More and more people are shopping from home these days, and whether they’re ordering groceries, home office equipment or COVID-19 tests, they increasingly expect their deliveries to be quick and on time.
Companies struggled to keep up with the rise in orders and expectations. One of their biggest challenges is optimizing the so-called last mile of delivery – when a driver takes packages from a regional hub to their final destination.
Wise Systems, a startup that started as a class project at MIT, now offers a dispatch and routing platform designed to make the last-mile delivery experience better for everyone, from drivers to dispatchers to customers.
Wise Systems’ routing solution is built on algorithms and machine learning models that are constantly improving as more data is collected. Meanwhile, the company’s web application provides a high level of visibility to fleet operations in real time. The mobile application also takes advantage of an asset that is often underappreciated in the industry: drivers on the ground. It enables them to take notes on unique stops, communicate with senders, and confirm delivery.
“Drivers, no matter what technology they use, are very knowledgeable about every stopping point and every one of those parts of town, so we believe in harnessing their knowledge to make their experience even better,” says VP Customer Experience Layla Shaikley SM ’13, co-founder of Wise Systems with CEO Chazz Sims ’13, SM ’14; CTO Ali Kamel ’16; Operations Director Jamal Derbali.
The founders began working on Wise Systems in 2014, but say they have felt an increased sense of urgency among customers during the pandemic.
“Ultimately what matters to us is the perfect delivery experience,” Shaikli says. “What that really means is something that is predictable, cost-effective, and automated to the people who use the product.”
A class project worth pursuing
The founders met in the 2014 Development Ventures class at MIT’s Media Lab, a course that challenges students to come up with ideas that will impact the lives of a billion people. With the MIT Center for Transportation and Logistics (CTL), they are beginning to explore ways to use machine learning and data to improve last-stage delivery.
That summer, the founders entered the Delta V accelerator hosted by the Martin Trust Center for Entrepreneurship at MIT, where they were introduced to companies that would help them contract the first pilots. Delta v was one of the many ways MIT helped early founders.
“What resource did we not use at MIT?” chicle jokes. “We applied for every award. I won a Carol Wilson award, Ali got a transfer scholarship as a graduate student, we did every planned competition, and we participated in the $100,000 MIT Entrepreneurship Competition. We definitely used every resource possible. We walked in Professor Edward Blanco’s office one day said, “We’re setting up a company, can you advise us?” He said: Absolutely. To this day, the network is very supportive, and we’ve been [the MIT Startup Exchange’s] STEX25 startup accelerator. Doors always open for us.
Kamel also believes that the culture at MIT helped give the founders confidence early on.
“Being at MIT, there is a sense that we can challenge the status quo, and it has helped us get that confidence to challenge companies that have been around for 25 years,” Kamel says. “This is the mindset that was instilled in us at MIT that continues to drive our ambition to transform the industry and to be the operating system that powers the last mile of every kind of delivery.”
Another thing that gave the founders confidence was the unfortunate state of the information systems that many logistics companies still use to plan routes and communicate with drivers.
“On previous systems, I’ve seen everything from phone books and print manuals to legacy apps on tablets that were integrated into the car,” Shaikley says. “Some phone applications, but applications that have been neglected to improve the user experience or the needs of drivers.”
The founders say companies often plan routes based solely on truck capacity without taking into account other factors such as traffic, fuel, historical delivery times and driver change length — all built into Wise Systems’ algorithms. Wise Systems has also integrated operations research from MIT’s CTL and building machine learning models that continue to improve delivery plans, providing drivers arranging each delivery and reordering that order to ensure on-time arrival.
Far from directing, the founders wanted their system to be easy to use, particularly for new drivers due to the high turnover in the industry. To build this system, they began riding with drivers during work shifts to better understand their needs and how they interact with their applications.
“We have a two-pronged approach to technology development,” Ali explains. “The [AI] The technology is there, but it has to be paired with good design, because you have drivers trying to do their job – and they’re trying to do it fast. They don’t want technology to be cumbersome. This was something we had to learn in this field.”
Today’s Wise Systems platform enables easy communication between drivers and dispatchers. Drivers can use the mobile app to navigate, collect signatures, take photos, scan barcodes, and access notes on specific points. Dispatchers can make sure deliveries happen on time and make updates to schedules in real time. All this information is documented to give companies a better understanding of fleet performance.
Wise Systems currently works with large courier companies operating around the world as well as multinational food and beverage retailers and distributors such as Anheuser-Busch. Earlier this year, Wise Systems partnered with Mitsubishi Fuso Truck and Bus Corp.. To improve last mile delivery in Japan, and recently opened an office in that country.
The founders say that customers using the company’s system have reached new heights in fleet utilization and in the percentage of on-time delivery. Wise Systems also doubled in size during the pandemic as companies first adopted an online model.
Even with success, founders remain committed to learning from their clients in a choppy, volatile manner more typical of an early stage startup. Just last month, Chaikli hopped into a delivery truck with a driver, eager to learn about the driver’s experience as she had at MIT.
“We want to make sure we’re ahead of the industry,” Shaikli says. “We want to keep building the simplest and smartest technology, and keep improving it as the industry grows.”
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Wise Systems: www.wisesystems.com/
Provided by the Massachusetts Institute of Technology
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