by eliminating unnecessary servicing.

Vehicles can drive up to 100,000 miles before some maintenance is necessary, but others may not. It all depends on the specific factors at hand, which predictive maintenance accounts for. These data-centric repair practices offer the optimal balance between costs and vehicle safety.

4. Tracking Driver Behavior

Drivers’ actions on the road can influence many other factors, from truck health to operating costs. Traditionally, fleet managers had to address these behavioral concerns through training and background checks before hiring, which doesn’t guarantee ongoing success. Using data from telematics systems enables a more effective approach.

Telematics solutions can let fleet managers track driver speeds, braking habits, seatbelt usage, cornering issues, and more. This data provides an up-to-date picture of driver behavior, helping managers recognize commendable performance and address unsafe driving. They can then tailor feedback to specific drivers to promote better driving habits.

One study found that 69% of fleet managers noticed an improvement in driving behavior after implementing telematics. As driving habits improve, so will cost efficiency and safety from fewer accidents and lower fuel consumption.

5. Managing Fuel Costs

Fuel is often one of the highest expenses for vehicle fleets and an effectively unavoidable one. While fleet managers may not be able to eliminate fuel costs outside of electric vehicles, they can minimize them through data analytics. Data from various sources can reveal paths to reduce fuel consumption and costs.

IoT and telematics tracking in trucks can reveal whether specific vehicles use more fuel than others. Fleet managers can then perform repairs to make them more fuel-efficient or replace
them with newer, more economical alternatives. Similarly, data over time can highlight which routes lead to the highest diesel consumption, informing future route planning.

Other data-centric improvements will help manage fuel costs as a secondary benefit. Route optimization, predictive maintenance, and driver habit correction will all result in lower fuel consumption, keeping expenses low.

6. Monitoring Shipment Quality

IoT devices can also help fleet managers monitor data about shipment quality. Many products may deteriorate in some conditions during transport, leading to waste. Data can reveal when
situations arise that may jeopardize shipments, informing immediate action to save them and prevent waste.

Lack of transparency leads to billions of dollars of pharmaceutical products shipping at improper temperatures or arriving past their shelf life from delays. IoT temperature trackers can provide real-time data about refrigerated shipments’ temperature, alerting drivers and managers when it gets too high. Companies can then adjust routes to deliver that shipment to a closer location where they can store it properly, avoiding waste.

These sensors can help protect food, plants, and other perishable shipments, too. Supply chains can effectively prevent product waste in transportation.

7. Improving Customer Service

All of these data use cases will also help fleet managers improve their customer relationships. Each of these applications will reduce operating expenses and improve efficiency, which translates into lower costs and wait times for clients. Fleet managers will build a more satisfied and loyal client base as a result.

Improved efficiency is particularly important for B2C (business to community) fleet operations. Studies show that 65% of U.S. consumers expect two- to three-day delivery speeds, but only
29% of companies have that as a goal. Fleet managers can meet these high expectations through data-based route optimization and inventory management.

B2B clients will also appreciate the improved speed, lower costs, and reduced waste. These savings will help them deliver more value to their customers, so they’ll be more likely to partner with fleets who can provide them.

Data Is an Indispensable Resource for Fleet Managers

Data can be one of a fleet manager’s most valuable assets if they know how to use it effectively. These seven use cases can help fleets become safer, more efficient, and less wasteful, despite ongoing supply chain challenges. As supply chain resiliency becomes increasingly crucial, fleet managers must capitalize on data’s potential.

Source by [author_name]