Paul Turner:
Hello everyone. Welcome to today’s episode. We’ve got a fascinating group of companies from all over the world in several industries to share some very valuable and useful information on readiness, commissioning, outcome assurance, and we’ll even touch on some of the AI trends that we’re seeing in the industry at the end here as well. So I’m looking forward to today’s discussion. Let’s start with yourself, David. David is the Chair of our technical committees, is organizing our worldwide organization and collaboration of some of our technical experts all over the world. Hi, David. How are you today?
David Tain: Good morning, good evening and good afternoon for you guys all over the world. Thank you so much, Paul. Yeah, absolutely. I’m really excited as a chair, as a chairman of the technical committees. I’m really pleased to be here in this second edition of the second ICXA Global Knowledge Roundtable, especially after seeing the great positive feedback we had from the previous one from all over the world, right? So just a reminder, the knowledge roundtables are very significant initiatives for us. They are key mandate of the technical committees, right? The main objective of us is just to help advance the profession of commissioning outcome assurance and operational readiness across the world cross-pollinating all this knowledge that exists segmented all over the world and experiences from all geographies, industries and disciplines, right?
So Mauricio Nichterwitz, he’s a partner at Deloitte. He’s joining us from Sao Paulo, Brazil. Glenys Rule, she’s an operations commissioning manager at Watercare Services. She’s joining us from Auckland, New Zealand. Enrique Cardona, he’s a principal engineer at H2O Innovation. He’s joining us from Pompano Beach, US. And Marko Vicentijevic, he’s a director at FourQuest Energy. He’s joining us from Abu Dhabi, UAE. So welcome, all and happy to have you here and I hope you guys enjoy the discussion.
So how can organizations develop commissioning-driven execution strategies early in the project lifecycle, ensuring that commissioning evolves beyond this technical verification or testing into a capability-building mechanism that shapes operational performance from the outset? Let’s start with you, Marko.
David Tain: Thanks. Very well. Thank you so much, Andres. How about you from the Andre Goosens? What is your perspective?
Marko: Sure. Thanks, David. So I always say that the best time to address a potential commissioning issue is well before you start pouring the concrete for the foundations. Now that might be a bit of an overstatement, but my point is that the earlier that you can start working on at least the commissioning philosophies and the overarching commissioning strategy, the better. So really it should start you in the FEED stage. Then as the project grows through detailed engineering, procurement, construction, you can kind of hone in and get specific with respect to the procedures, specifications, documentation processes as you go on. And what this allows you to do is to really work backwards from the start-up plan with the start-up execution plan.
You can then work backwards and prioritize and do your systemization and construction priority based on that, not just based on, you know, installing inch meters of pipe and measuring your progress in that way. And I kind of like the reframing the question of commissioning, not just being technical verification, because it’s not just technical verification. It’s really where the operations team gets their first introduction. It’s ready to get to meet the facility or the project or the asset. And so they should be part of that early as well. So early during the detailed engineering, you should have operations representation as part of those design reviews, HAZOPs, operability studies, model reviews. And I think the other way to get this going early is to incentivize it and adjust the metrics accordingly.
So as you’re going through the early stages of the project, making it not just about, you know, construction completion, inch meters of pipe installed, tons of concrete poured, but system completion punch list burned down, I think that’s how you can really make it commissioning throughout the project execution phase.
David Tain: Thank you so much, Marko. Great, great insights for sure. Glenys, what do you think about this?
Glenys: Okay. I really want to know who, in their career, hasn’t walked late into a project to start commissioning when the budget and schedule are already spent the assets they’ve built and they look great, but they’re not the standard and they don’t do what the operations team want. And the one thing you need to start with hasn’t been built yet and it takes you months in a conflict zone to just to get the software to talk to the valves and reduce the number of alarms to something we can live with. So I guess as Marco said, let’s flip the order of things. We don’t let the construction drive the schedule. We use the start-up sequence to drive the schedule and we move past basic checklists. It’s not about checking that a pump works. We look to optimize that. We tune the control loops, we rationalize the alarms, we stress test the system for abnormal conditions.
And then we become part of the asset lifecycle. So the project leaves behind good quality asset data including baseline performance. It’s not just a pile of disorganized paperwork. We use commissioning as a classroom. So we identify the training gaps early in the process. And then during our dynamic commissioning, the operators can work directly with our commissioning experts and engineers. And this hands-on co-commissioning speeds up the operational learning for the new plant.
David Tain: Excellent. No, thank you. Definitely. It is a progressive, incremental effort. You can, you don’t have to wait until the last minute, which is pretty much one of the key mistakes that all projects do. Enrique, well from your side.
Enrique: Yeah. Good morning everyone. So basically organization should treat commissioning operational readiness and outcome assurance as a single or unified management system, not a hands-off milestone. So that model effectively it starts early, embeds readiness into design and delivery, and assures the outcome. So commissioning-driven strategy should not start with the mechanical completion as many people understand it. So because you want to define in early stage the system boundaries, completion criteria and turnover packages. So that would give you the capability to understand and to define the roles responsibility for each one during each of the phases and how the system will be delivered. Or turnover to the commissioning team. So saying that we have to have a very good commissioning plan that includes FAT, pre-commissioning, commissioning start-up ramp-up performance, the trial period. So it explicitly links each phase with its expected outcome. And what is this would be engaging in the, in the life cycle of the project, meaning that if you’re, if you follow all these, all these steps on the early stage during the design, you’ll be sure we’ll be mitigating any of the delays that many people find during the start-up.
