Podcast interview with Dr Gilad Langer, Digital Transformation Executive, Tulip
Transcript of the interview between Daniel Langley, Director of Mitrec, and Dr. Gilad Langer of Tulip Interfaces
Continuing our deep dive into Tulip Interfaces, we came across this great interview hosted by Daniel Langley, Director of Mitrec, welcoming Dr Gilad Langer, Digital Transformation Executive at Tulip Interfaces.
To help raise awareness of the conversation, I decided to create a word-for-word transcript of the conversation, eliminating any errors in the automated transcript. It is my hope that others interested in learning about Tulip can now find this content more easily.
The source video is here:
Transcript
Daniel Langley: Well, hi everyone. Welcome to the latest episode of the Manufacturing IT Podcast. I’m joined today by Gilad Langer, who’s the Industry Practice Lead at Tulip Interfaces. Welcome, Gilad.
Dr. Gilad Langer: Thank you and thank you for having me.
Daniel Langley: Oh, my pleasure. I was really appreciative when you said you’d come back and be on the podcast, Gilad. I know you’re someone with a very high reputation in the industry. So could you start by telling everyone a little bit about yourself.
Dr. Gilad Langer: Yeah, of course. So as I mentioned before, this is the point we’re in in the industry is something that’s very close to heart for me because, in fact, I started my career in academia back in the ’90s, working on research projects that were really the archetype or the fundament of what we call Industry 4.0. Things like IoT, digital twin — we didn’t really call them that. We had these very long abbreviations and acronyms because we were academic. And since then I left academia in the ’90s and went to work for the industry and worked in a number of different roles, mostly in what we would call the manufacturing systems space. I touched many systems that we know today. And then a few years ago, I realized that everything that we were talking about as of now is becoming a reality with Industry 4.0. So I stepped back into it and took roles, mostly with startups, to try and bring this to the industry. Currently working at Tulip, and Tulip is, I would say, at the forefront of what is Industry 4.0. I also spent quite a lot of years in the life sciences industry. So I’m very, very much also part of Pharma 4.0, actively working on some of the Pharma 4.0 initiatives.
Daniel Langley: Okay, really interesting background then because a lot of people start maybe in manufacturing and learn through Industry 4.0, etc., but to start in academia is a really interesting starting point for you. So I know Tulip a little bit from what I’ve seen and the disruptive nature of the business. So can you give us a little bit of an overview as well into Tulip.
Dr. Gilad Langer: Yeah, I mean, in general, the short description of Tulip is a no-code platform that enables you to digitize and instrument your manufacturing processes. With that, it’s a digital way to support all the logistics and production control and continuous improvement, operation excellence initiatives that you have in a typical manufacturing-type of environment. But really, I think it brings around two very important things that are part of digital transformation. So when we talk about digital transformation, everybody thinks about technology. But technology is really just an enabler, and you can argue that it has been enabled also in Industry 3.0, plenty of systems and automation that we use there. What it does is it makes the use of technology and software simple, and now it becomes everybody’s domain. It democratizes the ability to digitize the shop floor. So process engineers who typically work in Excel and Word and other types of, maybe even more advanced programs, now have the ability to create software to enable their operators to do things better, capture more data, and improve quality, etc.
Daniel Langley: It’s a really interesting space. And from my background, Gilad, maybe recruiting for maybe traditional MES platforms, those monolithic systems, the on-prem systems, and what companies like Tulip are doing are quite exciting to see. Modular, no-code, low-code. So yeah, it’s great to see the kind of industry evolving as Industry 4.0 evolves as well.
Dr. Gilad Langer: Yeah, and again we have to think about it. It really is more than an evolution at this point. This is a paradigm change. I wouldn’t call it a revolution because it’s not. It’s not driven that way. But we’ve come to what some people call an inflection point where something in the industry as a whole is changing version or changing at a rate that is more than 10x what’s going on. And it is at the core of what industrial revolutions are throughout the history. These industrial revolutions, when they came through, they brought with them an order of magnitude productivity increase. And that’s what people are after. It’s not the technology, really. If you talk to executives, why this interest, if you will. And it goes all the way up to the World Economic Forum. And you think, why would the World Economic Forum be so interested in Industry 4.0? It’s because of that productivity, that order of magnitude productivity gain, which means financially it also has implications. And that’s what the executives are after. So I use that as a measure of when you say, is this technology truly Industry 4.0 technology? Really, the answer to the question you should ask is, can it bring out an order of magnitude productivity gain in my factory, in my line? If it can’t, it’s not Industry 4.0, regardless of how many buzzwords the technology comes with.
