Why There Is No Silver Bullet in Asset Management

Foreign. You are listening to Assets Unscripted. My name is Beren Bohms and I am your host and I'm delighted to be joined today by Johan Janssen van Rensburg, who is the reliability manager at sapi. Johan, first and foremost, thank you so much for taking the time. I really appreciate you being here all the way from South Africa. Now we've had some prior conversations and I feel that I've gotten to know you a little bit. But for the people listening in that might not know who you are, could you tell us a little bit about who you are, what you do for fun, what ticks, you know, what grinds your gears, what makes you tick and the role that you have at SAPI being a reliability manager. All right, thank you very much, Baron. It's really nice to have met you like you said earlier on a few weeks ago and nice to have had some good conversations and yes, thank you for the opportunity to just have a good conversation and I'm sure we're going to have fun today. So yes, a bit about myself became a grandfather today which was phenomenal. First grandchild. And yes, I'm at the getting towards the end of my career. So I've been around for a while. I started my career in the late 1980s and, and have been in maintenance and shall I say also reliability before reliability was a buzzword career. Yeah. So I've been in work for numerous organizations over my career close to 40 years now. Started my career as an electrical engineer, well as actually apprentice many years ago and then had the opportunity to go study further and qualify as electrical engineer. And through that I've always been working in operations and the maintenance obviously in different, like I mentioned, different organization, different types of manufacturing organizations over the years and most probably in the early, early 90s where maybe some of the listeners will know when computers became a lot more relevant in industry, CMMS systems were brought into businesses. That's where most probably my my journey with maintenance and then later on asset management as we know in the early 2000s started, etc. Etc. And I've, I've had the privilege to work in different roles, even production and general manager role and senior roles in organizations. In the past five to seven years I redirected my interest and started focusing just on the subject I enjoyed the most during my career around maintenance, asset management and reliability and reliability engineering. I really enjoy things like systems engineering, something that I find really fascinating and I think from a maintenance or asset management we can learn a lot from the systems engineer as well. But yes, like I said, what I do for fun, trying to cycle a lot more but not getting to that. I used to cycle quite a bit. And yes, from a career point of view, trying to give back. I think I'm at the stage in my career where not pursuing promotions or big titles in business, but it's giving back and also keep on learning. I've always enjoyed learning new things, tinkering with things. The subject that we, I know we're going to talk about later, AI and all those is something I found fascinating and it's, I'm curious to see where it's going to go. Like I said in a conversation a little while ago as well, if I was 10 years younger, I would have been even more excited, right? I sometimes wish I was younger because don't we all? People in the, the asset management reliability space is gonna, it's got some real exciting things ahead of them over the next years. It's gonna, I think it's already changed the, the landscape and the shape of things. Some really exciting stuff that's going to happen in the future. So absolutely there's, you know, that's a bit about myself that's wonderful. Thank you so much. I mean there's a beautiful symbolism, the fact that, you know, this is the start of your life as a grandfather, but you're also nearing the end of your career as a reliability leader. And you know, that's been close to four decades. I believe in operations, in reliability and maintenance, consulting, standards development. So you have seen the good, the bad, the ugly and everything in between within this wonderful discipline. And it's really interesting for me to meet you at this point and get to glean some of the insights. So I wanted to ask you about, you know, starting out, what was that like? Because you came up in a time, as you said, when computers suddenly became super relevant. CMMs, I mean some of those terms that we now so freely use today and that we all benefit from did not even exist, right or not in the sense with the same intention and purpose that they do right now. So how has maintenance thinking and the idea and perception of maintenance changed from those early days, right, where you know, it was very much hands on, you were just getting your hands dirty and that's, that's what maintenance is about to this more system driven environment that we have today. And how has your journey in all of this in Those close to 40 years, you know, starting out as an apprentice and where you are now, what does that taught you in a way that no system can ever Replace? No, I'm gonna fill all the questions you had in there. Let me try my best. I think we'll get to that at a later