The IoT Show S1Ep6
ALLAN BEHRENS [00:00:29] Hello and welcome to another edition of the IoT Show. The IoT Show is looks at insights and interesting topics and aspects of technology as applied to industrial organizations specifically connected to the industrial Internet of Things. And today we're going to be talking about automation and the potential for disruption due to automation and its connection to the industrial Internet of Things. I'm joined today by three very wise and interesting guests. I've got Sean Dotson from RND Automation and Engineering in the US. Hi Sean.
SEAN DOTSON [00:01:11] Hi how you doing?
ALLAN BEHRENS [00:01:13] I've got Jordan Janeczko from Atos. Jordan, you're based in New York, I believe or the East Coast.
JORDAN JANECZKO [00:01:20] Uh no, Vienna, Vienna.
ALLAN BEHRENS [00:01:23] And I've got Tom Raftery from SAP, who's based here in Europe with myself, I am based in the London production headquarters. So welcome, gentlemen.
TOM RAFTERY [00:01:35] Thanks, Allan.
JORDAN JANECZKO [00:01:36] Thank you.
ALLAN BEHRENS [00:01:38] So I think the first thing is let's just introduce each other. Sean, why don't you go ahead and just explain yourself and your organization. What do you do?
SEAN DOTSON [00:01:49] Sure. So my name's Sean Dotson. I'm the president of RND Automation and Engineering. We're a custom machine and robotic work manufacturer here in the United States. We build machines that assemble medical device, defence and ammunition, consumer goods, pretty much anything. All but all of our machinery is custom made, purpose built for that customer.
ALLAN BEHRENS [00:02:13] Great, thank you. Jordan.
JORDAN JANECZKO [00:02:17] Yeah. So my name is Jordan Janeczko. I'm with the company Atos we're a fairly large I.T. company. One hundred thousand people worldwide. And a substantial portion of what we do is for the manufacturing industries are discrete and continuous. I personally am in the centres of excellence. And also in a group we call the scientific community that does a lot of work in the area of trends and innovation. And I'm involved there in both data analytics and robotics.
ALLAN BEHRENS [00:02:40] Great. And Tom.
TOM RAFTERY [00:02:44] Yeah, sure. I work for SAP, SAP is a large software vendor. We sell it backend systems primarily to larger organisations more typically. I my role is a Global V.P, Futurist and more recently Innovation Evangelist. I was an IoT Evangelist, but there's been a bit of a little reorg in the company and now I get the broader title of Innovation Evangelist. And to be honest, I think it suits what I've been doing better. Anyway, IoT by itself, as we know, is kind of if I want to if I want to be provocative, I would say useless. It's only when you couple it with the other technologies in the innovate, in the innovation eco system that you can actually get results out of it. The whole analytics machine learning, you know, all those kinds of things, the edge processing, all that kind of stuff.
ALLAN BEHRENS [00:03:37] Great, thank you. And so I suppose you know, what I'd like this topic to to focus on is really the the age of automation. We hear a lot about automation in the press and from various pundits, including myself and some of Tom's former colleagues. What exactly is automation in the in the world of the IoT? Tom, why don't you start us off?
TOM RAFTERY [00:04:05] Sure. I mean, it it takes on many meanings depending on the industry. But if I think of someone like one of our customers, Caterpillar, for example, they've rolled out a big automation project across their whole manufacturing system where they're they're connecting up all the all the machinery in their plants and they're also connecting up their plants so that they can know they've like, I think, nine manufacturing plants globally. And they're now able to compare, as they say themselves, apples to apples they're able to look at initially they're doing 14 KPIs to cross compare the different plants, but they're gonna roll that up to about 200 different KPIs. And the the automation is across a number of different things that are obviously around manufacturing, but they're doing it kind of almost end to end. What they want to get from the system is they want to get the workers augmented so that the workers have more information to work with. They want to get the customers connected. So now customers buying from Caterpillar can actually buy from their phones and they want to be able to, as I say, get the kind of whole digital boardroom thing where they get all the information right up to the boardroom. So it's factory floor, right up to or shop floor, right up to management suite.
ALLAN BEHRENS [00:05:31] Great. Jordan, what is it to you?