Daniel Langley: Wow, I mean, that’s a really interesting perspective and that’s not something I’ve heard before, so that’s really interesting. Thanks for sharing that on that front. Where my train of thought was going with asking you Gilad is that you’re the industry practice lead. Firstly, what does that actually mean?
Dr. Gilad Langer: Yeah, well, I do a number of things for Tulip. So, industry practice lead. Really, it’s a new technology, it’s a new paradigm. People are not just going to wake up one day and adopt this. You can’t throw in an iPhone. If you’ve been using a flip phone all your life, and you throw in an iPhone, you need a bit of guidance in it. Because, again, why would you use an iPhone? It’s completely different. Again, it’s an order of magnitude productivity, an order of magnitude different way of thinking. Once you know how to use an iPhone and think about this one, it’s like just writing a text. The ability to write a text or transcribe a text is so much different and gives you so much more value, right? So, industry practice is really the collection of all the expertise that we have within the company, both experience with the industry but also expertise with this. And we bring this to our customers because we understand this is a paradigm shift, and nobody’s going to go, ‘Oh yes, I’m going to throw everything out that I have and put this new stuff in.’ So that’s really what it is. It’s a change agent. It’s a way to bring this to the industry, but also bring industry knowledge back into the company. You know, things like Lean and production control, and how you run a factory, and how you do sampling, and all the other stuff that goes into that. That’s not going to go away. These are practices that, regardless of technology, you need when you run a factory. So, that needs to be brought back into the company as well.
Daniel Langley: Okay, now that makes sense, and I guess a big part of any business at the moment is educating the customer and making sure they’re understanding the steps needed to digitally transform. But again, where does that line cross from someone like yourself then, between listening to the customer and understanding what they want and what they think and what their journey they’re on versus you bringing new technology or disruptive technology to them? Where is that middle ground?
Dr. Gilad Langer: So,any of these types of changes — they don’t happen discreetly. It’s not like one day I wake up and I’m all transformed. It’s a process, and it takes time. When you do traditional product management, you go to the customer and say, ‘Okay, Mr. Customer, what do you want?’ And then you go back and say, ‘Oh we will build this into the product.’ Now that works good for retail because you observe somebody on how he, I don’t know, shops for shoes, yes, right? And that’s not going to change a lot. But manufacturing has been more complicated, right? I mean, if you take a look at any manufacturing plant, there’s people that have at least a four-year degree in something. It takes some time to understand how to run a plant. It’s not like buying shoes, right? So the complexity is much more there. And then, at the same time, you can’t go to a plant that is even, I would say, advanced and say, ‘Hey, what do you want of this new technology?’ if they’ve never seen it before. And I equate it … because if you go to some remote village in the Amazon, and you bring with you … do you know what a Yugo is? You know the Yugo cars? You bring that to them and say, ‘Hey, guys, this is the best car in the world.’ Of course, they’ll say yes. They’ve never seen a car before, right? But that doesn’t mean that’s what fits, etc. And that’s essentially what we do. It’s like I said, ‘Okay, guys, we understand that you’re running your plant, but there are, so what if we could bring this technology and it could do this for you?’ And that’s kind of an eye-opener. Oh, okay, we haven’t thought about it that way,” and then we start the discussion there.
Daniel Langley: Okay, now that makes a lot of sense. And that feeds on to my next question. I know you spend extensive time within pharma, biotech, regulated manufacturing, but do you see a different industry shift between which industries are maybe more a little bit open to change and open to adopting some of the industry 4.0?
Dr. Gilad Langer: Yes, of course, and this is the age-old adage that in order to have change, you need a crisis for change. Now there’s plenty of examples of that. So industries that are doing well, and I equate the crisis to profit margins, right? So industries that are doing well with healthy profit margins, they naturally will not have a hard time with change. So what we see is that actually industries where the profit margins are low, they are actually much more open to adopting change at a faster rate than industries where, so let’s take life sciences, even within life sciences. We went through the pandemic, and they’re making good profits right now. And so it’s funny because they are at the leading edge of finding new therapies and new ways to create things. But when you say, ‘Hey, let’s put in some new technologies in your manufacturing plant,’ they go, ‘No, we’re doing well, thank you.’ But then if you go to a producer of antibiotics in a third world country with heavy competitive pressure, they’re very open to change. And I think you see their crowd. So, food and beverage where profit margins are very, very thin, CPG. Some assembly introduced like a retail assembly that’s electronic or something, they’re open to that because they have their profit margins are low in a heavy competitive space. An industry where they’re highly automated, for example, semiconductor, there’s more resistance there to change. So it really depends on the industry. You have to look at it from a kind of a profit margin, competitive pressure type of scenario — where the crisis is.
