Pharma Industry: Why BIM Can Become a Digital Transformation Cornerstone

ANNE BARD: Hi, everyone. Welcome to our class that we have titled Why BIM Can Be a Digital Transformation Cornerstone.

So guys, before getting started, I think it will be good to introduce briefly ourselves. So I start with me. I'm Anne Bard. I'm Design Lead in Front End Engineering and Design in GSK.

GIOVANNI GIORGIO: Hi, everyone. I'm Giovanni Giorgio. I'm a Senior Digital Engineer also in Front End Engineering and Design in GSK.

SHAKEEL MIRZA: Hi, guys. I'm Shakeel Mirza. I'm Senior Business Development Manager on our platform technologies at Autodesk.

ANNE BARD: All right so let's start by outlining the five objectives of this class. So first one, understand the lifecycle of a pharma plant, because it's about a pharma company. Second, the foundations of pharma digital transformation, and what is at stake. Then design a digital strategy and execute on it with key examples. And four, how to build the vision of a solution. Five, scaling a limited impact pilot to an enterprise level.

GIOVANNI GIORGIO: So in terms of the agenda, we're going to introduce the challenges and opportunities we have in the pharma industry. Then we're going to talk about, with the human centric approach that we'll take for digital transformation. And then we're going to present the minimum viable demonstrator that we'll build over time.

And then we're going to talk about how to connect the single sources of truth, in one source of truth, single data. And then how we move from minimum viable demonstrator, to proof of concept, to standard practice, so basically how we scale in our company, and then the conclusions.

ANNE BARD: So it should last 30, 35 minutes before the Q&A. So section 1, BIM has not been delivering value for pharma, or the ugly truth from the owner perspective. So OK, we proposed a provocative title at the beginning that can be a digital transformation cornerstone. And here we start our first section by saying that it's false advertising.

So because let's face it. Our BIM is not delivering value for pharma, I mean for the owner. And if it did, [INAUDIBLE] we wouldn't do that class. Because if BIM was delivering a fair amount of value for pharma, all the big pharma would be boasting about it. It would be on the strategic agenda of digital transformation of a big company at the same level of cloud deployment, machine learning, or automated vehicles, and so on.

GIOVANNI GIORGIO: Yeah, I mean you're right, Anne. Let's face it. It is not. But today--

ANNE BARD: No, it's not.

GIOVANNI GIORGIO: Yeah, but today, by sharing our research, we want to make the case that it should, and that it can.

ANNE BARD: Yeah. And if we take a step back from a finance perspective, assets are things of value that sustain production of growth. So the creation of those assets is a foundational part of the business, right? So then making sure that the very same asset will serve the strategic digital transformation that our entire industry is going through, should be inevitable, like a foundation or a cornerstone.

GIOVANNI GIORGIO: Yeah. I mean let's see if we can demonstrate it to our audience here. And let's jump in, to make our case.

ANNE BARD: Yeah. Let's do it. All right. So before that, let's talk a bit about new GSK. So just before the summer, big things happened for GSK, as a pharma company. So the first biggest emerging consumer health from the main vaccines and the biopharma business happened, and was successfully completed. So here you see the new branding, the new mission statement of our company that was publicly announced. So now, we are new GSK.

GIOVANNI GIORGIO: Yeah. There was a great moment in July, and really engaging and motivating. But we said that we are from engineering and design. So what's the main activity and the purpose of our organization?

ANNE BARD: Sure. So we are an engineering group in global capital projects focusing on the front end engineering phases of any capital project, so from business analysis, the business case, to feasibility study, to concept select studies. And our job is to design manufacturing assets. And to do so we do business model, capacity model, simulation, and of course also 3D models of the asset. And then we hand over to our colleagues in charge of project delivery.

GIOVANNI GIORGIO: Yeah, but we do more than just front end projects, right?

ANNE BARD: Yeah, we do more, and principally in the digital arena. That's why we are here, because, hey, you inadvertently embarked on the digital journey when we first met in 2017.

GIOVANNI GIORGIO: Yeah, that's right. I think we were already working on digital transformation of our engineering and trying to link into manufacturing, before it was really something in the company. That was even harder at the time I think.