point when we're going to talk a bit about back to basics or looking at basics things but you know, technology. I also grew up when I got my first computer when I was 16, you know, and it was in the. Right. In the early 80s. You, you, you don't realize at that point, I think nobody understood how it's going to impact the world globally. And I think that's what I've seen. And if you go back in the history of where maintenance started, it started well in the Industrial revolution where they built things big and strong to last forever. And as businesses grew and we know, I think a lot of people know the history, they decided you can't keep on building big and strong because it's costing you a lot of money. So design and all those things came into play and then production lines, etc. Etc. And there's some people in the early 50s and 60s that did phenomenal work around systems, around maintenance and the thinking around a lot of that set in manufacturing and especially in the motor manufacturing arena. A lot of those things started, but with the onset of computers like a little while ago, I had to present at the conference and what was quite interesting, I thought, you know, it's good to remind people where we've come from. And if you think the blue LED was discovered in 1992 by a Japanese guy and if it wasn't for him that discovered the blue led, we wouldn't have what we have today, LCD screens, cell phone screens, all those, because you couldn't have, you couldn't developed the color spectrum because you didn't have the three primary colors of which blue was missing. And that was in 1992. Right now for maybe for the younger people like you, it sounds like a long time ago, but for me, as when I started my career just started kicking off and I remember looking at one blue LED Mini when the engineer I was working with at that point and it was mentoring me, came into my office and he showed me the blue led and he told me, he said to me, do you know how this is going to change how we view things? And if you think about it, even in that same time, in the early 1990s when computers became relevant and local area networks made a cape started being the driver for CMMS systems or maintenance systems. And if it wasn't those pioneers that started those and from it, from the IT industry, then we Wouldn't have what we have got today. And obviously the things like the Internet and cell phones and that like we, the phenomena that we can sit and discuss things. So that in itself has shaped the way we execute maintenance. But if you go back to maintenance per se, you still need an artisan, you still need somebody that's going to get their hands dirty. You still need somebody to understand the fundamentals of electricity and the fundamentals of mechanical fitment of a bearing and assembly of need to know how to use a torque wrench. Simple things like that is still relevant. So as much as we've had technology driving a lot of things in our systems and controls and it comes back to motors, pumps, gearboxes, electrical switch, gear, wiring, all those, you still have those people. Those people are critical to any business. And if you, if you just step back and yes, you have got technology, you still need those people. And I think, you know, also in my early start of the career I had the opportunity to visit different countries for the one industry I worked for. And you know, I also realized and being from South Africa, people has got a view of artisan and technical people. And I had opportunity to spend some time in Germany and in Sweden when I was working in the timber industry. And there the value of OIN was different but yet the skill set is still the same. Yeah, and I've even in recent years certain sat in conversations where hearing from very senior people and, and you hear the challenges they've got with skill set, lack of skills on all those and that was in the US and you go, doesn't matter where you go in the world. Everybody has got the same challenges, we have got the same demands on, on people. And yes, you still need the people and especially that your, your maintenance staff to have the skill and that is the hand skills, the physical skills of doing things because or else we won't keep the wheels turning and the lights on and all those things. So yeah, so hopefully that answers to some of it. There is a lot, yes, like I said, technology has played a huge role and you've been there and you've seen a lot of these technological developments. Now obviously some of them or most of them are, are framed as this is going to be the next big thing, right. This is going to be the solution. And for those challenges that we see across the board, not just in South Africa, but also in the Netherlands in my case and in the States and elsewhere, you know what vendors like to do is position it as this is the next big thing. Right. And cmms in Its own right has been considered to be the solution to all of these maintenance challenges. And I find it really interesting to consider this because something similar is happening today where artificial intelligence, AI you already mentioned, that is, you know, the next big thing. Everyone sort of gravitates towards it and it's framed in a certain way. But I wonder why does our industry need this? Why