Supply Chain Visibility with IoT and AI | Roambee's Sanjay Sharma

Supply Chain Visibility with IoT and AI | Roambee's Sanjay Sharma

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- [Ryan] Hello everyone and welcome to another episode of the IoT For All Podcast. I'm Ryan Chacon. And on today's episode, we have Sanjay Sharma, the CEO of Roambee. They are a company focused on helping organizations get better visibility into their supply chain for on demand, on time, in full, in condition delivery of shipments and assets anywhere in the world. So we're gonna talk about the current supply chain landscape, visibility issues and challenges that companies face. What's needed by the industry to increase visibility for the supply chain, and how AI is playing a role in supply chain visibility.

If you're watching this on YouTube, we truly appreciate it if you would give this video a thumbs up, subscribe to the channel, as well as hit that bell icon, so you get the latest episode as soon as they are out. If you are listening to this on a podcast directory like Apple Podcasts, please subscribe so you never miss an episode going forward. Other than that, let's get on to the episode. Welcome Sanjay to the IoT For All Podcast, thanks for being here this week. - [Sanjay] Hi Ryan. Sanjay here.

Nice to meet you. - [Ryan] Yeah. I'd love it if you could start this off by giving our audience a quick introduction to yourself and the company.

- [Sanjay] So my name is Sanjay Sharma. I'm the CEO of Roambee Corporation. We are headquartered here in Santa Clara, operating in seven countries, and our mission is to use technology, a combination of IoT, AI, and analytics to deliver real time visibility of goods and assets that move within the supply chain of our customers. - [Ryan] Fantastic.

And when it comes to the supply chain, are there any industries associated with the supply chain or that focus on supply chain that you're focused on yourself? Or is it just across all different areas and things like that? - [Sanjay] I think generically, realtime visibility is a must have now for industries around, but our focus is basically towards industries that are looking for accurate and timeliness of data, so that they can use that information to take actions. And there are some industries that are more interested in this data than others, and those industries, for example, are pharmaceutical life sciences, food and beverages, the automotive industry, because just in time manufacturing is very important. So having real time visibility is very important. Customers who are in the retail industry.

So these are the typical industries that would really benefit more than other industries when it comes to IoT and real time capability. - [Ryan] Let me ask you then. So with your experience in the supply chain landscape, what does the current supply chain landscape look like from your side of things? Are there current visibility issues and challenges that exist that a lot of companies are encountering now? If so, what are they? But just high level it for our audience who may not be as familiar with the space.

- [Sanjay] I think supply chain, I would say the visibility is broken and piecemeal and most of the customers that we speak to are relying on third parties that are exchanging goods and assets from point A to point B, which is origin to destination. Some of them rely on emails and the traditional phone calls. Then there are others who basically rely on EDI acknowledgements.

But generally what we are seeing in the industry is lot of companies are looking to make their supply chain more transparent. And the first step in doing that is, is there a way I can even start by analyzing my supply chain and identify the glitches in my supply chain? And that's where real time visibility starts off, right? We are seeing a lot of customers, what we call it as a five day journey. Very interestingly, our customers would say to us is real time visibility starts off by putting IoT devices or sensors on goods and assets on either problem lanes.

For example, shipments from Rhode Island to Guadalajara has more problems than others. Let me inject visibility in there, or it's a problem skew. A 60 inch TV is broken than more often than others. Let me inject. So these are typical examples where customers start off their journey when it comes to realtime visibility. - [Ryan] And so let me ask you if for a customer or even just an industry as a whole looking to have better supply chain visibility, what is needed to do that? Obviously there's the technology component and a bunch of stuff, but I'd love it if you could take me through the different areas that really need to be focused on in order to drive visibility or better visibility in the supply chain itself.

- [Sanjay] The first step is identifying what granularity of visibility you need. For example, some customers move their products only in containers. So is visibility at the container good enough, or some containers are moving air cargo, is visibility good enough at the air container level? Or some customers would like visibility at the pallet level and some would like at the package level. So I think identifying the granularity of visibility that is needed is extremely important. So that's number one. Number two is once you have that visibility, what are you going to do with it? Okay.

