Erik: Welcome back to the IoT spotlight podcast. I am joined today by Peter Klement. Peter is wearing a couple hats. He's the Chief Technologist of Digital Transformation Consulting with DXC Technology in New Zealand and Australia. He's also advising XMPro. And he’s very active in the Industrial Internet Consortium. Peter, thank you for joining us today.

Peter: Hey, Erik, good to talk to you. Thanks for inviting me.

Erik: Peter, always a pleasure to talk to you because I know this is just a topic you are passionate about. And now I'm really looking forward to having a more structured conversation here around this particular topic that you just published a white paper on, which is “How to succeed with industrial IoT in manufacturing”, and then looking at some of the success factors.

But maybe before we dive into the topic here, I want to explain to the listeners a bit of your background here, and why are you a relevant person to be advising on this. Because this is a topic that is interesting enough that a lot of people are putting their voice into the arena. But it's a topic that is also new enough that I think not that many people actually have a great deal of practical expertise. Can you give us just a quick 90 second walkthrough of your background in this space? I know you do have quite a long background in practical applications of IoT now.

Peter: So I think I have a long, long history in technology in the consulting space and always try to balance the business side with the technology side. So essentially, if a new technology comes out, what's the business value of a new technology? That was always important to me. I started my journey in IoT around 2013 on a specific business transformation project in Sydney, Australia where I'm located and it was not called IoT project, it was called the Port Botany Business Transformation Automation project, the lengthy name, but it was essentially the container terminal here in Sydney. And they essentially transformed the port. And they integrated or you saw the convergence between it on premise and cloud and also operational technology.

So you had [inaudible 10:24], gate CCTV, Way Bridges, X cranes, and even self-driving straddles, that's the guys are the vehicles who pick up the containers from the trucks and put it towards the cranes. And they were made self-driving, for example. The interesting thing was there from a motivational perspective for those guys. They were obviously after operational efficiency in cost reduction. Actually, they save 50% of the headcount in the container terminals. So they reduced from 400-200. But on the flip side, they reduced the number of incidents by over 99%. So it was almost like between the operational efficiency and the worker safety balance. That's what I think I saw again and again, and that's also important. What is the value that, in this case, specifically IoT brings to an organization?

Erik: And I think maybe a good place to ground our conversation before we get into the details of this document that you've published is what are the challenges? I think now companies are quite receptive to the proposition that there is a value proposition, that there is value that can be created, potentially transformative value for either their operations or their ability to provide services in new ways or to augment products to increase competitiveness. But I think we've seen still relatively few companies be highly successful here, at least given the amount of effort that's been put in. And one of the unique aspects of industrial IoT is that you're actually wrapping together quite a broad suite of technologies, whereas cloud is challenging, but also fairly narrow in terms of the technologies involved in this space. We're really tying together many, many new technologies that are all fairly early in the development cycle together.

Why did you feel it was necessary to put the effort into writing this white paper? What were the specific problems that you were hoping to help companies to smooth through after they have a better understanding of the principles that you've outlined here?

Peter: Absolutely. At the beginning, once IoT appeared on the Gartner Hype curve, all the product vendors went to their clients and wanted to sell them IoT products and solutions. And I think, for a couple of years, the discussion was very much technology focused. So the capabilities, the art of the possible, the flashing lights, and what can they do through technology. When you talk to the tech guys, they get excited about technology, absolutely. But if you then go to the guys who own the budget or to the business side, they were just confused and could not actually understand what the value is. And the technology vendors often were not able to express the value that IoT brings to a specific organization.

I think over the last two years or so, you see a lot of discussion around business value around saving costs through automation, even discussing about how data is the new oil, how you can essentially enable new business model, new revenue stream through IoT data. So that's all good. But I think many organizations still don't know exactly A, where to start there because you mentioned it's a transformation, where do I start? How does my journey look like? So that's one of the challenges I see still in many organizations. The other organization is depending who drives it. It's not a holistic approach.

So to speak, the critical success factors are sometimes very limited. And example is exactly the business value. I may be able to find out the business value, and then try specific solution into my organization to transform my operations. But if I don't think about other aspects that the paper addresses like end-to-end security or the changes to the operating model, essentially, then then it fails.

