Jun 13, 2018 | 2 min read

Podcast #14: Navigating Connected Industry - from AI to Quantum Computing, by Maciej Kranz

Maciej Kranz is one of the more prominent thought leaders in IoT, and his book Building the Internet of Things and blog are essential reading for anyone interested in those topics. Our conversation covered the changes in the market, surprises since the launch of his book in 2016 and his views on the current state of the market and evolution across industries. He discusses the primacy of security and the surprise that so many organizations need help – which drove him to publish his companion workbook. We also covered key topics such as the evolving architectures of IoT, Intelligent Edge and Fog Computing, how China is approaching IoT and the importance of AI. As the market moves from optimization to digital transformation, Maciej provides essential advice to those looking to make the jump.



Building the Internet of Things: Implement New Business Models, Disrupt Competitors, Transform Your Industry by Maciej Kranz

The Building The Internet of Things workbook

Maciej Kranz web site and blog

IoT ROI Calculator

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Hello everybody, and welcome to the Momenta Edge podcast, this is Momenta Insights Partner, Ed Maguire, and today we have a very special guest, Maciej Kranz whose title is VP of Strategic Innovation at Cisco, but Maciej is actually a lot more than that, he’s been one of the most prominent thought leaders in IoT, helping to shape a lot of the thinking, and putting in practice a lot of the ideas and visions that have emerged around the connecting industry, and the Internet of Everything. Maciej’s book, ‘Building the Internet of Things’, is absolutely a required reading for anybody that’s interested in the space. I got it when it first came out a couple of years ago. Maciej it’s great to have you on. 

Ed, really a pleasure, and thank you so much for the opportunity to talk about my favorite topic! 


Fantastic. I think what would be helpful for some of the listeners who may not know you is, could you share a bit of your background and what had brought you to focus on what we call connected industry, but broadly includes IoT and many, many other aspects of technology and business transformation? 

I’ve been involved in the networking industry I would say for the last 30-years. Started in the late eighties, and I would say at the beginning of this century we started to get involved in deployment beyond the traditional IT environments, and then with the industrial ethernet and so-forth. To be honest, it was an interesting extension and a very different extension to our traditional business. But then I would say around six or seven years ago, we thought that the timing was right for Cisco, and for the industry to go big on this concept of connecting everything. Funny enough, you mentioned connected industry and I would ask to ram our first IoT business unit, and we called it Connected Industries Business Unit, exactly because we thought we were moving beyond the IT into the space of connecting devices, and connecting the industries.  

I ran this group for a while, and then once we felt that the IoT was taking off I moved over to the current role which was basically focused on incubating new business in the wide spaces, and a lot of them are natural extension, or they’re naturally fitting into the IoT umbrella as well. 

So that’s my history and involvement with IoT, and as you mentioned, a few years ago I put together a book about the topic as well. 


Could you talk a bit about what led you to write the book, and a little bit later we’ll get into what you’ve learnt since. But what was it that prompted the decision to put a lot of your thoughts down on paper? 

You’ve been in the industry for a while, and a couple of years ago when we were at the height of the IoT hype so to speak, there was little messaging around IoT about billions of devices getting connected, and all of us making trillions of dollars with IoT. But to be honest a lot of line of business executives, and people that run businesses were confused about IoT, they were not sure exactly what it was for, and how they can use it. So, I started to get a question more and more around, ‘Is there a book that will help us demystify IoT, and put it in a business context?’ So, for business decision-makers, how they can use IoT to drive their business value. I looked around and at that time I didn’t see any book like this, so I decided to write on, and it took me 2.5 years, and the book came out. 

To be honest, I think my main goal with this book was again to demystify IoT, but more importantly to help every business, whether you are industrial, healthcare or agriculture, whether you’re large or small, to help every business get started on the IoT journey. Because I do believe that IoT in many ways is sort of a foundation or capability of digital transformation, and as the industries become technology industries, it’s imperative that every organization gets started on the IoT journey, if on a negative side they want to survive, on the positive side if they want to evolve and grow their business. 


