On this episode of The Innovation Engine, we look at building the Internet of Things – why it, in many ways, represents the next generation of the Internet, the implications that has for companies in a wide range of industries, and some words of wisdom for those looking to dip their toes into the IoT waters for the very first time.
We’re joined by Maciej Kranz, the author of the recently released book Building the Internet of Things: Implement New Business Models, Disrupt Competitors, Transform Your Industry. The book hit the New York Times Business bestseller list at #3 in December 2016, and it was named a “must-read book for entrepreneurs in 2017” by Fortune.
Maciej Kranz is the Vice President of the Corporate Strategic Innovation Group at Cisco Systems. He leads the Cisco team focused on incubating new businesses, accelerating internal innovation, and driving co-innovation with customers, partners, and startups through a global network of Cisco Innovation Centers. Prior to this role, Maciej was General Manager of Cisco’s Connected Industries Group, where he drove IoT business for key industrial markets. Maciej has been involved in the IoT space since the mid-2000s, helping Cisco lead the way at enabling innovative IoT solutions in areas like smart cities, manufacturing, and many more.
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Will Sherlin: Let’s start off this episode with a little bit of storytelling, if you don’t mind. Early in the book, you share a very powerful anecdote about some of the changes Harley Davidson was able to make in their manufacturing process that I think illustrate a few of the areas where IoT has the most potential impact. Could you share that story with listeners to set the stage for the rest of the episode?
Maciej Kranz: Absolutely. I think we all know Harley Davidson, right? They are the iconic manufacturer of custom motorbikes, but a few years ago – before IoT – they used to operate like a collection of separate islands, where all of the functions from purchasing to logistics, and even stations in their production plants operated as silos. As a result, if you and I wanted to order a custom bike, it would take up to 18 months from the time we place an order to the time they actually ship and deliver the product. What Harley decided to do was to implement IoT by connecting all of these islands, starting with their production plant, on to one network. Once the data started flowing across, they were able to optimize their processes and reduce the time it takes to deliver the product from 18 months before IoT to as little as two weeks. Here it is, IoT in action.
Will Sherlin: That’s amazing. One of the overarching concepts you write about in the book is that the first stage of the internet represents connected people, and the second stage of the internet represents connected everything, basically. How will this next stage of the internet be different from the first?
Maciej Kranz: Great question. When you think about the last 25 years, the first wave of commercial internet, the main role of connected devices was to give people access to each other, access to the online data, and access to online processes. These devices performed these types of tasks beautifully. However, in the second wave of internet, when, as you said, everything gets connected to everything, the main purpose of IoT connected devices is different. It is to generate the data that can be then analyzed and pulled into solutions that create a business impact.
Will Sherlin: Figuring out where to start with an IoT engagement varies from company to company. For those that may be looking to get their feet wet with IoT but don’t really know what to consider, what pieces of advice would you give to them?
Maciej Kranz: First of all, IoT is not rocket science. My first piece of advice would be: don’t be a hero. Dream big, but start small. Typically, what your peers have done is they went to conferences where they can learn from their peers: What are the best use cases or projects that they can implement? What are the industry benchmarks? Then they would come back, look at their TCO information, look at their benchmarks, and see if there’s a gap. If there’s a gap, then it’s a foundation for the business case. In some cases, the company will build a business case themselves. In some cases, they would use a consultant.
If you’re a small business, I think the next logical step is to find an integrator who has experience in the use case you picked, but also knows your industry. If you’re a large company, you would use a cross-functional team, but a key piece in the larger company is to secure C-Suite support, because you’re not starting just on the one project. This is just the first project. You’re starting on a journey, and the journey over the next couple of years will transform your company, so you better have support from higher ups in your company to help you go through the process, and then just get started.
Will Sherlin: One of the chapters in the book focuses on four fast paths to IoT payback. What are those four paths?
Maciej Kranz: It’s actually kind of a key focus of the book, because when I started talking to dozens of companies that had been implementing IoT over the last couple of years, across all the different industries, certain patterns started to emerge, and then I grouped basically the most mature, lowest risk projects into four categories. The first category is connected operations. This is basically an example of what Harley Davidson did. Then there are remote operations, like asset management and asset tracking. The third one is predictive maintenance, and the fourth one is preventive analytics. If you look at these four scenarios, the most common ones that have been implemented by dozens of your peers – so, if you haven’t started an IoT, I would pick one of these four scenarios as your first project.