ANNE BARD: Yeah. Yeah, a lot of years working undercover, partly undercover.

GIOVANNI GIORGIO: Yeah, it was a bit weird period, when everybody was on the waiting mode, and we were in a capital reduction context that was not helping.

ANNE BARD: No. That wasn't that-- if you remember, we have relentlessly advocated for digital engineering, and more precisely for digital asset design to play a role in the wider digital transformation. And finally, finally, in the second half of 2021, at last we got from the management the official mission to define the global asset information modeling strategy for our global capital projects and global engineering organization, so it's a big thing. With the ambition of defining not only the strategy, but the entire associated digital lifecycle management.

GIOVANNI GIORGIO: Yeah, and that information modeling is just the tip of the iceberg, because if we never abandon the idea that asset information is a foundational element of digital transformation, contributing to operation and manufacturing performance.

ANNE BARD: Oh, yes. And unlike any other part of the business, going digital is not something fancy that you go to be modern, or following new standards or government directive. Well, not only. We want to do it, and we do it to generate performance in our own processes first, so our asset design and construction first. But ultimately, we want to transfer this value to manufacturing, as you pointed out.

GIOVANNI GIORGIO: Yeah. And that's easier said than done. So I think it's time to introduce the first challenge that the owner is facing, or the first limitation of a traditional digital delivery. We did not want just to transfer a 3D model, but a data rich model that can be easy to consume.

ANNE BARD: Yeah, but let's talk about the real world here. This limitation that we are going to talk about is very illustrative of what's happening from the owner perspective in the pharma industry.

GIOVANNI GIORGIO: Yeah, so what happens when BIM is not seen as a foundation [INAUDIBLE]?

ANNE BARD: A big waste so we said in front end that and then in execution, we have designed a 3D model. And we associate to this model a comprehensive set of engineering metadata, engineering information which are crucial to build a factory, on time and on budget. But also to demonstrate that the factory has been designed and constructed for fit for purpose, and compliant form pharma manufacturing.

GIOVANNI GIORGIO: And once the factory is successfully built and handed over to manufacturing, what happened to the asset data and to the 3D replica of the physical asset?

ANNE BARD: Well, you know as much as me. And it's written on the slide. Well, once a new factory it built, most of the time all of this data accumulated and at best, on the shelf accumulating dust, or worse into the BIM, the information BIM. So you even had a vivid example a few months ago in one of our sites.

GIOVANNI GIORGIO: Yeah, it was so much forgotten that at some point they realized that the 3D asset and the associated data were stored on a laptop of someone who left the company months ago. So the first task was actually to retrieve the laptop and the data from a locked laptop, which I still cannot believe that.

ANNE BARD: Yeah. And that example tells a lot about this first owner limitation, like the total lack of ownership and lack of vision about the digital asset.

GIOVANNI GIORGIO: Yeah. Basically, there is no digital life for our asset once construction is achieved, and we're going to explain why.

ANNE BARD: Yeah. So we are far from the value we are to cycle, like designing for value, building that value, and then transferring that value to operation.

GIOVANNI GIORGIO: Yeah, if there is any value so far, it has been mainly associated to the design and construction phase, and captured mainly by our engineering partners.

ANNE BARD: And as a consequence, there is no incentive so far, or very little, for GSK, or for the owner, to change the status quo, and to see value in owning the asset data.

GIOVANNI GIORGIO: Yeah, and this has been quite a limitation that we think is typical. Shakeel. Shakeel, what was the learning for you when you started to collaborate with us three years ago?

SHAKEEL MIRZA: Yeah. It's quite similar in the industry across the board, especially the construction industry has witnessed the adoption of BIM by the architects and engineers, as the early or first adopters. But the good question here is, why engineering first and only engineering? The simple explanation is that design is where the information is created, and BIM is the perfect method to capture that information in the digital format.

However, the owners like, GSK, who traditionally have been focused on operations as their core competence, and who relied on their engineering partners to deliver detailed design, felt unconcerned when the first impression was that BIM only delivers value for design. And this is exactly what you have explained. So you are not alone.