Yes, and that thinking has really resonated. What have you learned since the book was published? When you launched, you really did step into a gap in the market where people were looking for used cases, and you provide a lot of illustrations and roadmaps for people to get smarter, What are some of the things that have emerged that may have been different from what you initially thought, or what you’ve seen that’s reinforced some of the key thinking and tenants, in the book? 

The whole premise of the book was this was a sort of practical guide. I did list four sets of use cases I call ‘The fast paths to payback’, a bit of a tongue-twister! That organizations, if they want to get started on the IoT journey, they should focus on those, so they either focus on connecting their operations, or remote operations, preventive maintenance. I also put in the book a whole chapter on mistakes that organizations have made over the years in IoT, and how to learn from those mistakes. So, a lot of practical information around how to build the business case, sort of do’s and don’ts.  

I found that in general these concepts were very well received, but there were a couple of things that stood out, the first one was it was interesting to see that technology was not the major challenge or barrier to IoT adoption. There were some non-technology aspects around culture, around change management, around skillsets, around market structures, around business model, that turned out to be much more important areas that needed to be addressed for a successful IoT rollout, than the actual solution and the technology itself.  

The second aspect of this was the aspect of security, so obviously over the last two years especially we saw a lot of denial cyber-attacks, a lot of cyber-attacks using IoT infrastructure, and in some ways, security became moved from, ‘Yes, it’s important together with other things. Well, we need to have a security strategy before we get started on the IoT journey’. So, it became the number one criterion for enterprises to consider.  

I think to be honest, the third area which was surprising for me was, the feedback I started to get after people read the book was, ‘Yeah, I get it. I need to get started. I still need more help. It is complex because of the reasons we’ve mentioned, I need some more of a handholding to make sure that I’m ready to deploy my IoT strategy, and start my first IoT project’, which is why I recently published a companion white book to the ‘Building the Internet of Things’ book, which is basically a step-by-step instruction of how to get ready, get started, and then ensure long-term success in your IoT journey. 


That’s great. So, the security challenge is certainly one I think that was not initially incorporated in a lot of product designs, as you have people who were designing for functionality, and designing for utility as Edge devices. We’ve certainly seen with denial of service attacks and other compromises that that needs to be very much front and center. I think what’s also interesting, and you have done some work on this as well, is return on investment; I would love to get your thoughts, because determining ROI, if you go back a few years ago this was one of the big obstacles to adoption of projects, or at least justification for projects, was defining ROI. I’d be interested to get your sense on how that process and the ability to find ROI has advanced, and I know you also have shared some tools for calculating ROI. 

Correct. Exactly to your point, we found that it was essential to help and give the practitioners the tools that they can use to build their business case, build their ROI. So, we placed on my website an online ROI calculator that everybody can log in and use to create an ROI output. So, there were a couple of lessons learned. One was that even as you get started with your first IoT project, most likely you will not have a very clear and precise ROI, because you don’t know. Still in some way you’re going in and saying, ‘Let me do this first IoT project’, and it’s a little bit on a ‘Trust me’ kind of a model, which is part of the reason why my advice was think big, have a big dream in architecture, but start very small; partly because you need to have an early success, and build on your success, but also partly because you actually need to hone your understanding of what ROI you’ll get. 

Even in this first phase before you start your first IOT project, you should try, you should do your best to assess your ROI. Normally they probably will not be precise or very accurate, but at least get a sense of that. So that’s the first time when you will do your business case in ROI. But more importantly, once you’ve done your first small IoT project, it’s very important to go back, obviously assess lessons learned, but more importantly to do a very precise ROI analysis of that project. 

There are many reasons, and I’ve put this in a chapter in the book, that you would often see that your expected ROI would not materialize. For example, a lot of teams focused too much on the solution itself, and not wider developing solution, and tying the business process and evolution of business process with the solution itself. To your earlier point, maybe security was under-estimated as an area of investment, maybe the focus didn’t have the right training and the right skills, which is why if you look at the workbook we put so much emphasis on making sure that you assess, and you bring your level of expertise, and your readiness in all of these areas before you start on the IoT project. As a result, when you do the ROI, hopefully you will see the positive one, because you are ready. 


That’s a great point, and we’ll link to the ROI calculator on the site in the show notes.  

