Podcasts > Operations > Ep. 086 - End-to-end smart factory design
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Ep. 086
End-to-end smart factory design
Thomas Rohrbach, Co-Founder, Staufen Neonex
Thursday, April 29, 2021

In this episode, we discuss diverse forms of smart factories, common process changes and people challenges related to smart factory implementation.


Thomas is the Co-Founder and Managing Director of Staufen Neonex. STAUFEN NEONEX is the consulting and qualification company for the digital transformation of the industry and B2B companies. STAUFEN NEONEX develops and implements tailor-made strategies and pragmatic concepts to accompany those responsible in the fields of mechanical engineering, automotive and aviation on their way to peak performance. staufen-neonex.de


Erik: Welcome to the Industrial IoT Spotlight, your number one spot for insight from industrial IoT thought leaders who are transforming businesses today with your host, Erik Walenza.

Welcome back to the Industrial IoT Spotlight podcast. I'm your host, Erik Walenza, CEO of IoT ONE. And our guest today is Thomas Rohrback, Managing Director and cofounder of Staufen Digital Neonex. Neonex provides end-to-end support for manufacturers that seek to gain a competitive advantage by digitalizing their processes and operations. In this talk, we discuss diverse forms that a smart factory could take based on the underlying business requirements, and we also explored common challenges related to technology, process changes and people that should be anticipated prior to any smart factory project.

If you find these conversations valuable, please leave us a comment and a five-star review. And if you'd like to share your company's story or recommend a speaker, please email us at team@IoTone.com. Thank you. Thomas, thank you so much for joining us today.

Thomas: Erik, thank you very much for your time, your opportunity, talking about the smart way of doing operations. Thank you so much.

Erik: Thomas, before we get into the topic, I want to just understand a little bit more your background. Can you just share the path that led you to cofounding Neonex back in 2017?

Thomas: Thomas, I actually studied mechanical engineering decades ago more or less. This mechanic engineer was a little bit boring for me at the time. And I started a parallel full time engagement as project manager in a OPEX project footprint optimization topping in Germany, SME, and this helps me to survive and was experimenting and get involved since my person that time was not so eager to travel internationally. So get very much even as a student actually been involved in business in India and China at a time was quite nice.

Later, I had an MBA and manage this global manufacturing footprint optimization unit, this actually allowed me to start gaining this international supply chain production network experience quite early. I'm an operations-focused pragmatic person and looking forward making the business smarter and the operation smarter.

Later, I joined the Staufen Consulting Group, in that time, or starting in total more than 50 bigger factor in transformational project to combine the several existing proven success factors, especially when after joining China, I stayed in Shanghai for four years before that I traveled intensively. So China, Asia is our joint footprint track records, and especially in China, because here, the keenness on automation technology is a little bit higher.

As in Europe, that's why I was able to combine here the lean management OPEX principles with automation IT and technology and this was really nice. And one of my personal lighthouse projects here was this planning and implementation and launch of these. In China, you have this giant wide good factory, everybody knows starting with an H. But for them with their huge team, we build up this connected refrigerator factory in Shenyang, and this was a really busy time. But here we had chance to cling all our concepts and ideas and all things together.

For me it was like the ingredients of the chef menu where we can really combine all the best things of the different worlds and to forge something new in this kind of factory. After this serve project, I'm returning to Germany, in that time this industry 4.0 initiative has been born. And we then decided to develop and own practice out of the Staufen Consultancy. And we founded this Staufen Neonex here and develop Neonex further becoming the real driver for smart factory and connected supply chain.

Erik: They're certainly one of the more ambitious companies in terms of digitalizing their operations. I imagine you're also working a lot with the larger automotive OEMs who are also. Is this quite typical for you to work with companies that are leading in their industry in terms of adopting these technologies? Or do you also work with medium sized companies that are maybe approaching this for the first time, significantly lower level of maturity? What is the spread of the customers that you serve?

Thomas: Actually, it's like that, we are on one side of the digital world. We are working for the pioneers, for the most advanced companies as one of those and others as well, where we really need to get up and involve all the most modern technologies and solutions. On the other side, the daily business is also sad to say is to start on a different starting point. In some cases, the starting point is let's say 20 years over-aged IT infrastructure.