David: Thank you so much. Especially delays and troubles that are handed over to operations, right. So these delays and all these unknowns, right. Mauricio, what is your perspective from this point?
Mauricio: Yeah, it’s difficult now with the very good contributions, but I can see that projects nowadays are engineering-driven. What I mean is that I do the engineering, I procure what I can, and I construct what I have in the field and commissioning is always very difficult because we don’t have the best order, okay. So we need to change this mindset and really do commissioning-driven, system-driven projects. And we need to do it in the very beginning, in the front-end loading phase. So we need to think in the precedence network. We need to develop our commissioning plan and our operational readiness plan, and of course we need to check all these plans, all these networks and the schedule, okay, at the stage-gates.
So mainly at the final investment decision to check if everything in the project comes together, think about it in a commissioning-driven way, and everybody on the project is on the same page. A commissioning-driven project requires a change of mindset. This is very important, and it’s very important we start in the very beginning, David.
David: One of the keys is really, really important to reemphasize that Mauricio, because it’s a lot. It’s about not only the alignment, but more importantly, the change in the mindset. This change in the mindset is what’s actually, you know, what makes it difficult because everybody is used to the traditional way to execute projects, you know, scope, schedule, and quality and that’s it, right. So it’s just, you know, it’s more than that. It’s just delivering value, and it goes back to our first roundtable, which is ready to start up is not the same as ready to operate. So essentially, you know, you can be pushing the buttons and you know that doesn’t do anything for three days later, the plant has an unexpected shutdown. So for that, no. Thank you so much, Paul. I’m going to turn it over to you for the next question.
Paul Turner: Yeah, two interesting points. I heard from Glennys that commissioning as a classroom, I really like that phrase. I think that’s definitely true, right? It can be an abrupt change from the project environment to the operational environment. And the more we have the folks involved there to support that soft transition, commissioning as a classroom is a perfect, perfect term for that. Mauricio’s comment also on a systems-based approach, the only way that you’ll deliver a system is when you govern the project as a system, right? A systems-based approach upfront is fundamental. So I appreciate those answers. Thanks.
All right. So next question is how should engineering, construction and commissioning operational readiness and operations be unified to build operational readiness capability for the project and for the organization? Let’s start with yourself, Enrique
Enrique: So for an engineering perspective, you know construction, commissioning, operational readiness, it should be operated at a single or unified integrated framework. We share milestones, integrated schedules, single version of readiness. So in practice operational readiness is managed as a second-order capability. So the organization is not only ready for start-up, but also capable of repeatedly preparing assets, people, processes, and support systems for safe and reliable operation. So you have to have an integrated governance body to authorize how this process changes from phase to phase, how the design changes readiness start-up criteria. So you have to define all these steps in a in a common sense outcome and you know common sense, I mean what is expected. So what is the best approach to achieve it? So that’s a single stage-gate process.
These gates link the design, the design completion, construction completion, commissioning and training. Because that is the way you follow this, as I said before, you follow this management approach in order to get this unified framework. Because when you do the design, you start in the design phase, you catch early stage, what the possible outcomes are. And also you can also identify the risk associated to it. And let’s say if in the team you don’t have anyone else who is looking for possible risk that can jeopardize the production or execution of the work you can do as a design early phase.
Paul Turner: That management approach is, is fundamental, exactly like you say. When, when the management approach is only focused on scope, schedule, budget, well then you can’t be surprised. That’s what you get at the end, right? But with a management approach, you change that mindset and have a, a systems-based approach, then you’ll be able to deliver systems at the end to make complete sense. All right, let’s move to yourself. Marco, what are your thoughts on this question?
Marco: Thanks, Paul. So I think that the integration problem is due to the fact that all of these things tend to be siloed, right? So engineering is its own silo, procurement, construction, commissioning, operational readiness operations. And generally within the silos, you don’t really run into productivity or value leak kind of issues when you’re in the middle of the engineering. When you’re in the middle of the construction, it’s, it’s, it’s all fine. It’s at the seams. It’s where they integrate, where you switch from one to the next. And I think this is where operational readiness comes in because operational readiness, it’s not a checklist of things to tick off before we’re ready to go to the next phase. It’s really, it’s really about risk management for me.
It’s about identifying the gaps that exist from the current stage to the next one, whether it’s commissioning to operations or construction to commissioning and putting in place mitigation steps to manage the risk and to close the gaps. And I think one of the best ways to do that is these integrated steering committees where you have process engineering, design, commissioning, operational readiness, operations, all working towards a single set of KPIs. And this also helps you with change management because anytime there’s a change, you have to address usually the majority if not all of these different siloed departments anyway. So if you have that integrated steering committee, you can often manage change a lot more effectively and efficiently. And change management, in my experience, is one of the things that tends to slow projects down the most.
Paul Turner: I think you hit the nail on the head there. Yeah, absolutely. An integrated approach and that management approach right from the beginning to holistically look at everything. You can’t throw a bunch of groups out onto a project and expect them to figure out the silos. You need that strong governance upfront to make sure that everyone’s working towards the same set of KPIs. So I like that answer for sure. All right, Mauricio, let’s get your thoughts on this particular question.
Mauricio: Perfect. So it’s a problem around the world. This one, the integration of the discipline, so. Because that the CII Construction Industry Institute developed a framework that is Advanced Work Packaging framework. This framework really thinks about the commissioning-driven or construction driven project. So we define the system work packages. We pull construction, procurement, and engineering into the sequence. So we do a backward planning from the very beginning of the project and starting in FEL 2 and detailing it in FEL 3. Okay. So with this, in the very beginning, we think through the path of construction and the work package. This sits within our precedence network. We see how we will construct the systems, Okay.
