EP021: The Long Road to Digital Transformation - An Interview with Cisco's Maciek Kranz
This is an episode of the "Ventures in Industrial IoT" series brought to you by GE Ventures. In the series we explore success factors and challenges in Industrial IoT markets with CEOs, investors and experts.
IoT Spotlight Podcast introduction:
The IIoT Spotlight Podcast shines a light on Industrial IoT solutions that are impacting businesses today. Every episode we interview an expert about a specific IoT use case. Our goal is to provide insight into the planning and implementation of IIoT systems, from new business models to technology architecture selection to data ownership and security. The IIoT Spotlight is produced by IoT ONE, an information platform that provides market insight, partner development, and go-to-market support for technology providers, end users, and investors. Don't forget to follow us on twitter. You can contact me directly at email@example.com.
Far from being merely an isolated one-off event, digital transformation needs to be seen as a journey - a long and intensive one.
In the sixth installment of the "Ventures in Industrial IoT series" brought to you by GE Ventures, we are pleased to have with us Maciej Kranz VP of corporate strategic innovation at Cisco Systems and author of the book "Building the Internet of Things: Implement New Business Models, Disrupt Competitors, Transform Your Industry" on the show to share with us more about some of the insights in his book and other advice on how firms can successfully embark and sustain their digitalizaton journey.
Learn more about Cisco' Corporate Strategic Innovation Group: https://www.cisco.com/c/en/us/about/corporate-strategy-office/corporate-strategic-innovation-group.html
Learn more about Maciej's book: http://www.maciejkranz.com/book/
Learn more about GE Ventures: https://www.geventures.com/
Maciej Kranz is leading a mission to reshape and redefine the world through digital tansformation. As the vice president of the corporate strategic innovation group at Cisco Systems, he leads the group focused on incubating new businesses, accelerating internal innovation, and driving co-innovation with customers and startups through a global network of nine Cisco Innovation Centers
In addition, Maciej is also the author of a best-selling book entitled, "Building the Internet of Things: Implement new business models, disrupt competitors, transform your industry."
Learn more about Maciej Kranz: http://www.maciejkranz.com/
Cisco's Corporate Strategic Innovation Group is part of the Corporate Strategy Office. They're a team of recognized business leaders, distinguished technologists, market researchers, and innovation experts who are spread across more than 12 countries and are focused on acelerating breakthrough business and technology disruptions at Cisco. They do so by ignoring silos, bypassing traditional innovation models and bringing partners and customers closer for co-innovation.
"One of the main reasons why we look at integrating IoT technologies into business as a journey is because you're changing so many parameters."
"More and more companies think of themselves as data companies versus a robotics or a car manufacturer or even oil and gas company."
"I basically tell people you know stop talking about how many billions of devices we connect. It's not relevant. What's relevant is what business problems we solve."
Welcome back to the industrial IoT spotlight. I'm joined today by Maciej Kranz.
Maciej is wearing a number of hats he is the vice president of corporate strategic innovation group at Cisco Systems. He's a faculty member at the Singularity University a senior adviser to Acreto, adviser as well to Foghorn systems and a member of the board of directors of both IoTecha Corp and StarFlow Networks.
He also recently published a book on the topic of IoT and how it's changing businesses called "Building the Internet of Things: Implement new business models, disrupt competitors, transform your industry."
Maciej, thanks so much for taking the time to talk with us today before we kick off into a discussion. Anything else that you want to say around your background to frame where you're coming from in that in the topic.
Erik thank you so much for having me on on the podcast and the you know quite often enough when I when I sort of are having this conversation the first question I get is Oh Internet of Things it's about connected fridges and connected toasters.
And then we get into a kind of a technology discussion. But the reason I wrote the book and then and the reason I'm sort of on this quest of getting everybody started on IoT journey is that yes IoT is sort of the baseline about technology solutions but it really is about transforming industries transforming businesses transforming in a role that we play in our organization. So it's a catalyst for a digital transformation on multiple levels. And that's that's why I think it's so important that every organization with a small or large win regardless of the industry gets started on the IoT journey. So that's sort of my mission in life over the last couple of years.