This is then different starting point where we need to take the people from where they started off and develop step-by-step starting with use cases in between. So those two extremes and everything in between is possible. And that makes it both very interesting for me and all my team, and on our side, also challenging, because we need to focus our way of communication on the client situation. We cannot expect that everybody's on the same level. And that's why actually some of them ask consultants for support, it's actually also part of our role we are playing

Erik: I think it's quite interesting that you set up this new entity, this Neonex business adjacent to the traditional Staufen business. What's the differentiator? What's the value proposition around Neonex that would differ from other consultancies that work with manufacturers in the market?

Thomas: What I get feedback from our clients how we are perceived as that our holistic end-to-end approach and syncing and discussion with our clients and our concept what we're doing, and this combined with our pragmatic focus on the client's benefit. That's what they like most now.

They need somebody for the big picture, for the vision. And for this vision, we are not focusing on several verticals. We have holistic end-to-end view of the today's situation and then starting from there with defined improvements and potentials, and open their eyes. And since we are coming out of operations, for sure, we like also all these tech catches and stuff and modern stuff. But at the end, we’re only proposing and put solutions or concepts on the desk, which brings immediately measurable benefits.

So that means combining both those strong process knowhow out of this OPEX best practice world and combining this with the new possibilities out of this digital industry 4.0 aspects automations or this combination this makes what I heard what makes us a little bit unique now.

Erik: Let's maybe look at this from a different perspective, which is the question of what is a smart factory, so what might the vision be as a future? I think it's a little bit of a challenging concept because, of course, you can think of a smart factory as a factory in a dark, which is basically completely automated system. But almost probably almost all companies that's certainly not practical today and probably not even practical 20 years or maybe even 50 years in the future. So how would you define a smart factory? How do you help companies to think through? What does smart factory mean for them?

Thomas: A smart factory at the end or interconnected factory or intelligent factory, you name it, I mean, hundreds of different keywords behind, but at the end, we are talking about increasing competitiveness. And what does it mean? This also depends on your individual business model and what are the key factors in your business. But normally, industry, it is for sure, costs down, quality up, responsiveness and all this stuff, we don't need to dig deeper.

For us, at the end, a smart interconnected intelligent factory is the best possible combination and connectivity between people, technology, and IT. That's our definition. And at the end, this is very much appreciated by our clients, because we cannot assume that dark factory without any people will work out. I mean, in Germany, we made some bad experience 20-25 years ago with this approach, 100% automation rate. I know in China, this is the very attractive goal behind.

At least one thing is very nice on this really big vision forward is you get challenging task and a lot of inspiration for your milestones in between. For us, the characteristics at the end, what does it mean this smart connected intelligent factory, the characteristics are okay, a higher degree of flexibility, agility, collaboration between the people, peer-to-peer, peer-to-your managers, peer-to-machine man collaboration. We talked already about this mass customization and big idea behind is to become able producing batch size, lot size one, that means you will get your refrigerator with your individual designed for on-door and your trays according to your wishes and your pictures and your gimmicks and slogans on it. And all this means batch size, lot one for the prices of mass production.

So, this is a little bit the big overall target behind. To get this, for sure you need to self-regulated concept that you cannot manage this decentralized changing by central computing system or central managing systems. You need the decentralization and self-regulation. It must be efficient, otherwise you don't get this done, and connectivity connected horizontally, vertically. And since we are here talking about digitization, we talked about digital connectivity.

One of the biggest advantages or things to be done is that your team, the whole organization have to be becoming a learning company. What does it mean? Failures are clear and will be made, and it is here very much important that you allow that your team is able to make failures and fail fast is one of those important philosophies behind, allowed to fail. But if you have to fail, you fail fast, and not after three years designed the new superduper ERP or PLM system. So that's a little bit the main.

Basic behind and from since we are talking about operations today, those lean processes, this is for us the foundation because you need to somehow a standardized stable environment before starting with digitization. And lean processes will help to get started. And all those technologies that in between talk about AR, VR, manufacturing in-cloud and edge computing, this is all very important, but those are enablers. Those technologies stack have to support and enable what I just talked about. At the end, it helps to develop a more comprehensive, value-driven approach for what we are really doing it.