IT has been complex. But I think in the last 20-30 years, we find a couple of ways, including integration standards and products and other things to manage the complexity. Also, from a security perspective, we have come a long way. The OT side has always been a closed system, proprietary technology, many different vendors, and bringing these two worlds together, essentially creates a certain challenge also from a security perspective. So I think the challenge, what I'm seeing is people sometimes, when they go on to IoT journey, they don't have a holistic perspective what the critical success factors are. And this was the motivation to write this paper.

Erik: And then I, one of the things that I quite like about this paper is that the success factors are really largely focused on business aspects, certainly end-to-end security more technical. But I think that's to an extent where the core technologies might not, in some cases, be mature. But they're mature enough that with some hard work and a good bit of intelligence, we can make the technologies function. Now making them function in a legacy operating environment, making them make sense, that seems to be now the challenge.

Let me run through just to provide a baseline for the listeners what these six factors are. So number one, business value; number two, strategic alignment; number three, business process focus; four, operating model changes; five, capability uplift; and six, end-to-end security. And so none of these are really directly how do you install or how do you choose the technology? They're all really around how do you make this work in an organizational setting. How did you choose these six as the critical factors that differentiate a successful from unsuccessful project?

Peter: So I think the choice and it could be five or seven, and there may be others out there. So why I chose these six was specifically around discussions with clients. Also, you mentioned the Industrial Internet Consortium where we both are active in, they’re just based on discussion, again, not only on the vendor side but also on the demand side, so to speak, with what topics they are struggling. And some of the critical success factors are actually based on very specific client examples that I encountered over the last couple of years.

Erik: Well, let's just dive right into maybe starting with the beginning in business value. What are we talking about when we're talking about business value in an IoT context? Because often people are going to think specifically around a particular set of technologies that's going to be implemented. So bring us into the mindset of you and your team when you're advising a company and what it means to think about business value in one of these investments?

Peter: I think the business value is very specific to an organization. Depending in which industry they are, where they are, from a maturity perspective, different things are important for them that different areas where they can generate business value. What we did, essentially, we created almost like clusters or groups of business values, starting with business model innovation, where we think about how can I use IoT technology to generate new revenue streams or provide new services to my clients? That's a lot about this industry for that discussion around. We also look at customer experience from a customer perspective. Of course, the traditional operational excellence from efficiency automation but also increasing the product quality, we are talking about manufacturing here, specifically. And that's maybe the three which are to be expected.

But there are also three others which people usually not think so much when they talk about IoT. One is about the environment and using sensors to essentially measure not only the energy consumption and reduce it but also look, for example, in the factory floor for toxic gases or liquids which goes into lakes or rivers essentially. So, the whole environmental movement, corporate social responsibility, certainly area where IoT can generate value.

I mentioned already the port in Sydney and safety of people, and that means if toxic gases are released in a chemical plant, obviously, that's an environmental problem, but also health problem with the people working there. We all know Fitbit and Apple watch, so there are a lot of devices to measure vital signs, fatigue is a big problem especially if people are working shift in factory. So the whole worker safety is a big topic where value can be created.

The last but not least is a boring one that's about inspection or compliance essentially. Most companies need to inspect their assets on a regular basis from an audit perspective. And instead of someone essentially running around the factory with a paper based notepad and making notes, you can also get data from sensors and then prove your compliance to certain standards out there. So that's a little bit of the categories from a business value perspective.

And by prompting the clients, essentially, to think about these different business value categories that prompt essentially then to say, oh, that's an important topic for us clients describe what problem they have with safety or what they want to do from a customer experience where they get their complaints or how they think they need help with the product quality from a production perspective and that's how you tease out essentially the consultative project, maybe using the design thinking workshop, the business value for this specific organization.

Erik: My feeling is that in the earlier stages of engagement with these technologies, a lot of companies approached it from the standpoint of here's a new set of technologies, how can we use it, and then they came up with a lot of pet projects that were doing cool things with technology. What are the things where we see a real opportunity to create value for the business? And then is it possible to address challenges or create value in a new way given the new technologies that have come on the market in the past several years? If so, let's explore those and see if there's a business case behind it. And if not, that's okay. We don't need to force the issue. We can assess.

