Why Machine Learning Is a Delivery Driver's Best Friend

Feb 8, 2018 | 2394 Views

Despite many changes in technology, there are companies that use the old method of operations. For example; many companies still plan routes for their delivery trucks on the same way they did a decade ago. Also, managers create itineraries the day before, and then the hand printouts to drivers to follow or add them to the hand-held devices that their drivers carry at their hip. These outdated methodologies create turbulence in the daily operations and creates inflexibility in daily operations.

Many organizations have learned to tackle this problem quite effectively. One of those, Wise Systems, a Boston Startup is handling it effectively by pairing up the machine learning with data it collects from driver's mobile phones. It syncs information like the driver's speed and GPS location with other details such as traffic, weather, the place of delivery, and customer's availability in receiving the orders. 

To tackle such problems, a delivery route is created that can be adjusted depending upon the upcoming complications. If the technology determines that a driver will miss a scheduled stop because of the road closures, for example, it will adjust the schedule for the entire day, and if it's not possible, the driver will receive mobile phone alerts, a forthright hint to smoothen up the pace.

The main motive here is to create such routes that smoothens up the drivers' work pace, which helps companies save money by boosting the number of deliveries that drivers can make during shifts while also satisfying customers by improving their likelihood of on-time deliveries.  

Wise's machine learning comes into picture when optimizing delivery routes, and finding efficient routes is the main problem. Wise's algorithms learn from each day's data so that it can improve the routes the technology provides. The CTO, Ali Kamil mentions, "It's much more than taking the data and feeding it in."
For companies, it is very important to increase the efficacy of deliveries, as they compete for customers who expect their orders asap. For an instance, Amazon offers same-day deliveries of groceries and certain Prime products within an hour or two, requiring huge computing power and machine learning tools.

Creating such system is practically difficult. Another company, UPS has been building its own custom software, Orion, for more than a decade. More than 500 people have worked on the technology, but there is a no difference.

Wise Sytems had its first client, Aheuser-Busch in late 2016 to test the software with the wholesalers from Seatte and San Diego. Six months later, they rolled out the technology--a mobile app for drivers and a web-based tool for managers--to more of its' wholesalers across the country. As of this week, Wise has been implemented at all of its U.S. wholesalers - 20 in total, plus two others in Ontario and Qu├ębec. 

Anheuser-Busch used Roadnet for more than two decades. Roadnet is a technology that creates delivery routes up to the day off and helps build the plan and set the sequence, but those routes don't change after drivers get on job. The company found that drivers often deviated from the plan and that indicated they knew better than the technology, an easy slip-up when they follow the same route every day for years. It also highlighted the problem of incorporating some of the on-the-job knowledge that drivers had about their routes that technology has difficulty capturing. 

Wise Systems lets drivers enter real-time data through its mobile app. It helps in acknowledging whether a customer prefers to be serviced by a specific driver and whether parking is scarce. These shared notes are added to the app with a code so that the algorithm can take that information into account in the future. This kind of shared knowledge can be especially helpful when a new driver takes over an existing route.

After a year, Anheuser-Busch notices the several benefits of using Wise Systems. And Matlock Rogers, the director of A-B mentions, "Wise learns patterns and history, which helps it be more effective in the future." He can monitor now, where drivers are in real time, reducing the phone calls and texting otherwise required for updates.

In urban markets where employees are trained and using the tools properly, Anheuser-Busch says it has reduced the miles traveled per stop by 4%, which translates into fuel savings, lower wear and tear on trucks, and, for the driver, improved earnings based on higher productivity. Another benefit is improved customer service. In the past, drivers wouldn't be alerted to missing a delivery window, but now the scenario has changed.

Wise Systems says that its technology will improve over time as it takes on more clients, which in turn provide its system with more data to crunch. Imagine a network of 2,000 drivers--Wise's pool now--versus one that taps the collective brainpower of 20,000 drivers.

Lastly, Kamil mentions that the drivers love them because they are paid by deliveries and not time, and deliveries are smooth due to Wise. 

Source: HOB