Erik: This topic of fail fast, I think, is interesting, because it's maybe particularly challenging to apply to manufacturing

Thomas: Especially to engineers, they are decades long trained not to fail. They should be precise, and this and that, and after weeks they come out of their engineering office with a brilliant idea. But unfortunately, time changed, and now they should become agile, and design thinking, and user-centric. And for sure, for four generations of engineers, that's a big challenge, absolutely.

Erik: Because if we think about the problem of mass customization, for example, you could think of failure from at least two perspectives. One would be is this actually a strategy that will improve our position in the market? And that's more of the customer perspective. You can offer that as a service, you can see how many people actually buy the service, and then in the back end you just manufacture things by hand or in a non-automated way just to deliver those first.

But then when you say, okay, we know there's market demand, now we need to build this, then you get into CapEx investments and even quite complicated systems, how would you approach fail fast scenario once you make the decision that the market demands this, we want to provide this service but we're not quite sure the right architecture or the right suite of technologies and processes to bring this, how would you apply fail fast principles there?

Thomas: One thing we already talked about those isolated somehow protected areas for the team defined use case following one topic in no vertical. So the risk that you destroy your whole supply chain is limited. This is somehow like in [inaudible 17:38], you can manage it, you can observe it, you can check the results and get your proof of concept rolling out.

One proven concept and coming to the IT, I should take care of the whole stuff. The big topic is that we need, we cannot change this monolithic existing legacy systems. So when you have two, three options, the first option is to just buy some out of the shelf solutions, use case solutions, also known on your platform, you can see hundreds of them, Erik, you can identify, figured out, install it and make your experience prior investing millions in your big solutions.

The second topic, and that's what we are preferring is to get micro service based application platform. And the idea is behind that step by step use case by use case. These new features lead to a growing micro service platform and a monolithic system will be used step by step over time. And we believe how you can manage both speed on implementation and transformation speed, on the other hand, have a step by step development of your IT architecture.

Because somehow the key question here is how do we create a legacy monolithic application into a micro service application architecture? So that's actually one of our favorite approaches, because it's very low risk, and the customer can make their experience, can develop their team, and this is the open, easy to roll out and easy to develop further platform. Low cost, very quick and even so all the known cloud services you can also roll it out to the whole company within hours or days.

Erik: So maybe you can show your perspective on how the IT infrastructure of the future or how the a modern IT infrastructure should look. So I guess the traditional would be you have a scatter that manages how different pieces of equipment operate, then you have an MES that coordinates across the factory processes, and then you have an ERP system that manages more organization level data, but maybe production people are generally my experience not really allowed to touch ERP very much. And if we now talk about platform in this composition, where would that fit? Are we adding a new layer to the IT architecture? Are we replacing the MES system with a more agile platform that can perform that functionality in addition to other functionalities? Or how would you look at where the platform fits into the traditional infrastructure?

Thomas: After you make your first experiences and your proof of concept, and this platform has been somehow accepted or the result is services, business-driven, value-driven services, yes, this is then an intermediate level and platform. And you have both the flexibility of adding solutions and services according to the business need. And for sure, we need these integrated interfaces to your existing monolithic ERP or PLM system, and this first one must be ensured.

All the data should come from one source, no doubts on that. The production operations people are not allowed to make too many experiments here. Because if you are in R&D or in your laboratory, and you'll fail, okay, it's part of the game, you have failed fast. But if you fail any operations and your whole daily business, your whole supply chain is shut down due to some stupid interface problem, you'll really have big challenges.

So that's why to have this platform based micro service cloud native application based level, this is for us, a smart solution. For me, it's like a Lego for the industrial IT landscape is deployable on any cloud provider or premise. And all the standard tasks you need to manage, you do it once all these ID access management center locking and monitoring system disaster recovering, all this can be done in this intermediate platform.

That's why you have ones your corporate it in the ERP guys on board normally very quickly, because they feel okay, we can somehow provide both the safety, and on the other side, the better ones understand, okay, our operation need more flexibility and more UI focus tools and this kind of stuff. And that's a reasonable good approach from our point of view, very much appreciate it.