JORDAN JANECZKO [00:05:36] Saying, I think if you go back 10 years or so and you looked at what was out, you know, what were what were people doing when they were talking about automation, they were focussing on the assets. They were talking about how they could do something with PLCs or embedded programming to get the asset doing what it is that they wanted to do. Now, it's much more integrated into everything that's going on in the rest of the company. It really is taking that information out of just that asset and seeing how it integrates into the different processes going on. To understand how it can maybe be integrated with the warehousing or with all of the ERP systems and the other sorts of support infrastructure that is outside of the area of the standard process area and production facilities and how to better take advantage of what's going on. So I think it is that transition of sort of looking down towards the assets and now looking towards across both horizontally and vertically with the rest of the organization.
ALLAN BEHRENS [00:06:30] Sean, you're at the sharp end you're actually making a lot of this equipment. What is it to you? What is automation to you?
SEAN DOTSON [00:06:39] Well as Jordan said, we're at the asset and we're the ones who are building that equipment and actually producing the items. And in fact, Caterpillar is one of our customers customers. So we see a lot of those trends being pushed down our way. But more and more, we are being asked for that data collection for that data interface into into their production systems to get operating efficiencies. It's their wanting to know, you know, how well is the machine working and maybe how well is it working for a particular product? Perhaps it works much better for for one SKU than another SKU. And they should utilize this machine more for SKU versus SKU B. So it not only allows them to get just general production data and connectivity and float that that information up to upper management, but it allows them to make better decisions as to what products they're going to producing on what types of machinery. So these these requests are getting more and more from from our customers.
ALLAN BEHRENS [00:07:40] Great.
TOM RAFTERY [00:07:41] Allan.
ALLAN BEHRENS [00:07:42] I mean, if you gave a good example. Sorry, Tom, you were saying something.
TOM RAFTERY [00:07:46] Yeah. If I could give you a practical example of the kinds of things that that it can help with. I shot a video at the Hannover Fair last year where we had a demo of a flow control valve. So very typical industrial instrument. And these flow control valves have little LCD screens in the front of them where they capture information and they keep that information for maybe a minute, maybe two minutes, maybe three or four minutes, but then it's lost. After that, it's overwritten. But we were able to connect a little as a standard thing called a bullet onto it, which can take the information from that sensor and push it up to the cloud or push it to an edge device. And then if some some some thing that the flow control valve sensors or measuring, if they go out of tolerance, it can send automatically a message back to the back end and kick off a kick off a service ticket or kick off an alert to a manager or something like that. So right there, that's a very simple, very practical example of the kinds of things that you can do with automation. You can take. You can capture data that's never been captured before. And, you know, if it's a temperature sensor, you want to have some kind of edge processing there typically, because if it's saying, you know, everything is fine, everything is fine, everything is fine, everything is fine. You don't want to be capturing that information. You don't want to be storing it for two or three years. You know, it's the exceptions that you want to capture and then say, oops, something's happening. Now we need to make something happen in response to that.
ALLAN BEHRENS [00:09:16] Yeah. Jordan, have you got any examples of what your customer is doing?
JORDAN JANECZKO [00:09:22] Oh, well, that's the perfect examples are connecting sensors and having a better understanding about what's really going on down towards the assets and the idea that you're now being able to combine a whole bunch of different assets now in different ways. We've mentioned a couple already in the show being able to compare similar production lines and understand, OK, what am I doing better on this? You know, if you're taking care of overall equipment efficiency or we understand that in this facility, you're always, you know, X percent better than another. You can start actually doing some analysis through some of these connected devices and understanding where the bottlenecks. Where do I need to have lessons learned? How can I exchange information that's going on in these sort of complex areas? So the idea that you're taking advantage of automation for either A, getting more information, making that available and embedding that into how you're making an operationally efficient organization and continuous process improvement, that's those I think are the key low hanging fruit that if if your company isn't doing that yet, that's definitely where you need to be, because a lot of the interesting things that are coming up soon with business reinvention, smart services, turning your products into something where you are, you're actually selling it more as a service are only possible after your company gains those sorts of skill sets that allow you to to integrate those activities.
