 Welcome to our presentation, Open Standards and Process Automation, the key to industrial profitability. I'm Robert Cahy, VP of Marketing at Cplane.ai, and I'll be your host today. With me is Brandon Williams, CEO and co-founder of Cplane.ai, and Peter Martin, Vice President of Business Innovation and Marketing at Schneider Electric. Brandon is the CEO and co-founder of Cplane.ai, and the founder of innovation capital investment firm Ignite IP. A relative newcomer to the industrial controls industry, Brandon's career has focused on the development and commercialization of technologies and numerous industries including materials processing, cloud software, and water treatment. He is formerly a structured finance banker with Citibank in New York and served as a nuclear submarine officer for the US Navy. He is a graduate of the Wharton School focusing on finance and operations management and IT. Peter Martin is a recognized industry expert holding multiple patents for dynamic performance measures, real-time activity-based costing, closed-loop business control, and asset and resource modeling. He has published numerous articles and technical papers, and has authored or co-authored several books. Peter was named one of Fortune magazine's heroes of US manufacturing, and one of Intec magazine's 50 most influential innovators of all time. He is a recipient of ISA's Life Achievement Award and a member of both the process automation and the measurement control and automation halls of fame. Welcome Brandon and Peter. Thanks Robert. Thank you. It's a pleasure to be here. Thanks guys. Brandon, tell our audience a little about C-Plane AI. C-Plane AI is a Silicon Valley-based software company, and our software platform is really for large-scale distributed cloud solutions for IoT, in the telecom space, things like Vog computing, etc. What our software does is provides a degree of intelligence and automation using closed-loop orchestration that just makes it a lot easier to deploy large-scale IoT, industrial IoT solutions. We find that this greatly accelerates digital transformation initiatives in our customers. But the C-Plane software platform does is really solve for fundamental challenges. One is that there is multiple domains of technology that have to be traversed in these systems, and it's very complex. Everything from distributed control nodes or Raspberry Pi type devices up into a data center. So managing all of that IT infrastructure. Another is that you're deploying and maintaining applications in lots and lots of places. We make that much simpler across multiple domains of infrastructure. A third is that there's very complex networking topologies that require fully automated networking. Things like the software-defined networking help automate that and capabilities like time-sensitive networking help prioritize traffic on your network. The last, maybe the most important, is that the skill level to design and manage these complex systems can be very expensive without the right set of tools. We have found with our customers that we can eliminate as much as 90 percent of the engineering costs out of creating these complex systems and for their ongoing management, and that turns out to be very compelling. As a global leader in digital transformation of energy management and automation, Schneider Electric needs no introduction. But Peter, tell us about your role there, and some of the innovations we're seeing from Schneider Electric. Thank you, Robert. I had a innovation in marketing for the process automation part of Schneider Electric, and we're continually looking for how we can use automation and control to help our clients improve their operational profitability safely. When we look at some of the innovations that have been taking place in the last few years, a lot have been focused on expanding beyond a control focus of efficiency to more of a control and automation focus on profitability. We've come up with innovative ways of measuring profitability in industrial operations in real time, empowering operators to make better decisions, bringing in higher levels of control, and we believe all of these things will help our clients to turn their industrial operations into the profit engines of their business. Thanks, Peter. I think it's safe to say that if you pick up any trade journal or read any blog these days or attend any trade show or conference, the first thing that strikes you is that there is a lot of change happening with the industrial manufacturing space. Industrial automation, industry 4.0, digital transformation, industrial IoT, process automation, edge computing, edge clouds. Just to name a few, they're opening new opportunities for owners and operators to take better real-time control of their operations and business performance. It's not just about technology. Markets are reshaping themselves literally overnight. Product life cycles are becoming more dynamic and shorter, and the applications that support those products have even shorter life cycles. But probably the most important change is that the lines between IT and OT are blurry, and corporate leadership is expecting more not just from their chief information officers and their chief digital officers, but also from their manufacturing assets and operations too. The open process automation form, or OPAP, is taking on the challenge of creating open frameworks and standards that will address many, if not all of these challenges. Peter, give us an overview of OPAP. How it was formed, what's its primary objective, who's participating, and what's your company's role there? Thanks, Robert. OPAP is an open, collaborative, standard-focused body. We're made up of some of industry's most prevalent technology thought leaders and pioneers, all working together to drive the creation of open, standards-based process control systems that will benefit process manufacturers across multiple segments. Our members come from everywhere across industry, including end users from multiple segments, hardware software and solutions providers, systems integrators, industry analysts, academia and standards organizations. OPAP was