Great. No high level you break it down into eight eight different aspects that need to be considered maybe that's a good starting point and we can dive into particulars. How would you break down the different aspects that business leaders should consider when transforming their businesses using you know the set of technologies.
Yeah I think the term you know if you haven't started the IoT journey I would sort of have an advice.
Put three buckets. The first one is it gets started with sort of a first project. And from that perspective don't reinvent the wheel. You know there are thousands of and tens of thousands of organizations that already started on the IoT journey and they usually are focusing on four four different sets of use cases. The first one is connected operations. The second one is remote power. The third is the predictive analytics the fourth on the preventive maintenance. So that's the first one is pick one of these use cases implement a success. The second one is some learn from your peers mistakes and the technology's challenges. You know in the book I actually have a whole chapter dedicated to common mistakes learn from your peers' mistakes and the third one is as well maximize your chances of success both with the first project but also in the long running throughout the journey by following what you've mentioned which is sort of my recipe for IoT success. And over there I sort of list sets for area as sort of eight areas. First one is building a partner ecosystem and learn to co-develop with them. The second one is to attract and train new and existing talent. The third one is focus on solving real problems. The fourth one is prepare for a journey not a one time event. The fifth one is integrate technology solution with business processes. Six started with low hanging fruit. The seventh makes security everybody's top priority and the last one transform culture with technology. They may sound obvious but I can assure you so many projects I've seen across the years that have not followed up one or more of these ingredients and they failed. So in a nutshell do these things. You are maximizing your chances so from a short term a long term success.
I want to get into a bit and you know how you walk. You know walk partners walk people that you're working with through this this journey but before we get into some practical examples.
You called the IoT journey a lot of other people around IoT they used this language. This is a this is a journey right. This is a long term transformation. You don't hear so much the same language with you know cloud your you know you go into the cloud or with me even with big data or something which is let's say also there's a lot of a lot of hype or a lot of expectation around it. Why is this sort of IoT technologies different in terms of the impact that they they may have on organizations.
I think for me it's probably less so technology is one aspect of it but if you think about maybe stepping back a little bit when you think about some sort of Internet the the buying centers and the people who have been adopting Internet technologies including Cloud are having primarily I.T. organizations service providers and obviously as consumers in many ways and often that technology sort of industries in many ways IoT is different because IoT technology actually is targeted primarily at the line of business buying center the folks that run businesses they run hospitals, oilfields, cities, stadiums agriculture organizations or and others. And. From the negative these folks actually care about business outcomes they care about you know performance they care about quality they care about top and bottom line and they look at that technology as a tool to help them transform their businesses rather than the rather than a focus on let them deploy the latest sort of technologies or solutions. So this the first reason the second one is again if you look at say 20 or 25 years ago when the Internet sort of went mainstream you know a lot of these industries that I mentioned earlier were not the sort of massive adopters of Internet technologies. So in some ways they still have a lot of sort of business structures for example around the vertical integration. They have a lot of I would say backward approaches from the technology perspective in terms of our proprietary business from a proprietary systems. The worker workforce relationships are different as well quite often in some of these industries you go into a job you stay in the same job for 10 20 years the job doesn't change very much. So the reason I mention all of these is it's not just that technology technology is the catalyst for much broader transformations. And as a result you don't talk about luck with cloud. It's the way the cloud and integrated into existing infrastructure. You have to change a lot of things from a technology from the business from the culture from the workforce relationship perspectives. In order for you to be successful and you can't just do it in one swoop you have to look at this as a journey. So it was one of the main reasons why we talk about a journey because you're changing so many parameters.
Okay it makes tons of sense. And this is perhaps one of the reasons that IoT has not been adopted as rapidly as the technology has advanced. You see a lot of new technology that's coming to market that on the face of it appears quite mature enough and it seems to make sense from a business model perspective. But often there are adoption barriers that are unrelated to the technology related to can you know do we have the competence to implement and to operate this technology. Do we have the competence in our procurement department to analyze and choose the best vendors or the best partners and so forth. How do you start a conversation with a company that's beginning this journey. If there's multiple parameters that they're going to have to consider and you're going to be talking to somebody that you know maybe they're in the C-suite and they actually do have control indirectly over these. Maybe they're below and they actually don't have control over all the relevant parameters. But nonetheless there are central starting point.