ALLAN BEHRENS [00:10:42] Right. One of the things that people talk about is, you know, the the impending escalation of use of robotics and those types of technologies within the production lines and automation systems that have been used in the past. What are some of the implications of that within this world of automation, industrial IoT, Sean?
SEAN DOTSON [00:11:06] Well, you know, it's interest one of our one of our larger suppliers of robotics, is Fanuc Robots. They have recently released some pretty amazing software actually called ZDT, Zero Downtime, and it's in its software package that runs on the robot that also connects out to the rest of the network. And it's analyzing temperatures, current forces and all all the joints on all the motors and all the sensors that are inside the robots. And it's doing predictive analysis as to, you know, hey, maybe join the motor on three is starting to creep up there on current and and trending it and finding that it might be failing here in the next six months. And some of the larger manufacturers, primarily a lot of the auto manufacturers, are even tying that into their their maintenance systems so that the robot can say, look, my joint three is starting to to fail and it's going to fail probably in the next three months. And you have a maintenance window three weeks from now. And so I'm going to go ahead and assign myself to have that motor replaced in that period of time. So it's a it's a really powerful tool. It's also very useful. It records everything. When one of our customer calls us and said, we don't know what happened, the robot just crashed. We can go back and look and say, well, you know, actually, it shows here that somebody changed a variable at eleven fifty nine p.m. last night and that's why it crashed. So you may want to have a discussion with your, you know, your third shift operator as to as to why they were changing those.
ALLAN BEHRENS [00:12:45] I mean what sort of examples are you seeing up in the world, sort of connected robotics and automation systems?
TOM RAFTERY [00:12:53] Yeah, no. Very, very similar to what Sean said. A lot of the use is using digital manufacturing software to make sure to talk directly to the robot so that you can have your ERP system and your sales system talking direct to the robot so you can get down to kind of the the the ideal lot size of one that, you know, people have talked about for a long time is now actually becoming a reality. And then the other side as Sean rightly pointed out as the whole idea of predictive maintenance, of making sure what you know, what you call your critical bottlenecks, you're your gateway machines don't fail. You have maximum uptime on them so that they are constantly sending out the information, you know, from all the different sensors. I'm okay. I'm okay. I'm okay. Run those through your machine learning algorithms so that you know that if something does go out of tolerance, you know, Part X is going to fail with, you know, 87 percent probability by next Thursday, at 3 o'clock, so that you if you don't have parts in stock, you can get them in stock fast so that you can replace it so that your machine doesn't go down. Or if it's down, it's down for the minimum possible time. You get your first time fixed rates way up. That's that's the important thing. And you get your downtime way down so that you're like I say, your critical bottlenecks aren't bottlenecks that you don't run into manufacturing problems.
ALLAN BEHRENS [00:14:13] Do you see the same thing, Jordan?
JORDAN JANECZKO [00:14:16] Oh, yeah, definitely, definitely. Although I do sometimes get worried because there are a lot of companies that are a little nervous. They don't think they're advanced enough yet to start using machine learning and advanced intelligence sort of concepts. I think some sometimes some of the easier things are just having a better approach to how you get robots to interact with existing machines. Loading and unloading, milling machines or lathes or other sorts of things. Making sure that you understand how you could use automated guided vehicles in your in your warehouse or some of the things that are, you know, falling with into that robotics category and letting you be more flexible with how you do these initial sort of steps. It lets you better understand how these interactions take place. Sometimes you can have a more advanced view about what a machine is. A machine isn't necessarily only one asset now. It's a combination of different robots and machines working together to perform a task. And as you're trying to decrease a lot size of one that's talked about a lot with Industry 4.0, for example, robotics is a way of sort of gluing together different subsets of processes that lets you deal with personalisation or smaller lot sized numbers.
ALLAN BEHRENS [00:15:25] And Sean, I remember speaking to you some time ago about the changes that are happening with the advent of robotics and this sort of connected world. It's changing the way that you design and consider your machinery, isn't it?