I have a bigger picture question, if we go back about a year, Cisco had released a study that had shown there were a number of projects that were failing to move beyond the proof of concept stage, into production. If we go back about five years to when we first met, around 2014, there was an enormous amount of anticipation and optimism that we would see very rapid adoption, and it seemed that for a while there that some projects were getting a bit stuck, or they weren’t moving into production. Since then we’ve started to see things really pick up a bit, but I’d love to get your sense of where we are in this broader wave of adoption in the market, and how we’ve seen the very broad perception of how practically industries that are not necessarily connected, can adopt technologies in a way that will move into production applications? 

It’s funny, because as you remember when we were at the height of the hype with IoT, we thought that we were defying the height curve logic, so we were at the top of the height curve, and then we just go up from there. Well, it turned out yet again that the height curve was correct, and we went to the trough and now we’re going into the actual practical implementation phase. If you look at the study that you mentioned, I often thought that it was a sobering message, but also I thought it was an optimistic message, which basically stated, yes, a lot of organizations got started on the IoT journeys, they found out as you saw that only a fraction of these companies actually successfully completed their projects, which basically meant a couple of things.  

One is, they’re still in the proof of concept phase, and they’re working through their first project. The second one was the realization that the focus was on an IoT solution, rather than solving the business problem, and similar types of problems that they had to reset and pivot to their IoT efforts. The third one was an area like we talked earlier, approaching an IoT project comprehensively. 

So, what I would say, since then what we have seen I think is a much more realistic and grounded and thorough approach to IoT, versus a, hooray, let’s run with the flag, and within the world look great three months from now, kind of approach. We also realized that different industries move at a different pace, and they’re at a different stage of the journey. For example, in the industrial segment, like let’s say in industrial automation, IoT deployments are fairly mature. In the Cisco side we have around 14,000 customers and a lot of them are in the industrial space from the IoT perspective. Whilst, in construction for example, we’re sort early in the stage, where to be honest I recently had a conversation with a construction company from Europe, and I was talking to them about the great promise of IoT, and then the CEO stopped me and said, ‘Well, Maciej this sounds great, but you’re at least three steps of head of us. We’re still moving from pen and pencil to spreadsheets. So, let’s make sure we are grounded of where we are in this transition’. 

I also saw a lot of acceleration, for example agriculture; remember a couple of years ago, agriculture was not the primary market segment we talked about in the context of IoT. Now, it’s sprung up to be one of the leading ones, again, less about the technology, and more because they have compelling reasons to be focusing on IoT. In this case its shortage of water; in this case its lack of reliable workforce; and thirdly a big focus on food safety, and some other issues that basically drove agriculture for the last two or three years, to move to become aggressive adopters of IoT technologies. 

So, overall, I would say the benefit of the last two or three years was that we truly moved from hype, and people getting started on IoT journeys without being fully ready, to now a much more pragmatic business grounded approach, which I think will result in IoT projects that will have clear ROI, and clear benefits. 


I thought its very interesting that you had mentioned agriculture, and I wanted to address the question of data, and data privacy, which is certainly an ongoing debate. But certainly, in my conversations with people who were working in connected agriculture, there were a lot of concerns over data ownership, and data privacy, and of course this is not unique to agriculture as an industry. But I’d love to get your perspective on at least the evolving views of data privacy, and data ownership, because that in many cases had been a real obstacle to companies looking to invest in connected solutions. 

It’s a great topic. I just flew in from Europe a few days ago, so as you can appreciate with an impending GDPR implementation, it’s a very hot topic there as well, but honestly everywhere. Privacy and data ownership have different meanings in different industries, it would be different in healthcare versus in agriculture for example, but there are some common elements. I am very optimistic and very happy with the direction that the GDPR is taking us. There was a fair bit of group criticism about the complexity and so-forth, but I think the premise is right; which is, at the end of the day the end-consumer and business own their data. From that perspective, how do we build IoT systems to make sure that on the one hand we ensure that the data is actually residing in the right areas, which is why you see the cold concept of fog computing cause issue with the cloud, where you want to process the data for architectural and logistical reasons close to the search of where the data is coming from. But also, because quite often you want the data to reside on premise in your enterprise, versus taking it into the cloud. 