does our industry do this? We always gravitate towards these silver bullets, right? Is it cms, is it AI, is it iot? I mean there's plenty examples. But why do you think that is? And why do some of these waves or hypes or whatever you want to call them, why do they succeed or why do they fail? What's the sort of make or break factor in technological advancement? Yeah, you know, I think everybody is looking at, like you mentioned Sid just now, looking for that silver bullet. Yeah. I had a professor that I had lots of interactions with over my career as well and he said to me one day the silver bullet doesn't exist and is so true, you know, and because everybody looks for it, everybody looks for that. They are say, the instant gratification of solving a problem and making it easier and, and all those things, you know, and it's got its place. You know, like you said, the CMS systems were sold in the early 90s, made lots of conferences about this is going to fix all your maintenance problems, this is the solution. And you know, what is, what is interesting and this is the AI thing, very interesting and reading up and trying to keep abreast of it, which is almost near impossible these days. The rate of things change. The challenge around that is people are looking for a quick fix. The quick fix is not there. You still need some of the fundamentals in place of, to make sure things work. I recently had a conference as well and yes, there was a lot of different presentations, but a large majority of the people came back to the quality of their data. The data sets, the quality. And if you now go back to CMMS Systems in the 90s, people did not pay attention or let me reframe it. I think people weren't made aware of how important it is to start your data set and look after that asset within maintenance. And you hear these days where people talk about data as an asset. And I think we've got a lot that we can learn from the finance industry where your daughter that you have got drives economies because all the monetary values is basically data and data that you have got in a system. And if we paid the same amount of Attention to our asset data, physical asset data that goes into a system and attach the same amount of value than financial data, currency, if you can call it that, it will be a different view. And in the early 90s, a lot of maintenance systems come in and even till today, there are a number of organizations that now and again, quite, quite often they do a survey, try to cover the globe and see how many organizations really, truly believe that the data in their CMMA systems or EAM systems are, they can trust. Right. And there is a very, it's a very low percentage. And then having seen like you say, the good, the bad and ugly, if you see organizations that have paid specific attention and being, being very methodical and disciplined in collecting, maintaining, looking after that data and the data integrity of the assets that they manage, those organizations do, their maintenance systems are well managed. The whatever system they've got, they can, they start looking at doing proper life cycle analysis, lifecycle costing of an asset, etc. Etc. You know, so this was also quite interesting during some talk, you know that organizations go out and they say, all right, I can't trust the data of my assets, but I can go get some data of a group or set of attributes of data that somebody else has collected and they're going to go fix your master data and they're going to fix your bill of materials. Because guess what, they've got millions of records of standard pumps, motors, gearboxes and the design of those. So if your data is not good, we can help you fix your data. But we're using other dot. And that's where, that's the, that's the, the great thing with AI, artificial intelligence, that's where the value of that sits is to, if you want to improve your data, get your bill of materials, your asset data accurate, you can do it. But you then, you then have to put the right mechanism in place that how are you going to maintain it. Yeah, and that's what I find interesting with that evolving, call it that of ISO55000 around asset management. You know, they started with ISO, that started in the 2008 with BAS55. And then it, as they gained more momentum, there's a lot of interest. You had ISO 5001, 5000, 5001 and 5002, like most ISO standards, but now you've got the ISO 55010 and 13, all those that in the same suite, they say, all right, how do I manage my data, how do I manage my financial, how do I tie all those things together? Because if your asset data is not trustworthy and you can't trust it. The integrity is not good. You're going to fix, use AI to fix it maybe. But in five years time you're going to be back and it's not going to be working for you. And that's what I've seen with maintenance systems people implement, they roll it out, they think everybody is going to behave and use it the way it should be. Collect the data. No work without a works order. You capture all the data in the works order when the maintenance guy is done. And that's where explaining for the artisan why it's important where you want to record certain aspects of what they do become so important. So yeah, it is, it is interesting that it seems