SEAN DOTSON [00:15:41] Yeah, it is. I mean, you know, traditionally in automation over the last 20 some odd years, there was always a mixture of robotics and what we call hard automation and typically hard automation was was always a little less expensive than robotics. But of course, when you're designing custom, you know, hard tooled automation. Yeah, getting it right the first time is always a challenge. So you're there's a little bit of an iterative process, is there, especially when you do custom design. But I mean just quite honestly, the commoditization of robots and the intelligence and the lowering of the price has really driven us to to start using more and more robots. Anytime we have more than about two axis of motion, we're throwing a robot on it. Not only of the price and the flexibility, but the connectivity that it has to other devices. I mean, they're really you're throwing several mini computers onto a machine at that point, getting that processing power share between all those all those small little processors. So it's you're definitely going to see more and more robotics in places that you saw traditional hard, hard tooled automation.
JORDAN JANECZKO [00:16:57] Now, I think Sean's pointing out something important, and that's that the price point is coming down drastically on some of these things. And the flexibility is something that a lot of people aren't taking advantage of. And it's not necessarily only flexibility on the robotics side, but it's also flexibility on the software side, how to deploy new programs, how to test and verify, make sure that it's doing what you want it to do. And again, that's sometimes a new skill set that some existing industries need or existing companies in some industries need to approach in a slightly different manner. And I think that's one of the things that's exciting about robotics, that it lets people have a new way of sort of talking about job security and maybe being able to exist in some countries where it used to be more expensive to produce. Now, you can actually take advantage of these things and save some jobs, which, you know, a lot of people are worried about in the opposite direction of automation.
TOM RAFTERY [00:17:48] Another thing Allan, as we're talking about connectivity and having connected devices, we're seeing the move to product as a service and the product is a service world as well. And that, you know, for manufacturers that goes both ways. They can either be a customer of a product is a service where, you know, the device they're using, they don't actually own. They're just paying for the utility of it. It may be a big air station for compressed air and they're paying by cubic meter of air or something like that. Or they might be the manufacturer themselves giving it to a customer. And in that way, they are. So we're getting different business models. So they're now being paid not upfront asset, but it's almost like cloud computing. You know, you're going for the customer for life kind of thing. But also, when you're doing that, when you have the connected device out in a customer's place, you're getting information back from it. Real time information on how it's actually being used in the wild, the kind of information that you never got before unless you sent the service engineer to site and having that being able to get that data back and feeding that into your R&D division allows you now to produce, you know, the next version of the device and have it optimized for how the device is actually used, not how you thought it was used.
ALLAN BEHRENS [00:19:01] Right. I'm interested in this topic of, you mentioned that, Jordan, you know about the disruption that is potentially caused or not. I think you touched on that as well, Tom. Are these automation technologies and their connection to the industrial Internet of Things, are these disruptive technologies, I mean, will do how will people adapt and how how can they be consumed or assimilated? How about you, Sean? I mean, what what do you think?
SEAN DOTSON [00:19:33] I think they're certainly innovative and all I'm not sure I would really call them disruptive at this point, though. They're they're changing the way we're thinking about automation, the way we're connecting machinery. But when I use the term disruptive it to me, it's it's a it's a step function and change. And I don't think we're quite there yet. I think once you start combining some of AI and getting into then a little bit more connectivity between the robots, that's going to be more disruptive. There's a couple of companies working on some 3D, binn picking visual, bin picking applications for robots now. So you tell a human operator, hey, pull a teddy bear out of this bin. They can look past the boxes and the wires and all that and see a little furry thing at the bottom and then pull the teddy bear out. You tell a robot to pull a teddy bear out. Right now, we're having to teach it. What is a teddy bear? What does a teddy bear look like? And right now, they're they're working with some some vision companies that have some artificial intelligence that you just feed thousands and thousands of pictures of teddy bears, as we all know, they could be brown or white, really furry or less furry. And it learns what a teddy bear looks like. So now you're able just to throw this bin in front of it and say, get the teddy bear and it pulls the teddy bear out. So that to me. That's true. disruptive technology there. And it's coming. It's just it hasn't hit the market place, you know, as a as a ready to go product quite yet.
ALLAN BEHRENS [00:21:05] Right. I mean, told me using that same trend, is it is it not quite there or are you seeing something different?