So, there is data ownership by the enterprise, but there is also the privacy issue and there is a strong IoT element in GDPR as well, where when you see all the IoT devices, so say cameras, sensors, and actuators, they collect personal data, and how do we make sure that this data is not used in a way that it’s not in agreement with what the consumers want. For example, the third generation of parking solutions now, these solutions have on the camera registering and sensing where you have the available parking slots. This camera would also capture let’s say people’s faces, people’s data, but this camera processes this data in the concept of fog computing on the device itself, and they don’t send the data that includes let’s say people’s faces, or license plates into the central location. This data gets processed locally and then discarded. So, we’re developing systems now that in addition to providing scalability, also offer the privacy protections and architectural approaches to privacy as well.  


Do you see the privacy regulations, and industry specific requirements for data management being embedded or, I would say productized in the architecture of solutions, do you think it will become easy enough to be able to have almost templates for compliance for data management? 

I fully agree with that, and I fully believe it will be the case. Having said that, I think the key to what you mention is the architecture. There’s a lot of discussion for example around embedding security and privacy requirements, for example in each of the end consumer device, because obviously we saw a lot of denial, same as the tax for example leveraging let’s say in hot coded user ID and passwords into let’s say consumer cameras. We all talk about these scary ideas of hackers hacking into your data monitor and so-forth 

I think if we take the architectural approach, and solution level approach to security and privacy, it’s become much more scalable and much more practical and realistic. So, for example, yes there are some elements that need to be implemented on the device, but also a lot of the security and privacy capabilities can be embedded at the network layer, using in many ways tools that we already know, how to use. For example, asset inventories, posture assessments, micro segmentation are all base access controls, these are the sort of tools that we can deploy across the architecture that will allow us to control and provide a level of privacy and security, without the need for each of the elements of the security architecture to provide every one of these functions in isolation. 


You mentioned architecture and being able to architect different capabilities into solutions. You had earlier mentioned fog computing, and I wanted to follow-up on that, in terms of what you see on the technology landscape some of the innovations that really are changing in the way people think about their business processes, and their applications. The move from this centralized almost cloud-mobile model, to this more decentralized intelligent edge model is requiring a lot of rethinking of how people design their systems. I would love to get your perspective, I know Cisco has been very active in advancing a lot of thinking around fog computing, but what are some of the capabilities’ number one that can be unleashed through adoption of some of these newer models, and new ideas, and maybe some challenges or obstacles to really rethink and take advantage of some of the more decentralized approaches to distributing intelligence across networks? 

That’s a great question. Two weeks’ ago, I was at the SAS World event and we had exactly this conversation, because at the end of the day as both of us know, the main reason we connect all of these IoT devices is because they are the sources of data, and we want to capture this data, analyze it, and turn these systems into solutions to drive the business outcomes. So, it’s a generation of data, analysis of the data, and IoT quite often acts on the decisions based on this data. 

From that perspective, architecting all these connected devices in a way that we can capture the data real-time, near real-time, is a real innovation that IoT brings to the table. If you think about the centralized clouds, they are mostly two sets of use cases; one set of use cases is batch processing of data lakes, and huge sets of data, and the second set of use cases, for example vending machines, when you connect a bunch of vending machines directly to the cloud, that used case works because the vending machine sends a couple of packets every couple of days saying, ‘Hey, I’m running out of cans, please come over and replenish the supply’. So, the data is not very time sensitive, and the application is not very bandwidth intensive.  

When you look at the use cases, like connected or autonomous vehicle, where at the Level 3 or Level 4 of autonomous vehicle, it is estimated that there are around three to four petabytes of data that is being generated within the vehicle per year. If you look at the large oil-rig with around 100,000 sensors there is five terabytes of data being generated by these IoT devices per day. When you think about these volumes of data, and most of this data is real-time or near real-time, it’s still practical to transfer this out, to push all of this data, raw data, to the cloud for processing, which is why we want to process this data locally in the car, or on the oil-rig, and ideally add AI capabilities in these locations as well, so you can analyze the data and get the action back, and on these exceptions or alerts to the cloud itself. 