We define the order of engineering and the procurement to really deliver what the construction and the commissioning need at the time that these disciplines really need in the project. So it’s very important in a very robust framework that I indicate for everyone to search and learn a little more about it. And the second point is in the very beginning with the path of construction defined by the precedence network, we involve the operations and the maintenance to give their advice at the beginning of the project.
Paul Turner: I appreciate that for sure. Right? It’s that start with the end in mind mindset where everything’s integrated through engineering, construction, commissioning, and the right things are happening in the right sequence to help the next group succeed as well. Definitely makes sense. How about yourself, Glenys? What are your thoughts on this particular question?
Glenys: I actually think it’s really tricky because these functions all love to live in their own silos. So if you think of other high-performing teams, professional Formula One mechanics, tire changes, drivers, they all train together in one unit. Sports teams, players, coaches, physios, managers all work together for the same goal. And they trained together, but we let our engineers design it, construction assemble it, and then we throw the keys to the operations team. All too often, the operations team has never even sat in the driver’s seat and then wonder why it doesn’t work. So maybe we should be getting in the room early, agreeing on a commissioning strategy. We’ve talked before earlier in the podcast, driving roles and responsibilities, documenting it into a plan early, bringing operations and commissioning into the design phase.
That’s much cheaper to fix operational issues on the screen, but finding that same issue during hot commissioning can be really costly. Defining what construction success really looks like. It’s no longer good enough to hit my milestones or just pour concrete. Instead, construction teams must build for commissioning, and that means sequencing the completions based on systems functionality, not what’s convenient for the build crew. I think it’s come up in this podcast a bit. And then embed operations into delivery so the operations team isn’t just handed a set of keys and manuals at the end. They need to be with the commissioning team as much as possible. Testing assets, mapping alarms, running simulations and handover may has a much lower risk of being a high stress negotiation and instead maybe become a transition.
Paul Turner: There’s a lot of great expert advice in that answer for sure, that can save projects a significant amount of time and money. So appreciate your insight, Glenys. All right, David, over to you.
David: Yeah, I know. Thank you so much. Tremendous insights. And I’m hearing constantly one of the key, one of the key emerging themes in this, which is the integration of risk management. And that’s why, actually, you know, it builds to this. Yeah. The third question that I particularly like is the capability-based model that the ICxA is spearheading across the world. And it’s essentially that, right? So this mindset that Mauricio mentioned, this integration that Mauricio and Marco as well mentioned, Glennis with the commissioning, you know, a classroom and so on, right. So, and the full transition, as Enrique mentioned as well, particularly this question deals with the governance and the models, right?
So the question is what governance models, organizational structure, and cultural elements- which is really important about mindset and the decision-making process are required for organizations to evolve from delivering projects to assuring sustained operational outcomes and value realization. As I mentioned before, as a third-order capability. Mauricio, let’s start with you. Perfect.
Mauricio: My point here starts really the organization, okay, because a lot of times I see organization with the different incentives. Okay, so we have an incentive for procurement to save money, not the project result. The construction needs to construct on time and on budget, the engineering needs to see and develop the best solutions. But these incentives are not aligned in the project outcome. So the organization really needs to develop incentives, a bonus for executives and for the. Teams. To align with the project outcomes and the project outcomes in the first year of operation, for example and. They deliver that this project really delivered to the company. So we when we align these incentives and everybody thinks in the same way to deliver outcomes, to deliver the value to the client, we really have a change of mindset. Everybody’s thinking the same thing and align at the same objective.
So this is the first thing that our organization needs to do to change the future and to put. Every everybody in the same page. Okay.
David: Absolutely no, that’s essentially that is you’re absolutely right. This the incentives, right? So is key because that’s going to be driving the mindset and how this incentive look like, you know, monetary thing and this it is a change in culture, right. So how about you, Glenys?
Glenys: I think in a similar strain, it all starts with a strong, unapologetic buy-in from the very top. So if executives can’t stick to the game plan, people will cut corners to save time and money. And that’s when we need realistic budgets and schedules. And it’s got to be more important than exerting pressure to produce artificial front-end targets. So traditionally, you know, we’ll get gate reviews asking is the pump installed and operating? So we need to ask the right questions now modern gates ask: is the team trained? Is the software validated? Can we operate this safely? Contracts need to be aligned. We need to shift towards commercial frameworks to incentivize long-term asset performance so that success isn’t just a signed-off construction certificate.
It must be a demonstrated stable process that is operating well, using data to demonstrate that the asset achieves its actual design intent, like specific energy targets, chemical optimization, strict water quality compliance. That’s got to be more important than just putting concrete on the ground. And we’ve got a shift from a culture of, you know, it’s not my problem because I’ve handed it over and I’m out of here and on to the next project to everyone owns the outcome and everyone on the project, from the designer to the builder, feels a shared responsibility for how that plant runs two years down the road.
David: Excellent. Thank you so much, Glenys. Enrique.
Enrique: Yeah, that is pretty tricky question and because it means that it’s not structural, it’s more cultural things. So moving projects toward assuring outcomes means that the realization has to judge not only to substantial completion, but have a sustained performance is a value added as the years or three years. So this governance has to allow to have to follow accountability past the finish line so stage-gates do not come under interpretation once the metrics are met. So that means that each of the phases we are we are delivering outcomes. This outcome has to be met, so we have to focus on that. So for delivering the projects to assuring some operational outcomes and value realizations organizations need governance to manage value over time. That means that we are, we are supposed to focus more on the performance of the of the commissioning, not on the schedule based on the construction.