TOM RAFTERY [00:21:13] You know, I think William Gibson put it well when he said the future is already here. It's just not evenly distributed. So yes and yes and no to avoid answering your question, because, yes, I am seeing it. And yes, it is here, but not everywhere. So several of our customers are already deploying these kinds of things and these kinds of technologies. So yes and no is how I can answer that I think.
ALLAN BEHRENS [00:21:43] Jordan, what about yourself?
JORDAN JANECZKO [00:21:45] Yes. So going back to the idea of disruption in general, I think one of the things to keep in mind is that these different things going on affect different parts of the organisation at different speeds. So it might be that the planning team has a different view about how disruptive, disruptive this is compared to, for example, the quality team or the people that are responsible for, you know, third shift, those people at eleven fifty nine at night who have decided to change a variable for some strange reason. Everybody always blames the third shift. I think the disruption right now is is certainly taking place in the minds of a lot of people that are thinking about network connectivity and how to get this data prepared in a way that you can take it, start taking advantage of advanced analytics. And I think that's where they're starting to take maybe a little more or maybe they're starting to have a little more respect for the I.T. department, which they didn't already always have because of some of the advance security models that need to be put into place and things that weren't necessarily sort of the sweet spot about what the team was doing when they were actually doing a lot of I.T. savvy sorts of activities. I think a lot of them a lot of this step change that we see going on right now is the idea that the O.T. departments are really increasing their game with their ability to understand or not understand. But but invest more time with some of the I.T. things to understand that they will be connecting this up to the rest of the organisation. And how does that impact what they're trying to do? And so it might not impact everybody's job in the same immediate way. But I think as time goes on, we'll see different parts of the organisation adapt in different sorts of ways.
ALLAN BEHRENS [00:23:18] I mean, do you have any advice for companies that perhaps have employees that are concerned about these elements of disruption? Because obviously there's more rumour and speculation than actually facts in a lot of these topics. I mean, what advice would you give companies to help them deal with the potential concerns some of the employees may have? The evolution of these industrial Internet technologies and automation technologies as they as they start to win their way into the infrastructures, Sean.
JORDAN JANECZKO [00:23:50] Well, it would be interesting. I was going to say it be interesting there what Sean has to say yes.
SEAN DOTSON [00:23:54] I actually and funny enough, I was just invited to speak at a human resources convention here in Florida recently. It was about state of talent and how to retain your talent, how to find good talent. And I thought, why are they inviting an automation guy to a conference about human talent? So my joke was, you've heard all these great these great people talk about how to retain your talent. I'm here to tell you. You don't need talent. You just need robots. But in reality, what really is happening is, you know, the RIA has a lot of data on this. If you look as robot sales go up. Unemployment actually falls, so it's an inverse relationship between the two. There there's articles that was we see in the media all the time. Robots are gonna take our jobs and then by the same media outlet. Three days later, you'll see another article as well. The robots can take our jobs. This is a good thing. We're going to create these all these other jobs. So, you know, what we have found and the data supports it is, is that as companies become more automated there, they actually are hiring more people. People are not are not putting automation in and laying people off. They are putting automation in because they cannot find enough good talent. There's there's. We won't talk about the skills gap that's looming. It's a real thing. We as an automation company even have a hard time finding employees to to build the automation for other companies. So there's there's no danger. We're going to have jobs. Our titles may be different. There may be new things. But automation really can't be seen as as a threat to jobs. It's not to replace them. It's just going to change them.
ALLAN BEHRENS [00:25:37] Right. I mean, Thomas, I mean, companies the world is ready for this change. I mean, what is your view?
TOM RAFTERY [00:25:46] And I I'm in violent agreement. Absolutely. The is the world ready for the change? That's a different question. I think. I think that I always say technology is easy. It's people that are hard. And I think a lot of the changes that we're going to see and we're going to see increasing pace of change as well will have will would be difficult for some people and organisational development to change. Management tells us that the best way to make changes like this is to involve people from the get go and have them involved in the decision making process. And then when they are involved in the decision making process, they find the change easier to deal with. It's only when change typically is top down mandated that people find it harder to deal with. Like I say, if they've been involved in the decision making process, they're already bought into one of the stakeholders and feel that they've contributed to it. And then, you know, it's easier it's easier to to rule with.