Good question. And quite often the conversation starts with let's see what your peers are doing. Let's go through 10 20 30 examples across the industries of how different organizations are using IoT to improve their operations or to start transforming their businesses.
And usually when and by the way the fascinating conversations are not necessarily within the same industry but actually sort of getting ideas from examples in different industries. And then once you've sort of settled on. Okay I think I'm going to start with let's say remote operations kind of a project. Then there are some of these best practices. One of them is sort of have a great big vision and big architecture but start small again because of number of complexities but also because you are starting on a change management sort of journey. And from that perspective you will have naysayers you will have people that will try to stop you. You will have a lot of silos you have to bridge. So sort of start with a small project get the success clearly articulate the ROI and then ask for permission to do more challenging projects and the more transformative as well. You mentioned C-suite. It's so important to have a C-suite's support again for the same reasons you are you're dealing often with the mission critical environments and you're transforming them so there probably will be mistakes. There will be and will be challenges there. Make sure that that you have a c suite support and people that stand behind you and then build a virtual team and establish partner ecosystem. So you know it usually. So the areas that I would I would have a conversation with how to get started and then and then once you've build this virtual team build the ecosystem get the first project to get the first success under your belt and then you will be off to a journey great.
And is there a case that you could kind of walk us through some that you've worked with and you can anonymize the name of the organization if necessary. I mean I think it's you know it's useful to have kind of a concrete example of a company where they started what challenges they faced and then you know how they how they walked around this.
So I mean I can if we have time I can actually I can actually walk you through one example of each of these for use cases that I've mentioned. But but I can start with one which is around connected operations so Harley-Davidson. An iconic brand obviously of manufacture and the whole proposition is based on sort of a custom right.
Each of the of the buyers and drivers want to have sort of a special breed and special configuration of a custom bike.
But before IoT it used to take Harley up to a year and a half up to 18 months from the time you would want to place an order for a new configuration to when they deliver the product. And the reason for it is that they actually have any sort of operating what I jokingly call an archipelago of data islands even on the plant floor. They had different stations that were not connected, the data was not flowing. So as a result the process were very sort of sequential and very manual. And the same goes for for the rest of the other sort of a value chain from from altering all the way to delivery. So in this case a couple of folks from different walks of life in one of the plants in the US got together and there was an unusual batch. So there were folks from operational technology I.T. and logistics and finance. They got together in one room and said OK let's fix it let's improve our operations and. And they started by basically connecting all of the devices and processes within this one plant on one network putting the automation and optimization analytics software on top. And then they sort of started expanding beyond that plant. So the long story short when the data started flowing they were able to start optimizing their processes. They were able to reduce the time for a new configuration to get interviews from again as long as 18 months to two as little as two weeks. In the process they were able to reduce the time to troubleshoot problems on the manufacturing floor from days and weeks to minutes and probably equally significant they improved the bottom line by a 2 to 3 percent.
So that's one example okay great.
You said this was not so much started from a board or C-suite and you said this was a group of operational leaders that got together to brainstorm.
So there was very much an example of a bottoms-up sort of approach. But I can give you maybe another example in this case was predictive analytics so maybe again DNA in a sort of manufacturing industry. So I this case General Motors they use around 30000 robots mostly from a company called FANUC a Japanese manufacturer. And typically how the robots are installed on manufacturing floor is that the funnel will come in the configured robots and they sort of say okay call us if you need help. Right. But GM found in a couple of other companies. OK. What if we start connecting these robots that we can start getting real time data and we can start looking at configuration and tradeoff between use of material and how we use the robots and then they did that they had to connect with roughly half of the robots so far. And as a result of being able to analyze the data General Motors reported that they were able to anticipate and actually reduce the number of stoppages of other production lines by around hundred and on average at a system wide basis each of the lines stoppages cost the company two million dollars so they can do it. Obviously easy math. GM was able to solve or save 200 million dollars by implementing the zero in your downtime solution. So this was sort of a top down sort of bottom up approach.
Great, maybe just a little bit of a detour on this question but I'm sure the producer of these robotics also has an interest in that data because that can even get back into their production in their own D and so forth. How have you seen it. I think there's a very common question right now and there's multiple people who can find use and data. Once you give data away it's very hard to track how it's actually used and yet there's proprietary aspect to it. And how have you seen this managed so that you can maximize value and minimize risk so to speak.
