Delivering the Future of Shipping and Logistics with AI and Machine Learning

Our Q&A discusses how for companies to globally scale and lower costs effectively, they need to invest in technology to modernize their processes and streamline operations.

I Stock 1283514486

For an industry that’s grown to $1.6 trillion in spending in 2019, logistics is surprisingly outdated. A majority of organizations have a limited visibility into their supply chains due to departments working in silos, often still using pen and paper methods. In order for companies to globally scale and lower costs effectively, they need to invest in technology to modernize their processes and streamline operations.

According to Gartner, 50 percent of supply chain organizations will invest in applications that support artificial intelligence and advanced analytics capabilities through 2024. By incorporating AI and ML into their supply chains, teams can modernize their global supply chain and streamline their workflows with improved ETAs and price benchmarking.

To dive into this topic, we at Industrial Distribution recently spoke with Greg Price, President and Co-Founder at Shipwell, which combines transportation management, visibility and an integrated partner network in one scalable platform. We discussed how supply chain workflows are in need of modernization and how AI and ML will usher in the future of shipping and logistics.

See our conversation below:

Industrial Distribution: What’s the most pressing supply chain issue that can be addressed with AI and ML?

PricePriceGreg Price: Without a doubt, it’s the difficulty around quickly spotting, addressing and preventing issues. The global supply chain has become remarkably extensive and complex — most companies use four or five different transportation modes in their supply chain — so problems are incredibly hard to spot, understand and take action on.

On top of that, demand and expectations are at an all-time high. Consumers have become accustomed to having something delivered to their doorstep just one or two days after placing an order. That line of thinking has raised expectations at every level of the supply chain.

But many companies still track problems with siloed, sequential and manual processes, which crumble under this new paradigm. So the need for rapid analytical capability has never been higher.

ID: How can AI and ML be applied to solve those problems?

Price: Properly implemented AI and ML have the power to break down the silos that exist in current supply chains, providing true end-to-end visibility into the whole supply chain operation. By quickly identifying exceptions and solutions, they can have a huge impact on supply chain management.

AI capabilities deliver insights that can help minimize the level of disruptions throughout the supply chain, and in many cases, stay ahead of those disruptions entirely. Companies can recognize and divert shipments around routes affected by a natural disaster to alternate locations to avoid prolonged loading times as a port is affected by labor shortages. Or they can use ML to predict delivery ETAs and proactively notify customers if their shipment will be delayed.

Another area where AI and ML can have a huge impact is in optimizing last-mile deliveries. That’s critical because the shipping experience has become part of a customer’s overall brand experience, meaning a single delay could cost you hundreds of customers. By taking in vast amounts of operational data, an ML-powered system can learn the inner and outer workings of the business and make route optimization recommendations in real-time. It can provide accurate information and guidance on the optimal number of vehicles required and the most efficient route to deliver the packages to each location on time.

ID: What should a company that is interested in incorporating AI and ML into its processes consider before they begin?

Price: A lot of companies approach this the wrong way. They focus on the input rather than the output. It should be the other way around. Start by focusing on the business problem you’re trying to solve — like improving efficiency, reducing costs, highlighting risks and disruptions, creating better overall customer experiences—rather than having lots of data.

Also, when building your team, it’s vital to hire the right people. The ideal person is a business translator who can convert a business need into AI technology specifications. With an agreement of both sides, they can oversee the adoption and implementation of the technology while helping the organization own the business outcome.

ID: Are there best practices for fitting AI and ML into the way companies currently work?

Price: You don’t want to add complexity — managing a supply chain is difficult enough as it is. By having all issues across the supply chain organized and available at a glance on a single screen, like Shipwell’s Compass Dashboard, it’s impossible to miss an important update. Dashboards also focus the team’s efforts by separating processes into specific areas and flagging actions needing immediate attention.

Identifying actions is just the beginning, however. You need to provide the ability to take instant action directly from that central location. AI’s ability to spot issues also can be utilized to understand what solutions may be available to correct them. Sometimes an automated approach may be best, or when human intervention is required, the system should be capable of presenting options along with the ability to take action on them instantly.

Finally, set limits on the data presented to keep people from becoming overwhelmed. A tech-enabled supply chain creates a lot of data, but it can only be useful if it’s useful to the person viewing it. Customizable filters like date, region, shipment status or type let people cut through the noise and focus on specific issues.

ID: What’s the biggest benefit of AI and ML to the supply chain?

Price: AI and ML eliminate and automate many menial and manual tasks, freeing people for more strategic decisions and enabling shippers to scale their supply chain team’s impact without increasing headcount. In turn, fewer issues and inefficiencies reduce shippers’ costs and improve customer experience.

A supply chain that runs well leveraging AI and ML can build customer trust because it runs efficiently and provides visibility into the process. Today, a lot of information in current supply chains is opaque. All of the parties involved from end to end need to synchronize with each other to unlock hidden efficiency. A tech-enabled supply chain gives you complete visibility, connects to all your people and gives you the superpowers to make smart decisions when you’re executing and procuring transportation.

More in Logistics