EMS@C-LEVEL
As Forbes, Entrepreneur, Fast Company and SCOOP writer, Philip Stoten, continues to talk to EMS (Electronic Manufacturing Services) executives he learns more about their individual and collective experiences and their expectations for their own businesses and for the entire electronic manufacturing industry.
EMS@C-LEVEL
Electronica 24: AI and Digital Transformation in Supply Chain Management with Sourceability's Rob Picken
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Unlock the secrets of digital transformation in electronics manufacturing with Rob Picken, Sourceability's newly appointed SVP of Digital Transformation. Rob reveals how digital transformation isn't just about tweaking processes but is a strategic overhaul aimed at making data more accessible and actionable. Discover how the pandemic shed light on weak links in supply chain information exchange and how AI-driven data transparency can mend these fractures. This transformation promises to restore trust and strengthen relationships between EMS companies and their partners, ensuring all stakeholders can access reliable, actionable data insights.
Explore the game-changing role of AI in supply chain management, a tool poised to revolutionize operations by streamlining processes and reducing errors. Rob discusses how AI can handle vast data sets, significantly improving decision-making and demand prediction. This approach is particularly crucial for OEMs consolidating suppliers, aiming to reduce over-ordering and double-ordering issues. With the right SaaS team to implement AI solutions effectively, the future of supply chain management looks promising and much more efficient. Join us for an illuminating conversation that leaves us excited and optimistic about the potential of AI to transform this vital industry sector.
EMS@C-Level at electronica 2024 was hosted by IPC (https://www.ipc.org/)
EMS@C-Level is hosted by global inspection leaders Koh Young (https://www.kohyoung.com) and Global Electronics Association (https://www.electronics.org)
You can see video versions of all of the EMS@C-Level pods on our YouTube playlist.
Hello, I'm Philip Stoughton. I'm here at Electronica 2024. I'm on the IPC booth and I'm talking to Rob Picken from Sourceability. Rob, thanks for stopping by. Recently appointed as VP of Digital Transformation, Tell me a bit about the position and what that means. First and foremost.
Speaker 2Yeah, that's right, phil, so thank you for having me first of all. So I've just been appointed SVP of Digital Transformation at SourceAbility and it's an excellent opportunity to really change the way that our customers and suppliers interact with their own data and data from around the supply chain. So when you think about digital transformation, it's not just changing a process because it's fun to do so. It's about optimizing the process, optimizing the different parts of that process and different factors that influence it, to make the information more available, more useful and, ultimately, help customers and suppliers to make better decisions faster.
Speaker 1Yeah, it absolutely makes sense, and when I look at that, I think of this kind of transference from data through insight and through value. If you're not achieving value, if there isn't a digital dividend, digital transformation doesn't make sense, and I think that's held back the fourth industrial revolution for some time, because it's been hard to get the data first of all. We seem to have mastered that, but it's been much harder to get value. To have mastered that, but it's been much harder to get value. How do you see it working in terms of the way you drive value for your customers from that?
Speaker 2data. I think the key thing that's missing there. Phil, you're exactly right. The volume of data is never a problem. Sourcing data has never been easier and, particularly with AI, generating data and its value is becoming increasingly easy. I think what a lot of companies forget is that when you're acquiring data or using data, it has to be for a reason. So when we're talking to customers, particularly about our source engine product, which helps companies to buy components in the open market, or our data link product, which helps customers to understand what's happening in the marketplace, the key question is never what data do you want? It's where does the data go, what behavior does it drive? And then what decisions will be made differently with the information that you have.
Speaker 1Yeah, and I think, when I look at, I think we've just been through such a fascinating time. We've never had a supply chain event the size of the pandemic not as long as I can remember, and I've been in electronic manufacturing for too many decades, so we've been through this really disruptive time. It's really put pressure on relationships. We didn't enter that time with this digital transformation in place. I feel that digital transformation, ai data has got a role to play in actually repairing those relationships and making sure, if we go through it again, it's much better. Is that how you see it and is that how your EMS and manufacturing customers see?