formed a bit more than two years ago. The initiative was spearheaded by ExxonMobil, who has long called for the development of an open process control framework that would replace closed proprietary control systems that drive up costs, cycle innovation, and limit options end users have because they're locked to the systems they installed years or even decades ago. Snyder Electric shares ExxonMobil's vision and the goals of OPAP. That's why we invest our time and resources to ensuring OPAP succeeds. Several of our team actively support OPAP by participating in multiple OPAP working groups, including Trevor Kussler, serving as the forums co-chair with Don Bartusiak from ExxonMobil. Another of our team members, Tom Clary, serves with Brandon as co-chair of the forums marketing and outreach committee. Thank you, Peter. I'm sure the first question from our viewers and listeners will be, is this just another standards body? Brandon, can you share how OPAP is different? Sure, I hear that question a lot in the industry, but OPAP is not creating new standards or a new set of standards. We're collaborating to produce a standard of standards so that everything works together. And this takes into account business requirements of the entire industry ecosystem. While a number of useful and relevant standards are available, no single standard delivers the required portability and interoperability required to achieve OPAP's objective. Therefore, our first priority is to select from existing standards, defining an open and secure and interoperable process automation architecture that benefits end users and suppliers and integrators, involving everyone as critical to our success. And the standard of standards will enable industry to develop new systems comprised of cohesive, loosely coupled, severable functions, functional elements. Acquired from independent suppliers. It allows best of breed. These functional elements will be able to be integrated easily via structured modular architecture characterized by the open standard interfaces, which means everyone will benefit. Only when no standard is available or acceptable will an effort be made to develop a new standard. So really leveraging on the work that's been done over a decade towards this openness goal. Thanks, Brandon. It seems that we've been at this a while. Digital transformation is not new. And Industry 4.0 has been part of the conversation for several years now. There have been a few fits and starts along the journey so far. And it might seem that people are a little dubious of another industry initiative. So the key question seems to be, why is this important? Why do open standards and open systems matter? I'll make this one a toss up and let either of you jump in. Let me take a stab at your question, Robert. I have a unique, I think a unique perspective from my experience in the telecom industry that has successfully embraced open standards and the cloud industry, which similarly has built so much on open technologies and open standards. And also my experience in finance at Citibank on funding very large transactions for industrial companies. First, industrial manufacturers are always under pressure both to lower the capital costs, their cost of capital and the lifecycle cost for their process control systems and their whole processes. So they're trying to improve profitability of these operations. Many of the currently installed control systems are predominantly closed and proprietary. That's been the tradition for the last 50 years or more. That means integrating with other best in class, third-party components becomes very costly while making them expensive to upgrade and maintain so for their full lifecycle. Additionally, today's systems generally lack intrinsic built-in cybersecurity needed to protect equipment assets and other capital investments. That threat continues to emerge faster and develop faster than closed systems are able to keep up. So open, interoperable, and secure by design process automation systems as architectures will address all of these issues. So this is really OPAF's goal and purpose of ensuring that future automation systems adopt and reinforce standards that achieve true heterogeneity while providing intrinsic security, multi-vendor interoperability, future-proof innovation, and an easy pathway for systems to migrate that will help end users reap a lot more value and profitability from their operations as they move forward. So let me show you a few concepts that we've worked on in the business working group at OPAF that might help better explain the value and open standards-based systems might provide. Based on a lot of input from our forum members, and you probably know that our forum members ranged from Dow Chemical to Exxon Mobil and Shell to Merck Pharmaceutical. So a very wide representation of industrial companies or manufacturing companies. You might think, gosh, how can all of these fit in together? I put together three models that I'm gonna present here to Peter and get your feedback on Peter. You know, we'll have a discussion about how well these might represent the business case for open processes, open standards in industrial controls. The first of it is what I call the CAPEX model, looking over the investment lifecycle of building a plant, making a huge capital investment. You probably know that, for example, in the oil and gas industry, when you build a new refinery, that that's a $8 billion commitment and very big capital investment. What I'm showing on the left is the investment lifecycle for a plant, right? You have a very large initial investment, multi-year construction phase with an outlay of capital and, of course, no output from the plant. And once you get to commissioning of the plant so that it's operational, you start tuning your operations to optimize that plant. Your operation costs go down into a steady state, support-type continual investment with your contractors and with the vendors that have helped you build this plant. And it operates at some steady-state efficiency over time, typically. And then you have a shutdown period for modernization. And there's lots