ANNE BARD: That's reassuring. So section 2, a Human Centric Approach, so to find where the user is struggling with data across multiple sources. So let's recap what we just said so far. The owner doesn't get value out of BIM or digital delivery, worse, they even pay a premium to generate waste.

There is a disconnect between digital transformation expectation, manufacturing, and performance for the patient from the owner perspective. And BIM first promises about building performance. We believe that space matters, like the space of the digital asset matters too. Because space generates performance in our consumer life, like with the app like Google Maps, or Uber, or Citymapper that all use data streaming with the space.

And we have all the building blocks to create similar value in our manufacturing and engineering life. We think it's within reach.

GIOVANNI GIORGIO: Yeah, and to close these gaps, we need two things. One is to change our perspective and take the end users, so the data consumer approach angle, rather than the designer approach. And two, demonstrate that information and data could be consumed on the owner's terms, and not on the engineering terms, and not only matters for building, but also for manufacturing end-to-end.

And making this gap visible was on the origin of our journey, right?

ANNE BARD: Yes, it was.

GIOVANNI GIORGIO: Don't you think that another origin of these gaps lie in the nature of our business or industry? Since we're a pharma industry, we as the owner, we don't have a strong internal engineering, as an engineering organization.

ANNE BARD: Yeah, definitely a part of it. But it is also a bit of a chicken and egg problem. Like there is no need to have a strong internal engineering organization to own and maintain a digital asset, because there is no manufacturing pool to do it. So it is clear that a super complex 3D model full of data is of limited usage to get the product out of the door.

And also, if we force our colleagues in the operation to use a tool that is made for engineering and construction after the handover, they are not only going to hate us, it's not scalable as a solution.

So working on the shop floor means taking thousands of decisions every day. And the operation people have just no time and no need to dig into the gory details of a 3D model, and for what, you could ask.

GIOVANNI GIORGIO: Yeah, and that opens to another chicken and egg problem. If you don't put the potential in our colleagues' hands, then they're not going to know that this could solve some of their problem. I mean nobody asked for Google Maps or Uber. Nobody asked for a smartphone either, isn't it?

ANNE BARD: I 100% agree, but what Google Maps, Uber, or smartphone have in common, they are handy, intuitive, simple to use, with or without any training.

GIOVANNI GIORGIO: And that's why transforming the complex asset in something simple to use was our first research discovery, right?

ANNE BARD: Right. So section 3 now, Minimum Viable Demonstrator. So a minimum viable demonstrator to prove the point complex data can be consumed differently. So with the help of Autodesk, and thank you Shakeel, and Microsoft, we started to wrap our head around the information waste that we talked at the beginning, and how to democratize the 3D data consumption. So we believe that that was a first limitation. And we wanted to break that barrier.

Thinking about the Citymapper or smartphone, or Uber, or Google Maps analogy, we wanted to experiment the benefit of an intuitive spatial information navigation, like in Google Maps, using the 3D and geometry to find digital information extracted from multiple data sources.

GIOVANNI GIORGIO: Yeah, it's like a fusion between space and data from multiple sources, and this fusion is called the data convergence, and is the foundation for what we call the digital twin. It can be enabled only if the data sources are stored on accessible systems, accessible to API layers and connectors.

ANNE BARD: And by doing so, it allows you to create this experience of data consumption without forcing people in the operation to learn to use Revit, or any other complex 3D model tool, which is definitely a nonsense.

GIOVANNI GIORGIO: Yeah. Using an app platform is an opportunity to scale this accessibility and access democratization in a much deeper way, and potentially without locking us to a big proprietary data platform that we may not use in the full potential anyway.

ANNE BARD: Yeah, so that minimum viable demonstrator works. So it worked. We had sponsor, because we could have access to resources like for free. And solution, we had partners, so Shakeel is one of them. We had some user pools to move it forward to other use cases. So we had some--

GIOVANNI GIORGIO: Yeah. Yeah, we almost had the momentum to get started, but ultimately the conclusion was it really doesn't take off.