But there's Peter, maybe still a little bit of tension there between the desire to ideate maybe because you have some uncertainty about what's actually possible and really the need to have a strict business case approach where you're really making sure that you're putting effort into areas where there's really a potential output. How do you manage that that tension? Yeah,

Peter: I think there's a lot of research around innovation processes. And I think all this idea about innovation management can also be applied from methodology perspective for IoT technologies, of course. I think it's about developing an innovation process, leveraging IoT and the business cases is certainly the one thing. It's almost like you identify the business value, and the first thing you understand is the qualitative benefits. Usually, it's also probably easy to find a solution and to produce the cost.

But then when you need to measure the cost savings or the additional revenues, that's really hard, but that has always been the case. If I replace my old ERP system with a newer version, how do I make a business case? So I think organizations are used to tease out quantitative business benefits as well.

Again, coming back to the worker safety thing and the Port Botany,, they said we want to have a 50% cost reduction and reduce the number of incidents by 95%. Were they sure that they can receive 95 reduction of their accidents incidence on the yard in the container terminal? The answer is no. But they said every accident less is something towards the goal of zero harm. So I think it's sometimes the organization a little bit of belief that technology can help them to get better.

And I think we all know the challenge with business cases is in most organizations, if they are not Lean Six Sigma in most organization, the business case, there's no benefit realization process that works because people sometimes put benefit numbers because they need to. It's like a startup essentially, going to the investor and putting some revenue numbers. And actually, they have no ideas and the investor we realize this, of course.

So I think it's a little bit of this thinking, Are we convinced, can I make a logical argument that I can generate more revenue, that I can save costs, that I can improve my customer experience, I can do something from a product quality perspective at making educated guesses, maybe based on what other companies already did in other parts of the world, and then making the investment decisions?

Erik: And then we get to item number two here: strategic alignment. We are doing a good amount of work now here in China with quite traditional companies who lack a lot of core competencies in the areas that are really relevant for industrial IoT, so AI, machine learning, or in sensing technology, and connectivity, and so forth. And so, when we're talking about strategic alignment, at least in our case, often what we're talking about is how does an organization that is interested in a set of technologies that they believe will be very impactful for their business but does not currently possess a strong suite of those technologies?

How do they react? What is their approach to this? Because it’s not immediately clear what the approach could be. It could be hire, acquire, partner, develop organically. There's a lot of different options, and none of them is certainly readily apparent. Is that what you have in mind here? Or maybe you have a different thought process on what are the key questions or key challenges in strategic alignment?

Peter: I think you're absolutely right. If you have defined a strategy, usually, then you have a goal and you need new capabilities or change your capabilities. And then the question is, how do you get new capabilities and acquire capabilities or outsource or whatever the certainly something?

Here I think it starts again with the business value. Because once I have identified the business value that IoT can create, then I need to look at my business strategy. And there should be an alignment between the business value that IoT can generate and what the business strategy says. For example, if I have identified that I can improve my product quality via IoT, then I should maybe put something in my business strategy that actually improve my product quality. But it could also be the other way around that the business strategy set specific goals and I need to see if IoT can help.

So I think the business strategy can be the starting point for identifying business value. But it could also be the other way around that the business value you identify that IoT can generate and impact actually what's written in the business strategy.

Then the technology component is most organizations have a technology strategy from a technology and vendor perspective. And that limits usually the choices from a technology or product perspective, even in IoT. IoT platforms, for example, if I have an ERP system from a specific vendor, I think there is a strong preference usually to use also the IoT platform from this vendor. So the technology strategy sometimes gives a little bit of constraints around what technology capabilities and what products you can choose moving forward. But again, there are obviously there's also the possibility that there are gaps, specific products that you don't have in your technology landscape and that you need to introduce essentially.

And again, for example, if IoT platform is not in your technology strategy, you decide for a specific vendor as part of your strategic exercise from an IoT perspective, then obviously, this IoT platform needs to go into the technology strategy like your strategic CRM or ERP vendor. So I think it's a two way street and not a one way street how IoT can impact business and technology strategy.

Erik: In many existing systems, the value that's created in that system is also captured by that organization. In IoT, I think it is quite a bit more common that the value that is created is actually easier to capture by another organization, whether it's another business unit, another function, a third party company up or down the supply chain. And so, you have then a challenge of alignment in terms of pricing this value, building a model around the value data, managing the ownership of that data, all the more challenging right now because of the evolution with GDRP in Europe, which, which makes maybe sharing that data somewhat more challenging. How do you see this playing out?