Erik: How do you see the IT organization of all the [inaudible 23:37]? Because traditionally, many IT organizations have been more or less maintenance functions to an extent or deploy something and then maintain the system. And I feel like here we're asking them to be quite a bit more innovative in terms of thinking of how things could be done than they were in the past. And IT is potentially becoming much more of a strategic topic than it was 20 years ago or even 5 or 10 years ago. Do you find organizational challenges here in getting it to come on board or figuring out what their role is versus let's say manufacturing engineering, or is this typically a smooth communication for you?

Thomas: Here we also see the traditional old organizations and the new ones or the modern ones. But the IT functionality or the IT management, actually they are like the new pool docks. Because as I said in the past day, they were really [inaudible 24:39], IT is not so much focused only if email server broke down. Only when problems occurs, the top management get notice of and give them a call, but there's never this thing as a value driver and this now changed. Especially in case your top management is aware of the potential of modern IT system as part of the important infrastructure, you're not talking about robots and this is for sure, this was the old last 20 years very important and will be important tool in future.

But now those connectivity, those 5G, all these tech enablers we are talking about, this needs to be somehow operated and run. And here, we need new managers, it's like you need IT managers who can build a bold and big picture and coaches like spelling part of the top management, and not like administrators get me what you need, and I make it happen. No. They really must become a takeover this new role. And they are now asked to be here, the new business driver, but actually they are not, because they come from administration or also many of them.

And then some companies than hiring new guys, Chief Digital Officers on the transformation officer or some flaky gentlemen or ladies, and then they have their own word and playing around with the new passwords and the new technology and the evidence. The legacy team, they have to keep the old stuff running, and this gap in between is huge. And that's a big challenge to prepare the existing organization to take over this new role now, or to integrate the new big thinking guys with the traditional IT experts.

And this in their environment that in some cases the top management or the middle management is not so familiar with IT structure, IT architecture at all. So it is really interesting to observe how long management teams can have misleading discussions over hours, they have very intense discussion, but horribly mismatch the meaning, so it's amazing. Erik, big topic.

Erik: I see now a lot of large corporations, maybe not so much in the factory, but in other departments, everybody is hiring one or two data scientists. So every business unit, every function gets a couple of data scientists and maybe that decentralized approach works. It's then creating a new function, or a new confidence within all of these, but not so much impacted for IT.

On the technical side, Thomas, there's also quite an area of discussion, which is around traditional on-premise deployments of IT versus cloud versus edge. And I guess, for some people edge could even mean just a different type of on-premise solution, but I think it's still quite different in terms of how the system operates. In China, I guess we've seen, on the one hand, very strong promotion of cloud solutions by the government and also maybe some aspirational objectives by companies. But my feeling is the reality is that many companies are still not so comfortable with cloud solutions. Maybe in Europe and US, it's moving a little bit faster, but still some especially around public clouds, some concerns. How do you address the question of what should we deploy on-premise versus cloud versus a hybrid architecture with cloud and edge solutions?

Thomas: I mean, talking about Europe, China is different. Talking about Europe for sure you're absolutely right. And there are a couple of car makers around. Two, three years ago, if you just put the name ‘cloud’ into your mouse on their factory, you would be most probably shutdown immediately. So this is no go ‘word’, this is changing.

So that means the industry is becoming here a little bit more flexible. They don't say no from the very first second so they are open to discuss, they are open to learn to see and at the end, either, as you said on-premise, or hybrid private cloud that's in most cases than a solution which can somehow cover all the different stakeholders and make them happy that. At the end, the business driver get their solutions, they get their security.

And at the end, we have a system what does future entail and can be developed further. So that's actually how it can work. But you're absolutely right, they're still very traditional companies, no chance at all. Without central it, then you'll need weeks and months to get the concept and then any projects and then any resources. And three years later, they get started. So it doesn't make sense to talk about cloud edge computing with companies who have not yet defined starting point, this kind of openness, let's say.

Erik: And in Europe, among the more open companies, do you see also receptiveness to public cloud? Or is it pretty much then saying, okay, we can consider private cloud but public is still off the table?

Thomas: For sure, we have here a couple of these world market leaders and they are transforming also, and they have to transform. And they switch all their data center into cloud. They interface to client in public clouds. We know [inaudible 31:40], and all those big giants, they have everything, even the whole communication and file servers on public cloud is all okay.

