Looking for a way to make your relationships with shippers more efficient, effective, and transparent? AI is the answer.
Much has been made about AI’s use in route optimization, enhanced visibility and improved address validation. But, its ultimate benefit is all about keeping shippers’ customers happy.
“The biggest things that get attention are AI’s ability to automate repetitive tasks and provide cost reduction, but I think that’s only part of the story,” says Bob Czechowicz, Senior Director of Innovation, GS1 US. “The real benefit is that AI enhances customer satisfaction. The most important thing a last-mile provider can do is ensure the consumer has a great experience. This solidifies a shipper’s relationships with their customers. And that reinforces your connection to your customers – the shippers.” GS1 is a standards organization focused on the supply chain across various industries, including healthcare, retail, apparel, and general merchandise.
Czechowicz points out that consumer expectations have never been higher for the performance of the supply chain.
“The pandemic really drove up consumer expectations and accelerated the development of the technology to meet them,” he said, “Consumer expectations only ratchet up. They never ratchet down. So once you’ve set the new baseline for giving them more information and better visibility, that’s the norm. It’s not going backwards. So, you’ve got to do more to keep them happy. That, to me, is AI’s biggest benefit. It can augment existing processes to better meet those escalating consumer demands and ultimately generate positive reviews for the shipper. Today, those reviews are a differentiator for shoppers. They make purchasing decisions based on them. Shippers realize they look good when the last-mile is done right. That, in turn, leads to a shipper’s continued satisfaction with you as a delivery partner.”
Making the Most of AI – Where to Start
It’s easy to go into information overload about AI. Czechowicz offers some tips on where to start to add the tool into your operations:
- Make sure your data is up to the task – “You’re probably sitting on a lot of your own data, but to put it to work through AI, it needs to be quality data,” he advises. “It has to be set up to enable you to leverage emerging technologies like AI. That includes eliminating repetition within your data sets, fixing simple errors and ensuring interoperability with shippers’ systems. That’s data readiness.”
- Find the high-value use cases – “Everything comes down to identifying the best use cases,” says Czechowicz. “Decide what will provide the most value to your organization and customers, and start thinking about applying AI there. Then make sure your data is set up in those cases to enable you to benefit from AI.”
- Pick the right partners – “A lot of times, picking the right partner simplifies the initial decisions,” he says. “The right technology partner can help you choose the best use cases. Then it’s all about leveraging the benefits of that partner’s technology to decide which cases to chase first,” he advises.
Challenges of Adopting AI
One of the first challenges facing companies that want to leverage AI is a psychological one: “I think one of the biggest questions is whether your team is ready to do it right. The implementation of something new is obviously a change. So there’s the psychological hurdle to get over there,” says Czechowicz.
There’s also the very real issue of cost. “There can be high investment costs upfront,” he points out. “A lot of that is also tied to implementation cost. You’ve got existing systems that this new technology must integrate with. There’s also the issue of what it will take to implement a technology like this into your existing processes and systems. That all comes at a cost.”
AI – The Myths and Legends
Because of the sheer volume of coverage AI has received, misconceptions about it abound. “One of the biggest delusions is that AI is a silver bullet. There’s a misguided belief that it will solve all of your issues. And that’s not the case, as with a lot of emerging technology,” says Czechowicz. “You must take the hype with a grain of salt and just understand what it means for your organization.”
He also points to the myth that AI will abolish jobs. “There is widespread fear that AI is going to eliminate jobs. In fact, AI is designed to augment human capabilities, not substitute for them. Smart companies leverage AI to automate repetitive tasks, which frees up humans to work on more strategic things,” he says.
Lastly, Czechowicz cleared up a common myth that once you bring AI into a company’s process, it is completed. “I think there’s a misconception that implementation is a one-time thing,” says Czechowicz. “There’s a misguided belief that you’ll just install the software and let it run and do its thing. It needs constant tweaking and tuning. Yes, the foundational elements of machine learning will mean it will self-correct, but you still need humans in the loop to ensure that it’s being monitored and fed the right information.”
The Dangers of Not Adopting AI
“I think one of the biggest dangers of not adopting AI is all about what your competition is doing,” says Czechowicz. “This is something that’s not going away. It’s here to stay. And I think it’s just really intriguing how fast it’s moving. So I think the biggest risk of not adopting is what your competitors do. Being left in the dust is probably one of the biggest risks of avoiding this technology.”
Introducing AI to Your Team
Once you’ve decided to add AI’s capabilities to your operation, the next challenge is building acceptance and cooperation from the members of your team. How do you have those conversations? Czechowicz stresses it’s all about emphasizing the benefits to them and the company. “Having those initial conversations is all about getting your team members to buy into the outcome,” he says. “Show them how this technology will align with your company’s vision and enhance what you do on a very real level. I think storytelling is essential. Show them how it will free them up to do more strategic things. Emphasize that it’s an augmentation, not a replacement. I think there’s some key terminology to use. And the good thing is, the longer AI has a presence in the workplace, the more use cases emerge. Today, real data shows the positive outcomes to companies harnessing this technology.”
Because of the rapid growth of AI, Czechowicz suggests that those seeking to bring it on should encourage team members to delve into it with an open mind. “You want them to come at it with a learning mentality. Make sure you encourage them to learn what it is; to get literate with AI,” he suggests. “Within our organization, we formed a Tiger team of like-minded individuals from various functions – marketing, technology, legal, and finance. This cross-functional group talked about what they were hearing and seeing in the real world. Members of the group brought up interesting use cases, which enabled them to get a baseline understanding that allowed us to identify specific use cases.
He summarized it this way: “Just be ready to learn from it and let that learning drive where you go with it next.”
Final Thoughts
Czechowicz encourages those in the final mile not to be intimidated by the changes brought on by AI, but to be open to the possibilities it unlocks. “Don’t be afraid to start. Jump in headfirst and go in with a learning mentality,” he urged. “Look at what’s going on out there in the world. I think the biggest thing I would say is to focus on the data. Have the data be the catalyst that enables you to pursue emerging technologies like AI and even what will come next. Right now, we’re focused on AI, but there’s probably something else around the corner that we’re not even aware of yet. Having structured and good quality data will enable you to pursue AI and anything else that comes down the road.”