that we starting all over again in some ways that when we started in the early 90s with CMMS systems, when they became relevant, we following a similar path. I wouldn't say it's identical because you can't compare it. Definitely not. I think it's up to the organizations to. You actually have to draw a line in the sand is saying we're fixing but how does it look like going forward? Yeah, because coming back to the question you ask, you know our maintenance has changed and is very evident. You know we in the 80s 90s worldwide boom, factories being built, industry growing, people investing and it goes through the peaks and valleys. But you're at the point where people say well we cannot keep on investing in bigger factories etc. How do we make it more environmentally friendly and all those things as well. And people are looking back and saying why can't we reuse what we had or renew. You see it in people revamping old factories, turning into office blocks or repurposing them. And you're going to see some of those, they already are happening but you still need to maintain that asset, whatever it is. At the end of the day, what do you put in place, how do you manage it and how do you maintain it? Because if you well look after it, it's going to be profitable for you as a business in the long run. Yeah. And it's such a powerful insight as far as I'm concerned. I mean you shared a number of these or emphasized fundamentals. Right. So data, data integrity, the structure. But it all comes down to me to sort of the discipline because it's not a one and done type of exercise. Right. None of these solutions, not the cms, the aims of the world, but also not AI are just let's get a bunch of money. We buy this Technology and boom, problem solved, right? It takes real stewardship, ownership, governance to really make progress in a meaningful way. You need to be attentive to the fact that, you know, it's worth investing the time and money in doing things right and not just investing all of that time and money, the actual acquisition of a technology. But there needs to be room for that technology to elevate how you handle your maintenance and operations and reliability within that overarching process. So I found that a really, really great perspective. So you already talked about a lot about similarities between what you've seen in the 80s and now what's happening with AI. So having lived that experience and having all of the knowledge and hindsight is 20 20, obviously. But if I now were to ask you, right, you know, someone's coming up to you and they're going to ask you for advice and they want to invest in AI, what is the first thing that you would audit within their business structure before you even allow that conversation to continue any further? Well, I think I must probably touched on already you need to audit how they manage their data, the assets. Because other than how they manage it, it also gives you insight into the discipline that is the what value do they attach to your. The asset data that's in the system. Now a good example maybe to just look at a certain specific principle. So risk based inspection or RBI is that's quite well used in petrochemical and in those industries where you have legislated inspections you need to do. And the RBI process works well, only works well if you collect the data on a regular basis prescribed because then you can prove that you can extend the time between statutory testing or non destructive testing. You need to do pressure testing all those on pressure systems and all those. But it's purely reliant on how good the data is and you have to be disciplined. So there's a technology, technology has allowed people. If you look at a high pressure system that you need to typically in South Africa every three years we need to do like for example a boiler. But if you have a RBI process, if you can prove the to the authorities that your RBI process that is in place, there's a data you don't have to. You can extend that period within, within the, within the framework. Yeah, but that's got huge benefits to the business because you have less outages. But it all comes back to the data. It doesn't come back to the equipment, it comes back how do you manage and how do you treat that data and what value do you attach in it so you know, it's a simple thing like how. What do you, what do you focus on when artisan goes out and records work and does work, what do you look for? You know, what would you like the individual to record? I think a lot of and I've seen it over the years while there's a. The grouping of peoples in businesses are quite expensive and has become very expensive and artisans are technical people, technicians, engineers and people want to focus on their time to record how long things have taken because they can easily quantify it because they get paid a salary. I've really looked at where people just focus on that and you see what behaviors it drive where if you focused on the technical recording of what they do, rebuilding a gearbox or whatever, or they're working in a plant doing inspection, the accuracy and the validity of what they do, the assessment of the technical state of that asset that is they they're looking after is more valuable to you than the, the time. And now