ANNE BARD: No. So that lead us to section 4, Connected the Sources of data. So don't fight the legacy systems. Use them. Make them converge. So Giovanni, like, OK, big decision. Our minimum viable demonstrator didn't allow to take off, although promising, and although almost a momentum, we got almost some sort of momentum. But if thinking back, and we reflect on it, there are positive outcomes from this setback. Because without it, we would have had a massive blank spot.

So we should be grateful, because it forced us to pivot our purpose. This was pivotal, with a bit of wordplay, because the legacy systems are not as-- we could see them only in ugly [INAUDIBLE]. If we are honest. We were a bit looking down to the legacy systems that are outdated. They could be part of it. They have to be part of it, because we can't remove them. And we can even use them smartly, as stepping stone, for the digital transformation.

GIOVANNI GIORGIO: Yeah, totally. And because these are nothing that's just about just GSK here. This problem that we are about to share with you, I think are the same in every big pharma, and possibly in any big industry that is highly regulated.

ANNE BARD: Yeah, so let's explain this. And you have a busy slide here, so let us walk you through to it. So from left to right, you find again the life cycle, but rather you have been deployed in a linear way, with a few breaking points, or points of data wasted. We are going to explain.

So the first is [INAUDIBLE] overrun, and the other is at a set of data steps. Giovanni, I'll let you explain a bit more in detail.

GIOVANNI GIORGIO: Yeah. OK. So the first thing to do takes place in the first step of the life cycle, the delivery phase, from design to construction. We as GSK, need to own the data and set up our organization for this ownership right from the beginning.

And the ownership will start with setting up what we call the common data environment platform, or CDE, which will aggregate in one place the geometry, what we call the 3D model, and the engineering documentation coming from the whole supply chain, so from equipment supplier, system integrators, [INAUDIBLE] partners, et cetera.

ANNE BARD: Yeah, and the purpose of having a single platform is that both 3D, the geometry and engineering documentation can be put together also in a collaborative way. So with all the partners and contractors using the same environment. So the common data environment it's a federation of both design with the model and a federation of documentation or metadata that support that 3D model.

GIOVANNI GIORGIO: Yeah, and it's also easier said than done, because setting this collaborative platform and having it set up from a GSK, not from our AAPCM partner, it's really a big change of practice for us.

ANNE BARD: But yeah, we are getting there, baby step after baby step. The problem is that what happens after the handover, that breaking point, the first breaking point. Because each owner of the legacy system and what we call the legacy system is that it's all the gray box that you have in the middle from M-ERP or calibration systems, preventive maintenance systems, MES-- like all those systems that are preexisting to our strategy.

So the owner of those systems, they need data. And they are going to extract data from the common data environment as one-off. That is because there is no other usage that is set up. So they extract the data that they want, and then they have their operational system going. And by doing so, well, it's like you break it to use it. And by doing so, they make the asset obsolete it, just after delivery.

GIOVANNI GIORGIO: Yeah. And this is the first digital gap in our asset information lifecycle. But it's not the only one. You have another one at the end of the lifecycle. When we need to upgrade the asset, because a new product for example, this versatility to re-put data together, and rebuild the data model almost from scratch, it's sometimes that we know it's quite a lot of waste, and it's something like finding back an old PC, like I was mentioning before.

So yeah, that's still quite a lot of waste, and then another gulp in our lifecycle.

ANNE BARD: And today, and you know so far the static quo's position was or in certain area is, well, OK. There is waste. We know it. And that's perfectly OK, because we can still have our operation going, living with this waste.

GIOVANNI GIORGIO: Yeah, but the reality is that it's not really OK. Isn't it?

ANNE BARD: No, especially for the users. So it's not, and as explained on this diagram, all the links that we mention here actually are not automated links. They are manual linked on by people with their little hands. So answering a simple management question, or preparing a new job work, or just doing a document search becomes a nightmare. Because all the information has been exploded in multiple locations and in multiple systems.

So each time you need to re-group things, it's a nightmare. It's just a nightmare.