Speaker 2it A really, really useful point there as well. So the biggest issue with the pandemic was that customers realized they again had tons of data, but the information they relied upon for that decision-making process that we just talked about was often hidden from them. Sometimes due to historical trends, the way they work with their EMS partners For example, automotive companies couldn't really see the data in their supply chain because they never had to before. It doesn't mean their supply chain were deliberately hiding that information. It just means that they trusted the EMS partners to solve problems for so long that as soon as they had to try and help them to solve those problems and find other solutions, it was very difficult because the information exchange just wasn't there.
Speaker 2So one of the things we work with our customers really importantly in this marketplace, in the independent distribution space where we sit, of course, is transparency of data. So we try and help customers understand not only what information they're looking at, where it's come from, who the source is, how reliable they are and what can then be done in the supply chain to keep that security coming through. And we encourage that interplay between suppliers, ems organizations and OEMs through our data platforms to ensure that transparency is complete from cradle to grave and often beyond that in obsolescence management as well. Yeah, from cradle to grave and often beyond that in obsolescence management as well.
Speaker 1Yeah, Rob, I'm curious as whether you believe that the distribution side of the industry is is fully aware of the tension that was created in the relationship, particularly between EMS companies, because they were in situations where if they didn't order, they didn't get a delivery date, they had no change, no cancellation policy, very, very difficult for them and actually has created a bit of an inventory overhang for them. Is there an awareness of that and is there a strategy to actually use these technologies but actually work really hard to show value? And improve those relationships.
Speaker 2So first of all, we have to remember that decisions that get made are always made for the best of intentions and with the most information that's available. At the time and in the middle of the pandemic, no one knew what was going to happen. In the rest of the world, people were at home with their kids at the table and they had various different pressures in their lives as well. And overlaid upon that, of course, emss are at the really squeezed end of where they can make margin to make money. So of course, emss are looking for ways that they can collaborate with other people and make money and bring solutions to market. So I understand there's different pressures there as well, and that often conflicts with OEMs who are trying to find the right solutions.
Speaker 2One thing that we have noticed that we are helping customers do is consolidate their choice of suppliers and their choice of industrial production partners like EMS organizations.
Speaker 2We're working with one company, for example, who five or six years ago they're incredibly acquisitive OEM and about five or six years ago they had over 200 EMS worldwide acquisitive OEM, and about five or six years ago they had over 200 EMS worldwide and that caused a lot of tension because they would be trying to bid in different countries for the same build with two or three different EMS and then on the other side of the world, the same thing, and that caused a lot of distrust, not only between the EMSs and the OEM, but actually between different business units of the OEM as well.
Speaker 2They couldn't tell what they were buying and from where. So one of the things that we try to work on very aggressively with customers is to shine a light into all of their data and help them understand what's important for them. Again, you can't make good decisions without the right information and as soon as you're able to expose the data, it's not something you're providing to customers. Quite often the customers are realizing we have all this information, we just can't use it properly, and I think that's the key thing in building that trust. If you share the information, you share the data and you share the goals, then that's where the trust comes back from, and I think it's a different world now, as you well know, but that trust is starting to come back.
Speaker 1Yeah, I think that's really valuable. And the thing you mentioned earlier AI. It's obviously a big buzzword at the moment. People are thinking a lot about how they can a competitive market in the quoting end of the of the market. With respect to the use of ai, where do you see that adding the most value to your business and where do you see it adding the most value in your relationship?
Speaker 2with your customers? Yeah, really useful question. So I think ai in this industry is going to be transformational in the way that we work with our particularly large volumes of customer data. So back to what I said right at the start of the discussion customers don't buy data because it's fun.
Speaker 2Usually, if anything needs to be cut from a budget, discretionary spend is cut, and data would often be seen as discretionary, but I think with AI, it's being integrated in different ways across organizations and in supply chain planning. It can certainly help customers where, as I say, margins are squeezed. It can help them to optimize their safety stocks. It can help them to optimize reordering cycles. It can alleviate pricing pressures worldwide as well, because you can then start to see huge amounts more information. The other thing that it does that's really important is removes huge amounts of human error from analytical reports within organizations.
