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Christina Cardoza: Hello, and welcome to the IoT Chat, where we explore the latest developments in the Internet of Things. I’m your host, Christina Cardoza, Editorial Director of insight.tech, and today we’re going to be talking about smart logistics and tracking with John Dwinell from Siena Analytics. Hey, John, thanks for joining us.

John Dwinell: Oh, Christina, thanks for having me.

Christina Cardoza: Before we jump into the conversation, why don’t you tell us a little bit more about yourself and what you do at Siena Analytics in the company.

John Dwinell: Sure. So, I founded Siena Analytics back around 2013, and it was really at that time we saw that the tools for IoT had really come together, and we knew in logistics there was just so much data, so many images that were just being thrown away. And it was a great opportunity to bring that technology, to bring IoT into supply chain. And that was really—that’s the beginning of Siena, and it’s brought us all the way up to today, and a lot of improvements.

Christina Cardoza: Yeah, absolutely. And of course we all know how important data is to the success of your business today, and operations especially being able to get that in real time and be able to analyze and get rid of all of the false alarms and things like that. But I want to start off our conversation today—we’ve heard a lot about the supply chain in the news, a lot of challenges over the last couple of years. So, I want to sort of just set the stage: what the state of the supply chain is today, and what are the current trends or challenges that we are still facing?

John Dwinell: Sure. So, we started out with all of this IoT, and capturing data and images, and along the way the capability to bring AI and AI vision into this IoT solution has really helped transform visibility in the supply chain. And today this is a tremendous issue, right? So, supply chain organizations are under so much pressure to get higher throughputs, better efficiency, and to be able to scale as, certainly, e-commerce has grown. And so the tools and the visibility have really been critical to understanding where the bottlenecks are, and how to improve that so they can really realize greater performance and precision, better quality. So, quality and visibility are really big pressure points in supply chain today.

Christina Cardoza: Yeah, absolutely. And that visibility relates to business benefits across the board—not only improving inventory management, but even reducing transportation costs from trucks coming into the warehouse and picking up and delivering some of these products, and increasing inside the factory itself, increasing the operational efficiency.

So I want to talk a little bit about these IoT opportunities that you guys saw when you started Siena Analytics, as well as some of the recent advancements in the technology that are really helping you guys gain these business benefits across the board and start addressing some of these supply chain challenges.

John Dwinell: Yeah, so IoT has really flipped the problem on its head in a lot of ways. So, traditionally there’s enterprise data saying—okay, for example, this is the size of a case and so this many cases is what’s going to fill a trailer. And IoT is looking at the cases and saying—well, actually this is the size of the case. It’s real data flowing up. And that real data in real time allows you to make the correct adjustments over time so that you can allocate resources correctly. And there’s a lot of benefit and sustainability there, but obviously getting those numbers exactly right allows you to plan your supply chain more efficiently.

Christina Cardoza: So in order to get the accuracy of, say, the case that you’re talking about—the size—this is the real case. Or to really analyze this fast and in real time and get the business, the information and the measurements that matter when it matters. Are you guys utilizing any type of artificial intelligence or machine learning to make this happen?

John Dwinell: Yeah, that’s a big, big factor here. The volumes are very high, and the speeds that the volumes flow are also very high. We today are looking at over 50 million cases every day. That’s just a tremendous amount of effort. And that’s where AI helps change the formula for this really completely, because we can literally look at all six sides of every case flowing into and out of a warehouse and see what kind of condition it’s in, how it’s packaged, how it’s labeled, what’s there and what’s not there, and how does that meet the standards. How does that meet the supplier requirements? And doing that at scale in real time has just not been possible in the past. And so AI and the platforms that we work on have really made this possible.

Christina Cardoza: So, I know that the logistics and tracking space—they’re no stranger to technology and leveraging technology to get things out the door. But sometimes when you have these Internet of Thing technologies, or these more advanced technologies like artificial intelligence, it makes things a little bit more complex, and it’s not always—everyone wants to use it, but they don’t always know how or what success looks like. So what would you say are some best practices to implementing some of these technologies or measuring success along the way?

