(synth music) >> Announcer: Live from Atlanta, Georgia, it's the Cube. Covering IFS World Conference 2018, brought to you by IFS. >> Welcome back to the Cube's live coverage of IFS World here at Georgia World Conference here in Atlanta, Georgia. I'm you host Rebecca Knight, along with my cohost Jeff Frick. We're joined by Tobias Persson. He is the IoT Services lead here at IFS. Thanks so much for joining us, Tobias. >> Thank you, it feels really nice to be here. >> So, I want to start out by having you explain to our viewers what you do at IFS as an Innovation Service Lead. >> Yes, I'm heading up the IFS Innovation Services Team that came to official existence in May last year. It's there because of the fact if we want to get the IoT message out there, we want to be out there to mission about IoT. Actually helping our sales and presales to do the business discussions with people, with our customers, that is. As well as actually implementing solutions, rolling them out. So, we're kind of like from idea, talk to the customer, to real roll out, that's what my team does. >> So, you said you want to get the IoT message out there. >> Yeah. >> And what is the IoT message, from the IFS vantage point? >> Well, coming from a tech background myself, I've been involved in IoT space for quite some years, and the biggest challenge or difference between normal IoT and IFS IoT is the fact that you can actually do something with the data itself. Typically, when you're talking about IoT historically, it's driven by R and D. It's not a strategic effort at all. It's mainly done to figure it out. And IoT has taken some steps since then. And we're providing a way to actually short cut your IoT data directly into your most business critical system. And doing something with it, providing huge efforts and benefits off the bat. >> And you guys are really integrating IoT into the existing applications, existing workflow, so trying to grab that value, not as a stand alone science project, or something that's on the side-- >> Tobias: Yeah. >> But really integrating it into your existing applications and the existing work-- >> Tobias: Correct. >> That those existing applications are managing. >> Tobias: Yeah, that's true. >> What are some of the impacts that you've seen? Or, I guess, some of the customer impacts that they've seen? >> Well, it's all about automate step, in a sense. At least, that's the first step. I mean, we have seen customers just taking the data out and getting the running rs out, for example. That has huge implications on the amount of time you spend entering stuff, as well as having the data with quality so you can do something with it. But the biggest thing is, really, to automate stuff. Like send out a work order, for example, automate that. Or send out the replenishment for some consumable or whatever it is. So, anything you can run or post or trigger in IFS applications, field service management is actually triggerable by IFT observation. >> So, can you describe to our viewers how the process works. I mean, I know that IFS really prides itself on being so customer centric. >> Tobias: Yeah. >> So, how do you work closely with customers, from the very beginning, from the idea to the actual product and implementation. >> Well, taking it from the start and from the top, we obviously have a full set of IoT industry directors that are really skilled and seeing what's next for the market, being out there to communicate the message. Serve the station is obviously one. Digitalization is another one. So, we're talking about this in all kinds of places, right? My team comes in, kind of like the second stage, where the sales and presales have done a demo with the generic tools that we're providing them with and taking the discussion from there. And we're usually building something that is quite specific for the customer, using their data, really any kind of data to prove the point. Some kind of power BI dashboard, some kind of of actual IT observation going out. And the thing is, when we do that, they tend to really get it when they see things coming in from the physical world into their, this will be your FSM or applications environment. And they see an observation comes in and suddenly, boom, that's an action going on. So, that's what we're trying to do. And we're involving ourselves quite heavily in how to define what's your IT use cases, running workshops with customers, and pinning it down. It's not rocket science or anything, but it's kind of our own methodology to pin down what's your first step? What's your IoT use case that you aim for? And how do you plan to get there? That's what we're trying to achieve with our team. >> Has it been an integration challenge to go to devices and sensors and kind of the IoT world and to plug that back into the application? >> Well, that depends a bit. I mean, our application, our solution is really dependent that it's getting sent the data. Or actually picking up the data from a API or a database. We haven't seen a project yet where we're actually picking up stuff directly from the assets. >> Jeff: Okay. >> What we usually see, though, is that the customer has taken