Because one of the things is that organizations, they are putting success more on substantial completion, not on the outcome that is expected to. So the success of the project is the outcome, not the substantial completion.
David: That is a really, really important insight. Enrique is exactly that is, is putting the ice in the project and the ice in the project is not delivering as a silo is delivering value and not only that sustaining. That’s where the true value is going to be tested. How long and how robust can this deliver and sustain value for the organization, Marco?
Marco: Yeah, I agree with everything that’s been said so far. When we talk about outcome assurance, now we’re talking about sustained production, uptime, future OPEX requirements and the kind of overall life cycle value. So how do we achieve that? I think there’s a few things. One of them is adaptive governance and flexibility. So being able to change and adapt to changing conditions. You know, we’ve had some geopolitical issues here in my part of the world recently, and organizations need to be able to adapt to events like that and the incentives, which I think everybody else mentioned as well. I just like one specific example, as you know, where if I can use a carrot-and-stick analogy, we’re quite good with the stick.
Every EPC contract has warranty provisions, penalty clauses that if you don’t deliver this or if it doesn’t work six months from now or within the warranty period, you must come and repair it at your expense. But I’ve seen very few that actually have some kind of carrot where it’s, if this asset delivers what it’s supposed to deliver for a sustained period of time, if it has this uptime, then you will be rewarded for that. So I think we can still do a bit more to align the incentives with what we’re actually looking for. And the other part I think is the continuity of people. So project teams tend to finish a project, move on to the next one. And with that, you lose all of that knowledge. I think it was something that Glennis was speaking about, about the commissioning is the commissioning school. When the project team moves on to the next project, they take all that with them.
So having the continuity of people from project execution to operations and then taking lessons and applying them to future projects, that’s also where we can see some real benefits.
David: Oh, thank you so much, Marco. And you say something really, really valuable, which is the carrot-and-stick analogy. You, if you only put sticks, you’re just turning all your corporations and your, your, your, your ecosystem into a defensive, a set of defensive entities are supposed to be collaborative entities. The only way to turn them into collaborative entities is through that, to that carrot, right? So to make sure that the same way you have provisions, right? So for penalties, you also have provisions to, for success, right? So I’m clear that I would say more and based on what I’ve seen, the penalties clauses are very clear on the contracts. The ones that have ambiguity are the ones that are reward. So they have to have the same level of clarity and specificity. So, but now, thank you. Thank you so much. That’s great.
And then I’ll turn it over to you, Paul, for the final big question actually.
Paul Turner: This next question is actually quite fascinating in some of the trending topics you hear in the media related to AI. Now, I don’t think there’s any question that AI is going to transform the industry. It’s very fast-paced, and things are definitely changing, right? How the industry is going to change. I think we’re learning and adapting as these new technologies emerge. I’m not sure that anyone fully has the answer, but we still need to be prepared because this powerful technology is coming. So I think this will be very fascinating to hear everyone’s insights and thoughts on how the industry is going to need to adapt to some of these upcoming technologies. So the question fundamentally is: how can AI improve planning, forecasting, readiness, integration and risk management without replacing core delivery and assurance capabilities? So let’s start with you, Enrique.
I’m very interested to hear everyone’s thoughts on how AI is going to impact the industry and how each unique industry is adapting.
Enrique: Yeah. So AI can strengthen planning, forecasting, readiness assessment, operational integration and risk management by giving you data, detecting anomalies, and drawing on existing knowledge. But it should be understood as support, not as a replacement for commissioning. So you can, you can do a checklist, pressure test, commissioning sequence; you can do forecasting, readiness gaps, but you cannot put it all into a list and expect it to work in concert. I’m thinking more plant-wise. You might be building a plant. Commissioning cannot be done in silos; it needs a systems approach. So, saying that you cannot use AI, how do you say you cannot use AI for making decisions, only as a tool to give you advanced sequencing and advanced knowledge that you have from previous experiences? So readiness forecasting, scheduling, and training.
That’s the matter that AI can do it, but you cannot use it as a decision-making tool across the broader spectrum of the project. That’s what I mean.
Paul Turner: You mentioned amplifier AI is AI is really going to be the big amplifier going forward, right? For companies that have strong core capabilities, they’re going to be able to leverage these tools and accelerate their systems that work. For companies that maybe lack some of those core capabilities or have silos, than AI is going to expose those and probably amplify those weaknesses as well, right? You see that in a lot of industries where AI is kind of amplifying things that work, but also exposing things that don’t, just at a much more rapid pace. So I like that term you mentioned on AI amplification.
Enrique: Exactly. It should not be used as a substitute the commissioning discipline or operational judgment, accountability. It’s just a tool. It’s just a tool to give you amplified answer for existing data. Remember that this is pretty AI gather all these scenarios that they’re already data in. But In the plan is a new project, so you have to focus on more what is the outcome expected from that one because it’s unknown until you go and reach a start doing the operational readiness.
Paul Turner: Appreciate that, Enrique. Thank you very much. Let’s hear from yourself, yourself. Marco, what are your thoughts on how AI is going to impact the industry?