Will Sherlin: You mentioned that you’ve been looking at companies in a number of industries where IoT is already helping companies make major gains, and you also write about some that will be in kind of the second wave of IoT adoption. So in addition to manufacturing, as you mentioned with Harley Davidson, where is IoT’s impact being felt already, and then what are some industries that you expect to be next in line?
Maciej Kranz: I’ve actually seen thousands and thousands of companies implement IoT solutions in many industries, but the most advanced and mature are, I would say, in manufacturing, logistics, transportation, oil, and gas. So overall the industrial segment, but we are also finally starting to see some large cities becoming real. The next in line, I would say, are retail, healthcare, and agriculture, where we’re starting to see some interesting pilots, but just sort of early adoption rather than mature adoption. As you can see, the good news is that IoT adoption has been fairly broad across multiple industries.
Will Sherlin: There’s a concept that you mention frequently throughout the book that I wasn’t familiar with up until now: fog computing. What is fog computing?
Maciej Kranz: It actually is sort of a new buzzword this year, I would say. In a nutshell, fog computing is a distributable cloud. When you think about a first wave of cloud applications, they were focused mainly on batch processing; so, for example, if you have 30 years of seismic data and you want to analyze it, you would do it in a cloud. Also, some use cases like connecting a bunch of vending machines directly to the cloud made sense, because the data sent from vending machines was very infrequent and wasn’t very time sensitive. However, if you think about IoT – and we talked earlier about this next wave of IoT – it’s all about generating data. IoT devices generate a lot of data, so if you think about connected vehicle, it generates two to three petabytes of data every year. Ulrich generates up to five terabytes of data per day, so in this scenario, you can’t take all this data to the cloud for processing. You have to basically take a cloud to the data and start processing the data that’s close to the source. In this case, what fog computing does is extends the cloud to, let’s say, a car, where all the data is processed and stored in a car, and only the exceptions, alerts, or specific information you requested is getting moved to the cloud.
Will Sherlin: You mentioned vending machines there. You also write in the book about some other everyday objects, like ATMs, for example, that really have been applications of the IoT, in effect, for decades already. IoT is not necessarily something that’s new to everyone. It just kind of seems new. Is that right?
Maciej Kranz: Correct, and I think it actually is a great observation, because we’ve had many examples of IoT for decades. As you mentioned, the ATM was a good example. The reason we’re talking about IoT happening now is just scale. Now, we’re actually seeing billions of devices getting connected, which requires us to have a different approach from a data perspective, from a security perspective, and from how we integrate IoT with our business processes perspective, as well, but you’re absolutely right. We’ve been sort of working towards this moment for at least one or two decades.
Will Sherlin: You write in the book about how the job market for IoT workers and competition for IoT talent is already fierce. You think that any company who tries to go it alone is destined for failure. Why are partnerships and outside help from vendors, freelancers, or contractors a necessity for any successful IoT effort?
Maciej Kranz: This is actually absolutely a key requirement. When you think about the traditional 20th century model of a vendor or a solution provider, it was about one company doing it all, so one company will build a complete station or a complete Ulrich, or a retail store – it will be a custom solution based on proprietary technologies. Now, with IoT, because of the pace of innovation that is required and because of the cost requirements, we’re shifting to a collaborative model. I actually call it in the book a co-economy, where multiple companies will actually join forces. Each of these companies are sort of experts in their own area, and they will join forces to develop a solution for a customer base and open standards. It actually is a big shift. I firmly believe that companies that embrace these new models will be the winners in this IoT transition, and vertically-integrated companies that stick to the 20th century model will be the losers. They will just not be able to keep up.
Will Sherlin: Sticking with that theme a little bit, there’s a great chapter on change in the book where you mention a few types of models that may be good ways for people to get in the right frame of mind to think about the types of change that IoT can bring about. What are a few of those transitions that you write about?
Maciej Kranz: Again, these are not sort of theoretical ideas, right? They all came from talking to customers and learning from their experiences. The first one is prepare for the journey, not just for a one-time event. You really are looking at IoT as a transformational force for your organization. Think of it comprehensively, because you will be working on IoT projects with increased complexity and increased impact over the next few years.