Daniel Langley: Yeah, that makes sense. So, in some respects, it’s almost counterintuitive as well, isn’t it? The whole ‘things are going well, so we don’t need to change.’ I’m sure that’s what the automotive manufacturers thought as well for a long time.
Dr. Gilad Langer: Yeah, exactly. Well, there was a crisis there for sure, and there are many examples of that in the third industrial revolution that came about. And I would equate that — it’s a combination of the Lean movement together with the advent of the PLC. You know, the American car industry was in crisis. They were getting beat by the Japanese, and they had to change. So the semiconductor went through the same cycle in 2001, and it’s one of the most advanced, highly automated industries in the world … Lean industries in the world right now. But that was a crisis that caused that.
Daniel Langley: It’s an interesting one when you take that step back and look at the bigger picture, as you say, from the crisis and those companies that are on that curve versus maybe not. My next question was going to be around some of the common challenges that you face. So someone like yourself and kind of educating the customer, but also kind of relaying a little bit of some of the adoption that they want to have. Is there a common thread and theme on the kind of challenges that manufacturers are having that you’re seeing?”
Dr. Gilad Langer: Yes, there is, for sure, and there’s also an industry perspective. So there’s this, I’m going to try and generalize. So the whole notion of democratization is a bit, is hard for them to grasp. It’s intuitive in a way, but we’re so set in our ways and the way we operate with integrators, etc. If you want to put a new machine in, you call your supplier and your integrator, and they come in, they put a turnkey and go on, right? If you need to change something, you have to go back to your supplier to change it for you. Now comes this notion that, well, you don’t have to. You can actually build these automations yourself. That’s surprising. And then, so there’s a bit of a mindset shift there as it comes around. Paper is still pretty prevalent. The transformation of paper to digital is still problematic. It was problematic in Industry 3.0. People have to get their heads out of the paper or out of the Excel sheet. I think that that’s pretty relevant from that perspective. But the other things are things like augmented reality, the use of vision cameras. Sometimes I even get surprised just by the fact that people think it’s so expensive. So you would say, ‘Well, why don’t we put a sensor on the line or the camera to look at something?’ And the immediate reaction is, ‘Well, like three, four thousand dollars. We need to go buy something again.’ No, you can go on Amazon at sixty dollars, and the sensor, I think, is $13.
Daniel Langley: Okay, wow.
Dr. Gilad Langer: And there’s a bit of like, ‘Well, no, but that’s not industrial grade.’ And yet, yes, it is. Actually, you can use it, right? And it’s a mindset. There’s a whole mindset shift that goes around how easy it is. At the bottom, it’s how easy and how you do things. But it’s also a very, very easy way to prove value because that’s an order of magnitude productivity gain. The fact that it’s automatically cheaper and order of magnitude faster to get to the point where you can get value, that’s the order of magnitude gain. That’s what we’re looking for. So that’s a way to check if technology truly is Industry 4.0.
Daniel Langley: I mean, that’s a really interesting one. And most companies would assume that you’re going to charge, as you say, five, six grand for a sensor or a camera. And when you highlight for such a small amount, you can really start to see some return on value. That makes a lot of sense. Yeah, can we talk about … sorry, go ahead.
Dr. Gilad Langer: I’d say I just want to bring another example when, if you recall, Scalar Systems when they came around, the Wonderwares of the world, that story. It’s kind of similar to this. They put these industrial systems on Windows computers, which were cheap at the time. Before that, you had to have dedicated systems and advanced system. And there was a sense, again, of the same scenario. It’s like you cannot put an industrial system on a cheap computer, right? That was what they were saying.
Daniel Langley: The received wisdom!
Dr. Gilad Langer: Yeah.
Daniel Langley: That makes a lot of sense. Sometimes we do associate cost with value, don’t we? So we naturally fall into that pattern. One of the things that you mention is the order of change magnitude. That makes a lot of sense and I’ve not really thought about that much before. But when you speak to customers, is that a really easy way to identify whether that business is primed for a digital transformation or whether they’ve got the right change mindset, whether they understand that?