yes, they get paid but because that individual can they only operate or work for eight hours a day really for 40 hours a week or whatever, whatever country you're in. But your asset runs 24 7. That's true. And, and so where does the real value sit? You know, yes, you. Part of it is you have to people contribute to it but you want to understand the value of your, your asset and understand how long it's going to last, how it's been maintained, has been operated, how's the, the care that goes into it on repair, refurbished, replacement it is so even if you send something out to a remanufacturer or you don't do the repairs yourself, you know, what emphasis do you put on their quality control and their feedback and etc. Etc. It is so, so important. All the we, we are driven by the data. We are so reliant on the data is really, really phenomenal. We don't realize and yet there is, there's lots of data out there and coming back to the CMMS or EAM system, you go look in people's data and you're going I can't do anything with this. It is a, it's a challenge. And that's where if you talk reliability engineering, if you want to do failure analysis or start looking at the life cycle and start predicting around failure mechanisms and failure rates and all those it. If you don't have the data, it just makes a mockery of those techniques that has grown and developed over the years. That is so, so critical. Yeah, yeah, that's A fantastic insight. I mean, I think one thing to acknowledge as well is that with these technological advancements you should never expect shifts overnight. I mean, not a shift in functionality, but definitely not a shift in mindset. Right. You have to approach it from the right angles with the right due diligence. So this, this, this shift is really important. Now I want to move on to something else that did not shift overnight, which is, you know, you starting out as very much being a technical leader, then transitioning into becoming a reliability leader. And when we first spoke, you had mentioned that you actually took a step back. Right. I think in 2019 you made the decision to take a sabbatical and, and you explained you wanted to focus on that part that you found most rewarding, most interesting and that did the most for you and you started to actually re. Educate yourself, engaging with, with ISOTC, was it 251 if I'm not mistaken? Yeah, that's right. So, and I, I really appreciate that sort of mindset to. Okay, let me take a step back, let me focus on what I think is really important, what really matters, and then, you know, full steam ahead and develop myself and evolve my understanding of how things work. What prompted that shift right at that stage of your career a couple of years ago and what has it brought you since? Has it reshaped how you view reliability, how you view asset management as a discipline, maybe as a system rather than a function? So what has it done for you that sabbatical? So I think in my career, and I think a lot of people that age, to me you're getting towards your 60s now and into your 60s now. In the early days, the natural career progression was going up the ranks and then going into a management role where you manage people. And then that's how you used to progress. You had individuals that might go into different types of industries and the general. There has never been a role that you. Well, there are roles, and let me correct me myself, there are roles that you become a technical expert in a specific field or you become a design engineer. Now, like, you know, most engineers that go and study, you go and study to become an engineer. And very few engineers end up in a design environment because there are only so many roles for them. Majority of engineers end up in manufacturing, mining industry, if you can call it just a broad term. And if you actually want to progress, you have to take a certain route. And those routes were very common. And I think when I got to a very senior role and I, and I looked at what I was doing is you, you end up with very things that you, you enjoy, you enjoy a smaller part of your work on a, on a regular basis. Yeah. And the benefit I had when I got to that point is when I looked back and said, and I was at that point where my, both my daughters then finished school, they left home. The one was finished with finishing varsity, this, the youngest one was just almost through. And I thought, well, I want to do focus on what I really enjoyed. And I had the privilege in the early part of my career, implementing maintenance systems, writing audit instruments, developing thing into something that I really enjoyed. And that's when I decided to shift back to that with my wife's permission. And I think she, she saw maybe, how did I say. Unhappy I was. Because the majority of the work wasn't exciting. Yeah. Where the, the. I've always enjoyed the technology part. I think growing up in the 80s, being exposed to computers on the early stage, see what it can do, see what it's done over the years. Right. I always enjoyed maybe not the coding that much, but the hardware. And even earlier in my career installing a PLC on assembly line, getting to learn those. As an engineer doing that work myself, I really enjoyed that. So with the asset management and with