So in situations where there might be data provided from multiple organizations that needs to be combined in some way for maybe one or more of those organizations to derive some value, what are approaches that you've seen that are successful in allowing that to take place and not allowing one of these organizations to become a bottleneck there by to an extent hoarding that data?

Peter: I have at least two examples that I can share, and they're all in the public domain. It depends a little bit on the maturity of the organizations. And I think many organizations who don't understand the whole IoT thing from a strategic perspective, they make some strategic mistakes. I give you two specific examples. Let's take GE and their jet engine. It's all over the place. That's the usual example.

I was working for an organization that Australia who essentially operates train line, so they take coal out of mines and shipping to the port. And the locomotives are from GE. So if you buy a new GE locomotive that's quite an expensive piece of hardware asset as a capital investment and it has hundreds of sensors in there. It's like a data center on wheels. But if you as a client to port for 60 or 70 million, the locomotive, if you want to get access to the data that's produced from your locomotive, you need to pay GE money every month in form of a subscription model.

And if you think you can generate enough value out of this data, then you would certainly do this. And GE has a nice new revenue stream around data. But there can also be other scenarios. I know from a manufacturing client essentially. So, the asset vendors who produce the machines, the assets in the factory, the production systems, so they have sensors for many, many years, and they now think, oh, instead of feeding the sensor data only in the historians for audit purposes, like we did in the last 20-30 years, why don't we sell the data to our clients who manufacture something?

At that price point, but this manufacturer was very sophisticated. And they said, okay, so that's the subscription fee that I need to pay to get access to the data which is generated in my factory. And what they did, they went out into the market and say what if I retrofit a vibration sensor which is built into the asset externally on the asset and built my own IoT platform and analytics on top, and the business case revealed that retrofitting a vibration sensor which was built in the asset in building the IoT platform with the analytics was cheaper over 5-10 years than actually doing the subscription model? And that shows me that while there's a lot of hype around selling data, I think we are still experiment ending with the business model and what is it worth essentially.

Erik: And then the third area here, business process focus. So explain the importance of business process focus.

Peter: So I think obviously, you start IoT with the sensors that generate data. And I think, again, in the last couple of years, there was a lot of discussion and still is around data analytics, machine learning, AI. And that sent off the discussion at the moment. But in the end of the day, if you ignore IoT for a moment and look back, an organization is not built on data analytics. Organization works based on business processes and it's boring topic, but it has been around for ages.

And if then last November or December, McKinsey published a study which is very interesting and we refer to in the white paper, which talks about IoT capability gaps and the instrumentation a little bit, but very low. From a GAP perspective, data a little bit. But the biggest GAP was about integrating IoT into existing business processes. And I think that's a little bit of the challenge of the IT-OT conversion. You can create data and spit it out.

But if you look at how usually the IoT platform vendors position themselves, you collect data, you put it in a big data store, you put some analytics on top, you have a nice visualization. But there's no action. And it's also integrated in the business processes and all the business systems, it is an ERP and enterprise asset management system, a CRM, or what have you, a fieldforce automation system.

Again, it's a maturity thing. At the moment, most of the discussion around IoT is how do I use the data from an analytics perspective. But there are strong indicators that a discussion will shift towards so how do I integrate this almost like IOT data silos into my existing business processes?

Erik: It makes a lot of sense that this would be the development that using IoT data for analytics or for informing decisions is relatively low risk. As long as you have some reason to believe data is credible, then it has value. And you still have control over the impact that data has. Once you start pushing data into automated decisions that impact business processes, you lose control to an extent and you gain by giving up control, you gain potentially significant improvements in efficiencies.

Aside from security, are there other significant bottlenecks that you see that prevent companies from more actively using this data to automate or optimize business processes?

Peter: Yeah, the question is always what's the impact of security issues? And then we go back to a, again, very boring topic of around data management and data quality, obviously. If I just display IoT data on a nice dashboard, based on the analytics from a machine learning algorithm, and I may send out an SMS to notify someone, there's still a human being involved, who looks at the data and see that looks funny, engineer, I don't believe that that's true. And that may be based because the algorithm is not okay or based because you have crap data.