of reasons to do that if it's equipment refreshment or just upgrades because of new technologies, et cetera. So your efficiency goes to zero for a couple years and you invest some huge number to upgrade every system. And part of the reason you do that is that these tightly-coupled systems can't be incrementally or adjusted by piecemeal. They have to be done at once. So you can't take one thing out because the whole system would stop or not function. So there's no real interoperability. And then hopefully once you recommission the plant and start up again that you've proved efficiency in some kind of operations over time. Peter, do you have any thoughts about that investment model that exists today? You know, looking at the model, it makes perfect sense. I agree with the aspects of the model you present. And to be honest with you, my perspective is, to a large degree, this is the way industry views the investment profile that they're dealing with. But I think it's missing a major component. And that major component is the incremental business value that putting a control system in can provide. In other words, when you take a look at a CAPEX model, CAPEX is based on return on investment. And if you look at what we're talking about here, we're talking about the cost of the investment. The light blue line is the cost of the investment. The benefit is where you get the return and the benefit needs to be larger than the cost to make this investment make any sense. And one of the problems we've had in industrial automation and controls is that the benefit from automation is not easily measurable. It's very difficult to measure that. So the whole industry has moved into a cost mode. If you can't figure out what the benefit is, reduce the cost as much as possible because by the way, to a finance person, if you can't figure out what the benefit is, there is no benefit. So bring the cost down. I believe that's a real mistake. I believe the profile's good, but the focus on cost only is a mistake by industry. I believe what you're showing here, Brandon, is exactly the way industry thinks. What we need to do is start showing that there's a lot more benefit that can be realized from control systems, from automation than we're realizing today and balance the model a little bit. Does that make sense? Yeah, that does make a lot of sense, particularly to somebody in finance, I think. That's a really good point. I'm gonna present my model on the right of the investment lifecycle for open systems, then turn it back to you so that you can provide some more insight here. So the OPAF model is with open systems, you get more competition for the control system, and so it will affect your initial capital outlay, which is really perceived, and if you look in the telecom industry, the cloud industry, or any of the others that have adopted open standards, they will all tell you that they've brought down capital costs significantly by using open standards. But most importantly is that when you have this open system and you can make incremental changes to your plant, and from an investment standpoint, you can make much smaller, less disruptive incremental investment decisions, which by the way, I think makes it easier to get to that value model that you created that you're gonna make an incremental investment in automation, you're gonna see how that relates. Again, in my thinking, I talk about efficiency, but I think rightly you mentioned profitability. If you look at the green line, you have a potentially smaller initial outlay of capital, but then you get to make these small incremental investments over time, which should have easier sort of ROI-type calculation that looks at the effect on the operations in a much shorter life cycle that can be measured. And so you have this sinusoidal up and down that every three to five years perhaps you're making some kind of swap out of equipment or controls or things that are much less disruptive, I should say, to the operations, allow for continual operations, eliminate the shutdowns, increase the productivity of the plant over time. And I think also significant is that you end up with a much higher terminal value of the plant. If you go out 30, 40 years, you've made continual investment and upgrades that these plants that live a very long time might still be competitive in a very competitive global market because they've been upgraded as you go instead of sort of run into obsolescence and sold for, you know, for pittance. Anyway, that's the model for OPAF, that's the argument and the benefits. Peter, what are your thoughts? No, I like this. I think that cost model for OPAF is exactly right. And, you know, it presents a phenomenal opportunity for industry. When you look at the fact that, you know, with OPAF, end users don't have to worry so much about that big modernization event. We can start thinking about continuous improvement rather than just sinking costs. And that's what the little sinusoidal wave shows in the ongoing basis. It's a continuous improvement opportunity. Now, when I look at what's really going on in industry today, I mean, the curves are nice, but it's also important to observe what's happening in industry. What we find in many, many cases is clients make that initial investment in a distributed control system or some type of an automation system and they put it in. And typically, the system is put in to the specification defined in a request for proposal. And that specification is very tight and normally does not exercise all of the capability that the automation system brings to the table just because they're putting the system in. And when they put the system in, the idea is don't worry because we'll use some of that latent capability later on. And what we've learned over the years is later on doesn't tend to happen. What happens is the project team goes away, you know, the people on site are busy, they're doing a lot of work, even though they have the capability, they don't have the time to do the work. And then 20 years later, they pull the control system out or modernize it. And when they modernize it, they replace it with a control