AI, you've got the technology and you've got the maintenance engineering bit. And for me, like I said earlier on, if I was 10 years younger, I would be even more excited. But just those combinations of the two and where they are becoming more intertwined with each other is really phenomenal to see. And if you see what people can do with technology, you just look at condition based. When you look at vibration analysis, infrared thermography, ultrasound and all these technologies that are, it actually opens your eyes, your technical, not your visual eyes, but your technical eyes. What technology can see that you can't see with a naked eye. And you say, all right, I've got this data. What does this data tell me? It's like that ECG monitor, heart rate monitor tells you something about the human body, but you've got all this technology telling you something about your asset. How can I manage it and look after it properly and how do I combine all those things? So that is the exciting, but the challenging thing comes in. I think with the AI, people are maybe coming back to the silver bullet thinking that here's a technology, it's going to fix all the other problems as well, and it won't because it can do something for you. But you need to start combining all those bits and pieces together as to try to pull, pull those and that's what I saw in the 80s after 90s when CMA systems came out and they said, well, how do I get this system to talk to my finance? Right? And it were the people in the middle. And it was difficult. It was difficult because how do you pull the data between databases in? How can you look at the data that you can see what's sitting in your finances, what is sitting in your maintenance? It was difficult, took a lot of effort. That's where EIM and eventually ERP systems came because you've got now one system that looks after the whole spectrum. And that is where technology and AI starts becoming valuable because it become easier to make the links. The challenge we do have is security from, from like we have with technology, people hacking to people's operating systems in their plants. So comes with another challenge. So, yeah, it's, it's interesting. It is, it's definitely interesting. And let's just, you know, dive headfirst into that topic, you know, the big topic, the one that everyone talks about artificial intelligence. To do that. I would like to share an observation that I've made with you and I wonder what you think about this. And it goes back to something that we were discussing before we had this conversation. I think I mentioned last time that we were buying a new house. We bought a new house and it is a house that needs to be constructed. So naturally I'm over at the construction site quite a bit now. The first time I went, I went to meet with the builders, we went over the plans and there was nothing there, just an empty plot of land. But a couple of weeks later, when I showed up, they had actually done the fundament of the house, which was great. I come back a couple of weeks later and the builders had constructed the ground floor. So the kitchen was there, dining room area, you know, everything was there. I stepped out, I went to an event and I came back a few weeks later. And then on top of that ground floor, they constructed, you know, our first floor. So that's the, the bathroom, there's the kids rooms, everything is there. That's great. Last time I came on top of that first floor. Now there's the attic, right? My study is going to be there. And they put on the roof of the house. So the house is essentially finished. And that made me realize that, you know, that that is a structured approach to how you create something out of nothing, how you create value. That I think very much applies to how we create value with artificial intelligence in asset management as well. Because what I think is going to happen. If you expect, you know, to get this nice and cozy roof over your head because you suddenly invest in AI, what's going to happen? If you start with the roof, it collapses. But you need to start at that fundament. You need to start with the fundamentals, with the basics, to get things right. And I wanted to ask you about this. How is AI creating that real value? Right. Where is it value driven versus a lot of noise because people don't yet understand that they need to start building from top to bottom and they need to have the fundamentals in place. So, you know, one thing, and I'm sure you've seen and several of those as well, is the issue around digital twins. You know, we have a digital twin, but even if you look at how that starts, you know, somebody walking through a plant, videoing structures and whatever. Yep. Assets, motors, gearboxes. But you can video it and you can map it, but you still need to describe for the AI what it actually is. Right. And that's, that's the thing. You know, I often make the analogy. If you stand in a operating or manufacturing facility, that equipment doesn't know if it's day or night, it doesn't know if it's the northern hemisphere or the southern hemisphere. It doesn't even know which country it's in. It couldn't care. It's a. It's a design lifeless motor and a pump and a gearbox. It was most probably built in India or China or Brazil or America