But once you trigger something automatically in a business process without the human being involved, then the risk goes up and then you need to make sure that the data quality, not only the data quality, but also the output of the algorithms of the machine learning algorithm is where it needs to be. So I think currently with analytics visualization notification by SMS, that's okay. If the data is not okay, and you get crap data. But an intelligent human being looks at the data and see it cannot be and does some investigation and finds out the data is not okay.

But once you start plugging it into an existing process and automatically trigger something, a work order, or order spare parts or shutting down a factory because you think there's a problem, which there is not maybe, because the sensor does not produce the right data, and you think it spits out toxic air somewhere from a gas tank but it's not the case and you shut down now your whole factory, then I think that data quality gets more important than it currently is if you just look at the data, and let the human being make the decision what happens next.

Erik: Number four here: operating model changes. So this you could say would be a higher level change to a business process to an extent, more strategic change to the business. How do you differentiate business process changes from operating model changes in this context?

Peter: I think the business process focus looks obviously on the process flow, while the operating model changes is really changes to the org structure of an organization. And I'll give you again one specific example from a client I was working with.

So in many organizations, IT was for a long, long time, consider the cost center. And that's why the CIO reported to the CFO. So this manufacturing client, what they did essentially, they moved it from the CFO under the responsibility of the supply chain director, which is a Chief Operating Officer role. And what they did is essentially, they merged the Operational Technology team and the IT team under the supply chain function.

OT needs to come together from a system perspective, from a technical perspective and different sometimes IT and OT systems are more from a business process perspective. But the people who essentially develop and manage and design OT and IT systems should also seen integrated technology function. So that's the internal view. And then if you think outside of the organization, there is supply chain value chain.

But different organizations need to work together end-to-end, and then the question is are there also changes in this ecosystem do you create? So do the responsibilities change? For example, can you create a business case not only for your company but together with your suppliers and customers, essentially, because all of you need to make certain investment in IoT technology so you can optimize the process flow from an end-to-end perspective, which means that new forms of cooperation? That's also something which is seen in the operating model changes from extended enterprise perspective.

Erik: And this point seems to be where a lot of the risk is. So business process focus where we're maybe looking at percentile improvements, which can be very impactful for the financial performance of a company, if you get a 5% improvement in your bottom line, this is very impactful. But an operating model change can be an existential impact to the company. So we see this with Amazon, I think, on an annual basis they have their conference and they announced which new areas they are moving into. And what this often means is that they're moving from a partner for the participants in that market to a competitor. And they've decided that for some strategic or financial reason, it makes sense for them to have their own product in that category.

I think for a lot of traditional companies, if we're talking about certification, for example, how that work will be done in 5 or 10 years and whether, for example, having a force of engineers that are deploying the service is going to be the process. How do you advise companies here? Because this is a space where there is a great deal of uncertainty and it's probably a space where it's significantly more difficult to test something in a simple POC or a pilot phase, then in in process changes, for example. Here, we tend to be talking about larger changes that done on a very small scale might not provide enough information to let you confidently decide that this is actually the right approach. How do you tend to advise companies that think that there might be a need for a dramatic change in their operating models?

Peter: So, operating model changes or operating model transformation has been around since the beginning of time. If you again, think that all the shared services discussion, so can I essentially across different divisions of business unit have only one team that does HR or procurement or financial accounting, and then oh, maybe I offshore it essentially, or outsource it even? So there's a lot of outsourcing of business processes in the shared services space. I think operating model changes that has been again based on technology capabilities, even before IoT out there for many, many, many years.

I'm really talking about changes from an IT-OT convergence perspective to have an integrated technology function and that I need to look at my ecosystem. And if I need a maybe my investment in IoT technologies, not alone to optimize my supply chain end-to-end. And instead of only seeing my customer, someone I sell products to and my suppliers, I get a raw material for to say, okay, if we want to optimize the supply chain end-to-end, we need to come up with a new work of collaborating essentially, and not the usual supplier-customer relationship.

Erik: Is this a potential shift that you think would make sense? Or will it eventually be adopted by a large proportion of companies? Or do you think that it's going to be a relatively narrow section of companies that decide that this is actually a useful transformation?

Peter: Again, I differentiate. So the value ecosystem, the extended enterprise, different value chain partners collaborating with joint business cases and new forms of collaboration, I think that will take a long time. It will probably more the exception because it's just too hard, sometimes from a commercial perspective, how it works.