GIOVANNI GIORGIO: Yeah, and it might be also a problem in case of an audit. Auditors might conclude that if you are not capable to find an access document or information in less than 5-10 minutes, it's almost like you don't have it.

ANNE BARD: And this is problematic. But there is another nightmare that comes too. Once you have found this thing, if you have to do a simple update, so not only are we starting a new project, like maybe updating a material of construction, updating a diagram after a maintenance, you might have to update multiple documents to do so, because that material construction might appear in many systems or many documentations.

And updating becomes not an action, but a project, involving multiple players. It's long and painful, and it can even create some data integrity issues. Because if it's not done consistently and all at the same time.

GIOVANNI GIORGIO: Yeah.

ANNE BARD: It creates problems.

GIOVANNI GIORGIO: Yeah. But the good news is that this vision is shared also by our colleagues in maintenance and operational engineering, which become an opportunity for us to bring them along in our digital twin journey.

ANNE BARD: Yeah, I was surprised that they agree with that. That was a winning battle for our research.

GIOVANNI GIORGIO: Yeah.

SHAKEEL MIRZA: Yeah, Build Connectivity. So it's all around building the connectivity based on what Anne and Giovanni explained about the legacy system and the importance of CDE and BIM data. And it's important here to realize what are the main challenges of this digital transformation, or this flavor of digital transformation, the current technological backdrop.

It's no more about paperless operations. The core of the problem is not digitizing the information, as data is readily available. Like you're talking about data-based E-based. And the digitization of the analog information is cheaper and faster. Think about 2D scanners, and for assets think about laser scanners. Your consumer grade smartphone comes with a laser scanner today, making it very, very cheap and quick to digitize the complex assets in 3D.

Digital transformation today is about how we enable a user to extract insights quicker from the existing pile of data for higher efficiencies. We're talking about big data, right? So the data availability is not the problem. The main problem that digital transformation seeks to solve is how we accelerate the extraction of insight from this data.

So in today's industrial landscape, the operations team is already using data, right? To do so across multiple silos, like you explained Giovanni, so [INAUDIBLE] technical manuals, and you showed it very graphically as well. And it's not about unavailability of data. It's about how to reduce overhead of looking across multiple data silos manually.

According to McKinsey's study, a typical collaborative worker spends 59% of their time looking for information, which is more than half of their time will be spent in looking for data simply. This is where BIM deliverables bring the engineering design data in a well structured format, easy to query data that can be connected to other big sources of information, such as ERP, MES, and you explain other information sources, as well Giovanni, that you are using at GSK. And like you said, most of the enterprise customers are using.

GIOVANNI GIORGIO: Yeah, I mean that's correct, Shakeel. And having a good data structure allows us to retrieve data easily and quickly. But I think what's also is a key to success is having a simple interface that allows easiness of data consumption.

ANNE BARD: So thank you, guys. Thank you Shakeel. And thank you for your insights, because it's really helped us to find a new alignment with our colleagues. That was a surprise, but we were gaining energy out of it, and to go further into our research.

GIOVANNI GIORGIO: Yes. So we come up with what we call the linkage layer strategy. The aim is to link the 3D geometry to documentation delivery, delivered by a new project. But also try to link our 3D model to the documentation already sitting in existing legacy platforms, such as our quality vault for GMP documentation, maybe existing SharePoint that cannot be yet replaced, and our legacy system for engineering [INAUDIBLE].

ANNE BARD: So [INAUDIBLE], let us try to walk you through to this visual. So the core now is the common data environment, or the CDE. Now remember in the previous slide, that was the first step that we want to get sort of set about the delivery phase of the digital lifecycle, the asset lifecycle. So we want to put it at the core, and it to become the hub where we will connect all the information, where we have both the [? fidelity ?] model and engineering documentation delivered by the capital project team.

The next step is to create this linkage layer that you mentioned. The idea is to establish a link, linking geometry like the object to data using the tag of the object of the component as the bridge or the unique link between the geometry and information. So then the 3D model becomes a sort of universal search engine, whereby navigating 3D, or navigating by 2D, or Navigating by system-- when you grab an element, the interface will immediately propose you all the documentation or source of information where that object appears. And then you just have to select what you need, and correlate data to do what you have to do.