Marco: So I use AI a lot in projects. I use it in my personal life. I use it in my professional life. And something that I’ve noticed and I don’t know if anybody else has noticed it, but I noticed that when I ask the AI about something that I don’t really know a whole lot about, I get a very professional confidence on the answer. And I think, wow, this is this thing is a genius. But anytime I ask it about something that I actually know a lot about, I think wow, this is sometimes just completely wrong. Sometimes it kind of misses the point. And I think it touches on something that Enrique said, which is and yourself, which is that it’s only as good as the data that it actually works on. So if it’s trained on good data, it amplifies that, like you said, and it gives you good outcomes and good results.
Paul Turner: I think that’s key for sure, right? AI is definitely going to be a powerful tool and I don’t want to discount it. We need to be adapting and using these tools. But it’s that core capability, that expertise, judgement to know what you’re getting, whether whether you can rely on the answers and amplify the responses that you’re getting. All right, you’re, you’re next, Mauricio. Let’s hear how you and Deloitte are addressing AI and using these powerful tools to help us on projects.
Mauricio: Perfect. So I think AI can help you like a copilot. Okay, yeah, you need to you can check your premises and with AI I can insert my precedence network and ask if AI sees some problems, some risks, some issue and give me some advice that I can check. I can insert my cost, my CBS or my WBS and check one against the other and AI can give me advice on what it can do, along with a lot of other things. I can set my, my schedule, plan my schedule and check the risks, Okay. So we have a lot of potential. Uses of AI as a copilot. Nowadays, I can see It is very useful for generating documents, such as schedules from scratch. I insert some information and ask it to create the project schedule. I have tried that a lot of times, but AI has problems doing it because it creates a lot of assumptions that are not true. Okay, so. I believe that the best way to use AI nowadays.
Because AI has evolved a lot, I think the best use is as a copilot for checking and developinging some alternative plans.
Paul Turner: And AI even from a year ago maybe wasn’t what we were hoping and expecting it to be. Now it’s becoming quite powerful. It’s hard to even imagine in a year from now or five years from now how sophisticated these tools are going to be. I think we definitely need to be learning and adapting to see how we can use these on projects because they are only going to get more powerful for sure. How about from yourself, Glenys? How is Australia and New Zealand adapting to this new AI world that we’re finding ourselves upon?
Glenys: As for us, I think it’s not about replacing human commissioning engineers, it’s about making us better. And it is moving so fast, as you say, that I’m really looking forward to be able to let it deal with the admin. If you like scanning drawings, asset lists, automatically generating testing documents to free us up to actually do some real engineering and some commissioning. Maybe scan designs and have some peer review so that we can get second opinions on designs, pick up design flaws. Maybe already have digital twins, so feeding real-time commissioning data into our models and simulating scenarios based on real plant data so that operators can practice the responses in the virtual world. And then maybe continuous optimization. Really looking forward to when AI can help us fine tune chemical dosing pump speeds in real-time to keep the plants running in its sweet spot.
The stuff that takes such a lot of time and effort to do manually. And also, we’ve all got a wee notebook, which is full of random useful data, rules of thumb, lessons learned. But what happens when we leave the project? That knowledge is built over decades, and it leaves with us. And with an ageing workforce, that’s happening more and more. So I’m hoping that we can use AI to ensure that the lessons learned during commissioning don’t get lost when people leave. Yeah, maybe ensuring the knowledge we gain during project delivery actually protects and optimizes the asset for the next 20 years.
Paul Turner: Definitely some opportunities to apply these technologies for sure. Now I do see that we have some questions in the chat. Before I get to those, David, I’d be interested to hear your thoughts on AI going forward and maybe how the industry should think about some of these technologies or maybe adapt as we move forward.
David: Yeah, Paul, that’s a really fascinating topic, as a matter of fact, something that we have been progressively engaging and learning more. And first of all, I concur with what the panel says. This is not a replacement. It will never be a replacement. It’s an accelerator of knowledge. And I use AI, and Marco mentioned something really interesting. This is, you know, every time that I ask something that I don’t know, it gives me a really beautiful answer. But every time that I ask something that I know, it actually makes some inaccuracies, right? So, and that is a really big limitation. So #1, AI, even though it’s really powerful, is not what it’s going to be in the next few years, yet it is really powerful. Another item that I see particularly coming from Glenys mentioned about the digital twins.
Something that we’re really, really heavily starting to get involved in is the data, right? So, I mean, AI is as good as any software, as good as the data it receives, right? So that’s where you can see the mistakes and the acceleration. So AI far from being a replacement, it is an integrator. It’s going to help you to change this mindset. It’s going to help you to accelerate your decision-making process. It’s going to help you to get faster to your next step, but will never be a replacement for what the next step is going to be. I can see already big projects relying on so much in AI and essentially, you know, compounding the error, right. So which is this is not different from what we have been seeing in any scientific matter, right. So error has a compound effect and the same way that it can accelerate your decision-making process, also accelerate the errors, right?
So one can lead us to, and if you blindly trust in AI, it’s going to lead you to disastrous consequences. Yet in my particular case, from what I’ve used and what I’ve seen, AI is accelerating knowledge, but also being cautious of always validating the reliability of the data that AI is fed. And no, my thoughts, generally speaking, are that AI is going to change. It’s changing already. The ecosystem is changing already; the way corporations are operating is changing; the way projects are started to deliver. You know, I have seen a tremendous exposure. I had the great privilege of being in Sao Paulo, particularly with the PC Expo, and I saw a lot of great, tremendous insights into the great advancements that are, are being done in the region, right. So with Deloitte and all the, all the partners very pleased to see how technology is emerging, particularly in that region.
It’s really strong, really robust and as Mauricio mentioned as well, right. So it’s, it’s, you know, AI is being an accelerator, but we also need to be very cautious of how we use it. So really pleased, as I mentioned, you know, to see how we are all across the world using this technology to accelerate, to catalyze the evolution of the ecosystem.