And one thing I have to say, compared mainly to China, here the mindset is generally more conservative, and it takes time, but sometimes too slowly from my perspective. It's clear to everybody that is a big topic. And since the use cases and their competitors pop up with some additional value for the clients, they ask questions, then after a couple of weeks and months, let's see, okay, and then they are ready to listen, and then we can start, talk about the new architecture and what you need and so on, but has been changed a lot over the last two three years that's ongoing heavy.

Erik: So far, we've been speaking from the assumption that our company has decided to invest in digitalizing their supply chain or their factory. But if we take a step back and come back to the question of why, why do this? What do you find are the primary motivations? Is this related to rising labor costs? Is it scarcity of labor or high turnover and then looking for organizational stability by automating more? Or is it typically more around looking at new growth opportunities by, for example, doing small batch or mass customization solutions?

I imagine that you're often involved in these discussions, from a corporate strategic position, where do we want to be, and then, of course, it leads to discussion of how do we get there? But what do you find the more compelling reasons to even think about changing how you're operating today?

Thomas: As I said, Me and mostly all the operational managers, global supply chain managers, they are at the end pragmatic persons because they have to deliver and they have to deliver 24/7. So that's why I mean to gain competitiveness or profitability, that's for sure one of the key drivers. Either you are in difficult waters or high waters, then profitability is a topic, coming back to play even or for sure gaining competitiveness or just secure competitiveness. And this can be either speed, responsiveness, quality level for some companies is still a topic or just costs and this quality costs service level.

To a angle, this is still valid and if the solution or new concept helps them to gain here competitiveness, this very much welcome. And for sure, everybody's aware there's those disrupting changes within the industry, also own industry or they own customer expectation. That means this wind of changes in most of arrived and operations. They are aware that they cannot put use the next 10 years as they successfully did, by the way, in the last 10 years.

And they know that the former success factors will not work out in this so called [inaudible 35:30] exploding complexity. We also know all this innovators dilemma, this nice book from Christians in hand, this almost now touched base on all the producing companies, or the former very famous producing companies. And there's tremendous pressure to change the products, to change supply chain in their own operational model. This will lead to the motivation to move forward.

By the way, the operational organizations, they are used to transform. They did their automations in the 70s, they did the lien in the 80s, and 90s, and now the next phase. Big question is the question of speed, but here I believe, at the end, it's a question of competitiveness. And important is without any financial impact, they will not make any automation decision, and so on.

Mainly in China, but also here in Europe, the big idea also behind this automation and smart factory approach is to get rid of the people, because not only they are expensive, and so on and so on, but also because you don't have them anymore as situation in Guangdong, or here the demographic factor in Europe also lead to the point that a lack of specialists and skilled people will lead automatically to a higher automation rate. Even at the end either it's more expensive than do it manually. But if you don't have a hand, you have to take a robot.

Erik: Thomas, so I think it's been a very interesting conversation. Maybe we can tie this together now in one or two concrete cases. Would you be able to choose one of your recent projects and walk us through what a typical digital transformation journey would look like for Neonex, maybe from this initial conversation of why then through the discussion of how and finally into the actual implementation?

Thomas: Yes. For example, let's take another wide good industry case to also change on different continent, let's say America, and after the qualification of the management team, alignment, harmonizing of the understanding. And then condensing everything in a state of the art or smart factory or factory of the future boot camps, that’s somehow normally how we then come to the point and bring it to concept.

Starting from that point here, we then identified a couple of potential use cases based on some quick scans. And after boot camp, this has been transformed to heat map, and out of this heat map, you see, okay, what are the most attractive use cases for this and that in this company, or factory. Here in this case, we are still doing the transformation of two factories or plants and parallel each is amounts with 3,000-4,000 people. One is wide good [inaudible 39:02], and another one is washing, for example.

And just a few have a bunch of use cases and that case they didn't have the proper MES system, it turns out that 70% of the identified potential can be covered by advanced modern MES system. So, here we came to the conclusion that it might be wise and that's what also our advice to introduce a proper MES system, which allows all this use case like smart workstation that we have an advanced production planning and scheduling that we have here a modern and on escalation management behind there’s a rule [inaudible 39:48] sides automatically. What if this and this happens, what is the consequence and what is the workflow to get from this escalation management rule engine?

