Artificial intelligence, better known as A.I., or automation. It all may still sound very space-age. The truth is that A.I. is very much happening right now in many facets of home and business life.
A.I. is the study of the ability for machines to recognize, consider, and derive information. It made waves in 1956 as a group of students and researchers at Dartmouth College created computer programs that learned checkers strategies, solved algebraic word problems, and proved logical theorems.
Research proceeded over the next few decades as computing technology advanced. Commercial, government, and educational institutions were all in the search to create expert systems that simulated human knowledge and analytical skills.
Fast forward to the 1990s and early 2000s and A.I. was building a solid reputation backed by faster computers, algorithmic improvements, and access to larger amounts of data that produced real, verifiable results. A.I. was now making its way into the home with web search engines and strategic game platforms, and has only gained traction in everyday uses such as movie recommendations on streaming channels like Netflix, product suggestions based on your buying trends on sites like Amazon, human speech recognition and feedback such as Siri, and even creative tools like ChatGPT.
In the business world, almost 50% of companies have adopted machine learning and advanced data analysis in some capacity according to a 2020 survey (McKinsey, 2020).
While some of us still dream of having an intelligent machine like the Jetsons’ Rosie to handle our housekeeping and manage our family lives, the current course of A.I. development continues to focus on problem solving – making information readily available to consumers, simplifying communications, and solving complex business challenges all in a matter of seconds.
Mechanical automation has been a mainstay for operational efficiency in many areas of the supply chain including assembly, packaging, and sorting. Computing automation is now taking the spotlight to make an impact where it matters most for businesses: operational efficiency and cost savings.
The concept of single-order dispatch automation has been around for years catering to the consumer market by way of services like Uber and DoorDash. These delivery models were built from the ground up on completely autonomous concepts never utilizing manual dispatching. A customer places an order for their takeout delivery, the order is broadcast to the best drivers currently available to work, a driver accepts the order, and voila – food delivered right to your door.
The last-mile can be much more complex with multiple routes, varying time windows, vehicle constraints, driver limitations, and the sheer volume of shipments. That is where years of development and testing behind Autonomous Dispatching comes in.
“Automating the last-mile was no easy feat. We are taking A.I.-driven dispatching further with layers of complexity and considerations to automate driver assignments for 10s, 100s, and 1000s of shipments all within minutes,” explains Christy Cocchia-Barbaree, Director of Product Management at CXT Software. “Think of the popular delivery platforms we all use but on a much larger, grander scale working thousands of shipments into full, optimized itineraries to ensure the best outcomes for each of your drivers, clients, and shipments.”
The concept is captivating but how does it work? As on-demand shipments are created in the courier and logistics software, the Autonomous Dispatch automation tool evaluates the parameters for the shipments against available drivers and parses through hundreds of considerations in seconds to assign the most efficient driver to take the job.
The level of thinking and customization that goes into Autonomous Dispatch – and the timeliness of its computing and results – are not possible in traditional dispatching.
“Think about a game of pool. Most novices look at the table and consider the easiest and closest shot to sink a ball. World champion pool players may be thinking a few steps ahead and considering if they make this move and that move, then what would be my third and fourth shot?” describes Beans.ai CBO, Akash Agarwal. “A.I. is thinking in the same way but even more than four steps ahead. It is thinking 10, 20, 50 steps ahead, not only for this one game of pool but for hundreds of games of pool – or hundreds of drivers in our case – all at the same time. It is a much larger data set than you or I are used to thinking about.”
Computers have one goal in mind. They serve a purpose. In their role as a dispatching engine, the purpose is to provide the most efficient outcomes for your deliveries. Whether you want the most time efficient choices or the most efficient itineraries with the least miles driven, Autonomous Dispatching will provide you with the driver assignments to achieve the goal at hand.
“Automation is simply purpose-built thinking focusing solely on the task at hand, with the task being to provide the best possible results based on the shipment and driver options you have at your disposal,” adds Agarwal.
A.I. at its core is advanced machine learning to problem solve based on the data it receives. The computer-driven problem solving performs a sequence of algorithms – or computations and measurements – that run over and over and over again to produce a solution.
As it receives more information for new shipments, it takes the data from the last set of algorithms and the results that were produced creating an adaptive, dynamic approach with each cycle. The technology is essentially learning and adjusting to provide the most efficient delivery patterns for your business over time.
“Machine learning and cloud computing have advanced over the last few years. What used to require a room full of servers at IBM can now be done on a laptop on-the-go during your busy day,” adds Agarwal. “With the advancement of technology, algorithms now run faster than ever. You can complete more calculations in even less time. This allows us to build robust, highly customized solutions. To have this powerful automation integrated into a full shipment management platform was a feat that was not technologically feasible years ago.”
The machine learning behind Autonomous Dispatching is guided by parameters provided to the tool and the nature of your business. Critical factors that influence the fundamentals of the driver assignments can include:
Imagine thoroughly considering these options every single time for every shipment for every driver every day. A.I. is not only thinking about who has the largest vehicle, who may be closest to the pickup site, or who has the lightest itinerary for the day. It is thinking about all factors all at once and making the most efficient choice in seconds.
“With every new shipment, the technology is taking the considerations and evaluating them over and over again, learning the best patterns and drivers for the optimal outcome. The more information the A.I. has to work with, the better solution it can provide to deliver the best results,” explains Cocchia-Barbaree.
Technology is always changing but in ways to improve how we do business.
“Advancements like Autonomous Dispatch are the path to consistency in your delivery process. The technology is not biased and follows the data and parameters you provide to it to always deliver optimal choices. Optimal choices mean on-time deliveries and reduced costs keeping your clients and drivers happy and keeping your business running smoothly,” adds Agarwal.
Automation does not take the place of customer service or the dispatch experience. It allows you to fine-tune those facets of your business. By giving your dispatchers the right toolkit, error rates are reduced, dispatcher efficiency is increased, and you can focus on key cost-saving strategies for your business.
The need for efficiency and lean budgets is crucial to many shippers and carriers’ operational and financial goals. Under the woes of economic uncertainty and rising prices, managing costs and improving delivery performance will be a fundamental way of business.
“The market is shifting. The influx in shipment volume that came with COVID over the last few years is dwindling, and changes in the economy and inflation affect volumes as well. Future-proofing yourself with technologically-sound business strategies and tools can help operators get ahead of the curve,” states Agarwal.
Historically, technology has paved the way for improved productivity and cost management across the supply chain. While automation has taken other industries by storm, its introduction into the complex last-mile arena is a fresh new approach to streamlining operations and reducing costs during an economically challenging time.
Article contributed by Nadia Zaman, Marketing & Communications Coordinator at CXT Software
Published in Customized Logistics & Delivery Magazine, Spring 2023
CXT Software is the leading provider of last-mile, route, and on-demand shipment management technology for logistics needs throughout North America.
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