system that's doing exactly the same thing that the first installed control system was doing. So because of the cost and the time and the effort to replace and modernize, we never see that continuous improvement. With OPAF, because once you get the initial system in, your cost profile levels off, you've got that opportunity for continuous improvement. And by the way, I believe it's huge. I believe that the incremental operational profitability potential that industrial companies can get out of their control system investment is much bigger than most people can imagine. If we actually measure the cost-accounting components of an industrial plant in real time and then work along that little sinusoid that you've demonstrated there, we work to continuously improve, we'll be able to monitor the profitability continuously improving over time, which provides an incredibly strong return on investment, which is exactly what industrial companies are looking for out of their capital budget model. So I think this is fantastic. Well, I think you add a lot to the conversation about profitability and making that a focus. By the way, again, coming from corporate finance, I think you're exactly right. I love the term continuous improvement that you've brought into the discussion. The second model, there's three of these models, so we're more than a third of the way through now, really. But another take on this is what are we doing with the data? Open systems go hand in hand with open data. And again, you see that in a lot of other industries. And there's a lot of standards around open data that allow for sharing of data among systems. And that's been a huge breakthrough in productivity. I've heard it said that data is the new goal in this industry. Let me throw this out to you. Currently, companies over the last decade or more have spent an absolute fortune on collecting data. Sensors of all kinds, tens of thousands of sensors are certainly possible in a manufacturing process today of almost any complexity. And that data is getting generated on continuous. It's time series data in a lot of cases, and it just creates huge volumes of data. And these giant data lakes that everyone has decided is the new goal. They're going into data storage where they're being analyzed and processed. Huge investment again on data processing and data storage. There's billions of dollars already being spent here. And the next generation that I'm seeing, particularly in our involvement with Microsoft, Azure, and Amazon, and Google, is really driving next generation insight and understanding from all of this data. There's next generation tools like artificial intelligence in the cloud. There's a huge marketplace that we've seen, even we've been approached by some startups that are promising operational improvement by providing new modeling techniques to the data. So again, we have collection, processing, insight, and understanding. But unless you feed that back into the system in a real time basis, not once a month or once a quarter or once a year, but in some kind of real time basis, depending on the process, then really, in my opinion, I guess you've wasted all of this data gathering and data processing investment that's already been made. By modernizing and keeping your process controls up to date, it's really the only way to make that last step of operational improvement to drive new data. You're going to change the environment, drive new data, and complete the loop again. I just see this as hand in hand with Pierre with what you were saying about continuous improvement, that the data collection and the involvement of the process control system in acting upon this data and insight is really the critical next step. And that has to be continually upgraded, sort of like we showed in the last slide. What are your thoughts about data? Well, you know, it's interesting. I do like this slide, and I like the concept you're trying to get across with the slide. When you look at industrial operations, I mean, really, for the last 40 or 50 years, we've already been collecting more data than anybody can imagine. I go into operations, industrial operations, and they are process historians that are collecting thousands of points a minute, storing them away on disk, and they sit there on disk, and to be honest with you, they store this data for years. So you have years of data in the plant, and nobody ever touches it. It just sits there. I mean, it may be used initially for some initial terrain graphs, but it really is useless to collect data and not use it. So the reason I like this chart so much is it shows a control loop, as you point out, because I believe the new gold is not the data. It's what you do with it. It's the actions you take. And, you know, actions come in two forms. There's real-time actions that we call control, and then there's transactional actions, which we call management. And what we need to do is not just collect data, we need to collect data that can activate decisions, that can make sure that we're making decisions in the right time frames to improve safety, to improve efficiency, to improve reliability risk, cybersecurity risk, environmental risk, safety risk, and profitability. Bring it all together and close the loops on every one of those. To me, the new gold is control. It's much more of a goal than the data. Now, you can't do control without measurement. So, you know, when you think of data, data provides the capability to measure things. For example, you can't control reliability risk. If you're not measuring reliability risk, you can't control profitability. If you're not measuring profitability, so a precursor to control is measurement. So, if we think about data from the point of view of bringing the measurements in that we need to control and manage, and providing that information to the people throughout the operation that have an impact on safety, that have an impact on security, that have an impact on profitability, that's when we're gonna get the value. I think back over the years, 20 years ago, 25 years ago, everybody was talking about integration as the new goal. Integration