We have here something like quality inspection planning dynamically and digitized so that the inspection planning are dynamically adjusted to the results, so the statistics into the feedback from clients and the quality management systems, for example. And if we talk about asset performance management specially for environments where you have huge CapEx investments and machines and assets, that's a key topic.

Here in addition, we work on this digital machine parameterization where the programming will be done, so so MES and in the backbone behind. So, that's all the typical use cases handled by MES. In addition, we then use what we just explained as this layer for the micro service app and solutions. We have something like quality event visualization. We are talking about modern automation technology, collaboration about farming, where we are bringing in new technology, automation technology on the shop floor. Interesting is here talking about advanced analytics.

Let's say, for thermoforming and refrigeration industry, there are critical forming processes where you form the inner layer, for example, a wide inner layer. In your refrigerator, you can imagine if you open your fridge you see and this is deep drawn and here, this is a quite critical process. Especially if you produce the millions of then in a year, so you can imagine each send saving will lead to tremendous some.

And the different aspects of outside temperature, humidity, temperature of the plastic materials, sickness of plastic materials, a nightmare of other parameters need to be adjusted and this actually cannot be done without smart analytics and artificial intelligent here. We made a huge analytics works and the found parameters and influencing factors which are not yet known. And at the end, this then leads to a better deeper understanding on what's really going on and really combine this with the qualification of the team.

Supervisor, sometimes, quality engineers, process engineers, this leads to sustainability, this helps. Also, you can imagine those huge factories, this material handling is a nightmare, and they are hundreds of people transporting material. And if you use analytics to double check and to see and to optimize, this will help tremendously. And this shows in practical details, which benefits data analytics, manufacturing analytics can cling to the operations.

Despite the question Erik, as you said, okay, is this then data scientists locally or centralized and this and that, this is the next question. If they once understood, okay, this is a big tool for me, I need to have it embedded in my organization, then the question starts, okay, how my data analytics organization will look like in five years? How all the data management will be? Who's responsible for which data? Where's database? And all this question resulting all of that will follow. Energy management, all these use case mobile maintenance, so this is probably like my last topic here for this case.

Imagine this maintenance organizations you have 300 maintenance people, and they somehow need to immediately react after the machine broke down, especially assuming this is a bottleneck machine and the searching time for the right information to get back to their office, then the spare part management to spare part all in all, this can be tremendously, tremendously simplified and become more effective by simple digitalization. That's what we are doing now.

We are actually demystifying the digital transformation. There's some artificial intelligence behind, but we don't name it. It's not important what is behind. The question is asking the question why we are doing is and what we are going to achieve, and what do we need? And then this tech stack is providing the right solution on enabling this.

Erik: And in this example, just so I understand that Neonex would be orchestrating this end-to-end process. Are you also doing the data science, at least for the pilot phase or the integration of systems? Or do you do work either with the internal organization or with an external system integrator, or maybe a technology vendor that can also do integration? What is the team look like that's implementing this?

Thomas: For example, for all this proof of concept, let's say data analytics, we have our own data lab and scientists who run this with a client's team. But we are in a driver seat to make this proof of concept successful, and then handed over step-by-step to make our clients independent and get the solution sustainable installed.

We talk about MES for sure. We are in between the MES integrator and the client because some of the solution providers, they are going to install what is most simple, most easiest for them. But this is might be not the best solution for our clients, so that's why we are defining with the clients how it should look like and then make it happen with the integrator and to get install what is best for the client and what is not the easiest for the integrator or for the solution providers. So that's what we are doing closely cooperating and orchestrating these several stakeholders and solution providers.

Erik: And maybe you can be a little bit specific here. What are the trends that you see as being driven in the next five years? Are there specific use cases, specific technologies, specific priorities that you expect on the horizon?

Thomas: One of the major trends you can read about, that's why we are also talking about it's your focus, Erik, is Internet of Things, IIoT. But for most of our clients, it is they heard about, they have one, two, so use cases far away. They have a comprehensive understanding. So for this IIoT, digital twin is allowing for data transparency, and this remote management. This is, for me, one of the top trends in future to connect supply chain, also after this COVID disaster, the footprints will be reconsidered patchily, and risk becoming more important in the evaluation scheme.