Dr. Gilad Langer: No, I mean people matter, right? Of course. And that’s what we say, but when you look at how Toyota talks about change, they classify the groups and the distinct groups as the early adopters, which we all know. Those are the people that like technology, are going to adopt this and they’re going to bring it into the mainstream, which is the people that are going to adopt the technology but they’re just kind of in the middle, and there’s the majority. Of course, then on the other side, there’s what they call in Lean speak the concrete head. People are never going to get it. So, really, you have to understand that mechanism. You have to understand who you’re talking to, right? And you need to identify your champion and your change agent, the ones that are going to carry it. And then there’s this notion of bottoms up versus top down. One of the things that characterizes these new technologies is that they are kind of grassroots, bottoms up types of things. A process engineer takes something, quickly shows value, loves it, he’s your champion, he brings it up to the mainstream. But then you get this top-down motion. Okay, this is technology, this is IT. You get the corporate people coming and saying, ‘Can we really use it? Does it fit our architecture, our structure? Would it really show value at scale?’ And you really need to manage both of those if you want to get into a company and be successful.
Daniel Langley: Yeah, and I think that’s one of the hardest things, isn’t it? To really kind of identify those different criteria where you maybe score a customer of whether they’re ready for that change and how efficient they’ll be at adopting that change. Because the saying is, you can only lead a horse to water, and if that mindset isn’t changed, you can include all of the tech that you want, but if the operators, the people using it, are not ready for that change, or not educated on the benefits of that change, you’re not going to see return.
Dr. Gilad Langer: Exactly, and that’s what we’re after. Nobody can argue when you show success or show value. We see a lot of people picking a process engineer, finding a technology, finding Tulip, doing a little pilot, a little app that shows some level of improvement. Maybe defect tracks a few things and show some correlation. It goes up to a super manager, and once you get there and unmanaged, you can see, well this guy spent very little. I didn’t have to pay anything yet, right? Because you pre-trial, or maybe you paid for some small subscription, and he should add value quickly, you can argue that that’s what you’re looking for, right? You need to come back and say somebody did something, and it showed value. That’s what works in manufacturing. We can’t get away from it.
Manufacturing is all about improvement and optimization, and that’s the name of the game. And if you don’t show that, then you’re dead in the water. And that’s where traditional technologies have failed because they could not very quickly show value. You had to do a top-down approach, put the whole system in. You have to go through the whole ROI, and capital expenditure process and show that you’re going to do it. Then you have to wait years until you come back, and then in that time not necessarily show value. And that’s why it fits Lean. Lean is all about that. Do your Gemba walk, identify opportunity, change it, show value, build on momentum. The new digital technology is aligned to that methodology. And that’s why they can be successful. And if they don’t align, again, it’s another way to check. If they don’t align to that methodology, well then you really have to question whether this is truly game-changing.
Daniel Langley: It’s really interesting. And I think for me, one of the real things that I keep hearing is that time to value or speed to value because it’s so important these days to have that acceptance of whether this investment is actually going to return something, rather than wait 18 months, 24 months for a monolithic system to be installed, implemented, up and running. Can you get that quick return to get the buy-in, right? What I was going to say also, the natural shift as well is where the population is shifting. You’ve gone 25 years in your career where you started before when these buzzwords — now work buzzwords — they were long academic words. So, what are you seeing now in terms of the workforce that you’re working with? Is there a mindset shift, a culture shift to adapt to the latest technologies?
Dr. Gilad Langer: Yes, for sure. Everybody talks about Workforce 4.0, the fact that the young people are digitally native. They expect some of these technologies. I think the problem is that the young people have not made it all the way, if you will, to management. Some have, and there’s a transition, of course. It much depends on the company that you’re dealing with. And I think the bigger risk right now is that this young workforce, as they come to these plants and start looking at how things are done, and they’re meeting these archaic systems. Firstly, they don’t even know how to use them. And then they get told, ‘You have no choice; you have to do that.’ So it stifles innovation. The fact that you have these old technologies that you have to adapt to stifles innovation. And people very quickly get into this manner of like, ‘Okay, I’m going to work with this ERP that is archaic, and I have to do all these weird things to get stuff.’ And then within six months of that, they’re used to doing this, and they get stuck. They’re basically getting into the groove. They’re stuck in that big hole, and they have a hard time to get out of it.
Daniel Langley: Yeah, and the challenge I see is that, yes, coming into technology, that’s the sexy world to enter for a lot of people entering the workforce. But being on the manufacturing side, the shop floor, the dirtier side of the business, having that experience is so critical. But how do you get people away from sitting with a cool iPad to them being on the dirty concreted floor of the business?