that step already, so they're getting data into some kind of... It could be a printer management system, it could be a whatever management system, and we're getting it from there. We are talking to partners that would allow us to get the data strictly from an industrial context, and industrial protocol, a specific machine, whatever it is. But as of now, we are reliant on the fact that somebody is sending stuff to the IoT hub-- >> Jeff: Right. >> Which is the official usher component. >> So, you're just really taking advantage of that data flow that's already there and really adding an extra layer of value-- >> Tobias: Yeah. >> That they can extract by pumping that into your application. >> Operation allows the whole thing, yes. >> But that is really the key-- >> Yeah. >> The differentiation, is that you're not just seeing the data, you're now saying, okay, what is this data telling us and now what do we do next? What do we do with it? >> Tobias: Yeah. >> So, can you give us a real specific example with Anticimex, and what-- And this is the rodent control, pest control company. And how this company is using your product. >> Yeah, I mean. >> Rebecca: And seeing a real return. >> Yeah, from what I know, Anticimex Finland has deployed this, they have about 3,300 traps in effect out there, at the moment. And they're using this for, well, the traps are connected, obviously, so they send the data, for shots fired, how full it is, battery levels, stuff like that, to do the IoT solution. >> Rebecca: Shots fired, I love it. >> Shots fired, yes. (laughs) So, it's not like a single off, you have to empty it directly, it's kind of a pressurized air container, doing all kinds of killings in a row, if you will. And you need to know how are my traps doing? >> So, it's really, again, just a another layer of efficiency improvement-- >> Yeah. >> By, not just setting and coming back after so much time, but actually having the data for the activity in those traps. >> Yeah, no, they are really, in a sense, they have opened their eyes. They know how their assets are doing. They know when they're full, they know when to pick it up and even if they don't have to go there today. That's also good information for which they need. >> Jeff: Right, right. >> So, they're doing this to optimize their service visits and doing like a full automated work order flow. I think the statements from Jussi Ylinen, the managing director of Anticimex Finland that will be here as well later on, they have been doing something like 6,000 automated work orders in the last six months. Which is a huge productivity advantage. >> Jeff: 6,000 automated ones. >> Yes. >> So these are ones coming directly out of the system, based on the feedback from the IoT. >> Tobias: Yeah, not passing any employee at all. >> Wow, that's a huge number. >> How revelatory is that, for a company to have all of the service visits be automated? How much of a change is that? >> I think it's huge, actually. I think it's quite easy to imagine that would be a good idea. However, until now, it's been kind of a hassle to get there. I personally do think that there our solution provides that gap and services as a short cut, as I mentioned before, to get there. >> But I'd imagine, too, it's a process flow on the customer's side, too. Because they got to, now, accept the fact that they don't know exactly what the schedules are going to be for the next several weeks or for those days because they have to allocate some portion to the automated process, or they're feeding that in at some level, upstream, to make sure that gets integrated into all the rest of the activity. >> Well, you could have, if you wanted to, manual intervention in all stages, if you want to. You need to, probably, if you need, if you're on an oil rig or something, that you have a critical part, automated order coming in, that should be accepted by someone along the way, that's perfectly fine, as well. So, it doesn't have to be fully automated if you don't want to. >> Jeff: Right, right. >> But it can be. >> So, I know that you're not only an IoT evangelist within IFS, you're an IoT evangelist in general and in your professional life. >> Yeah I hope so. (all laughing) >> So, can you talk to us, big picture, big strategy, where you see IoT going in the world but then also as it relates to IFS? What does the future hold? >> Well, the easy answer is, you may have seen the old commercial where they state, well, we need to be on the web. Why? It doesn't say. Well, that kind of, you know that you need to consider this. But you don't really know how to get there. That kind of approach is somewhere along the line where we are right now with IoT. I mean, we used to be something like a buzz word. People tried to figure it out. Nowadays, it's more like people have taken steps, they have the data somewhere. It's usually stored somewhere in some database or some system or whatever. But it's the actionable part that's missing. I don't think people actually tend to look for the actionable part in a ERP company. But that's actually what we're providing. So, I think in a few years to come, it will be seen as suspicious not to have your stuff connected, not to have your open data. Instead of being the other way around. I think this will be a very natural part of not being blind to how your assets are doing. >> Jeff: Right. >> Why would you like that? That's the old fashioned style. So, I think this will be a very natural step in any kind of of product development of all service centric company in years to come. >> And do you think it's indicative of people accepting a lot more data sources into their decision making processing? >> Yeah. >> And adding that layer of automation? 