or Germany, wherever it was built, depending where you buy. But it comes with. That was this design. That's the. The kilowatt rating is designed for, that's designed for what to do you still need the attributes from, call it that of that physical asset. And that's where it start. So when you've got that and you can start with that foundation and with that attributes that you need to populate into a system comes what's the. This user gearbox, for example, what's the type of oil I use? How often do I check the oil quality? Is the dipstick in the right place? Can I access it to take a sample? What temperatures should it run at? And all those things and all that data you still need. And that is the foundation. That is the foundation. If you implement a maintenance system, a greenfield, new factory built, you need all that asset data that needs to come into the system. Yes, that's where AI you can start. If you are building from new. I think most organizations will say, let me do a digital twin at the same time, or at least have. Because the time to do. That's where AI is playing a huge role in your drafting. Drafting or capturing the physical layout of assets. Marking pipes, marking cables, being able to find. If you've got a whole pipe rack with different steam, water, whatever going there. You can label them, you can. You can find them easy. And that is where the digital twin. Because your human resource or the human asset, they come and go. People that bought the place might not even maintain it. And that's where the AI comes in. You say, all right, new artisan on site. He needs to go find this valve, put on the VR goggles and off he goes. Or he walks and he can call it up on his cell phone and says that's the. Because I can see it where the plant has been mapped, I can find it easy. And yes, then the maintenance. Capturing the data you take, you can. You can associate the tag, you can pull the maintenance data. What do you need to do? You can pull your. Your safe working procedure. What's all the safety requirements? What's the task? I need to do all those. That's where. That's where the. But if you really think about it, that's that AI has always been there. Yeah, it's always been there when the first things were designed and built. We have just digitized it. We've made it a lot easier that our record keeping. And you still need to be disciplined because that you still need to maintain. I don't know how many people don't realize that whatever system you've got, you still need to maintain and do housekeeping. You need to go and audit the data that's in your maintenance system. You need to on a regular basis. What I'm seeing in the. In the database, does it reflect in the plant, you know, when equipment has been changed out, does the database get updated? You know, is the rotable. The history around that rotable? Somebody needs to maintain it maybe in years to come. I know it will maintain itself. I don't know. I did work for organization where that pressing plant where they were we were looking at using RFID tags on. On presses and as you move the different tools into the press that you can track it remotely when it's gone out for refurbishment in the workshop with the tool and die guys and then goes back. So certain of those things you can maybe track certain type of industries. You must automotive plant with an assembly plant. Some of those things you can track these days they track the whole assembly of a car. But at the end of the day, you still need to maintain, somebody to go and check, does the data reflect reality? It makes it easier. I think it's this, this really important thing that we need to keep in mind. As you say, that maintenance for the foreseeable future still takes place in the physical reality. You can have this entire data stream that supports the work execution in that physical reality, but it's not replacing that sort of activity, is it? So it is there to support, it's there to augment, it is there to enhance what you're able to do. But your human worker, at the end of the day, they still need to do their due diligence. And as you say, you still need to consider, does my data still hold up? Is it still accurate? Does it still deliver me the insights that I need? Or do I need to readjust, recalibrate and move in a different direction? I think it's a wonderful point. I have one final question that I'd like to land on and it goes back to something that I've heard you say not once, but I think twice or three times in this conversation. Had I been a number of years younger. Right, so it's a bit of a cheeky question, but knowing what you know now, let's say that you were starting your career today, right? You're fresh out of college, ready to go. What are the skills or mindsets that you would prioritize, knowing what you know now, heading into where the industry is at at this moment? Look, I think over the years I always said as well, a lot of anybody's development is around the attitude. Like that saying goes, you, you hire for attitude and you train for skill. So mostly if, if you apply yourself, you can, you can learn. Now anybody that's done the tertiary qualification or even doesn't need to be tertiary, if you've applied yourself and learned a new skill set, it proves that you can