So, from that perspective the whole concept of fog computing is to basically drive consistency of the architecture, all the way from the cloud to the edge. So, if you have analytics application like for example in the case of vending machines, you can safely put in the cloud – you can do that. If you need to put in analytics application to analyze data in motion in the connected vehicle, you can do that as well. So, what we’ve been driving is the recognition that now you need to augment and evolve the current cloud architecture to move into the distributed cloud architectures. And secondly, you need to have a cohesive and consistent architecture that will allow you to implement a different set of use cases on this continuum from the cloud to the edge. 


Are there any specific enabling technologies that you think may not fully be appreciated, in terms of the transform of effect, just from the perspective of an enterprise, looking in, evaluating all these options? There’s an enormous amount of innovation happening across many-many disciplines and domains, I would love to get your sense on where you think there are some technologies, that are emerging, or other enabling forces that could have an extraordinarily powerful, even multiplier effect on investments that people are making today. 

Great question, and you and I have had this conversation before. It may sound funny because obviously we’re having a conversation about Internet of Things, but I don’t believe that IoT by itself is very transformational. As we talked earlier, the main goal of IoT is to generate the data, and then in some cases act on the decisions based on this data. So, you need to augment IoT with other very powerful and often over-hyped technology. One of those is obviously machine learning, and AI in general. We talked about the relationship, I often joke that IoT is the body, and AI is the brain, and there is this symbiotic relationship that IoT needs AI to make use of and make the data useful. At the same time AI needs the ingestion of all the data coming from IoT to really train the AI systems. 

So, that’s one area. The second one, we’ve already touched on, its fog computing, or distributed cloud, it is essential for us to evolve our cloud architectures, to take full advantage of real-time capabilities of IoT 

The third emerging area, which is also top of a high curve these days, is blockchain. Again, when you think, a lot of IoT implementations are in environments where the multiple parties, that are transacting multiple transactions with each other, and how do we establish the level of trust, the level of security, the level of transparency, but also efficiency across these different participants is key, and blockchain, especially private blockchains have a promise to actually allow us to do that. 

So, I think of the combination of IoT, AI, blockchain, and fog computing as these four legs of the stool that you need to think about, and to your point organizations need to get familiar with to take full advantage of the technological acceleration you are seeing these days. These four technologies I believe are foundational for digital transformation in every industry. 


We’re very much believers that this combination, well, being able to harness the innovations from all these different domains results in what we’re terming, ‘An era of combinatorial innovation’. Each component, or each leg of the stool in a sense acts as a force multiplier to the capabilities of the other technologies. I think we’re in violent agreement here! No doubt, absolutely. 

I wanted to follow-up on the digital transformation side, and just get a sense from you, we’ve watched say the first phase of what we’ll call ‘Industrial IoT’ or ‘Connected Industry’, if there are some business model or organizational transformations that you’ve seen work well, and whether there are any specific lessons or takeaways from those companies, or those projects, that have really been successful? 

The good news is that we have lots of example of successful IoT implementations, and as you know I’ve put a bunch of them in a book. On average I would say especially in the industrial space, if you look at the first set of IoT implementations, they were focused primarily on improving existing processes. I would say the average benefit across these deployments was between 20 and 40 percent efficiency of productivity improvement, which is significant. But the good news is, we now see more and more organizations moving to the next phase, which is now that they’ve optimized their operations, they’re starting to investigate new value propositions, like mass customization, mass personalization 

We see the new business models emerging, micropayments and other interesting concepts here. We’re seeing a broader movement of industries merging, like transportation and technology, or the next one on the horizon is retail and manufacturing; into new industries like drones emerging as well. So, we moved from optimization to now truly digital transformation. 

Some of the best practices and lessons learned that I’ve seen from the industries, and we touched on this earlier, one is ‘Think big, start small’, the second one is, ‘Build the coalition of the willing’, the successful organization bring in multiple organizations. We talked a lot about a classic divide between IT, and operational technology teams, or building automation teams, and it is essential that these organizations work together, at the technology, architectural, and organizational level.  