ALLAN BEHRENS [00:26:55] Right. Jordan.
JORDAN JANECZKO [00:26:57] This is exactly the same conversation I had with the company last Thursday when they were visiting us in some of our facilities. It was there in the press there in Switzerland. They're in the process of right now building a new plant. And they were talking about how they need buy in from their existing employees because they can't just sort of say, surprise. We have a new plant. It's 40 percent smaller. How does this affect your job? It needs to be something that's continual. Not only because they need that sort of acceptance from the organisation, but also because that organisation has a lot of knowhow and understanding about what their company does. What are the crown jewels? What makes them so unique? Why are they being successful today with what they're doing? And they don't want to lose that. They don't want to have some sort of big bang approach where just a couple of strategy people and management makes a decision and then just sort of bang, bang, bang pushes it through. They lose a lot of expertise. They lose a lot of people, and they won't have that sort of acceptance for what's going on. It can be it can be somewhat dangerous not to try and have this is a broad discussion. And in fact, what you'll see right now, we're involved in a lot of IoT activities with universities and some some things that are given federal grants in different countries. And you'll see that very often those are combined with social studies, things that are more in an MBA approach, not a man, not purely manufacturing, but really analysing how you have that change management approach and how do you deal with people who are in the organisation.
ALLAN BEHRENS [00:28:19] Very interesting. I mean, what are the sort of practical steps that you'd advise companies who who have perhaps these sort of beginning sort of phases of looking at greater automation and connectivity to the Internet and Internet of Things? What would you what advice would you give them Sean as to what to do next and how to get more involved in looking at these types of technologies and processes?
SEAN DOTSON [00:28:48] Well, I think Jordan hit the nail on the head when you got to involve your people. You've got to get your factory level operators involved and talk to them about what processes really work and what doesn't work. We're invited into factories all the time and we're say we're we're told this is the problem right here. Look at this section of the process. Here's here's here's the issue. And we ask all time, can we look upstream? And then they always say, well, why are you looking upstream? Well, because this might not be your problem. Your problem may be upstream. So let's go look to see if we can solve that problem. So be open to what you think is the problem. May not really be the problem. Also, we recommend to people is start small. If you don't have automation, you need to look at something on a smaller scale. There's a skill set that needs to be built up by by your people, not just not just your operators, but your mechanics, your I.T. departments. You don't want to jump in with two million dollars with automation if you have nothing because you're destined to fail at that point. So start small. And then once you have success, you know, go to the next larger process and then, you know, keep keep continuing on at that point. But don't don't try to jump in from zero to one 100 immediately.
ALLAN BEHRENS [00:30:11] Jordan, have you got any thing to add to those sage words of advice?
JORDAN JANECZKO [00:30:16] I would incorporate those sage words of advice into a general. What I've noticed with a lot of customers that we did talk with, they obviously want to have a structured approach, return on investment to understand, OK, what are the benefits that I get if I invest this much money? How much time is the payback period? All of that's very important. But it's not only a question of operational efficiency and do I have X more widgets produced in one hour it's a question of what skill sets do I need to bring up? It's a question of is this enabling me to go through some final some final steps that improve quality? The return on investment calculation that you do isn't just a question of production, speed or other sorts of things. It includes soft skills. It includes where your vision is for what you want to be doing in the next 1, 3, 5 years and what this is for a step going in the right direction. Again, there are some things where the automation experts say automate everything and it's not cost effective to do that. But the I don't think there are many industries left where you could just say don't automate anything and you don't have to worry about it. You need to get those skill sets. You need to start incorporating that into what's going on and you need to take that holistic approach about saying it's not just about automating down towards the asset, it's taking a look at process and it's taking a look at all the integration that goes on horizontal vertical again, warehousing, supply chain management, ERP systems, partners, design, process design. It's it can be wonderfully complicated, but it also needs to start wonderfully easy with a very clear understanding about where your benefits are and what you want to get a first step in the next step and the next time.
ALLAN BEHRENS [00:31:55] Right Tom, How about yourself?