Paul Turner: Compounding success and compounding the error right to AI is really the great amplifier. And for companies that are being leaders and have world-class capabilities, they’re going to accelerate; the ones that have some gaps in their capabilities, that’s going to be exposed wide open for everyone to see as the crazy pace of change continues to increase, for sure. All right, we’ve got some really good questions here as well. So these are open to anybody who wants to add their thoughts. I’ll put them up on the screen here and interested in getting everyone’s insights.
Q & A
Paul Turner: So first question here is the important points in commissioning projects that must be assured before starting. We have latest updates to the documents full package and maybe this is somewhat related to AI as well, right? The information that we’re dealing with, the documents we have, the accuracy of information AI is going to help here as well. So interested in anyone’s thoughts on this particular comment.
David: Yeah. And to supplement that is essentially it comes down to starting with the end in mind, right. So I mean you can even even the way you structure your packages, structure your information, right. That is a really valid point. I mean, if you don’t have that, and I’ve seen that across my career, if you don’t see that clear, you’re going to be scrambling with unidentified last minute turnover packages and delivery packages where you know you’re not going to have a team that is prepared. You’re not going to have a team that is ready to receive it, let alone to operate it, right. So now you are into the improvisation mode and that’s one of the most disastrous effects, right?
So as soon as you start improvising, particularly when you are transitioning to live operations, you know, you are pretty much playing roulette not only with the budget, not only with the financial, but also let alone, worse, with the safety of the project, right. So that’s improvisation must be avoided at all costs. Yeah.
Enrique: Yeah. And the risk associated with it.
Glenys: My team has a bit of a motto. We go slow to go fast. So what that means is that we make sure that we’re ready before we move off and we don’t artificially speed up at the start and waste time at the end. Excellent.
Paul Turner: All right. Some very good insights for sure. Next question is from JAV. Hi, JAV, good to see you. AI question. Some are trying to use AI to replace humans on projects, while others, like those I support, are shaping it to assist humans rather than replacing them. I think there’s some great insight in that question in the companies’ or corporate approach to how they’re using these tools to cut and trim or actually to leverage these tools to exceed, maybe in things that they couldn’t even do before. So interested to hear everyone’s thoughts on this one.
Marco: Yeah, funny enough, I’ve been reading some articles recently that a lot of the technology companies that have been replacing their coders with AI have realized that it’s actually more expensive. They’re spending more money in AI tokens than the salaries of those programmers that they had on payroll before. But I totally agree with JAV that it should be used to improve the productivity of professionals and knowledge workers and take away kind of the drudgery of, you know, working with data, working with Excel spreadsheets, making PowerPoint slides and free up more time for the important decision-making, maybe the creative, the creative kind of knowledge work, the engineering.
Enrique: I would add, you know, is AI is a, is a tool that gives you a faster response. Or let’s say that you are, you’re on the field and you need something fast. You can use AI to give you that answer, but not as the process. You know how to achieve the outcome is something that you have to have the feel and experience that you have to input in this in not the AI is going to just give you what is what you have to fulfill in order to do the check the checkmark. You know, pass or fail checkmark.
David: You know, it’s interesting, if I may add something interesting here. So everybody is and I see this trend and now especially with the emergence of AI, everybody is asking the million-dollar question. And as always, Paul calls the AI question. We’re we’re tending to forget this is in the entire ecosystem. We’re tending to forget that, you know, it’s a people product, right? So we can’t have the most sophisticated tools, but we are facing a sociotechnical problem. And this is a phrase that I always you know, it’s building on what Mauricio mentioned about the change in the mindset and particularly with the culture, right. So this is a quote that’s arguably was done by Peter Drucker. Nobody knows, but the famous quote says that culture eats strategy for breakfast. And that’s true.
I mean, it doesn’t matter how much AI you are trying as Marco mentioned, all of a sudden these corporations are replacing with bots and AI and they are realizing that it is. I mean, these projects are complex networks of humans. And as a complex networks, they are subject to adaptation. They are subject to complexity of rearranging the systems. These are systems and unless we embrace a changing mindset, unless we truly embrace, go to the basics and go back to the system thinking, we treat projects and treat assets as you know, as complex adaptive systems. It does not matter how much AI and I and I am always fascinated by the power of the AI. Don’t take me wrong, I’m I’m pro, but we never need to. We always need to remember. We can’t forget that this is a sociotechnical problem, right?
So we can talk, I mean, we can have entire conversations and entire forums are about AI, but unless we actually treat this as a sociotechnical problem system thinking we’re going to fail, we’re going to fail. I mean, we, it doesn’t matter how good the framework is, it is a human problem. And that’s where the value of experience, you know, it comes right. So experience and insight matter. You know, unless we understand how we can merge that concept, we can put, you know, you can put a beautiful plane outside, but if you don’t have the right pilot, you’re not going to even take off. We have more questions.
Paul Turner: Next question, everyone is interested in AI for sure. So AI systems can support in predicting issues during commissioning scenario as simulation. And I think this aggregation of data and prediction elements is certainly a powerful use of AI. Who has some thoughts on that one? I think Glenys mentioned a lot about the digital twins, right. So this isn’t predictive power so this is it’s something that I’ve seen personally, you know, is that and now with the emergence of digital twins, right. So I’ve seen fascinating, not only in the in the, you know, in the future. I was listening the other day to one of the conferences in the medical field. In these Knowledge Roundtables, I always try. I try to listen not only from the project world, but also from other disciplines. And especially the other day I was listening in the in the medical field. This digital twins, right?