keep on learning. So your attitude, I think, is so, so important. And I think if you ever, you need to foster a culture of continuous learning, have a curious curiosity for interesting. I sometimes got a curiosity for rubbish, rubbish information. But it's fascinating certain things that, that you learn. But if you've got a curiosity and enjoy reading, enjoy experimenting or learning something new, that will be to your advantage. I think for any engineer that I think that the field of. And maintenance is not maintenance like we had in 18 maintenance. The fundamentals are still there, but there is so much to it. The one challenge we do have is you go to any university or college or whatever, there's still no very specific focus around maintenance, reliability. It's still very fragmented. Because I've had the conversations with a number of young guys, say I want to focus on reliability. Where do I start? And I go, we need to know what, how does a maintenance system work? You need to understand rcm, you need to understand risk, you need to, you need to have curiosity and a detective type of mind to doing root cause analysis. Because, you know, you learn from failures, you learn not to repeat it. You learn so much from that. And so you've got all these different things that you need to learn. You don't need to have be an expert in all of them, but you need to understand how they work. If you don't know how a maintenance or CMMA system work, you're not gonna appreciate the value of the data. You're gonna start, you know, you're gonna be in a battle to, to understand. You need to know how planning and scheduling work, how do you plan for work, how do you do project management? You need to have all those disciplines. But for. I'm most probably not answering your question, but the answer is it is an exciting time. I think I saw it when PAS55 came out in 2008 and the pioneers of those, there was a number of people in South Africa and there was a lot of people across the globe that acknowledged that we need to become more professional around maintenance and asset management. And if you look, ISO55000 only came out in 2014. So it's still young. The standard is still young and is growing and there's a huge uptake on it. You've got your skeptics and when people hear ISO, they think of auditing, but it's not that per se because ISO gives you a phenomenal framework of how to look after your, your assets. So there is so much happening in a very short period of time and not even. And this is why it's the latter part of my career. If it, like I said, ISO50000 is 12 years old, right? Really. And that's not, not old. But there is so much happening. And if you look at what's happened just, just in a short period with AI and the leaps and bounds, it's, it's done. It is really exciting. It's. But you need to know, do you have to be discerning? And yes, the benefit of being getting older, you can also get a bit skeptic. But you also realize to be discerning and it is something you can't impart on somebody is a lot more difficult because everybody needs to make their own mistakes and learn because you learn from that. But I think it's also, you know, the ratio of this to this is so important. You know, even if people tell you something and it doesn't make quite sense, rather listen than trying to tell and read and. Yeah. And enjoy it. I think that's the, that's the ex. That's the real. You need to have a. You need to find enjoyment out of and the technology and understanding how things work. No, it is a, it's a phenomenal. It is a phenomenal time to. To be around for. For a young engineer. Absolutely. And it's not just an industry. If you look at what's happening in the facilities with buildings and all those. Our buildings are being managed and huge infrastructure projects. It is, it's not just there are so much happening in the different, different sectors of physical assets now do we take care of them? How do we manage them? How do you make them make our lives easier? You know, and I'm sure in 10 years time there's going to be somebody that sits here and talks about how you maintain your robot that sits in your garage. You know, your robot packed up, the one joint is not working anymore. What do you need to know? You need to have a titanium bolt and you need to have it the right clearance else the arm is going to keep on sticking. You know, those things are going to need to be maintained at some point and you're going to need to take some spanners out and a soldering iron and I don't know, fix the wiring or. Right. Replace. Give it an upgrade. Software upgrade. You need to understand how the software upgrade on the, on your robot is going to work. So yeah, it's, you know, it's this whole idea of continuous improvement. I mean, as you say, exciting times ahead in asset management, exciting times ahead in your life as well. Congratulations once again on becoming a grandfather. I think that's wonderful. Wonderful. Thank you so much for these great insights. This is the end of this episode of Assets Unscripted Assets Unscripted is hosted on the future of assets.com website and that website is created in partnership with both IFS and ultimo. Hope you enjoyed this episode and we look forward to you listening in to the next one. As always,