The second one, linking to your previous question, is about talent. There’s a lot of discussion around talent these days, especially manufacturing, but I see the most innovative IoT companies – actually in addition to implementing I0T solutions and technology – investing more internally in their talent, and also being more creative externally with developing joint curricula with universities or offering apprenticeship solutions. Your talent needs to be ready. They need to have a mindset of constant change, constant learning, so that they can keep up and stay together with IoT technology as you are evolving that process. Move to open systems, open technologies. We talked about this. This is one of the winning transitions. If you’re large enough to have both an IT organization and OT – operational technology organization, the team that runs your plans or your logistics or facilities – look at converging these teams, because one of the keys to IoT is connecting all the major organizations within your company and for the data flow to flow, let’s say, from the plant to the enterprise to the cloud. These are a few examples.
Will Sherlin: The last thing anyone wants when trying something out for the first time is to make mistakes that will sink them right off the bat. As I mentioned in the intro, you have the benefit of having worked on IoT-related projects for around a decade. What are some of the things you’ve seen that you would recommend people avoid when they are getting started with their own IoT projects?
Maciej Kranz: This is actually the essential part. I firmly believe, especially in the early stage of a major transition like the Internet of Things, that we all have to be learning from each other and sharing not only our wins, but also our failures. There’s a whole chapter that I’ve dedicated to that topic. Let me give you a few of the most pronounced areas where we need to watch out for our potential mistakes. The first one is implement IoT solutions in isolation, separate from the related business process. I can give you an example. There was a city that deployed a state-of-the-art inflow detection system in manholes. The solutions worked beautifully as designed, but the return of the investment did not materialize. Why? Because the solution was not integrated with the related business process. In this case, the city’s sweeping and cleaning practices. Once the city realized this problem, they integrated both of the underground and above the ground processes into one work flow and their ROI followed. It’s not sufficient to think about an IoT solution. You need to think about a business process, how to integrate it, and how to adjust it to make it successful.
A second example would be immature technology. When you think about automatic parking examples, the first wave of parking solutions was based on sensors that were basically imbedded in the ground. These were very expensive and very error-prone solutions, so the second wave of parking solutions was based on using a camera as a sensor. It was much cheaper, much easier to deploy, and much more accurate. Make sure that when you’re looking at a solution in scale, you pick the solution that is based on a fairly mature and well-tested technology. Again, don’t be a hero.
The third example is to identify real production projects versus science projects. I can give you an example. A couple of years ago, I was involved in an effort to build a connected refinery – so basically connect all the elements of the refinery using wireless technology. We worked on this project with a bunch of our partners for two years, and then when we finished, we realized that the company that we were doing it for would not actually buy and deploy the solution, and that we were actually working with the advanced research group instead of with the production team. The lesson learned here is to make sure that you work with the people who actually have buying power and decision-making power before you put a lot of resources into the project.
Will Sherlin: One of my favorite parts of the book is some of the anecdotes that are sprinkled throughout. You’ve mentioned smart cities a few times, and Barcelona is really kind of leading the way in city-wide IoT implementation. Can you share a few examples of what they’re doing? I think parking may have been one, but are there other areas where they’re really building out savings or improving the lives of their citizens or tourists to Barcelona?
Maciej Kranz: Absolutely. In some way, Barcelona has been sort of an icon of IoT and smart city for 10 to 12 years now, and for us and many other IoT players, has been sort of a lab. They’re been great in opening the whole city for us and saying “Work with us.” One of the things that they’ve done is they’ve taken an architectural approach. They’ve designed entire architecture for the city, so you don’t have to recreate the real every time you want to connect a hospital or a library or a sporting venue. It was all built comprehensively from the ground up. They had a big vision, which allowed them to do that. You mentioned that they’ve deployed parking systems. They’ve deployed transportation system that were optimizing the transportation infrastructure across the city. They connected their sporting venues, intelligent buildings, as well as some of the wastewater capabilities as well. The impact has been tremendous. They claim there were tens of thousands of new jobs that were created as a result of them becoming this sort of iconic smart city around one or two thousand new companies that either moved to the city or were created in the city as a result of that. And the savings that they’ve registered from automatic parking or IoT-enabled lighting solutions go into the tens of millions of dollars.