TOM RAFTERY [00:31:56] Smiling here, listening to Jordan, talking, automate everything and reading the stories about the what they call the production held at the Tesla Model 3 Line is going through at the moment because they tried to might automate everything and they went too far and there to actually back out of it and take out some of the robots that they put in there. But in general, I think for organisations. I think the advice that we typically give them is to run a few pilots first just to see, you know, where it would go through it, maybe even a design thinking session first to two to come up with the ideas for pilots which would want to pilot and then run a few pilots and see what where you're getting your best results from and then work from there. We tend to say to people, you know, start small but think big. And in that way, it's kind of a safer way to approach some of these projects. And, you know, if you're running pilots that way, then you can see early on without expending too much where things might work and where things might fail.
ALLAN BEHRENS [00:33:06] Sean, when companies think about the scaling sort of principle, do they need to take into account where they might go to? Is that something that, you know, these days is less important? Scaling is less of a challenge than it used to be.
SEAN DOTSON [00:33:26] No. No. I mean, they absolutely have to take that into account. You know, we will we always ask people what we what are your production volumes currently and what are your production volumes going to be next year, three years, five years from now? Because because this is equipment that that lasts five, 10, 15 years in some cases. So you don't want to buy a piece of equipment that is certainly far more expensive than in an overreaching for your current needs. But you want to be scalable and you want it to be adaptable to that growing need. We're seeing more and more the change of pace of products is much more rapid nowadays than it used to be. You might run the same the same model product for three or four years. And now we've got companies that are that are changing models every six months. So you definitely need that scalability, definitely need that variability. And then and that's where touching on my previous point where robots come in. They are very flexible. They're redeploying all in a matter of, you know, taking them completely off one machine and putting money to another mission. So they they definitely you definitely look forward on on where you want your company and your production volumes and range of products to be in the future. Otherwise, you're gonna end up with a piece of machinery after a couple of years.
ALLAN BEHRENS [00:34:53] The software infrastructure, though, doesn't have the same some of the same remnants, does it? Tom, you know, what we've heard in previous shows is it's much easier to scale the software. Well, when I say easier to scale is much more practical to scale. The software infrastructure than it is to scale some of the physical assets that show. I mean, is that is that something that creates a bit of contention in what Sean's talking about?
TOM RAFTERY [00:35:24] Probably, yeah, we're we're a software only organisation, as you know, we don't. We don't do any hardware. So if that's that's not something I'd be hugely qualified to speak on. I mean, I can speak about the software side of it and how easy it is to scale that, but not the hardware and not the conflict that arises between the abilities to swap out hardware and swap software. Having said that, I mean, yeah, we're seeing a big shift in software as well. The kinds of ERP software that we have been selling in the past is actually quite difficult to swap out traditionally because, you know, it's a big project to put in an ERP system. And usually organisations will try and avoid having to swap out ERP system. You know, unless it's every 10 or 15 years, a kind of lifetime that Sean was talking about. But with the move to cloud delivered solutions, now that becomes easier because now the software vendor is responsible for keeping software up to date. And the idea of swapping out an ERP system becomes, you know, redundant.
ALLAN BEHRENS [00:36:37] Right. Right. Jordan, I mean, are you seeing anything on that side?
ALLAN BEHRENS [00:36:41] Oh, definitely. So, I mean, it's it's a complex world that we're talking about right now. If you get into the idea of, you know, can you take advantage of the fact that cloud can scale faster than any physical hardware can? Yeah, that's great. That's fantastic. The I think some of the tension that you get between the operations department and the I.T. department is very often that there are so many different standards out there that are still relatively new and fresh. You're not exactly sure if the things that you can rely on, as Sean was saying, if you've got a product that you bought for your shop floor that you want to work for the next 15 years, there are some problems that that sometimes people see if if the software is changing so quickly that all of a sudden what they had working won't anymore. And I think that's one of the actually since this is the IoT show, it's worth pointing out that this is one of the reasons why industrial IoT is going to look different than smart homes and some other things where the products you buy usually are only going to be used for a year or two years. And then you replace, you know, maybe there's an exception with your vendor, your refrigerator, but there's a lot of home products that just have a have a shorter time span. And so we definitely see the market playing out differently for the industrial IoT world than we do for smart homes, even if even if there are similar sorts of constraints that you need to think about for bandwidth, the amount of data that's being transferred to some sort of central area. And again, it gets back to something that we touched on a little bit before, which is edge devices that are being closer towards the assets are getting cost effectively more powerful. And you have to then independent of the ability to deploy things into the cloud back and need to be able to manage what you're pushing out towards the edge. And I think that's that's where sort of the rubber is going to meet the road for some of these advanced companies. OK. I do embrace automation. I do embrace machine learning. What does that mean for how I manage the software that's been deployed under the edge devices that are close to my assets?