John Dwinell: It’s true, there’s a certain intimidation factor with AI; it’s new technology. If I only go back a few years, it was a kind of dark art. You really—you needed a real specialist that there were very few of in the world. And there’s been a lot of advancements there.

We have a very friendly, no-code environment that takes away the mystique of the training. We’ve simplified that so we can capture the images, label that data, train new models using the platform, and engage the customer’s domain experts to help with that themselves, and really see these models come together, which is very exciting. And train them to recognize that what’s really critical is small variations from one customer to another—exactly what they need to see. So, the AI model is very adaptable to that. But you need the platform; you need the tools to make that approachable.

Christina Cardoza: Yeah, I love sort of having that no-code capability because I know a big part of just being able to utilize AI is that it used to be limited to experts, data scientists, developers—that not every organization has the in-house skills to do that. So, when you allow this to be used by business users or even domain users, they’re the ones that really understand the problem. So they’re the ones that can really make those actionable decisions or really make those changes and see if things are working well.

But I want to talk about another little issue that people have had with AI, and obviously it’s not little by any means, but just while we’re talking about AI in the past—how it’s been perceived, especially when you’re using all of this tracking and logistics data and you have personal information about customers—where they live or what they’re ordering, things like that—there are security and privacy concerns to that application. So, how can businesses in this space ensure the privacy and the security of their customers, of their data, of their company, especially as cyberthreats continue to grow?

John Dwinell: Yeah, I think security is really important, especially in Internet of Things. You’re capturing data in real time right there at the edge, but it needs to be brought to the enterprise, sometimes to the cloud, and those connections from edge to cloud or edge to enterprise—they need to be secure. So we work very closely with the information-security teams. We leverage the technology and the platform Red Hat and Intel to be sure that we have a very secure environment.

And security—it’s critical issue. These buildings need to still work efficiently, so there can’t be cyberthreats that are going to threaten that. So the platforms are all very approved and, to your point, they really need to be secure, and that’s a constant battle these days.

Christina Cardoza: Yeah, absolutely. And I love how you’re working with other partners in the industry, and that it’s something that you’re continuously on top of or continuously tracking. Because security and cyberthreats change every day and you can never be 100% secure, but it’s important to make sure that you’re secure as possible. You’re standing up to all the trends, updates, patches, things like that.

I want to get into a little bit of how Siena Analytics helps. What are the products that you guys have that are actually making all of this happen, like the no-code capabilities you were talking about. And also if you have any customer use cases or examples that you can share with us.

John Dwinell: Yeah, so one thing I want to make sure I point out: we talk a lot about the tools, and an exciting thing for Siena was we’re now part of the Peak Technologies family. And Peak has really broad experience in the supply chain, and so they really understand the customer’s challenges in supply chain. And we touched on that earlier—that connecting the domain knowledge with the technology is really important. And so for us it’s not just the tools, but the breadth of experience that Peak has that we can bring that to the customer base and help solve their problems.

And just, for example, some of the most common challenges in supply chain are the vendor compliance. So, that incoming quality of product. And this is where having a real deep understanding of the supply chain is important, and also having the visibility to identify at scale what packages are compliant and why, and what packages are not compliant and what’s wrong, and be able to provide that feedback to the suppliers so they can make improvements. And that sort of collaboration is critical to improvements in the supply chain today.

Christina Cardoza: So, one thing I’m curious about is depending on what type of business you are or what industry you’re in, the supply and the demand of things fluctuate. So, especially around the holidays, things—the demand for things, the demand for tracking or for delivery—just gets increasingly bigger. And so I’m wondering how these tools and how Siena Analytics helped deal with these changes and is able to scale or be flexible as a business or organization needs it.