And I think that you know there are a lot of cliche statements about data these days right. But I think that approaching data strategically is sort of the first aspect of it. And at the end of a day more and more companies think of themselves as data companies versus a robotics or a car manufacturer or even oil and gas companies. So thinking of using data judiciously and to your point. So controlling they use an access is key. What I've seen is that again sort of the first one is sort of making sure that the data is properly collected and stored there are use cases like for example oil companies right now unless some of their seismic data from 30 years ago because now they have more modern ways of extracting oil but also a lot of data is sort of data in motion. It's a streaming data. And how do you actually get insights from that data before the data is basically becomes too old and that sort of loses value. But then to your point also there's a question of how you get access to the data for the vendors. So like for example Cisco we deploy our routers and switches throughout our customers in environments and many of our customers give us access to that data from from these routers and switches, not sort of the payload but the data that allows us to help troubleshoot and help anticipate problems with the network before they occur. So from the serviceability and from the management perspective there are also aspects of data becomes sort of from the privacy and security perspective. Right. And not only how you clearly communicate sort of what data what you would be doing with the data and how your data is used but also sort of on making sure that the best practices are being followed.
So. So great question a multifaceted question.
And he said there were two other use cases that you had in mind.
Sure. So probably the most popular use cases I've seen is remote operations or remote Asset Management. Now lots of great examples here because I'm not sure they'll have to come up with a sort of a system wide solution in this case you can have a surgical solution to solve a particular problem if you don't mind I can give you a completely different examples of them or sort of the industrial world. So in this case it's a hundred and fifty store ice cream chain in central India. And the problem they had was that they had power outages over there and then they sold the generators in the generators in the stores and then sometimes there's a power outage at night or managers don't turn the generators on. And as a result the company was losing money because the ice was melting. More importantly they were creating a health hazard by freezing and refreezing icecream. So in this case a very simple solution. They worked with one of the local startups who dropped sort of self-contained temperature sensors in each of these fridges connected them to the networks and then connect them to that sort of a communication system.
So now as temperatures start to go up the employees and managers are getting messages through loudspeakers and SMSs and phone calls hey do something maybe you need to close the door or you need to turn the generator on if the temperature continues to go up. These messages will get escalated all the way to the CEO. I get a very very simple solution but what I loved about it is it sort of underscores the point of being hyper local because you actually need to think about the environment you're in. What problems are you trying to solve versus let's say plopping a solution developing in Silicon Valley and dropping it in India and hope it works and the other way was also very powerful in this company you actually saw 100 percent return on investment in the first year of operation of this system and the last sort of set of most common use cases that I've seen is around preventive maintenance and we've seen the preventive maintenance solutions in manufacturing and the utilities in agriculture. But the example I'm willing to give you is from from my mining industry. So if you don't know if you've ever been to the open pit mine but it's sort of been a formidable site. You basically looking at a hole in the Earth two miles across one mile deep and there these little specks going around the edges and the specs of these huge holding trucks that basically have tyres taller than a human being and they basically carry iron ore or other minerals to the to the station and the ports. And every time one of these vehicles breaks down it's cost the company on average two million dollars of lost revenues per day. And by the way the only way to pull out this vehicle is to use another of these huge holding vehicles which the bill doubles the cost. So it may it may take days or weeks to figure out what the problem is how to autoparts get the parts in and fix the problem. So what the company did they installed a bunch of sensors around the vehicles started collecting data feeding the data into the machine learning systems and then basically providing predictions. And initially these systems when I got involved were providing roughly 80 percent of accuracy three months in advance meaning 80 percent of problems were sort of predicted up to three months in advance. But as the system started to learn more in some cases we can get to high 90 percentages of our of challenges meaning these vehicles will always get fixed before they could break down and very rarely they break down.
Okay perfect. Let's go back to the third one because I think this is a really interesting point that a lot of the companies that are driving the economy are small relatively unsophisticated companies from an IT perspective. And if they're faced with you in a you know a say GM style you know kind of top down implementation it seems extremely daunting. In these spot solutions the one that you mention excellent example of the mentality of let's do something simple to implement a way of solving a very known problem and then you know hopefully generate some data and that data might then be used to ideate and identify additional problems that can be solved and you can build on that as a foundation. I had a question I was you know in a podcast yesterday.