Speaker 2The number of companies that I see who spend a ton of time normalizing manufacturer part numbers or data to remove a one should have been an I or a slash, or an O or should have been a zero.
Speaker 2Ai can do that in the blink of an eye and put it in the right context for you. So one of the things that we struggle with when providing data to customers is that we can't control the level of experience that a customer has. Perhaps they have a new intern who's working really hard to learn the ropes and learn the industry, but doesn't come from electrical engineering background. Or perhaps you have someone who's been in the industry for 40 years and actually doesn't understand new technology, like high bandwidth memory, for example. So you can use ai to present the information that is the most relevant to them, yeah, without having to have their experience be completely homogenized across the organization. So, essentially, it allows you to deliver customized data in a format that's correct for the person or the language or the industry, and that's something we're working with our internal tools sourceability very hard right now.
Speaker 1Yeah, I think when I look at AI, I think of the application of AI. I think actually understanding AI is half the equation. Understanding the problem you're trying to solve is the other half, and you clearly do that from a point of view of the history you have in the industry and I think bringing that domain knowledge with a broad understanding of AI is where the value is. Do you have a team that are operating within your organization to deploy AI?
Speaker 2Yeah, really importantly, we have an entire SaaS organization which has product development and AI engineers in there as well. So we use AI to, at the moment, strip out information from customer unformatted emails. So, instead of having to have a customer send you a bill of materials or a list of components in a pre-agreed, defined format that works for us, we're able to take information from a customer in whatever format they choose and use the AI system to make sense of it. So, again back to what you're saying tailoring information to a customer and meeting them where they want to be met, so important today, particularly as you look at working across language barriers and you look at working with new suppliers and new organizations.
Speaker 1Yeah, and I'm hoping in some way it can, as you say, reduce errors Again. In this recent crisis we saw over-ordering, double-ordering. I remember that being a disaster of the tech rec in 2001 and being really surprised that it happened again. But there was so much froth and panic going on in the marketplace that it did happen again and maybe having some historical data that will help us predict demand a little bit better, with very bad prediction demand and driving demand predictions from consumer through brand, through EMS, all the way back to you guys and actually through you guys, to the people that are making the part. So it's, it would be exciting to see opportunities where everyone can do that.
Speaker 2Well, I think you raise a really interesting point, though, about being able to predict what's coming next, and there's a lot of effort in this whole industry, and you'll hear this week AI will be the phrase of the month, but I think the work that we can do around looking at historical trends, not particularly of technology, but of specific manufacturers and specific manufacturing sites, particularly with the number of legacy nodes and mature nodes that are being manufactured in China right now, for example, and all of new investment which is going into new cutting-edge five nanometer and below nodes in Western Europe and North America I think what we'll find with AI is that we're able to look at historical trends of pricing, availability, lead time and consumption and then predict what's going to happen with different suppliers and different technology types. I think that's work in progress for many organizations and we're starting to look at it as well. We're starting to look at it from exactly what you said previously.
Speaker 2What does the customer need from the data? Because AI is being smeared all over everything right now, whether it needs to be or not. I don't really want AI in my smartphone, but it's there whether I like it or not. The use case that customers have for AI is enabling them to consume that data and again make better decisions faster and within sourceability, because we have the three different business lines of franchise distribution, independent distribution and data tools and services. We want to meet the customer wherever they are, in whatever terms they use, and AI is really helping us do that.
AI Optimization in Supply Chain Management
Speaker 1Yeah and that gives them an entry point into your organization. I think it's a really interesting opportunity. I think the supply chain is the first area that we should be really leveraging AI. But at the end of the day, the EMS company is generating a ridiculous amount of data and AI is the only way they're going to really be able to make sense.
Speaker 2I agree. I think you're exactly right.
Speaker 1Well, pleasure to talk to you. Have a great show, thanks very much Enjoy it. We'll chat soon. Thank you very much. Thank you.