Will Sherlin: There are some staggering numbers throughout the book about the number of connected devices there will be in the world by 2020, the economic impact the IoT is expected to have in the years to come, and much more. I’m sure there are many, but are there a few that stand out to you that you think really show how far the IoT has come since you first started working on it?
Maciej Kranz: Actually, the IoT has been on top of the Gartner Hyper Curve for a couple of years, so we’ve definitely done a great job of getting people’s attention around IoT. If you think about the number of connected devices that will exist by the year 2020, which is just a couple years away, the projections range from 50 billion to 20 billion to 7 billion. The same with economic impact. The numbers also range from roughly one trillion to as high as 19 trillion dollars in the next couple of years, which is just staggering. To be honest, these numbers actually don’t matter. Yes, they show the impact of the IoT across the globe, but for your listeners, or for people who run the organizations, for people who run businesses, what really matters is what IoT means for your organization, right? What ROI you can get out of IoT implementation. Yes, these numbers are big, but I would ignore them. Focus on what impact IoT can have on your business.
Will Sherlin: You mentioned the Gartner Hyper Cycle. The IoT, like many other technology areas that can come and go, can feel like something where people start to wonder if the reality will ever live up to the hype. I personally have questioned on this very podcast, for folks who are long-time listeners, if we really need to have our refrigerators hooked up to the internet. After reading your book, I will be the first to admit when I’m wrong, and there’s a great story in the book about a dairy company in India that actually harnessed the power of IoT to great effect. Would you mind sharing that anecdote with listeners to maybe illustrate why a smart refrigerator might not be such a bad thing in some cases?
Maciej Kranz: I absolutely agree with you. One of my frustrations has been that there have been so much hype around consumer IoT, especially the idea of the connected home. While I do see that there is some merit in connecting your fridge or washing machine to the network, I think that the concept of interconnecting these devices in the home is still very early. The reason I actually wrote this book is because I wanted to focus on where IoT is real today, which is in the business setting and, as you mentioned, this ice cream example is one of my favorites in the book because it’s powerful, it’s easy, but it’s also hyper local. It’s focused on solving a particular problem in India that we may not have here in the U.S.
The story is that there is a 150-store ice cream chain in central India, and over there, quite often, they have power outages, so the company installed generators in every store. But what they noticed quite often was that the managers in the stores were not turning the generators on, the ice cream was going bad, and they were losing thousands of dollars and creating a health hazard in the process because the ice cream was freezing, melting, and refreezing. What they did was they basically dropped a bunch of temperature sensors in the freezers in every store and connected those to a cellular network and to a sort of alert system. Every time the temperature would go up in the fridge, the store manager would get an alert or a phone call with a specific call to action, like check if the door is open or turn the generator on. If the temperature would continue to rise, these messages will start getting sent to a manager, to a district manager, and eventually to the CEO of the company if there is no action. It’s a very simple setup, but the impact was tremendous. In the first 12 months after the installation of this system, the company saw 5X ROI, or 500 percent Return On Investment from using the system. Of course, the health benefits were tremendous as well.
Will Sherlin: Let me ask you to close things out with one more anecdote that’s in a totally different industry. Rio Tinto, if I’m pronouncing it correctly, is a mining operation, I believe, and they employed IoT to predict when their very expensive trucks were likely to break down, right?
Maciej Kranz: Correct. Actually, it’s actually a great experience. If you go to Rio Tinto or other sort of large open pit mine, it’s actually amazing. You’re standing in this hole in the wall that’s two miles wide and one mile deep, and there are these sort of specks on the sides of this huge hole, and these are basically these huge tracks where the tire is the size of a human being. Every time this truck would break down, it would cost the company roughly two million dollars per day of lost revenue. When you think about these open pit mines, they’re usually in the middle of nowhere. They are hundreds of miles from nearest settlement or city, so sometimes it may take a while to diagnose the problem, to order the parts, to fix such a truck. What Rio did was they implemented this predictive maintenance system where basically, looking at the past history, the system will start giving advance notice. Let’s say two or three months in advance, it would say, “Hey, there’s this element in the engine. It starts to get hot. You have 10 days to fix it before it breaks.” It gives them the time to order a part and fix it before anything happens. With these systems, the more data you give them, the more accurate they are. So now these systems give Rio Tinto roughly three months of advance warning with 90 to 95 percent accuracy, so there are huge savings for them, and they can operate these trucks continuously now for months and years.