But as the interviewer and somebody asked How can Smart Cities connect everything or that was the gist or what is the strategy. And this is a problem in mentality of why do you want to connect everything. Why not identify what are you or your you know long term problems as a city and then say you know has technology evolved in the past three years that now allows us to address this problem in a new way and let's solve that problem. I'm interested in your perspective on this I guess the high level you know how do corporations make the decision between when is the right time to think big and implement a corporate wide solution. And when's the right time to think fast and implement a spot solution that solves a specific known problem.
Yeah it's a great question. And you know going back to the smart cities is sort of funny because I worked for Cisco. And so you know we posed to build networks. But I I basically tell people you know stop talking about how many billions of devices we connect. It's not relevant. What's relevant is what business problems we solve. We know that connecting things just for the sake of connecting them we connect them because they become basically they allow the data to be to get generated generated and and and and connect it from the devices and we can analyze the data and turn them into solutions. So in this case you know if look at smart cities as an example we've talked about smart cities for ages but what has been a challenge for smart cities is basically coming up with the use cases that were actually relevant to the cities. And so these are complex from the ownership and the. And the sort of the right of ways perspective and so forth. And in North America and in Western Europe we basically focus on as we sort of use cases it was either parking second or third generation second or third term revenue. Most important revenue streams for the city lighting because one of the biggest expenses for the city or our trash bins are trash trash pickup. And we can get into these use cases. But but each of those basically had a clear return on investment. And once you deployed a citywide infrastructure and network for one of them adding an additional use case was relatively easy.
So if you think about you know if you think about that again the journey with the enterprises is I would typically argue that for your first project you should actually start with something very sort of focused like this ice cream example. Right. Because because again you're trying to minimize the vectors so far of sort of variability here. But at the same time we're also seeing a lot of examples of companies for example coming up with the automation system in one factory in a different automation system in different factory and that when you actually want to build a system across the factories they actually have to redo things. So once you've done you sort of start on your journey you have a team you have established process you should be able to take calls that are as they come company wide projects and then build a comprehensive architecture and so forth. So to summarize I think when you pick sort of a very surgical standalone projects make sure that they don't that they don't require for you to basically go back and redo these projects two or three years later. So pick the ones that you can then integrate into a broader set of architectures and ecosystem is as great I was interviewing gentlemen from PTC Thingworx.a few months ago and he made the point that he advises. You know people in this space too. It's a think big but smart small meaning you know think first around what you know what system might hypothetically be useful and then you can start to address issues like standardization of automation system across factories and so forth and then just start one but at least when you start that that small project you have in mind kind of the larger scope and you can hopefully have some foresight into this kind of duplication challenge and so forth.
Competitive disruption this is one of the topics that you bring up in your book. We've been talking a lot so far about solving problems. Often these are the problems we've been really focusing on so far are often cost based. And we've seen now some significant examples of disruption a bit more in the consumer space the Ubers what do you see in the industrial space in terms of either today or in day let's say the five year time horizon in terms of the opportunity for competitive disruption of revenue models due to IoT deployments.
Yeah great question. And we've already seen a lot of disruptions happening today.
So I'll let me tell you sort of what I see today and sort of what that that how we see sort of these things project into next five years. But what I see from the disruption perspective is first of all the disruptions are sort of established market structures. So if you think with a lot of industrial world like for example automation, industrial automation traditionally these types of markets and automation is roughly 200 billion dollar market have operated as sort of one company developing the entire solution. So if you wanted to set up a new factory or build a new train station you would go to one vertically integrated conglomerate and they will develop the entire solution from A to Z using often proprietary or some proprietary technology. But with IoT and the sort of accelerated cycle of of technology innovation we now are seeing customers increasingly asking the question is like why should I be paying a premium for a custom solution based on yesterday's technology and instead they are these customers are inviting specialists whether they are horizontal specialists like Cisco or Oracle or Intel or SAP or others. The vertical specialists as geographic specialists to work together in developing best solutions based on open systems open standards open architectures in some way. I also futureproof as well. So that's one big change. The other big change I've seen is sort of a balance of power. We traditionally have seen of customers buying technologies and solutions from the vendors. But increasingly what we see is customers actually don't want to just be buyers they want to co-develop these solutions with you. Actually makes sense right. The customer actually knows what problems they have and their environments and technology providers also are sort of experts in their technology. So by doing things together by co-innovating and co-developing together what I call a co-economy. We're getting the best of both worlds.