Are you going to optimize your delivery times? Are you going to make sure that you need visibility because you want to have effective security on your goods that gets transported? Are you getting visibility because you want to manage risk around spoilage or damage? So I think the second aspect of this is once you have that data, what are you going to do with it? So that's the second part, right? The third part is once you have made improvements in the supply chain, can you use now this data even further along to make your supply chain autonomous? In other words, can you take this real time visibility and translate that into a transformative initiative within your organization that enables the supply chain to be self-healing, dynamic, and contextual. - [Ryan] Absolutely. What about other things, I guess from an industry perspective, I've talked a bit about this with other people, about standardization in the industry to make this- make solutions more easily adopted, technologies more easily integrated in.

Is there an element of that in this space as well? - [Sanjay] Yes and no. I think when it comes to the standards of adoption, there are some standards that already exist. So for example, if you are a company that is using airlines to move your cargo there is something called Cargo iQ, which is a standard coming from the IATA organization.

And that actually tells you, what are the things you should be looking for when these goods and assets move from point A to point B? But there is nothing like this on the ocean side of things. When it comes to monitoring shipments in the ocean, when it comes to standardization of inventory, there is standardization at choke point. So for example, if you're bringing any products into the US market, the border security forces has a standard on how it has to be defined. What needs to be declared and what kind of data they need from the goods and assets that get onshored, on US land.

- [Ryan] What about- I guess if a company is listening to this looking to increase their visibility into their own supply chain or their products, how easy is it to implement? Because you mentioned that in order to really do this successfully, you need to understand the granularity of the data you need. You need to understand all those important pieces, how the integration's going to go, how the- what technology's gonna be required, but with supply chains that have existing infrastructure, legacy systems that are there already, how easy is it to layer this on to enable increased visibility? Is it something that is more feasible now given the technology and where things are or how is that approached? - [Sanjay] Yeah, I think the phase one is fairly easy. It's about selecting a provider, a service provider that identifies and matches with your granularity requirements, and then just implementing that solution and lot of the solutions that are out there in the market, including Roambee, basically you can just start monitoring your shipments within days. The second aspect is, okay, now you started monitoring. You have alerts and notification on the anomalies and the excursions that occur in the supply chain. How do you handle that? How do you deal with that? That also basically would take few weeks for your team or the company's team to familiarize themselves upon and make them actionable.

What becomes harder is when you are now collected serious amounts of data on your products, on origins, destinations, your lanes. What do you do? How do you translate that into improvements in your supply chain. For example, some customers would take that data and start looking at transporter behavior. Others would look at that data and start looking at profiling the lanes and the routes that they take. So there are many ways of skinning this data, and that sort of becomes harder because that's pretty much tying down to the business and fundamentals of the company and also what the priorities are. - [Ryan] Deploying solutions like this, there's always the company that is more of the buyer looking to get access to certain data to improve efficiencies and grow the business.

But then there's also the end user that has to interact with these interfaces and handles more of the day-to-day of the supply chain pieces. How big of a experience difference is it for both of those stakeholders? In a lot of solutions that I've talked to guests about, a lot of times it's a very different vantage point that they're coming from. And building a solution that kind of achieves both of those goals is not always easy. When you talk to companies out there looking to bring this visibility into their business, how tied together is that discussion with the end user who's involved in the supply chain? Day-to-day and the company itself who is looking to have access to this data to make better business decisions. - [Sanjay] You're absolutely right. The same data would be interpreted very differently and consumed very differently within various stakeholders, whether it's internal in the organization or external.

And I call it the data magnification, right? For example, an end user might be interested in knowing- if I'm a warehouse manager, I would be very much interested in knowing when my shipment, which was scheduled to leave, has left and then once it has left my jurisdiction, I'm no longer responsible for the second leg of this journey. The second leg of the journey might have an interest saying, for example, we have customers where the receiver says, I'm not really interested in the entire date of the journey. Tell me when the truck is going to be 50 miles away from my destination. That's when I'm interested in knowing. So I think it's the data magnification.

You are collecting data, but slicing this data for various users. Again, is non-trivial. It's a business- it's a business rule, I would say, on how this data needs to be repurposed.

And there are platforms. I think the choices that the customer has today is there are quite a few platforms that allow them to do this with low code or no programming, and it's all configuration. - [Ryan] Absolutely. Yeah, I think that's an important part.

Just as important as the ability to collect the data through the different environments that the supply chain runs through. The connectivity piece comes in. This is a conversation I've had with people in the past, with like just enabling better visibility through having access to better connectivity wherever the pieces of the supply chain are traveling and that sometimes doesn't always exist. So as technology has improved, as connectivity options have improved and work better together, you're able to provide greater visibility across the board to do exactly what you're saying, which is build a solution that works for all the different stakeholders that are intended in hopefully a low lift capacity to get this into the company to see the value, and then obviously scale from there. - [Sanjay] That's right.