We clearly have seen the focus on skills and skills gaps, not only from the actual skills, but also the mindset. When you think about my father-in-law, he was a technologist in a steel mill in Poland, his experience was, he went to work for this company, he worked progressively in the same organization, went to the same building for 40-years, and the job didn’t change very much. Now we’re moving into this model of, you have to reinvent yourself as an individual every couple of years, you have to have a mindset of constant learning. So, it’s a big cultural shift of organizations and individuals evolving their skills. 

Then there is much more focus from the enterprises, on investing in their own workforce in evolving skills. So, for example, I have a lot of examples of companies who invested for example in people that were working on the line, and they helped them evolve their skills to become quality engineers, or supply-chain experts. In the process they gained a benefit of automating and digitizing the operations, at the same time employees gained the benefit of upgrading their skills and making more money. We see a lot of examples of industry working with academia on curricula, so you’re sort of getting a generic data scientist, you’re getting a data scientist who is familiar with your industry. The apprenticeships are back, again, the same concepts, it’s a win/win for both participants. 

So, the interesting part is, as we talked at the very beginning of the conversation, yes there’s a big technology evolution, and there’s some exciting developments there, but you have to take a comprehensive approach across all aspects of your enterprise to be successful with digital disruption. 


It’s interesting that you bring up the skills-gap, because a few months back I’d interviewed Jeanne Beliveau-Dunn, also from Cisco, about what Cisco has done. It was amazing to hear that as you think about developing the skill-sets, I thought what was so interesting was that one of the most important things that Cisco did to help drive adoption for its network was to offer education certifications and really push education. She also mentioned the adoption of this Internet of everything strategy has created 75, at that point it was probably a lot more, different job categories, so jobs and roles changed. I thought that was a fascinating insight from the work that you guys have been doing. 

You’re right, and when you think about it, obviously within Cisco we’re working on network economies, and there are a lot of IoT courses for High School graduates, for college students. But at the same time, like the work that Jeanne has been spearheading from Cisco perspective is, we work with the industry with academia, with our partners, with our customers on creating these consortia, and these models where we together are working on these new job skills, and how we have curricula, and how we have apprenticeships, how we have jobs ready for these new categories. 

Just think about the manufacturing, in the US and Western Europe alone there are tens of thousands of jobs that don’t get filled in manufacturing alone, because we can’t find qualified people to fill these jobs. So, it’s a question of bringing new people into the industry with these skills, but as we discussed earlier, even more importantly it’s how do we work with the existing workforces that have wonderful, amazing, experiences and skills of often working dozens of years in these environments; how we help them grow their skills so that we have the best of both worlds? We have their experience of working in industry, but at the same time we give them and help them gain new skills that will allow them to apply these long-learnt skills into these new IoT and digital environments. 


I think that lesson really applies for almost any industry that you can think of. 



We now have to become lifelong learners, and learn to adapt, so nothing more compelling for a college student is mission to learn how to learn. I think they used to say whatever you would learn in college would be obsolete in 10-years, although certain principles of course are timeless. 

You’re right, I’m 53 and I expect that I will be reinventing myself at least three or four times over the next couple of decades. So, it’s this concept of lifelong learning, it never stops, and we must continue to do that to stay relevant, but also to have fun. 


There’s one question I forgot to ask you, I know this is circling a little bit back off topic, but I did want to cover China, because you’ve done some work in China and I would love to get your perception on some of the differences in terms of how China is looking at Connected Industry, and some of your experience working here in the US, and in the West. 

Yes, I wrote an article about a couple of months ago. I’ve been going to China since early 1990s, and by itself the journey was an amazing transformation. Over the last few years as I’ve been focusing more on IoT, the change in China has been dramatic, but a sort of indication of the broader trend, which is, we moved from Chinese companies being focusing more on what we’d been doing in the West, to now taking more of a leadership position in many of the applications from transportation; the large EV electric vehicle charging networks, and EV focus, with big initiatives around smart cities, not only from the evolution of existing cities, but they’ve been building brand new cities that give a blank canvas of how to deploy smart services. 