GIOVANNI GIORGIO: Yeah. And you do it--

ANNE BARD: Yeah. I want to do that. We'll fully find in less than 5 minutes, which is the challenge?

GIOVANNI GIORGIO: Yeah, which is a challenge. Yeah, right. And the beauty of it is that this linkage could be established after delivery. So you don't need to preestablish the link during delivery by using just smart data ingestion and knowledge graph technology.

ANNE BARD: Yes. And we want to test this pathway, because we want to limit the change management to allow supply chain. So we just want them to be disciplined enough to put data into a central space, and using a naming convention and the tagging. And hopefully then we can have the tech people do the rest. So the most important point, every component needs to be tagged in a standard manner.

OK, so section 5, Ambidextrous Strategy. So the small learning and the big initiatives, so from the minimum viable demonstrator, to POC proof of concept, to a standard practice.

So guys, I think that once we'll demonstrate that we can leverage the challenging end legacy systems to our transformation advantage, we won't be finished. Unfortunately there are still more challenges awaiting us, right?

GIOVANNI GIORGIO: Yes, and we may not know them yet. So the only way for us and this is what we're trying to explain here on these four workstream diagrams. To continue the transformation, we need to have a parallel approach, a dual strategy as we call it. One is to continue to leverage in-flight capital projects in which we already have managed to implement a common data environment platform, and to test the linkage layer, and learn bit by bit.

And then trying to link all the key elements that are related for a workstream and trying to learn and deploy basically the strategy that is on the right-hand side here.

ANNE BARD: And the second is to develop these four workstreams at the strategic and global level. Hopefully the combination between this local tactical using in-flight project and a global strategy initiative together, will allow to set up the full lifecycle and the ecosystem that goes to set up our entire asset information model that we aim to build.

GIOVANNI GIORGIO: Yeah, and hopefully eliminate once and for all, the sources of data and time waste that we mentioned about.

ANNE BARD: Not only this waste elimination is already a source of value, but I think that by establishing the standardization and linking the things becomes the foundation or even further more value, because once you have this foundation you can certainly correlate more, diagnose more, do more with less.

GIOVANNI GIORGIO: Yeah, but there's still quite a lot of work to do. We--

ANNE BARD: Yeah, yeah. No, yeah. We are only at the beginning.

GIOVANNI GIORGIO: Right, so I just want to quickly talk about one of the PoCs that we run, this was done in Parma in one of our manufacturing sites where we deployed and we launched for the first time our CDE, the common data environment for design, and manufacturing, and construction of a new facility. And just an image to show like three main benefits, basically we got from that.

One was that we immediately could have a 3D model that was completely federated between all the different suppliers, and we could having really one single source of truth from a 3D perspective, and metadata perspective as well to be used during construction. It is using at the moment, during construction.

The other one was that with the CDE in place, we could create some workflows that could make our process simpler, like approval of document, issue new document, management of issues that are happening on the plant or in design phase. And then we can keep track of that, because we know that we generated some KPI, because basically we knew how much we were saving every time we were implementing a new process in terms of time, and we could basically we demonstrate the benefit not just from an FTE from hours spent, but especially from how much quality and robustness now we improved in our process.

And the last one it was-- yeah, go on.

ANNE BARD: Sorry, well go ahead.

GIOVANNI GIORGIO: Yeah. Yeah, just last one on the bottom was more like a way that at the moment that they are implementing, where you can actually track issues, and log issues on the 3D workflow, and basically anyone can say, oh, this is not working. Please make an action. So it's much more readily and easy to communicate, if there is an issue in the construction space.

ANNE BARD: Yeah, and especially on that last one, I wanted to add is that part of the project team is also operational people, and what we hope is that there will be a cross-pollination between project team and operation team. Because when they will see that how easy it is to use, maybe that issue tracking in project delivery could become issue tracking in operations. So we hope that there will be some sort of cross-pollination idea that will generate this pool that we are lacking, and find a more [? pool ?] towards this.

GIOVANNI GIORGIO: Yeah.