John Dwinell: Yeah, this is where I—again, IoT is extremely helpful, because the supply chains, I mean, it’s remarkable. We’ve seen this over the past several years with Covid, how resilient they have been. There’ve been a lot of challenges, but in a really extremely difficult, unforeseen environment.

But as the scales—really the accuracy and precision of the information is critical to be able to make those adjustments at a reasonable cost. So IoT is feeding back very precise information about the good and the bad as product comes in so that planning can be more accurate. And that’s critical to being able to quickly adjust to changes in volumes in the supply chain and still be able to have the capacity and the throughput to move those through.

Christina Cardoza: That’s great. And so one thing I want to go back on real quick is that you mentioned you’re working with Intel and Red Hat for some of the security things, and I should mention the IoT Chat and insight.tech as a whole, we are sponsored by Intel. But I’m curious because this has been an ongoing trend that I’m seeing, is that no company can really do this alone. You really have to work with partners in the industry to make this happen and leverage some of the expertise of others to really make your expertise grow and shine. So I’m wondering, what’s the value of working with partners like Intel and Red Hat, or other partners that you’ve worked with to make this all possible?

John Dwinell: Yeah. Our partners are extremely important to us, and we really have a broad range of partners who’ve helped us with this journey. I think IoT, as exciting as it is, it’s still evolving. So getting the right solutions, the right technology pulled together, we work very closely with Intel, we work very closely with Red Hat. We work closely with other partners like Lenovo on the hardware. And Splunk is an important partner for us in terms of analytics. Many different partners play a key role in having the right solution. And we’ve been able to watch the technology as it evolves, but be a part of these conversations and help guide the technology that’s needed. And I can’t thank our partners enough. They’re really critical to making this all work.

Christina Cardoza: Yeah, absolutely. And since this is all still evolving, do you have any predictions on where this is going, or what will come next to the supply chain, or how Siena Analytics plans to be part of this ongoing future?

John Dwinell: Yeah, I’ve been in this for a long time, and I see this as the very beginning, oddly enough. AI in supply chain, really intelligent supply chain, is just beginning, and there’s tremendous opportunities for growth. Really, edge-to-cloud is something else that’s also really—it’s bursting onto the scene. But I think it has still tremendous opportunity to continue to grow.

That real-time information is—any sophisticated supply chain organization needs that real-time visibility. And I think that will continue to grow. I think we see a lot happening in standards and collaboration. So companies work very closely with their suppliers and a vast array of suppliers. So those standards are really critical to making the whole supply chain work together and work efficiently.

Christina Cardoza: Yeah, I’ve heard that a lot. We’re just at the beginning of some of these advancements and evolutions that are happening in all these spaces, and that’s really exciting because I never saw this technology being used in this way, especially in these areas making such big improvements. So I can’t wait to see where else all of this goes. But unfortunately we are nearing the end of our time here together today. But, before we go, just want to see if there’s any final key thoughts or takeaways you want to leave our listeners with.

John Dwinell: I say, be open to the technology. It’s moving quickly. It’s really very exciting, but it can bring a lot of efficiencies. Find partners who understand supply chain and understand the technology—that’s really critical. Someone who can work closely with you on this journey and help bring in the best solution so you can have the most intelligent supply chain possible.

Christina Cardoza: Great. Well, with that, John, I just want to thank you again for joining us today.

John Dwinell: Thank you, Christina. I really appreciate you having me on your podcast.

Christina Cardoza: Absolutely. It’s been such an insightful conversation, and I invite all our listeners to check in on the Siena Analytics website, see what else they’re doing, see how else their solutions continue to evolve—as well as insight.tech as we continue to cover this space. And so thank you to our listeners for tuning in. Until next time, this has been the IoT Chat.

The preceding transcript is provided to ensure accessibility and is intended to accurately capture an informal conversation. The transcript may contain improper uses of trademarked terms and as such should not be used for any other purposes. For more information, please see the Intel^® trademark information.

This transcript was edited by Erin Noble, copy editor.