So can actually even improve the way of treatment. So essentially they were referring to a cancer patient, and we’re not there yet. But in the future, the way I personally see it, and I agree with the doctors say that you’re going to have, you know, a person that is that it requires, you know, a particular cancer treatment. And you’re going to pretty much pull all the data and start simulating with this digital twin and eventually come up with the right, you know, with the right treatment that is going to save his life or at least prolong it, as opposed to being dependent on the Pharmaceutical industry, all these trials and that take years, right? So that’s going to be an amplifier, although we are not there yet. But I mean, it’s just the same way it’s going to happen with an asset, right? So a little bit simpler, it’s still complicated, a little bit simpler.
You’re going to be able to simulate and create all these predictive systems, not only to simulate how this is going to start up, but also maintenance, right? So something important, right? So budgeting maintenance, right. So spare parts, critical spares. So what is defined as a critical spare, what is not defined like that. So I think simulation is the third way to do science and that’s something that you know, is emerging. We have in this normal scientific method, you have inductive or deductive analysis. Simulation has emerged as the third way to do science, right. So I think that’s important, but it always comes back to the people problem. I cannot overemphasize that, even though as a chairman of the technical committees pushing the technical portion, I will always emphasize that this is a human problem. The technical comes after the human side.
Does anybody else have anything to add?
Mauricio: One point here is that, for a good simulation, we need good project data. We need to have the base conditions in very good shape, and most projects do not have reliable data that we can use to do a good simulation with AI. We need to infer a lot of things; we need to create workarounds and the data is our big problem nowadays. If you have good data about the schedule, about cost, about the risks, premises and put it all together, of course. We can have very, very good simulations with AI in the digital twin, but how many projects really have a good digital twin? That is my question. Even then, few projects have a good model with all the information, so our biggest problem here is information and data. So with data we can, we can do a lot of things, okay.
Paul: Yeah, that reliability- not only the reliability, the existence of reliable data, right. So that is a big problem, right? So, and you know, I think personally with the emergence of AI, more than creating new data, AI is going to help organize and integrate that data, right. So for the future, I mean, AI will never be a crystal ball, yet is definitely going to accelerate the organization of the existing data to make sure that we use the right one, right? So it’s exactly what you’re saying, Mauricio, is, you know, the big problem here is the data, you know, especially with changing environments, right? So you can, you can have two projects, exactly the same thing executed by two different project managers, and you will have different results. It doesn’t matter with the same budget, same scope, you know, same timeline, and you will have two different results. So no, that’s data is the key.
Okay. So does anybody else have any other insight before we go to the next question?
I think this next question is interesting too, because we talk about some of the opportunities that AI is going to present, but it’s also going to create lots of challenges too, right? And here’s a good one from JAV: AI is just like human nature; AI is going to maybe try and cheat or manipulate or external bad actors interfering with our systems here as well. So there are lots of opportunities and I think lots of challenges ahead of us to deal with this new technology.
Enrique: Yeah, this is as my research says, is how data is. It should be managed because you have to be. You can trust AI, but even when you trust AI, you have to know at least why you’re asking and what outcome you expect. Because if not, you can be tricked. You know you can have a set of unreliable data coming to you. Thanks.
David: Yeah, well, yeah. And everything can be manipulated by cyber attackers. I mean, I say as AI, you know, everything, everything evolves, right? So not only the good things, so also the bad things are going to evolve. It’s just a matter of, you know, this is the importance of the governance, right? So, and it is impossible to have a particular topic in artificial intelligence, a global, a global governance system, yet we can ensure global governance systems for commissioning outcome assurance and operational readiness, right? So that’s going to be this governance is going to be a protective layer to a point of these cyber malware. So cyber attacks, right? So it’s going to be the organization, if you have a robust, for example, I can think of if you have a really robust operational readiness program, part of the operational readiness program is exactly that.
How what is, what is your cyber protection, and depending on the type of projects, right. So you’re going to have requirements of IT requirements that are going to protect you against this type of risk. I mean, it will be very presumptuous to say that you’re going to be, you know, invulnerable to any of that, but but governance is the key to, you know, to ensure that we can mitigate as much as possible these malware and cyber attackers.
Marco: I think as a as a time saver for certain tasks, it’s great. So just recently we had, I think, around 850 isometric drawings that we needed to figure out the volume of those pipe spools. Normally that would take somebody a good part of a week to build an Excel sheet and enter every single pipe. The AI took about 10 minutes to do it. We cross-checked; I think maybe we decided to cross-check about 5% just to make sure that it was kind of accurate, and that was it. That freed up an engineer for about a week to go and do real high-stakes engineering work rather than tallying up volumes from isometric drawings.
Paul Turner: I think we lost Glenys. We really appreciate, first of all and thank you to Glenys. Unfortunately, I think we had. We had some technical issues there, but a great contribution from Glenys.
One last question here on again on AI for me. During my job now, I’m not allowed to hire any engineers to or have any engineers write any report by using AI. So it sounds like there’s limitations on what AI can be used for in this particular individual’s projects. They can only use individual information. So that’s a tricky one too, because there’s a balance, right, If we need to be learning and adapting as these new tools are coming into the industry. But yet corporations may be hesitant because it is so new and fast changing how and where these tools should be used. So there’s definitely a balance there on adaptation versus limitation. What are your thoughts on that one?