Dr. Gilad Langer: Well, the question is, do you have to? I mean, I think that’s the problem. The fact that you are, you tell them, ‘No, leave the iPad outside and come to the floor.’ This is a story that I typically tell. It’s based on a real-life scenario but not to this extreme. But you have the plant manager that drives into his plant with his Tesla, parks that, charges it, right, has all it’s connected to his phone and his watch and the wearables and all that. He walks into his office it’s all “gadgety”. And then you walk up to him and say, ‘Why don’t we put some of this stuff, some of this technology on your shop floor?’ And he’s like, ‘No, that’s untested.’ You know, they’re afraid to put them in. And why, if you ask? It’s because that’s not what he’s measured on. He’s not measured on the gadgetry. He’s measured on the plant, whatever it is, adhering to the schedule, keeping the volumes up, making sure that he can produce the quality. And if you bring your gadget in there and they go, ‘How is that going to impact that? Is it going to bring me so much more quality that I’m going to take the risk to put in something that I’m not sure about?’ And that’s the issue. So, if you can prove it, and that’s what I’m saying is, like, we don’t need to transform the whole plant to be like Tesla. We can just start somewhere small and show that it does work, and then we can go from there. That’s low risk, rapid time to value, and that’s what plant managers want.
Daniel Langley: That makes a lot of sense, and I can really envisage that, and I guess you’re going to have that on you, where some people in there, maybe in other areas of life happy to adopt technology, happy to accept that it works, de-risk, but then when it comes to their shop floor, they’d maybe be a little bit nervous. Now that makes a lot of sense. So, one of my questions next, Gilad, was going to be that you’ve been in that really nice part of the world where you’ve worked with the technology companies, but then you’ve also been a consultant, and you’ve led engagements and stuff. So with so many companies offering digital solutions, digital transformation, Industry 4.0 solutions, how can a company, a manufacturer, identify the right partner? What nuggets can you share with the audience who might be sitting there on the manufacturer’s side thinking, ‘How do we see the wood from the trees with all these companies selling Industry 4.0?’
Dr. Gilad Langer: Yeah, exactly, and it’s really hard. So when these technologies come about, there’s a huge opportunity, and this huge opportunity, a lot of startups, a lot of people trying different things. So it’s like springtime. Well, I live in California, so in Spain, we have like a spring that all the flowers are up, like, yeah, it’s everything is coming out, everything is green. How do you pick the right seeds? How do you know how do you… this is really hard. And this is without a doubt. There’s a few things I think at a high level that you have to think about. First of all, these are emerging technologies, so the solution, trying to find something that is tried and tested, forget about it. Okay, I actually have to think about it in a way that I want to test and try as much of this new technology as possible. So, what you need to do is in the company establish a way where you can continuously evaluate these technologies, whether they’re going to bring you value or not. And not just go, ‘Oh, we’re going to go — and again top-down, Industry 4.0 — we’ll do an Industry 4.0 roadmap. Here’s the technologies we’re going to go with.’ But it changes so fast that as soon as you put that roadmap together, it’s already obsolete. It’s already legacy because you haven’t even encountered some of the technologies that are maybe coming down, improvements that your existing technology vendors are going to have. So, it needs to be a process of continuous evaluation of these new technologies and how they fit, how they gain, how you can bring value. That’s one. The other is that there’s some, as I and I mentioned a few of them, some very simple rules that you can put in place in terms of evaluating whether these truly are going to be beneficial. And the first of all is that, is this notion of bottoms up and high value. You need to be able to show value very quickly in a specific area. Go do a Gemba walk, find a place where you… there’s a problem and say, ‘Okay, all these technologies that I’m evaluating, which one will be a good fit for this? Evaluate them, see if they bring value very quickly. If they have this ability to align with your Lean process or this continuous improvement process. Then there are two other things that I usually use to classify whether. The first one is democratization. Does this technology bring around democratization? Can a process engineer, quality engineer, supervisor, operator use this technology out of the box? Think about an app on your iPhone. Like, I have with my kids. First of all, they have multiple apps, and you probably also do, multiple apps to do the same thing. You don’t have to have one; you can have many. And how do they check if it works? They’ll download it from the app store or whatever player or app you’re using. If they can’t learn how to use it within the first 30 seconds and it brings them value, it’s out. It’s the same process. Like you need to be able to use this, understand it, etc. You can’t just, ‘Oh, you need a week of training.’ That doesn’t work. So that’s democratization. The other one is this notion of bottoms up. You need to be able to use that technology, isolate it in a little piece of your plan. If they come back and say, ‘No, we need to install the system. You need to create all this master data. We need to connect to ERP and bring data down. Otherwise, we can’t configure it properly.’ That’s not a bottoms-up type of technology. Simple rules like that will help you weed it down to really some of this. And of course, the use case itself, right? If you want to help the operator to do the right work instruction type, that’s a different thing than capturing data about the performance of the machine versus capturing data around whether we are executing and adhering to schedule and other things. So, it needs to fit all these different use cases.