So, it’s sort of this focus on aggressiveness in taking ideas from vision to execution, a think big mentality. Sometimes controversial, but big focus of the government, and government obviously has identified IoT as one of the big initiatives. But I do believe that even though the way Chinese government is implementing IoT may not be applicable to other countries. But the role of government in driving the agenda in setting the roles, and being the customer, I think is critical for all of us.  

Overall, I saw this big IoT engine which is a combination of government priorities, and the focus a very much aggressive ‘can do’ attitude of start-ups. Also, a little paranoia of larger enterprises that they need to adopt IoT to survive and be competitive, not only in China but around the world, I think is what I took from the last trip. 


Great. Well, just as you look forward, are there any lessons from what you’ve seen with some of the more forward-thinking regions, like China, and certainly with the forward-thinking technologists here in the US? What’s your vision for the next five to ten years of Connected Industry? What are you expecting to see, and what are you hoping for? 

I published my predictions for this year, just recently as well, there are a couple of things that really struck me over the last couple of months. One is, it’s important to be hyper-local, that you need to start with business environments, you need to start with understanding of the business culture, business structures, before you start thinking about implementing IoT solutions. So, you can’t take let’s say a preventive maintenance solution developed, let’s say in Belgium, and plop it in India and hope it works; because we’re starting with a business problem, rather than from a technology perspective. 

One of the things that I’m taking away is, the IoT application and adoption is very broad. We started with industrial, but as you and I talked about, it’s now in agriculture, it’s now in pretty much every industry. The role of the governments in driving the agenda is becoming even more important, the role of research is becoming more important. The topic we’ve talked about as well which is IoT is a piece of the puzzle, and bringing the comprehensive approach to technology, with other aspects from blockchain, AI, and many others is important as well. 

So, I would actually expect that a lot of IoT leadership from application, and from the innovation perspective, will come from the markets that are outside of the traditional markets of Western Europe and North America, because their use cases are so compelling, quite often in these environments you don’t have a legacy issue, you can just leapfrog from where you are today, to the latest and greatest. Also, there’s a hunger and a sense of urgency that I see in many places from Asia, America, Latin America as well. 


That’s great insight. My last question Maciej is one I always like to ask, is just a recommendation of either a book or resource, if there’s anything that you are currently recommending to folks, or some resources, would love to get your thoughts on that. 

There are many books, mine is one of them now, it could help organizations get started on their IoT journey. I’ve been promoting some of the other authors as well that have taken different aspects of IoT into consideration. My advice is if you’ve already started on the IoT journey, great, congratulations, just make sure that you do it in a comprehensive way as we’ve discussed. But if you haven’t started, first I would suggest a couple of things… 

  1. Don’t be a hero, don’t reinvent the wheel, pick one of the four use cases that I’ve mentioned, these four fasts paths to payback, because thousands of your peers have already done that, so you can learn from their experiences. 

  2. Learn from your peers’ mistakes. In my book I’ve put a whole chapter around it.  

  3. Take a comprehensive approach, I’ve called it my recipe of IoT success. 

  4. Don’t look at IoT in isolation, look at IoT in the context of other technologies. 

  5. Engage with the community. There are hundreds of thousands of IoT conferences now, so go to the ones that are very specifically focusing on the area you want to focus. If you’re in agriculture and you want to focus on preventive maintenance, I’m pretty sure there’s a conference like that which you can go to and listen to the experts, and talk to your peers, and exchange ideas. 

  6. I would also argue, get involved with a community, not only from learning but also from driving the agenda perspective. Get involved in standard buddies, get involved in sharing your best practices, and your successes and mistakes, because it takes a village; all of us are on a journey, we all should be working with each other, we all should be learning from each other, no one company can do it alone. 

That’s great insight Maciej, and as always, it’s been enormously illuminating and a lot of fun talking to you and hearing your thoughts. 

That wraps up our podcast. Again, I want to thank Maciej Kranz who is VP at Strategic Innovation for Cisco, but also one of the prominent thought leaders in the space. Really grateful for all the work and contributions you have made to the community and to the industry. 

This is Ed Maguire, insights partner, and that’s bringing you another episode of the Momenta Edge podcast.