And then there's business model disruption.You know a couple of years ago we did a study we reached out to some of our leading IoT customers and we asked them why the transition from the product or service or the business model and the roughly 80 percent 86 percent of them actually said that they were moving towards a service oriented business model.
Why. Because now they can have all the data coming from the from their operations and they can make an intelligent decision that instead of let's say building a new plant new assembly line the can just you know buy capacity that they need and and basically bring the savings down to the bottom line. So. So if you think well that's sort of what's happening today. But what I see happening in the future one is we already seeing some merger of our technology industry and transportation industries. Basically every industry becoming technology industry and we see some interesting correlation between let's say retail and manufacturing. So that's one trend. The second trend is new value propositions. When you think of a Harley Davidson example they are a custom bike manufacturer. But increasingly what you're seeing is sort of the benefits of mass customization, mass personalization and the cost of these actually being almost the same as. So your model T approach to two products.
And then we see new industries being created the combination of IoT and AI and blockchain and fog computing creating industry and of enterprise drones for example.
And and then of course are the migration to a new business model.
So you know it's sort of funny because as as much as I'm sort of invested in the IoT success I actually hope that five or maybe seven years from now we actually don't put IoT anymore like with e-commerce 15 20 years ago nobody liked e-commerce anymore it's just part of everything that we do.
I hope that with every company large and small in every industry sort of starts adopting IoT as part of Operation and in five years when you and I are having this conversation we'll just say remember the discussion about IoT it's just part of the process. And we take it for granted.
Great. No I I agree that we have IoT in our name so we may have to be right. I'm sure there will be a new term that we will welcome and rally around.
Last last question and you've you've participated in the many many deployments. It sounds like a good number of them have been successful although I think Cisco actually released a report earlier in the direct estimate with 75 percent of IoT deployments had failed to meet their objectives yet. Yes exactly. So what advice would you give an organization that starting this in terms of taking their first steps wisely in order to minimize the you know the risk of failure.
And you know I sort of mentioned in the beginning of a conversation. But I think it's so important that first of all get started. Second don't be a hero don't reinvent the wheel. We've discussed these for different use cases that are across the industries most common use cases that your peers have already using so connected operations, remote operations, predictive analytics, preventive maintenance pick one of them and get going. Thirdly sort of dream big but start small gets support from your CXO and build the ecosystem and build a team. Fourthly learn from your peers mistakes. Because like with any new effort there will be mistakes and most likely some of your some of your peers have already made these mistakes. And lastly we started with this discussion around the recipe for IoT success. Use this recipe because it's based on sort of sweat of many deployments and best practices. And if you do that you will maximize your chances of success.
You know and maybe the last point is this type of journey is a team sport.
It's not for loners it's not for sort of you know lone innovators in a garage. Right. So I approach it comprehensively. Bring your company your industry your peers with you on the journey. And that if you do all of these things I'm pretty sure your product will be successful and then you will not look in the rear mirror, you will just charge ahead.
Great. Great answer. Thanks so much for taking the time to speak with us Maciej and thank you so much Erik.
I really enjoyed the conversation. How can people learn more about the work that you're doing at Cisco learn about your book reach out to you.
Sure. So I would suggest OK you can obviously read the book it's on all the major retailers. I also have a website. maciejkranz.com and also the LinkedIn group. So we actually have a little discussion on the building the Internet of Things LinkedIn group of other best practices and exactly the topics that we discussed here as well. So so go read the book. Join us at the LinkedIn group and ask for advice and help.
We are here to help you be successful. Alright perfect when we'll get those initial notes. Thanks again. Have a great evening. My shark. OK great but really thanks a lot. I appreciate the time. Yeah likewise. Great conversation thank you so much. They can buy me.