is the new goal than industrial operations. And we started integrating everything together. And really, what we found was nothing worked all that much better when we were done integrating. Because integration by itself provides no value. What you do with integration provides value. I'm not saying integration's not important, it is. And then just recently with IIOT and Industry 4.0, every article I read said connectivity, we can connect everything to everything else. Once again, connectivity by itself doesn't provide value. It enables us to do things, to provide solutions that create value. And now where everybody's talking about big data, we can get data everywhere. It's not that that's bad, but data doesn't drive value, it's what you do with it. And so I love the fact that you've got this control loop. You're talking about using the data, creating some data, establishing some data that allows us to make better decisions. But the goal is in the decisions, making sure that we're making the right decisions on the right timeframe and the right place so that we can impact results that drive incremental operational profitability, efficiency, reliability, safety, so on and so forth. Does that make sense? Yeah, it really does. What it reminds me of is I'm a CFO of an industrial company and I've been approving line items for data collection or data processing for a decade, but no one can tell me what the benefits are or what the, as you say, the profitability benefits are. I think these last two models maybe can help shift that conversation a little bit. If I'm a CFO and I'm saying, look, I'm not gonna invest, I'm not gonna take the risk, the capital risk, of investing in a steady-state plant going forward. I'm only gonna approve capital investment as something that can show steady improvement over time and modernization over time through our investment model in the previous slide, or in this model is that I'm not gonna continue to invest in data collection until you can show me that you can make operational change with some kind of feedback loop or control loop, as you say, and drive profitability. And hopefully this helps a CFO or any kind of C-suite executive drive that conversation for their team. So let me get on to my third and final model here. I drew this based on the conversation. It happened to be with oil and gas and pharma in the same room trying to make the same argument for efficiency improvements, what I thought of as efficiency improvements. And I just thought, how can these two very different industrial processes, corporate goals, kind of an investment time horizon? They couldn't be more different. And how can they still both be such strong advocates for the open standards, for the OPAF standard of standards? And so what it reminded me of is what I think of the efficiency frontier, represented by this yellow line here. And you see this in a lot of different contact. One area that it's most resonant is in the capital investment or any kind of investment type model where you're looking to balance risk and return. And the goal isn't to maximize return because you couldn't be taking unwarranted risks. And it's the same way here that if you are operating on this efficiency frontier, then you are optimized for the trade-offs. And the trade-offs in this is really flexibility and efficiency. The pharma industry, the very last decision, the last decision that they make is the industrial controls actually and the commitment to rapidly build a plant because all of their effort goes into getting regulatory approval for their new drug and then it becomes a speed-to-market game. So once they get to that point, they have to maintain flexibility and agility. And so flexibility is hugely important to them. It's not really about efficiency. Oil and gas and chemical and the continuous process companies have a very different profile. They get to some steady state and it's all about incremental change and efficiency. Now, of course, there are risk factors for them that could be a change in environmental regulations, security is always a big threat, a growing threat, and so the security profile continues to change. Downtime is the death for them, right? Because any continuous process, downtime equals zero efficiency and was to be avoided at all costs, they have to operate at peak efficiency for the longest period of time. So when you have flexible control systems, it allows you to both build in flexibility and to build in this efficiency and you just tune your incremental investments, you tune your system to be able to optimize for your own risks and for your own efficiency frontier, as I've called it, from an investment standpoint. If I'm a CFO, I have to do this evaluation and figure out where should I invest to have the most impact, the least trade-off, at least downside for our profile. This is how I've tried to present this as part of this discussion about how pharma and oil and gas can stay on the same investment model, even though they have very different objectives. What are your thoughts, Peter? You know, I really like this chart for a lot of reasons. I think it points out some very important characteristics of industrial operations and they're really characteristics of the industrial operations more than they are characteristics of the control system. But of course, every control system has to adapt to the characteristics of the operations. I mean, when we build a pharmaceutical plant, we normally, in the chemical side of the plant, are looking for great agility, as you point out, because we have multi-product, multi-grade plants. I mean, I've worked in pharmaceutical plants where they have a batch of a certain cancer drug that they make 200 gallons a year, and that's it. And if you created a process just to create that drug, it would be sitting idle for 364 days a year. And therefore, the question on that side is, how can I use the same vessels and the same manufacturing process to make multiple different products and multiple different grades to serve my marketplace? And on the other end of the spectrum, you have refineries, oil refineries, that basically take crude