The integrated technology function, I think that will happen as people create these IoT solutions that span IT and OT and they just see from a development support enhancement perspective that it doesn't make sense to have those guys sitting in two different teams of different bosses, different incentives, different reporting lines, and that they can create synergies by just integrating it from a technology function perspective. And as I said, already examples out there where I'm seeing it already in the last two years. So it's happening already.

Erik: And then number five, capability uplift. So here we're talking about people. Obviously, people likewise, we've been dealing with the evolution of skill set requirements for the history of modern enterprise or really for the history of humanity. How is it different now?

Peter: So I think you made a good point here. I think new technology always requires new capabilities and an organization. And then it's up to the organization to decide if they build up or upskill the capabilities, the skills of their own people or if they outsource it. From an IT perspective, there were new technologies days in commerce, there's mobile, you mentioned cloud, there’s social there all the time.

And analytics and outcomes, IoT is just another technology, and the technology guys are excited about it, that will pick it up anyway sooner or later. The interesting thing, because in IoT, the virtual and the physical world comes together, and usually, the physical world, the asset world, that's where business people sit. And they've business people, and they have maybe engineers, and they understand the asset and how it works.

But now with from an end-to-end and an IT-OT convergence perspective, I think the guys who sit more on the business side, they have a steeper learning curve, for example. If I have an asset in my factory and that's controlled by a PLC SCADA system and that’s a closed system and never gets outside of my factory floor, I don't have a security issue. But if I open it up essentially, then suddenly, everyone theoretically can get access to my asset. And then I need to suddenly learn about specific security, things that I in the past never had to learn about.

And also, in the complexity of the integration, not existing standards, how I can use data, what's analytics. I think there is a steeper learning curve on the business side around IoT than it's on the IT side. And maybe not steeper, but it's easier for it, guys because they're so used to all these new technologies coming along all the time.

Erik: But I think on the IT side, you're also seeing the requirement that IT professionals become more proficient in the business requirements and the operating requirements of a business because their role is now becoming somewhat more strategic, as opposed to more of a maintenance function. Do you see a lot of companies that are interested in trying to either retrain or educate their IT teams around more of the specific business functions or in hiring people that have both a strong IT background, but also a very strong functional expertise?

Peter: From an end-to-end solution perspective, it obviously gets more complex than in the past. And you cannot expect anyone to be into the details of all the different IT and OT technology components. So we should not look naturally to the individual, but on a team basis. And I think the operating model changes. If you have suddenly a team, which have OT and IT capability and you have a team group, that helps a lot. But there's still obviously upskill requirements.

And the IT guys, to your point, yes, they need to understand what's essentially a historian, what's a PLC SCADA system, for example. And at least on a high level, maybe they only see the data coming through the pipe and do something with the data from an analytics perspective. But they certainly need to also understand a little bit some of the operational technologies out there. But I think they can almost lean back and look at it more from a data perspective they are consuming. While as I said, some things around integration and cyber security, the OT guys then also need to think about how do I secure my robot on the factory floor?

Erik: But I have two investors who owned a couple recruiting firms. And the demand right now for professionals that have a fairly deep technology expertise, whether it's in IoT or cybersecurity or machine learning, and have operating experience in a particular functioning is extremely high right now or at least the supply demand imbalances is quite steep. So I think at least right now, maybe companies are wishful that they can find that individual that bridges the skill sets, but that's certainly a tall order to ask if any one person.

Peter: Yeah, that's maybe a little bit of another perspective here. And that's essentially the business expertise, the industry expertise. Again, if I think about ERP as an example, we all know that there are individuals who just understand the basic ERP platform. But there were always these in this specific product vendor perspective without mentioning the product vendor functional consultants in HR or in financial accounting or in procurement or in sales and operations who understood the software from a business process perspective.

So again, if we think IT specifically in the business application space, especially in the ERP space, is combination of technical product knowhow and business process knowhow was always out there in the IP world. And that someone who's focusing on financial accounting or HR suddenly needs to understand how our production process works on a detailed level, not sure about it.

Erik: And then, Peter, this last point, six end-to-end security, so this is certainly getting a lot of tension. And for good reason, where do you feel we are right now in terms of awareness and the ability to appreciate challenges and address challenges in the companies that you're working with?