'Cause a piece you didn't talk about, that's obviously part of that, is AI in some point in time, right? >> Yeah. >> 'Cause now, you got the automation, you got all this stuff coming in, you can't send the entire fleet out tomorrow if you only have x number of vans and you got x number, 6,000 service requests. So, then you add that AI component, the machine learning component, the prioritization component in, again, moving more of this manual scheduling process or routine, scheduled maintenance-- >> Yeah. >> Into a much smarter way to execute the details. >> Yeah, it's all in the step of going from data collection, data acquisition, figuring out the technical stuff behind connectivity, getting the data out. And now with the next step when the revolution comes. How do we approach that? With AI, with machine learning, with actionable insights, whatever. And to be quite frank, I don't think people necessarily don't want to see that. They want to see what comes out of it, but they don't want to see behind the curtains on that. >> Jeff: Right, right. >> So maybe, just maybe, in the near future, people will need to bring in someone that knows machine learning from A to Z in the companies. Or at least use someone that does their insights for them. >> Jeff: Right. >> So, how will IFS expand it's IoT offering, at the next World Congress next year? >> Well, as you know, we have had a few early adopters adopt the program for IoT, yeah. And they seem excellent and they're actually being the first ones out, they're live right now. They have a really good story to tell. So, that's good. In a sense, we are taking it from the heavy asset centric, from our rig, that's one part. We have taken some steps. Service is the next one, being Anticimex in Kucera. We believe that connected field service is the main thing to go for. The real good IoT use cases is for connected field service with assets, or sending data throughout. And, to me, the next strategic step, since we are having a whole lot of revenue coming from manufacturing, is actually connected manufacturing, or connected manufacturing lines. Industry four point zero, whatever you like to call it. That's our next strategic move with IoT, as I see it. >> The lines have been connected for giving data, but not necessarily for actionable data back into the lines, right? That's where the really big change is. >> Yeah. >> For the automation, automation back into it. >> Yeah. Automation, you have the full scale automation, pyramid where you have the POC that runs the low level control system. Then you have the scale down, the many systems as well. The thing with IoT is not only do you get the data for specific assets, you also get the full picture of like, how are my factories doing? On this level to this level? So, we come small, like a less operator, more kind of strategic view on the whole thing. >> Jeff: Right, right. >> But you need to be able to get the data out from different levels. And actually access it and make sense of it. >> Jeff: Right. >> Which factory is doing best? For example. >> Jeff: Right, and what are you managing, too? You're managing to the device you're managing to the whole output. >> Yeah. >> So, maybe based on economic factors, you want to run things hard, which is maybe not optimal for maintenance but because of the economic situation-- >> Yeah. >> You're going to press it. So it's really, that variable management opportunity-- >> Absolutely. >> Is a very different way of kind of looking at your output. >> And one way, one view really-- >> Jeff: Right. >> A scalable view, really. There is a stand just behind us, where we'll show a an industrial demo, together with Accenture, which will actually trigger a service request from a physical device, an engine, in this case. That goes into the system, the IFS system, that is actually scheduled, sent the repair guy that comes out, wearing a whole lens and fix the issue. >> Jeff: Right. >> So, that's an end to end thing. It's actually manageable and doable with our solution. >> Jeff: Great. >> And that was one of the things that the CEO talked about during the keynote too, is that it is automating certain tasks, but then really leaving the more unique tasks up to the human and the human connecting. With machines and also with other humans. >> Tobias: Hmm. >> So, tell me a little bit about differences that you've seen in the market. So, IFS, based in Sweden, many of its senior leaders in London, but of course, you have places all over the world. Do you see any differences, in terms of the customers in Europe versus the US? And how you're thinking