The fast acceleration of e-commerce is owed in part to the development of artificial intelligence. AI is what allows retailers to know what to stock, where to stock it and how to ship it. And often, AI is working hard for consumers in the background without them even knowing it.
“[AI] is the glue that can connect the good customer experience digitally to … the store [experience],” Sudhir Balebail, program director for IBM’s (NYSE: IBM) Sterling Order Management System, told Modern Shipper. “The worst thing you can do is [get a customer] excited about a product, and as they get closer to the cart, find out the product is not available.”
The COVID-19 pandemic highlighted the disparities between brands that are effectively using AI and machine learning to do everything from tracking orders to managing inventory and those that are not.
Party City is one such company. The gift and party store increased its digital sales 36% in Q3 2020 thanks to the implementation of new order fulfillment capabilities, including buy online, pickup in store (BOPIS). Adidas also saw similar benefits in 2020, leveraging AI to reduce shipping cost per order, increase net sales and improve fulfillment reliability through an expansion of “ship-from-store.”
Both companies are users of IBM’s AI platforms and because of that were positioned to benefit when the world changed in 2020.
“That shift created both opportunity and a lot of new challenges for them,” Chris Wong, global vice president of strategy and offerings for IBM’s Consumer Industries, said. “Everything from website overload and remediation to using stores as fulfillment centers [changed].”
Wong said IBM’s retail customers have been able to quickly shift to more digital offerings, but not every retailer is able to adapt quickly.
“I think there are natural constraints,” he said. “Some of the [existing] technologies were developed in silos and now in a systems model [we are trying to bring them together].”
To illustrate, Wong pointed to payment systems, which now must integrate across mobile, online, checkout and kiosk. “It’s a critical process because if you get it wrong, you can charge the customer twice,” he noted, saying that IBM’s goal is to “de-componentize” the systems and then add AI on top.
AI is not only a consumer tool
While AI plays a critical role in managing inventory and helping stores fulfill orders, the use of it extends throughout the entire supply chain, and that involves transportation managers.
“There are select applications in machine learning that we’ve found that actually make the shippers’ lives easier and improve the brand experience,” Jason Traff, president and co-founder of Shipwell, told Modern Shipper.
And that is important going forward, but something that Traff and Shipwell saw coming four years ago. He said the company believed the supply chain was going to speed up because of e-commerce growth and that the interaction the consumer has with the shipping experience would become part of the brand experience.
“I think we saw both of those come true during COVID,” Traff said. “The industry collectively has recognized both of those points. They were on a 10-year vision plan, but not this year. Now, because of COVID, it’s this year.”
Traff said the pandemic has highlighted the role shipping departments play in the process, and machine learning is helping these departments better manage shipments and tracking, improving the overall customer experience.
“Most shipping departments haven’t been given much love,” he said. “Now they are dealing with so many more shipments than ever before and they have become customer-facing. Can we make their lives easier and move them from reactive to proactive? Because we connect to capacity in over a half dozen different ways … and all those shipments are attached to orders, we actually know where those shipments are every day.”
Traff said there are still Fortune 500 companies Shipwell talks with that manage their entire supply chain in silos. In fact, he said that the use of AI and machine learning to create shipment visibility is still “real innovation in logistics because it is the first time you can act proactively.”
One company that had, and continues to have, an issue with visibility within its supply chain is exercise company Peloton (NASDAQ: PTON). On its earnings calls on Feb. 4, the company acknowledged the backlog of orders it had with deliveries stretching into months for some consumers. Peloton saw huge growth in demand for its products during the pandemic, but its supply chain was fairly static – shipping products from Asia to U.S. ports via containers. As congestion in the ports built up, Peloton products sat idle, waiting to be unloaded. The company is now planning to spend $100 million to improve its supply chain.
On a recent episode of FreightWaves’ Great Quarter, Guys, Seth Holm, senior research analyst for FreightWaves, discussed the Peloton situation.
“Peloton didn’t have enough bikes and treadmills in inventory to meet demand, so they had to run factories 24/7, and a lot of this stuff is produced in Asia,” Holm explained. “It was then placed on container ships and it goes across the ocean to LA or Long Beach.”
Holm suggested Peloton’s issues are a combination of events, including shipment visibility.
“Some of the fault probably lies with the manufacturers back in China. Some of it probably lies with the ocean container lines — [there] have been labor shortages at the ports — and then it goes to Peloton for not being able to coordinate this whole process and get products delivered to their customers. And they clearly don’t have the technology on the back end to get visibility into the status of their freight,” Holm said.
While not speaking to Peloton’s situation, Traff said solving these types of issues depends on vertically integrating systems and leveraging AI throughout the process to identify issues and minimize gaps in inventory or delivery. It is also not as easy as it seems, he added.
“The faster you can actually tie your business together and be more vertically integrated, the faster you can react and be more nimble,” Traff said.
IBM’s Wong issues a similar example.
“When the customer clicks through to get to that dress, and it only goes to the retailer’s home page, they … have to go find that dress,” Wong said. “It’s about mining that data and being sure that the experience the consumer wants is consistent.”
Balebail said the ability of retailers to monitor inventory and sales levels allows them to adjust strategies if items are not selling or relocate inventory to areas of the country where it is selling.
“A lot of our customers have come back and told us … our product saved their business,” he said.
That deep level of insight, though, brings up the AI conundrum of privacy. How much privacy are consumers giving up in the process and is that an acceptable level for the service they expect?
Consumers love to know when their online orders have been delayed. Some have even made games out of “chasing” the truck on its journey, thanks to Amazon’s tracking abilities. But the ability to notify consumers of delays is an important part of the entire customer experience, but also one that requires more in-depth data insights into the shopping experience. The retailer must know the consumer’s address and it must track the order, which means it needs to know exactly what the consumer ordered and what truck that package is on. This information is constantly tracked, cross-referenced and managed through exception using AI.
“If they know a truck is delayed … the system can automatically flag that this order is at risk [before a customer complains],” Traff said. “Basically, every customer interaction is a make-or-break order. For a lot of logistics, it’s the best you can do [make the customer whole in some way].”
This is valuable information for all, including the retailer, which is able to identify buying trends so the next time that consumer comes to its website, the retailer knows what items to suggest.
“Many people are still uncomfortable in understanding the decisions that AI can bring,” Wong added. “IBM has done a lot of tooling to eliminate bias [in its products].”
Without AI, though, the consumer experience would not be the same, and many businesses may not have survived COVID.
“A lot of these customer services, if they were handled by traditional methods, they really would have backed up,” Wong said, citing an IBM grocery customer as one that was able to navigate online order growth that led to more customer service inquiries. IBM helped build order management capability “and we are using natural language and AI capability so we can handle call center requests via AI, whether it is chatbot or AI interaction.”
The speed of AI adoption comes from experience, Balebail said.
“We believe AI should not be a black box, and it should not be in a place that people can’t explain, and [that is should] be something that is helping … to drive the business,” he said. “Inevitably in this AI project, you have a set of folks who believe in the solution. Those folks need to be able to go back to management and say, ‘this is how much AI saved us.’”