Peter: I think that awareness is definitely there. And there's enough in the press around cars being hacked and insulin pumps in hospitals and everything. Again, in IT, for the last 15-20 years, there was a lot of skill built up in products around securing servers and clients and networks and the firewalls and virus scans and intrusion detection systems.

In the OT side, there's actually nothing out there. And that means that on the operator technology side, there are no products, there are no skills, there are no capabilities out there. And if you can plug in the internet cable, I think that's where the challenge start. Because many of the concepts and products that we use in the IT side, I cannot put a virus scan. I mean, if you look at your personal laptop, you know how much CPU and memory and hard disk it sucks up, especially if the scanner runs. You have, sometimes, low boards with IoT sensor devices.

They sometimes don't even have a very small footprint or a little bit of RAM, very tiny CPU. The concept, how you secure an end to end solutions have to change. And that's where we are only beginning to understand that sometimes you cannot secure an IoT device because you cannot put in some software that essentially protects it like a firewall from the bad internet and the bad actors out in the internet. And then you need to find other ways to secure it.

So I think from a security perspective, we are just the beginning what can we have from a solution perspective? I think that's one of the areas where there's still a lot of R&D going on what's the best way to secure an asset or a car or a robot or whatever it is.

Erik: So self-driving vehicles and so forth, but assets that have the capability to really harm individuals and are also heavily automated, we expect these to be out in the world and in really the coming years. Peter, after writing this paper, where are you today? Have you gotten input from customers? I know this is published recently. But maybe you can share a couple perspectives from some of the feedback that you've gotten on the paper, particularly interesting from the end user side or the nontechnology provider side?

Peter: Absolutely. We've starting this discussion on the market and it triggers the right conversations. I mean, if you think about when you develop a solution, there is something which some people call deciding principle. So if you develop an IoT solution or if you transform your organization via industrial IOT or Industry 4.0, what are your guiding design principles to do this? And that's a good starting point. It helps also, a lot of clients we talk to not only focus to your point on the technology solution and maybe not only on the business value in the business case, but think a little bit more holistically what are the critical success factors in the IoT journey.

Erik: But do you tend to take more of a highly structured framework or highly detailed assessment approach? Or do you start more with casual conversations around these areas and kind of flesh it out more subjective approach before diving into the details? Just what do you find works better for the conversations that you have with your clients?

Peter: So I think this discussion is still on the high level. It's always good talking points in the first discussion to talk about have you thought about what would be the critical success factors? And that's how we use it. But again, once clients understand that there are critical success factors, then it goes from this more informal approach into a more formal structured approach.

Because again, if I'm coming back to our very first point, on business value, all these categories understood, but then the question, what is it for my company? What is the business value of IoT? And that's not something that you do in the 45 minute meeting with the customer. And that's where we then do something like design thinking workshops, where we flesh all this stuff out very customer specific.

And once I think we have the big lampposts and the visioning in place, then it goes down to typical, in this case, IoT or Industry 4.0 strategic exercise with roadmaps and what capabilities are needed, what's important, where do we need to uplift our capabilities? Do we need to have an operating model change? If yes, how do we do this? How do we approach security? So it starts with a very informal conversation to create awareness and interest to address this and created the condition that you can essentially sell inside the organization and get support and funding and then look more from a strategic perspective. And then almost like from a maturity model, maturity curve perspective, how you introduce IoT, how you transform your business via IoT, always been aware of this critical success factors along the journey.

Erik: Also, for me a pleasure to read this document. I think it's a great brief or refresher also for myself. Any last thoughts that you wanted to share with our listeners?

Peter: Yes. As I said, also, IoT as a technology in what's around is maturing over time. So I think we are still learning a lot in certain areas. And that certainly will continue, especially as not only IoT. We talked a little bit about IoT and data analytics, how this fits together with mobile assets. But there are new stuff coming up like blockchain, and then how does the blockchain story fit IoT into the end-to-end solution? So I think it's just one stepping stone. But I think there's still a lot of to learn and a lot of capabilities to build over the next couple of years around IoT.

Erik: Well, Peter, thanks again. How can people reach out to you? What's your preferred method of communication?

Peter: I think you probably will publish something in the notes from the podcast perspective. Other people can just send me an email to Pklement@dxe.com.

Erik: Wonderful. So we'll certainly put that in the show notes. Peter, thanks, and have a great day.

Peter: Thank you very much for having me, Erik. All the best. Talk to you soon.