about maybe making a bigger push into the US? >> That's a really good question. I'll have to think about that for a while. (All three laugh) I think what we are seeing in my team, at least, that's kind of on our horizon, is that Germany in general are heading toward industry four point zero, that's kind of a really hard driving fact. That's stated even by the government. So, we need to get into that, as well as pushing for field service management as a solution. US, I think, we should be doing more in. Let's put it that way. >> Great, great. Well, we look forward to hearing more about what you are doing in the US. (All three laugh) >> Jeff: More. >> Exactly. >> Jeff: That's a good thing. >> Tobias, thank you so much for coming on the Cube. We've had a great time with you. >> Thanks for having me. >> Jeff: Thank you. >> It was a pleasure. >> I'm Rebecca Knight for Jeff Frick. We will have more from IFS World here in Atlanta, Georgia just after this. (low energy techno)

>> Live, from Atlanta Georgia, it's the Cube. Covering IFS World Conference, 2018. Brought to you by IFS. >> Welcome back to the the Cube's live coverage of IFS World 2018 here at the Georgia World Conference Center in Atlanta. I'm you're host, Rebecca Knight, along with my co-host, Jeff Frick. We are joined by Peter Scheltus, I hope I'm saying that correctly. He is the global strategy and sales director enterprise operational intelligence here at IFS. Thanks so much for joining us, Peter. >> Yeah, thank you for having me over here. >> So let's start this interview by having you tell our viewers a little bit about what you do at IFS. >> Well, our product actually is a very cool product if you want to improve your business. And, I'm talking business, not IT. We use an IT tool for doing that, but we are supporting managers to make better and faster decisions. 'Cuz in the current environment, current world, change is everywhere and change is coming more rapidly than ever, whenever. And what we do with IFS here, why we create a kind of a digital twin of your organization and to support all the managers in your organizations to make better and faster decisions, connected to each other. >> It's interesting the digital twin concept 'cuz we see it a lot, like G.E. uses it a lot. We make a digital twin of say a 737 because one of those operating say out of Dubai is very different than one of them operating out of Alaska, so they can run tests and stuff. I've never heard anyone say a digital twin of an organization. That's really a novel approach. So, how do you do that and what are some of the benefits that come out of doing that. >> Well, yeah, that's a good question. When you talk about a digital twin, there's a reason for having that. And you think about complex assets, and what you'd like to do is not only look at the asset, but would like to do predictive and even prescriptive. And the question mark if you're looking to organizations, they are complex as well, but they are not that visible. And they are not tangible. It's about people, it's about organization, it's organization charts, it's about processes, it's about systems, it's about risks, it's compliance, finance, whatever. Everything, projects, programs, so I can continue with that. But the question mark there, and all those elements are connected to each other. But how can you as a manager, if you have to manage that all, how can you make a good decision then? If you don't know how it looks like? And, what we do is, I actually visualize those complexities and bring that to the end-user, and the end-user in this case is the business owner or actually a business guy working in an organization, so he's capable of making those better decisions. >> That's the enterprise operational intelligence, or the EOI. >> Yeah, this is how we call it. >> That's what we call it. And then when you're looking at this complex organization, the digital twin model, can you kind of switch what you're optimizing for, 'cuz that's always the big question, too. What are you optimizing for, because then you might turn your levers very differently depending on profitability, speed, there's a short-term opportunity, a lot of complexity. in what are you actually optimizing for? >> Yeah, for sure. I mean there are so many elements connected to each other, so it is complex. And what you do see is that you have the classic BI tools and the classic data discovery tools, and what they do is they create pictures out of the data, because there are so many sources, where's so many data, but we do it a different way. We do it a different way for a reason because it's not about the target to make the data better, it's about making your business model better or your company better. And then we start actually modeling your organization, and plotting actually the data, not only financial, but also strategic and operational data, and even also risk and compliance data to the business model. And then, we have the platform, with having included three different engines, which is actually a model engine to create the model of the company. We have a data engine to work with all the data coming from all the different sources, and