ALLAN BEHRENS [00:38:36] Sean where would one go for advice and how would you recommend other manufacturers, especially SME's, who don't have these sort of huge I.T. teams and research teams looking at these types of technologies? How would one get going and how do you try and get the knowledge required to help you expand your sort of automation and industrial IoT capabilities?
SEAN DOTSON [00:39:00] Well, I mean, quite frankly, there's them a couple ways. I mean, selfishly, a little bit. The one of the better ways is to go find yourself an integrator and then somebody who does this sort of stuff for a living. Certainly large organisations can can handle this internally to a point. You know, another avenue is, quite frankly, working with other companies in your industry or fringe industries, maybe not competitors, but sharing best practices, you know, talking to these companies who have done this before and and learning from some of their mistakes and what worked well for them. And finally, I'd recommend looking at some of these organisations that like the RIA, the Robotics Institute of America, and there's the A3 for advancing automation. These organisations all collect a lot of this type of data and sorry my light turned out there, Here we go.
TOM RAFTERY [00:40:06] Speaking of automated systems.
SEAN DOTSON [00:40:07] Yeah, exactly. don't always work the way that you want them to. But we're you know, we're working talking to some of these trade organisations that that's their sole focus is to is to look at what those next how technologies are coming down the road. And then how do you mean if you apply those?
ALLAN BEHRENS [00:40:26] Okay. And Jordan. Any advice from yourself as to who to look for, for advice and find solace?
JORDAN JANECZKO [00:40:33] Well, I was certainly happy Sean was saying systems integrators, because that's one of the things my company does. I did, however, add to that that, you know, it's always a good idea to talk within your own organisation and look for pockets of people that already have some expertise, some things that might be sort of hidden in the organisation. I think a lot of companies underestimate the amount of experience that their people have and that some people think that it's interesting to try and do advanced analytics algorithm themselves and to see what they could do with some of the data that's laying around. We find very often going through some of the interviews that we have with people to talk about, you know, value stream analysis and what they're trying to do to optimise their processes and include automation in there. We very often through the interview phase, find people that actually already exist in the company that have tried some things out, maybe a little bit under the table, under the radar of what's going on with management. And in addition to, obviously, if you don't have those skills in-house looking for the right trade organisations or integrating partners, look into your own organisation and see what you already have.
ALLAN BEHRENS [00:41:36] All right, Tom. Anything to add?
TOM RAFTERY [00:41:38] Not really. Thank you. I think Sean and Jordan covered it pretty extensively. And fairdoose. I mean, trade organisations. Yeah, absolutely. Going to events is always a good one because at events you you're not just seeing the people from the industry speak about it, but you're also there with peers very often and speak to them, as Sean said, not necessarily competitors. But, you know, if you can get people in similar organisations who are willing to to share best practices. That's that's a great way to do it. Yeah, I think that's about it. One thing that hasn't been mentioned, I guess, is the likes of, you know, online resources, the likes of even, you know, YouTube's is often a good place to search for some of these things. But you need to obviously be be aware that not everyone on who's posting stuff online and things that it knows what they're talking about. So you want to take that with a bucket of salt.
ALLAN BEHRENS [00:42:30] Great. And something that was mentioned in an earlier show is also don't just look in your own industry vertical, look outside because other people have a lot of things that they're researching, a lot to add to to the argument. So I'd like to thank my my honoured guests, my Sean Dotson. Jordan Janeczko and Tom Raftery. Thank you very much for being so interesting as in a fascinating conversation. For those who are watching, they'll be a key takeaways document that will be available on the Websites, on productions. And you can go and download that at your at your own discretion. Thanks very much for listening. And we look forward to talking to you again.