Daniel Langley: I think those are really good nuggets of wisdom, Gilad, so thanks for sharing those, and I think those would be really beneficial to companies trying to identify the right partner from — I don’t know — the cowboy?
Dr. Gilad Langer: Yeah, yeah, I think there’s a lot of rebranding we have to, that’s kind of what you have to watch out for. Again, everybody’s trying to ride the wave of Industry 4.0. You can take your Yugo and put one of these kids on them and make it look like a Ferrari. Yeah, but you have to kind of scratch the paint to see that truly it isn’t, right?”
Daniel Langley: No, I think that’s a fair point. And this leads on to my next kind of question. One of the things I keep hearing, I mean what I’ve seen the last couple of years, and probably you’re the same on LinkedIn especially, is the rise of these Industry 4.0 influencers, these manufacturing influencers. And one of the things that I keep hearing is that manufacturers need to become data companies. They need to harness their data, they need to harness their insights. So naturally, there’s this natural kind of conversation now about how do companies harness their new data? Where do they start? Which data is important to harness? What are your thoughts on that whole kind of data companies manufacturing, etc.?
Dr. Gilad Langer: Yeah, so that comes from the core of Industry 4.0. So, the Industry 4.0, as it was framed up in Germany, had these maturity scales, the six stages of maturity. And if you really read through that, you will see that it has to do with being able to gain insights from your data. So capturing data in a way that you can create. But that’s only one dimension, right? So the data is one dimension, the other dimension is this human-centricity and this bottoms-up. It’s not enough just to capture data. You also have to bring in the human. If you take a look at digital technology outside of manufacturing, the example I usually bring is Uber and Lyft, which I’m sure everybody knows. You know, what is Uber and Lyft, if you ask the question? Uber and Lyft, by the way, and many more, I think now there are many different variants, right? It’s actually a taxi service. Under the hood, it’s a taxi service, right? So what’s different? Because, so, comparable to manufacturing, you have a line that produces something, that’s the taxi service, right? It doesn’t change, it needs to do that right. The difference is two things, and then I’ll bring it back this. First of all, it’s democratized. Why is it democratized? Everybody can be a taxi service provider, and everybody can be a taxi service consumer. So democratize the taxi service. And how did it do that? Well, first of all, it makes it easier for humans to consume the service, both provide and consume the service. If I want to be a taxi service provider, I need to get an app, I need to fill out a questionnaire, they do some checks, and off you go, and you need a car, by the way, okay. And sometimes they’ll even provide the car for you. So they’ll actually lease the car for you. So that’s from a provider perspective. From a consumer perspective, I just need a smartphone, right. And then they go, ‘Okay, so that’s the human part of it. It’s not enough just to have data. Of course, the data comes in because, guess what, how do they find how to dispatch a taxi to you? Well, they have all the data, the GPS data, they know this, they have algorithms to run. It’s not who is the closest, it’s how fast can they get to you and your preferences as well. That’s how they use the data, right? But the data means nothing without the context of the human who’s going to consume it and what we need to do with it. So reading through this, like we’ve been collecting data for the last 30 or 40 years. We have historians and systems and all this data. Can you use the data for something? No. So you can’t just say, ‘Oh, we have data.’ It’s not enough. It needs to be in a usable format where you can actually find the benefit of having that data. You have to ask the ‘why,’ what is it going to be used for in the context of the human who’s going to consume and make decisions based on it, right? So, again, it’s all about performance. Is the data going to give you an order of magnitude productivity gain? Just having the data is not going to give you any productivity.
Daniel Langley: I think that’s a really good conversation there, Gilad. Thanks so much for taking the time to share your insights. I think what we’ve got there is a lot of nuggets of wisdom that hopefully the listenership can really benefit from. So, I appreciate your participation. Thank you.
Dr. Gilad Langer: Yeah and thank you for having me on. It’s been a pleasure to get to express my views and share them very openly.
Daniel Langley: No, good stuff. Well, thanks, Gilad.
Dr. Gilad Langer: Thank you.