we have an execution engine, but it's all embedded in one platform. And it is integrated by design, And with sorry, but one more thing to add, which is realLy cool, is in the end, it's not only backwards looking, but due to the fact that we have the execution engine, you can even put basis rules on top and algorithms to go to predictive and even to prescriptive decisioning. >> I'm reacting because you keep talking about the visualizations. I'm always struck by the beautiful visualizations that come out of a lot of these tools. And they're pretty pictures, and they're kind of complicated, but so often you look at them, and you're like, so what am I supposed to do? What am I supposed to do now based on this beautifully complex picture, and it's not usually very obvious, so delivering actionable incites is very different than just creating a beautiful visualization of a bunch of data. So, what are some of the ways you help people actually make decisions? >> Well, there are two elements in and one element is of course, I'm talking about role-based cockpits, so per role is different, so you get actually what you see. I mean if you are the CEO or the CFO or you are team leader or whatever, you know what your work is, I assume. Then you give them the picture they want to see, so we have multiple pictures we can show. That's one thing. But in the end, it's about people. People have to do something, and people have to change. And what we have experienced over the past years is if you give somebody a tool, just a cockpit, and nothing hasn't really changed. So what we are a big supporter of is also to bring in and kind of a performance coach. And a performance coach is different role, and sitting next to whatever, a manager, and explaining and working with him together, what is it what we see? What can we do about it? How can we improve? Where can we lower costs? Where can we improve value? Where can we find it, so, kind of a performance coach is really important in the implementation approach. >> Do you see that there will always be a need for a performance coach? Or does the performance coach help the user understand, oh these are the questions I should be asking when I see data that looks like this? I mean, what's the evolution there? >> Yeah, it's really interesting. It's not always necessary. Of course every organization does have it's own majority, and if organizations is already quite performance centric and know how to work with metrics, the performance coach is not even needed. But you have all kinds of different organizations. So most of the time we just advise to use it as well. But again that's step by step. Think big makes more steps. So it's a agile approach as well. >> I'm sure the performance coach will eventually get baked into the software where it tells you if you tweek this lever here, it's going to that impact. If you tweek that lever here, it's going to have this impact. We see some of that in kind of the sports fitness devices where now there adding a smart, software driven coach beyond just telling you that you ran four miles or whatever. So, I would imagine that's got to be something you guys will implement because you've got the data. You know what the factors are, you've got the digital plan. So any good examples that you can share of customers who are starting to put this into practice and some of the results that they're getting. >> Well, we have quite some customers over the world, actually all kinds, well not every country in the world, but or region, yeah, definitely. We have them from power plants up to financial institutions, up to airlines and everything in between from manufacturing, et cetera. What we do see is that when you start with the EOI concept, we start most of the time with the board, because if you want to improve your organization from strategy to operation, that should be really bundled so that people do the right things. But if we don't get a clear view on strategy, how can you expect that all the operational people can do the right things? So that's how we start and you work with that and you have those first benefits, which is already after a couple of hours. While having the most nice example, if I have board, and I give them all a white piece of paper, and ask them, can you write down the strategy of the company and I get five different back. And we just say, it is important to have strategy connected to operations, how can we start change there? So, that's the way we start it. And then you already see benefits there. But during the process, and with the model capability of the platform, by bringing more and more into the connect cockpits, the more you see and the more benefits you'll have. So we have examples of total productivity of a company in a power plant of increasing 20% productivity. >> 20%, wow! >> Yeah, absolutely. And we even have performance where we have 90% savings, 90% savings of getting all the reports in place. Yeah, that's a really interesting numbers, I can tell you. >> It's amazing how much inefficiency there is still in so many places that can be wrung out with the right kind of application and the right focus. >> Yeah, definitely. And