Mauricio: Yeah, a lot of organization is facing this challenge. We have a lot of opportunities with AI, but nobody knows where the data that we sent to AI will be stored. Okay, so if I send my data, my classified information for ChatGPT or the cloud are they using my data to inform on other people or not that they did? Is the AI learning from my data or not, so the organization is very careful about that and because it is sensitive data. So the evolution of the organization is not in the same pace. of the evolution of AI. So a lot of people is using more for personal use rather than corporate use, okay and, of course, the small. Companies and start-ups using a lot more the AI because they don’t have this the same restrictions we see when we work with the big companies, huge companies and we are facing this type of problem.
We want to develop an application but we have a lot of limitations because of data concerns.
David: You know, Mauricio, you mentioned something really, really interesting is goes back to, you know, the adoption of AI and how you know it’s, it’s, you know, it’s not the same thing. First of all, the evolution. So AI is, is evolving faster than organizations and that’s a key thing because, you know, as I mentioned, it’s not the same thing trying to implement AI to a multibillion dollar corporation like an ExxonMobil or Petrobras something than trying to implement that to a small start-up, right? So #1 the risks and rewards are different and #2 you know, the, what is at stake is totally different. And of course it’s a cultural change, right? So now, for you to implement AI into a big corporation, it has to be a massive change of culture across the organization.
And that’s not moving a big organization toward that is really difficult because you know, you, you have a lot of departments, multiple networks, sub networks inside the organization that need to advance together. It is really our role, as you know, as knowledge creators, consultants, builders of this ecosystem to hold the hands of these organizations and help them understand what are the benefits, right. So, and you know, work with them through this part, because as we mentioned, we concur here. Nobody really knows the answer, but what we can do is navigate together, right? So this path, I think that’s where the value comes is not simply to implement, but to navigate together this AI path that we all are facing and culture as sociotechnical plays a key role here. So that’s absolutely.
Enrique: Yeah. Also, you know, in the on the AI, one of the things is that you get essential information, but always you have to tailor or adapt to your system. So whatever you’re doing with AI, every information that you gather, you have to tailor any anyway tempered to whatever is your outcome expected to happen.
Paul Turner: And this closing comment probably sums it up perfectly for any companies that are wondering how to navigate this complexity AI without governance is going to accelerate your mistakes. And that’s why ICXA has outlined our outcome governance framework, structure of our three core standards for commissioning, operational readiness and outcome assurance. These are the standardized proven processes that we’ve written and released and are available to members to help companies govern through this complexity with strong systems and core capabilities to navigate this changing world. So before we conclude, David, is there any last comments you’d like to add or say to the group before we end today’s discussion?
David: Yeah, well, absolutely. I mean, first, I’m fascinated with every Knowledge Roundtable is great and it’s fascinating, particularly all the insights that we learned from, you know, in all the contributions from the commissioning school with Glennis to the changing mindset organization from Mauricio, all the items, you know, the challenges that we have, you know, in different regions and from Marco and the analogy of the carrot and the stick and of course, the incentives. And of course, Enrique, just making sure that this is, you know, the transition is robust, integrating all from the mindset. So we have common things and one of the values that I see here is that we’re all facing the same problems. And the value of this is that we’re solving it from multiple lenses, from multiple geographies, companies and disciplines, right?
So we actually, you know, we can have, we have here multiple different corporations, different expertise, different areas, but we’re trying to solve the same problem. And that’s exactly how the knowledge is created, right? So by cross-pollinating, integrating multiple perspectives and applying from one area to another one. I’m really pleased, you know, really first of all, I’m really thankful, grateful for you guys for accepting the invitation and contributing to all these valuable insights. So and I think it was a tremendous and successful panel; really tremendous and successful insights that emerged from today’s session. And yeah, so I would like to do maybe a quick roundtable with each of you guys, and yes, let’s start with you, Glenys.
Glenys: I’d really like to thank you for the opportunity. I think we have a lot of shared and common issues and perspectives, and it is good to get together and have a chance to talk about that.
David: Thank you so much. Marco?
Marco: Nothing else for me, just thanks to everyone. It was very insightful and I was happy to be a part of it. Thanks.
David: Excellent, excellent, Enrique.
Enrique: Yeah, everyone, you’re welcome to stop by and ICxA.net. We know that we are struggling with commissioning, as I said to Paul. As you know, when we when we meet is that the need to happen an industrial commissioning structure is essential because right now we have commissioning in other business markets, but not for industry. Industries are standalone. You know a whole different scenarios that you have and that impact people, that impact all the things that need to have governance in order to achieve success.
David: Excellent. Thank you so much, Mauricio. Final words.
Mauricio: Yeah. Thank you, Paul. Thank you, Dave, and thank you to my colleagues; it was a pleasure to be here with you. It’s amazing to talk about project management, commissioning and outcome assurance. And so it’s very, very good to be here.
David: You know, thank you guys and again, you know, looking forward to the next round tables. So, Paul, turn it over to you for final words.
Paul Turner: Yeah, I appreciate everyone’s input. Lots of great value provided here. For anyone that’s watching, please feel free to reach out. We’re here to help at the Institute of Commissioning and Assurance, icxa.net. Email us at info@icxa.net. We’re here to help individuals. We’re here to help organizations. Anyone who is trying to navigate the complexity of projects, the processes are all outlined here and laid out for you to leverage the knowledge of all the experts on the call here and help everyone have successful projects. So yeah, once again, appreciate everyone’s inputs. Great discussion, great comments from people that joined live and stay tuned. Watch for the next one, we’ll be doing these regularly. Thanks for joining everyone and have a great day.