Posted June 4, 2024

Enhance the equipment rental delivery experience

Companies are leveraging artificial intelligence (AI) and machine learning (ML) in their connected transport strategies, cutting costs and improving customer satisfaction.

by Tony Tye

Intempo CX/MX software
The strategic adoption of Artificial Intelligence (AI) and Machine Learning (ML) technologies presents a transformative opportunity for equipment rental businesses to revolutionize their delivery operations, optimize their routes, and exceed their customers’ expectations for timely deliveries, and in turn, improvie their reputation as a trusted supplier. 

In the fast-paced equipment rental industry, enhancing the customer experience while managing efficiency and high transportation costs has always been a challenging balancing act. This is especially true for independent rental organizations, where the complexities of managing a diverse rental fleet, serving growing geographical areas, and meeting customers’ expectations tend to fall on a small operations team – perhaps even one without a designated dispatcher.

Regardless of a rental company’s size or team structure, the demand for a streamlined and efficient pickup and delivery workflow is paramount. The strategic adoption of Artificial Intelligence (AI) and Machine Learning (ML) technologies presents a transformative opportunity for equipment rental businesses to revolutionize their delivery operations, optimize their routes, and exceed their customers’ expectations for timely deliveries, and in turn, improvie their reputation as a trusted supplier. This may change the nature of some roles within the organization, but it also creates new opportunities for employees to learn and grow.

Imagine a scenario where the chaos of rental fleet logistics becomes 10 times more straightforward. Instead of grappling with manual planning tasks, AI algorithms predictably optimize delivery routes, minimize idle time, reduce fuel consumption and even account for prioritized pickups on the return trip. From there, strategic AI and ML technologies allow for route optimization, load optimization, order optimization, and real-time adjustments.

Here are a few real-world examples of how connected transport can delivery an enhanced rental delivery experience:

1. AI algorithms can streamline planning processes
Pickup and delivery planning involves hundreds of moving pieces. Teams must account for various equipment types and weights, promised delivery times, truck capacity, traffic, driver compliance issues, sometimes even third-party haulers and their associated costs.

Many organizations rely on a night-before planning process, but changes inevitably pop up overnight. Morning-of scheduling demands a dynamic, flexible approach that accommodates real-world disruptions and unforeseen changes. AI can reduce some of the stressful last-minute changes by accounting for dispatch details, job site addresses, customer time windows, traffic forecasts and driver constraints/habits to propose optimized delivery routes. This empowers fleet managers to quickly respond to overnight modifications and reschedule requests; make informed decisions throughout the day; prioritize critical deliveries; and tailor routes for maximum efficiency and customer satisfaction.

2. Better stop-time predictions
Planning isn’t just about predicting how things should play out – it’s about continually adjusting expectations for how things actually do happen in the real world. Maybe a particular highway sees consistent slowdowns due to rush hour accidents; maybe one contractor is rarely present on the job site and locating the contact for delivery takes much longer than expected.

Accurate stop-time predictions are critical in optimizing delivery schedules and resource allocation, and AI/ML allows for much more accurate forecasting individual stop durations. These technologies can account for factors such as unloading times, customer interactions, and site-specific nuances much faster – and more predictably – than a manual analysis can.

3. AI allows for more precise load optimization.
Efficiently loading equipment onto transport vehicles demands meticulous planning and organization to maximize space utilization and ensure safe transportation. AI and ML technologies can simplify load planning by optimizing loading configurations and analyzing equipment dimensions, vehicle specifications and weight distribution.

By automating the physical planning process, dispatchers can enhance efficiency, mitigate loading errors, streamline equipment loading procedures for seamless deliveries and improve fleet utilization. Correct load planning also has the potential to mitigate the risk and enhance safety – a key concern in the equipment rental industry.

4. Real-time monitoring and communication keep everyone – including the customer – in the loop.
Effective real-time monitoring and communication are essential components of successful equipment rental deliveries. Drivers need a fully functional app that’s easy to use on the go. Dispatchers need an intuitive interface that doesn’t require 100 clicks to complete a basic workflow. Counter and back-office teams need a centralized tracking system where they can see the status of every delivery in real time – and customers need to stay informed of their expected delivery time and any delays that might occur along the way.

Instead of leaving monitoring and communication to chance, technology can partially automate the process to increase transparency and provide a more reliable experience. (For smaller independent rental organizations that compete on service…this can be an absolutely crucial differentiator.)

5. AI-driven analytics make continuous improvement achievable for day-to-day employees and corporate leadership.

To successfully scale, companies need to continually improve their operations and enhance performance, sometimes at a basic day-to-day level and sometimes at the big-picture level. AI analytics allows for both. Rental companies can drill down into deviations between planned routes and actual routes; common causes of delays; and the measurable impact on their bottom line. This information can inform continuous improvement initiatives and promote an environment of consistent learning.

6. Connected transport strategies reduce wasted miles, wasted fuel, and unnecessary wear and tear on corporate delivery trucks.
Time is money and when it comes to pickups and deliveries, every mile comes at a very real (and very high) cost. Connected transport can deliver measurable hard-dollar savings by reducing wasted miles, unnecessary fuel expenses and wear and tear on delivery trucks.

This makes it a no-brainer investment for corporate leadership and a win-win initiative for the individuals that lead the connected transport charge in their respective organizations.

7. Connected transport can reduce reliance on and more efficiently utilize third-party hauling resources.
Many rental companies rely on third-party haulers from time to time. It’s not quite inevitable, but close – especially as they grow. However, rental companies can use AI and ML to intelligently assess demand patterns, equipment availability and customer preferences to optimize transportation logistics.

Using historical data and real-time information, they can strategically position their equipment across various locations. This in turn lets them identify the most suitable third-party transport companies for specific jobs, but only when their internal resources can’t handle the demand. Factors like distance, availability, urgency and cost are all factored in automatically, ensuring the most efficient possible allocation of company resources. 

Embracing the future of connected transport
As AI and ML technologies take further hold in the equipment rental industry, early adopters are in the best possible position to enhance operational efficiency, optimize resource utilization, deliver exceptional customer experiences and reduce their costs. A strategic approach to connected transport can dramatically improve the equipment rental delivery experience, in turn creating sustainable growth opportunities, high-performing teams, and engaged customers in the ever-evolving and competitive equipment rental landscape.

Tony Tye is the product manager of InTempo’s CTX/MX routing/scheduling programs.