oil in, break it into its component parts, and sell it on a continuous basis, because they have such market demand. I mean, the market demand's very high. So the oil refineries are literally designed from inception to be throughput-based. I want to process as much of this crude as I can to meet market demand. And then the batch industries, like pharmaceutical or agility-based, and both want to be efficient. I mean, it's interesting. Both want to be efficient, but you're exactly right. You need much more agility and flexibility in the batch-based markets than you do in the continuous markets. But if you look at that, and instead of the horizon being an efficiency horizon, we think of the horizon as a profitability horizon, then agility becomes an action plan to improve profitability and efficiency improvement becomes an action plan to improve profitability. Both all industries across the entire spectrum, even into discrete manufacturing industries, which you haven't really covered in this chart, all industries are looking to improve profitability safely. So I believe that instead of it being an efficiency frontier, that yellow line, we ought to think of it as being a profitability frontier. Every industry wants to maximize profitability. And if you think of that as a profitability frontier, we have some commonality across these diverse industries that we can pull together to drive more and more value out of the operation. Does that make sense for anyone? Yeah, it sure does. And I think we'll change the name of our golden line here to the profitability frontier. And the area off to the right of that line is the profitability zone. And I think you've correctly drawn the connection for how control system plays such a critical role in determining where you are on that frontier, which of course is the whole purpose behind OPAF is to drive that. I think that certainly adds a lot of value to some of these frameworks that I've tried to create based on the conversation. Again, I don't have decades of experience in this industry like you do. So this has been tremendously helpful. I will say that I can't comment in any specificity, but we are working closely with Schneider Electric on exactly that kind of operational flexibility. You talked about automated startup and shutdown. We've been invited in to help think through some of those challenges with Schneider Electric, which has been a great benefit for us. And I think to bring our expertise has been around automation and orchestration is benefiting some of the thinking at Schneider Electric. Peter, thanks so much for providing perspective and depth on some of these frameworks. I think it advances the thinking and conversation quite a bit, so I really appreciate value of your input. One of the last things that I can bring up is OPAF has made tremendous progress, incredible commitment to move this forward very, very quickly. The new OPAF's standard version 1.0 is complete. Really, the first steps are already in place to make this a reality. The way that I like to talk about it is that the train is leaving the station for OPAF. And so OPAF is determining this future state of process automation, like I said, is tremendous momentum and speed that it's moving forward. So the decisions that will influence how your control and operations for your business are already being determined and considered. If you're listening to this and your company's not involved in OPAF, your active involvement and participation is actually gonna ensure that your own perspectives, your own specific industry needs are part of this next-gen process system thinking. And so if you wanna get your input to be considered for your future operations, for your business needs, for your specific objectives and success, really, you really need to be involved and the time to get involved is now. So the industrial landscape is changing very quickly. And I think it's better to help lead that change instead of to just follow. So the train is leaving the station for OPAF. Thanks, Brandon. Those were really interesting models. And Peter, thank you very much for your industry insight relative to them. I think our listeners will have a lot to gain from your perspective on how they can be more efficient and profitable. We're running a little short on time now. So Peter, could you tell our listeners how they can participate? And once they've joined, what's the normal flow of events and activities look like with OPAF? Certainly, Robert, thank you. But first, let me reinforce what Brandon just said. This is a once-in-a-lifetime opportunity to select or develop standards that will change the future of process automation forever. Becoming a member allows you to apply your expertise and voice your requirements and it allows you to serve as an advocate for your industry segment. You'll be collaborating with a global network of industry thought leaders who have set aside their competitive interests to reach consensus for the good of all industry. We need the proactive participation of end users to help our business and technical working groups meet their specific objectives. There's no hard and fast rule about how many people from your organization should take an active role and how much time you should commit to the forum. In our experience, the members who contribute the most resources and take active leading roles across the forum's various working groups tend to see better early returns on investment. For more information, you can send Brandon a note or visit the OPAF website at opengroup.org slash forum slash open-process-automation-forum. That's a mouthful, but you know what it is. But really, the best way to learn more is simply to join and then contribute people and resources to the group. You can become immediately involved by attending or taking part in our next OPAF meeting, which will be coming up periodically throughout the year. So thank you, Robert. Thanks, Peter. So again, thank you very much, Brandon and Peter. Your insights were tremendous. And I'd like to thank our viewers and listeners for their participation. We look forward to seeing you on our next presentation.