there is a reason why there is that possibility because when organizations grow, they will be impacted on different, how do you say it? >> Departments? >> Departments, yeah, different departments. So, then you're lacking an in twins view, if everybody is looking in his own silo, which is a common nature of grow, but while having the connected cockpits and connecting the dots there, you find really money. >> That's what were lookin' for. >> I know one of the big objectives is for customers to be able to see results right away and to see benefits right away and that was also a point that was made in the keynote by CEO Darren Roos, is this real time to value the customers are looking for. Do customers have almost unrealistic expectations though because of this 24/7 world that we live in, that they are going to see something right away, this return on investment. And is that ever a challenge that you're trying to meet? >> Well, not really. You can expect it, but up so far, and we're quite busy for several years right now, it was always the other way around. So, the customer was like, "Uh? Wow! Ooh!" (hosts laugh) >> So, they didn't expect us, and that's what I like then see you coming, and then bang, the result is there. But as I said earlier, "Think big, but make small steps". And then the old implementation approach, and the model-driven nature of the product, gives us the opportunity to work work in sprints, because I don't believe in waterfall approaches, or blueprinting organizations because what happens today or tomorrow, we don't know, and well, how can I handle if I have to do blueprinting up months, you don't know what's happening. So that's why we have a very agile approach and the sprint methodology in the implementation, and every sprint is actually a business case in itself. As one example, we have now, with a service customer in the UK, we even have a cost-savings of 27 million pounds over a couple of years, and it's not my mats, but there were their own figures. So, they figured out like that, so that's good. >> It's a journey of a thousand miles starts with a single step. >> It is isn't it? >> It's such a simple concept of a lot people are still baked into this, "I need to define it, I need an MRG, "and a PRD, and we're going to put this big implementation" and that's just not it. Just do, right? Just move a little further, 'cuz you're never there anyway, right? >> Exactly, it's a transformation path, but it's a daily transformation. >> I'm wondering if you've observed any ancillary benefits of this digital twin concept in the sense of encouraging more experimentation in companies? As Jeff was talking about, "If I move this lever this way, "and this this way, if I make this tweek, tinker here or there, are you seeing that in the sense of companies, and individual employees, just being more willing to try things? >> Yeah, but it's very depending on the type of organization. I have to be honest. But yes, I do see, of course, people are used to get their information. The early newspapers, less and less newspapers on paper are there, and so, which is helping to use cockpits on a digital way. But the thing is, and that's very interesting, if we all walk the same way, and that's the funny thing is if you do it on the approach like the EOI approach, from a strategy to an operation approach, instead of making pictures out of data, then you direct everybody in the same way. And in every organization, you have people, they walk like this, people they do like this, and it's a combination, but the interesting thing is, if you all walk the same direction, then the benefit is bang, it's massive. And that's really interesting because if you have people that walk the other way around, yeah. And that's actually the digital twin, and I think EOI in this case, if you talk about digital transformation. For digital transformation, you need a digital twin, you need IFS EOI. >> I need a digital twin. (hosts laugh) >> It's a great concept, again we hear it all the time in industrial devices as a really interesting way to model and test, and like you said, "Be predictive and prescriptive", but I've never really heard it applied to the application of an organization which is at least as complex as a jet engine. >> It is, it is! For people it's the blue worker and the white worker, and the color in this case, and now this is the next step. And it sounds logic, isn't it? >> Yeah! >> Absolutely! >> Yeah, especially when you start testing and tweeking things. >> And in the end, you have reality, and reality is changing. And then you have the digital twin. And of course, so the digital twin should be changing of course. If the real world is changing, and this digital twin should be changed. They're both connected, but if want to make scenarios and predictive elements in the digital twin, then the real organization has to change. And that's absolutely the next step, and we're just good at it. >> Well, thanks so much for joining us, Peter. It's been a really great conversation. >> Thank you. >> I'm Rebecca Knight for Jeff Frick, We will have more from the Cube's live coverage of IFS World in a little bit.