ANNE BARD: All right. So section 6, Conclusion. So Shakeel, you have been witnessing us during the past few years. You have seen our ups and downs. My question is, how do you manage to not to lose patience with GSK and with us, and how would you conclude this presentation to close the loop, to come back with our claim that BIM can be the foundational cornerstone for our digital transformation?

SHAKEEL MIRZA: Thank you. Thank you, Anne. And it has been a great learning experience, and a great pleasure working with you and Giovanni. And I hope we will continue, of course. Because the journey is not finished. But it might not come as a surprise to the public here, but in technology scaling or technology adoption, the key word is not technology. It's adoption. Right? So adoption is the tougher part in the technology adoption.

Because technology is mature, and in most cases, it's more much more advanced technology is available than what we can use at a scale in the industry. So my key takeaways are around organizational aspects of this change basically, which were primarily the road-blocker as well, which is all around change, driving the change.

And here, yes, I would certainly start with the conclusion, the first conclusion that BIM is the cornerstone of digital transformation for an owner, particularly that was the main endpoint here. Why? Because that's where all of the questioning started, how we can improve the process where the information waste, huge information waste, was being witnessed. It was available, the data, highly detailed data structured virtual representation of assets were available, but not used. That was really the point of departure, the frustration that you and Giovanni came to Autodesk with.

So certainly that was the departure point. And the question was how we can leverage that mine of information. We felt that, yes, especially you felt, Anne, that there was something that needed to be done with that data, so how to go forward that.

So the next step, next big step or pivotal moment was this minimum viable demonstrator, where we started with the question around how we could increase the operational efficiency based on that data log inside the BIM model. And that was the answer to a lot of questions, how it can be done. So making it very tangible with that very small snippet, which we are calling minimum viable demonstrator which was primarily just for demonstrating purposes.

A lot of things were [INAUDIBLE] it, but it made the mission very tangible to communicate it to the other people. Why this is one of the conclusions? It's because that minimum viable demonstrator principally helped you create that coalition. You did say that it helped you land the resources, the support from key folks. So that was really more about the internal change of guard, that momentum, that word you used. So that was certainly a big win.

And back to the conclusion from this side, is that we need such type of demonstrator or something tangible to create the coalition around the vision of future in any digital transformation project like this one. And the last point is around finally the realization that, hey, once you have data connected across different silos, you have BIM that's coming with the structured design data, you have other silos that we are connecting to APIs like Joanna explained. And that was our MVD.

Then it really highlighted that a little bit less tangible and direct need, which is that of common data environment. That, hey, we need to have an environment, a platform, where people can collaborate in real time. And Giovanni talked about it in the quick win around how a federated data or federated model was shared across different supply chain partners on a CDE.

So that CDE, of course from technology perspective, but the conclusion here is that the CDE, what I see or what I hear when you talk about CDE is that, as owner, it's helping you to orchestrate your supply chain through standard processes, and structured data. And also the supply chain themselves are, of course, providing-- what they were providing before as well without CDE, but they can better collaborate across different partners of supply chain, and with you as well in real time.

GIOVANNI GIORGIO: Yeah. I totally agree with you, Shakeel. And if I can now, just a few high level point for conclusion, is that the key factor for digital transformation and adoption as you mentioned Shakeel, is how easy we can access and use data mainly. But also what we can do with data, and how we can manipulate them, and aggregate them, and how we can improve our decision making from the day-to-day shop floor decision to the company strategy decision.

And just to conclude, I think BIM is now really helping to orchestrate the digital delivery, because of the structured data that become easy to leverage. Then through simple and intuitive interfaces, as a owner, I think we are finally able to consume the data. But I think the journey has just started. So there's still a lot to do.

ANNE BARD: And after our consumption, we will be able to correlate, and then do diagnosis, and then predict which is the sort of holy grail that we see in the future. So thank you, guys. Thank you for the conclusion. Thanks, everyone, for listening to us. I hope that you get some insight. And we are looking forward to answer to any questions that might come up. So thank you again.

GIOVANNI GIORGIO: Thank you.

SHAKEEL MIRZA: Thank you.