Or especially in Asia, what I learned also from your podcast this is a top topic in Europe is also a topic it's not yet on everybody's agenda, but good topic. For sure, for me, automation will be one of the key topics for next the 5-10 years. Automation of either direct processes that means physical automation of handling, of assembly, of entering people, all this what you all know from this old Orange arms or the new call-up robots available.

And since these solutions are getting cheaper and cheaper and cheaper, it becomes more and more important and reasonable the application. So, that's why automation of physical processes, but also automation of data handling and data process. Mainly, if you have not yet an integrated fully automated system, you use RPR robot process automation what is known for a couple of years in this giant consumer-oriented company with 100 millions of data sets. But since this solution getting cheaper and more flexible, it is also becomes reasons but for the smaller or not smaller, but B2B businesses with lower numbers of data.

So that's a cool thing, which helps to speed up and to save some money. Mixed Reality, AR, that's a lot of experiments did in the past gaming industry support that. And now really bullet proof application use cases are available, and this will help to support this trend also within the operations in the next five years. On the other hand, we can talk all about those technologies. But as I said, the customers are indeed on different levels of these tech advancements now. Those are a couple of trends we see here from our daily business.

Erik: And how about for Neonex itself, are the new capabilities you're planning to build out in the coming years, new directions that you find to take the business?

Thomas: We are going to grow into the process industry. For sure, this data analytics to revenue consultancy is becoming more and more important for us. We have already cool and very efficient solutions, for example, data to even value stream analytics and design tool which helps us to come to the point very quick and don't need weeks of analysis anymore. Or we have analytics and simulation tool that based where we can simulate decision making for example, in supply chain. What is the result in inventory, and this combined with training will help it get sustainable.

So in short, this kind of data analytics and asset-driven consultancy, that's something where we will develop further, and to also become a little bit more to towards a scalable business model. Our job is not to be at a very front line of the pioneers. We are observing all those these tech trends. They use your tech radar, Erik, to help to understand what's going on. But it needs to have a certain degree of maturity and safety level prior. We are going to use this for our clients’ projects.

That's why this becoming now more reliable. And that’s why more IoT digital twins solutions, and more of these AI solutions, for sure, those are for next three, five years, our main direction, so where we develop further.

Erik: Alright, well, I'm sure we'll have some opportunities to work together then, I think we’re very much aligned here.

Thomas: Would appreciate it, yeah, for sure, Erik. Yeah.

Erik: Well, Thomas, for me, this has been a great conversation. Any last thoughts, anything else we should touch on?

Thomas: No, for my side. Thank you for your time, give chance talking, chatting a little bit about smart factory and this kind of stuff for the operations, having in mind. That's why sometimes operational people are presumably a little bit conservative. They are under this tremendous pressure. That's their main mindset to deliver every day and I. That's why it is sometimes not easy to get into this world. But I believe here, we also have a cultural change aside.

And if we use these tech trends, not just to push and to introduce because it's so nice and sexy and bling, bling, no, because it needs to bring really value to their daily life to their supply chain, then it is easier to get this modern things introduced. And then it's your job, our job, and integrators to build a new integrated framework to make their life easier. Let them bring faster value, more efficient value to their clients, and then everybody's happy. Our end users, you and me, also, end users and the producers as well. So that's our vision we all should work for.

Erik: Thomas, I imagine a number of our listeners are also kind of deep in this topic or assessing this topic for their own organizations. What's the best way if somebody wants to continue the conversation with you, for them to reach out either to you or to the Neonex team?

Thomas: The best thing is to check out the website here, www.neonex.digital. There's this first entry point. What we usually like very much we developed a management qualification program which is totally done virtually, customized, it is done in one or two weeks with a couple of hours only and this helps clients teams to get aligned and qualified. And that's normally a very good starting point for companies who are not yet [inaudible 55:58]. So they understand, okay, we need to get started, we need to accelerate our digital transformation. And that would be my recommendation to get started.

Erik: Thomas, thank you so much.

Thomas: Erik, thank you very much. Thank you and take care. Stay healthy. Bye-bye.

Erik: Thanks for tuning in to another edition of the industrial IoT spotlight. Don't forget to follow us on Twitter at IotoneHQ, and to check out our database of case studies on IoTONE.com. If you have unique insight or a project deployment story to share, we'd love to feature you on a future edition. Write us at erik.walenza@IoTone.com.

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