By Michael Brooke

When it comes to fulfillment and delivery, artificial intelligence (AI) is being used to create a number of significant benefits. This includes expanding route optimization and asset management across networks, for all stakeholders. AI can be use to optimize fleets to eliminate bottlenecks, reduce empty runs and improve asset utilization

It’s also vitally important when it comes to responding more quickly and accurately to fluctuating supply and demand – this especially true when it comes to providing excellent customer service.

The technology is also reducing cargo delays and overall dwell time while maximizing output to the port’s logistics hub. Overall, thanks to the power of AI, a more fluid, predictable supply chain is created that’s easier to track compared to conventional methods.

AI can be used to analyze customer data and predict which products will be most popular in a particular location, allowing companies to stock their fulfillment centers accordingly. AI can also be used to optimize routes for delivery drivers, helping to reduce costs and improve efficiency.

Emerging disruptors in the fulfillment and delivery space are also using AI to innovate and differentiate themselves from traditional players. For example, companies like Deliveroo and JustEat are using AI to optimize the delivery process, from routing to dispatch to customer service. These companies are leveraging their data and technology to offer a more seamless and efficient delivery experience, which is helping them to gain a competitive advantage over traditional players.

In Canada, freight forwarding is a 16.7 billion dollar market with a number of major players who for decades were content with phone calls and faxes. In 2013, a company called Flexport entered into the market.

The company was founded by Ryan Peterson and in an interview with Daz Rush of the a16Z podcast, he stated the following: “I knew what the customer experience should be. I wanted this dashboard to give me visibility over all my freight, tell me what it was going to cost, when things were going to arrive, what all these weird terms mean. The industry still uses Viking English. We say bill of lading, instead of loading.”

Peterson says that when they started, he wanted to create a simple dashboard – something like Turbo Tax for importing. The company analyzes data from millions of shipments to identify trends and inefficiencies in the supply chain. As a result, Flexport can offer customers greater efficiency and less expensive shipping routes. The data also gives clients useful insights into the global supply chain. When it comes to streamlining the shipping process, Flexport allows customers to track their shipments and manage customs paperwork in real-time.

In terms of incorporating AI into fulfillment,Chicago based 3PL provider ShipBob uses a number of workflows that aim to automate processes and reduce the need for fulfillment associates to make decisions on their own.

Kristina Lopienski, Director of Marketing Communications explains that ShipBob routes each order to the fulfillment center closest to that order’s destination, finding the closest (fastest) and most cost-effective warehouse and shipping option each time.

“We use a box selection algorithm to ensure orders have consistency in shipping costs by calculating the ideal package size for a given order combination.” Their Cubiscan machines determine the right size depending on the dimensions and weights of each product, while also taking each customer’s packaging preferences into account to tell them which package type and size they should use for any order combination. “This means we select the best suitable packaging while reducing dimensional weight” says Kristina.

ShipBob’s sorting machines are connected to their proprietary Warehouse Management System and scan every single package after they are labeled and are on the conveyor belt. The scan validates the weight/dimensions of each order and routes them to the correct carrier sort lane to be ready for pickup at the shipping service level.

The analytics provided to merchants includes an Ideal Distribution tool to help merchants get a better understanding of which fulfillment center locations they would benefit from, based on historical order data. It compares their current versus ideal inventory distribution, and forecasts how costs, shipping zones, and transit times would shift by changing to the recommended regions.

When it comes to investing in the future of AI, over 300 Canadian companies are looking to Montreal-based Scale AI. They are one of Canada’s five innovation superclusters, created to advance the Canadian AI innovation ecosystem. They offer funding, expert guidance and a community of like-minded peers. Scale AI is investing in Canadian companies across a range of industries that are utilizing AI to enhance their supply chain. Since its inception, they have invested over $300 million.

Scale AI offers companies a number of different membership levels. They will connect members with financial, technical and educational resources, as well as peer support, focused on artificial intelligence and intellectual property expertise, all engineered to help them scale their organization, their partnerships and their potential.

The Port of Montreal worked with Scale AI on a project with the objective to reduce container dwell times for critical cargo by 50 per cent. They developed a logistics tool called CargO2ai with a humanitarian focus. The tool was specifically created to deal with the Covid 19 pandemic and ensure swift delivery and fulfillment of medical and safety supplies. CargO2ai uses AI to quickly identify and prioritize the critical cargo that Canadians need to avoid supply delays and stock shortages during precarious economic and public health situations.

When it comes to humanitarian purposes, the Port of Montreal and its partners have processed 5,800 critical-cargo containers.The project has improved communications between all stakeholders and has reaped tremendous benefits. Daniel Olivier, the director of business intelligence and innovation with the Montreal Port Authority spearheaded the move to using AI. As he explains, “I used to receive the cargo manifest 24 or 48 hours out. Now I get it up to 10 days out — in some cases as early as the vessel leaving Europe. Olivier states that the Port of Montreal has been able to significantly improve the timeliness of the reception of the data. This has made things much better for the Port from a planning perspective – from railcards, to trucks to labour.

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