And further along, while there is no connectivity available, is there the- does the solution have the ability to continue collecting the data? And when there is connectivity, can you push the data so that it can be replayed? And then more information can be derived out of that replay. - [Ryan] A hundred percent. That's a great point.

Let me ask you, so with the- with obviously the explosion of AI, a lot of companies are now talking about how AI and IoT are working really together in a solution like this, in an industry like this, how do you see AI playing a role in supply chain visibility, because obviously this is- we've been talking a lot about the ability to collect more and better data, but with that data, how is AI coming in and helping analyze, helping just improve the overall experience and understanding of that information? - [Sanjay] The way to look at this technology is to look at through the view of an example. So for example, if you combine artificial intelligence and an emerging technology like graphic neural net, for example, if you combine this, you can really start thinking about the impact of a disruption in a supply chain on the supply chain network itself. For example, if your product is stuck at the Swiss Canal, can you basically take that disruption and start looking at what that disruption would look like within your supply chain, but the fact that your products are not getting in your customer's hand, what impact would they have? The fact that they don't have that product, what impact would it have on an industry? On an economy in general. So network propagation, as an example, is a very big theme in supply chain. And can I basically bubble up a small disruption that happened within my supply chain and really be able to see an impact within the entire network.

So that's one piece, right? The other piece is looking at the play of AI and ML into digital twins. So when I basically are launching a new product or redesigning my supply chain or putting a new supply chain network in place, before I turn on the button and launch the network, is there a opportunity to make a digital twin of the very same network and start simulating it with pseudo but real time data, which will allow me to start looking at where the choke points are, what kind of challenges I would see. So I think combining AI with digital twin concepts like that would really benefit the supply chain and the supply chain operators.

- [Ryan] I totally agree. I actually had a conversation earlier today about a company that's focused on fake data, is the way they kind of market it, but it's the ability to have realistic data that, for instance, you have data that's maybe has a lot of privacy restraints and things like that, but you want to have access to realistic data to run simulations, to build digital twins, right? To show what kind of situations could arise and really test this out to give yourself the best chance of success, which I think is a really interesting approach to this kind of industry that we're talking about now. Last thing I wanted ask you before I let you go here is for companies out there listening to this looking to build that visibility into their supply chain, what is the best way you recommend that they get started? Or what's the advice that you have for them to be successful going down that path? - [Sanjay] I think from a tech stack perspective, I would encourage companies to start looking at open standard tech stack that can run on any cloud. That can support any kind of sensing devices that are out there, whether it's a disposable or a reusable, but most importantly, it can also be integrated with their existing IT ecosystem. It could be an ERP, it could be a warehouse management system, a yard management system, and things like that. So that's the choice of the tech stack, but I think it is very important to start looking at internal stakeholders and the consumers of data.

Who would- which groups of individuals will have access to this real time visibility data and how they can be enabled to take actions. I think that's the second part of it, which is people and process, right? How do you basically put this information on the fingertips of your workers who can take action. So that's the second piece.

And the third piece is starting to think about transformation, right? Within the entire supply chain, where do you start your transformation journey? Is it at the planning stage or is it at the distribution stage, or are you going to do it indoors, outdoors, or in transit? I think there are some choices that a customer needs to make when it starts thinking about digital transformation. And lastly is looking at the choices that have been made in enabling real time visibility and digital transformation. Are these products, platforms, tools, technology, future proof? Can I basically make sure that the investments I make today in people, process, and systems can outlast some of the transformation journeys that companies are embarking on. So I feel those- these are the key value points that should be taken into consideration by an enterprise.

- [Ryan] Absolutely. No, fantastic insights. Thank you for spending the time today talking about this.

This is obviously- supply chain's been a pretty hot topic for a while across many different industries. And the fact that it's- IoT is playing a large role in that, I'm glad we're able to dive deeper into that today. For our audience who wants to learn more about what you all have going on, maybe follow up with any questions or talking points from today's discussion, what's the best way they can do that? - [Sanjay] I think they can get up on our website.

It's and then there is a wealth of awareness material there. Resources, blogs videos, and obviously contact information via LinkedIn or our email channels would really also help. - [Ryan] Perfect. Again, appreciate the time.

Thank you so much and excited to get this out to our audience. - [Sanjay] Thanks, Ryan. Bye-bye.

2023-06-28 20:11

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