Mission innovation powered by AWS: Digital Engineering | Amazon Web Services

Key Takeaways

Welcome to mission innovation powered by AWS. I'm Alex Martinez. I lead our global partner solution architecture teams for public sector and I'm joined today by Christopher Finley, vice president at SEIC. Chris, can you give us a brief overview of your role leading engineering uh for SEIC's innovation factory? Sure. Thanks, Alex. I'm Chris Finley. I lead uh our engineering portfolio uh within SEIC's innovation factory and within engineering there uh my team is responsible for developing our innovative engineering products and solutions uh the capabilities to deploy them the workflows the processes the frameworks the training uh and then to provide the resources to go and uh execute on programs. Fantastic. uh modeling a simulation design, it's all been critical across the federal government. Uh but it's kind of traditionally been a little bit slow, resource intensive, and that's why I'm so excited to get a chance to talk to you today about how we're applying innovation to it. And uh that's really all about digital engineering. Uh we're talking to customers now who are really changing their calculus about how they fall and go through rapid iterations, what they integrate across different types of engineering processes. Uh and they're really using this idea of digital twins across all of the federal government. Uh while still driving efficiency into how they deliver those services uh with that um you know as the vice president of engineering at SEIC, you're focused on this particular area. Why digital engineering? You know, what led you to to this path? Why did SEIC decide to invest in digital engineering as uh you know, one of its kind of core strategic areas? Yeah, that's the that's the real question, isn't it? Uh the answer goes back quite a ways. You got to go back probably 15 years or so before I joined SEIC, back to my time at Rathon, where we were working a program. I actually was able to use some of the the earliest versions of some of the more popular digital engineering tools today. I like to say I was using them in anger. I had my you know fingers on keyboards help you know meeting program deadlines to do a bunch of work and I was able to see just during that first uh effort the you know firsthand the value that doing digital engineering it wasn't called that at the time uh that it brought to the program. It was able to shift those defect detection uh curves to the left and was able to provide clear unambiguous models and and and when change happened we were able to do rapid impact analysis uh because we had even back then some form of the data was integrated and connected with upstream and downstream um portions of the solution. Then over time the DoD started to uh take a look at digital engineering. they stood up their digital engineering working group which myself and some some of my colleagues at SEIC participated in and in 2018 they they announced their digital engineering strategy for the world to to get behind and rally behind which we did uh and and that's when we started to to make some investments in digital engineering and then little over a year ago in late 2023 the department of defense released instruction 5000.97 seven which at its real high level mandates digital engineering for all future engineering acquisition. Um and that was a celebration day for for us and it validated not just SEIC's investment in digital engineering at that time but a lot of my own career and personal life decisions that I made to get us to that point and it's kind of how my digital engineering journey went. Well, that's fantastic and we have a saying there's no compression algorithm uh for experience and it's it's absolutely the case here and it's great to see the team led uh by such a practitioner that's been hands on the keyboard uh in in understanding these challenges. Fast forward to today um what do you see are the biggest challenges uh that US federal agencies have in their digital engineering initiatives? I would say from my observations and experience, a lot of our government mission partners are still trying to figure out how how to do it, especially in light of the mandate. So now they have to go do it. So how do I do it? And and there's a lot that want to do it. They understand the benefit, but again, it's they don't know how or where to start. So I think that's one of the the biggest challenges. and and some that have started uh and some that are still looking to start they have and and this is not just for digital engineering this is any any kind of new change it's the culture and the upskilling aspect of doing something new or different um I like to say organizations are not going to be able to hire their way out of this problem digital engineering is still a niche skill set there's not enough people to go out and bring them in to get you up and running to have to change your culture upskill your force uh to be able to accelerate the change, the pace of change. Yeah, as as technologists, we get really excited about what are the technology challenges, but it it often does come down to the people, the process, uh that really allows it to be successful. uh as I think about those people uh you know outside of um some of the federal spaces we've had these huge disruptions and kind of compelling events you know from uh supply chain disruptions that occurred uh during the co pandemic uh to increases in complexity of systems we've gone to additive engineering we have all of these new types of uh capabilities that are in the hands um how are you seeing those specific challenges impacting federal agencies and your end customers right at its core or it's it's making it harder for our government our government partners to keep up with the rising costs. Um even without the supply chain disruptions, the systems are just becoming more and more complex. Then you throw in the supply chains and you throw in everybody else is also trying to keep up with technology. So we're trying to provide the outcomes that our customers need at the speed of relevance is the phrase we like to use. Um, so, so when you combine the need for it to be faster, the need for it to be cheaper or at least not more expensive than it used to be, um, and it needs to be better, right? So, you know, the old adage was faster, better, cheaper, pick two, right? It's they now need all three and that's the challenge and digital engineering is one lever they can pull to help get to some of those those outcomes. Well, we jumped in and and I know you've had a career of experience here. Uh maybe for folks that are you know a little bit new to the technology space um when we hear digital engineering um what exactly is that and and how are how is it helping uh kind of get as you mentioned um all three areas of the the price performance technology uh triangle. Yeah. Digital engineering is uh engineering gone digital and what what that means uh from my perspective is taking the way we traditionally did engineering solution development using what I'll call a documentbased methods Excel spreadsheets powerpoints word documents 2D drawings uh I know we're we're long um we're long gone from you know where we used to handdraw the drawings but you know doing some kind of partial modeling and then putting everything out on a on a flat file. It's taking all of that and getting all of the solutions into digital models and any relevant data into databases. Uh so that's digital engineering at its core. And but in order to really unlock the value of digital engineering, it's to connect that data together. So, how do I connect the requirements to the architecture to the CAD to the electrical to the software to the mission data that we're collecting for sustainment and tying that all back in uh so that's connecting all of that data. Uh we call that the digital thread. So being able to not just connect the data within a particular engineering domain but across those domains as well. Um so that when you do that you have better understand you have a better idea that your design especially as they're becoming more and more complex that your designs are complete that they're consistent and you can trace. So and the traceability is important because any system that we've ever developed changes over time and when you make that change you want to be able to do rapid impact analysis. I like to say you want to know what you're stepping into before you step into it. And having that digital thread with all that connected data allows you to do that. Fast forwarding to AI, if you don't have your data digitized, you can't start to take the steps to get to AI or generative AI. So, so it's almost like the foundation for being able to get to generative design. Yeah. I mean, that's a fantastic description and you're really already kind of telling us something that we should expect to see. And so I'm curious, you know, given where we're at today in this, you know, data focused effort, where do you see digital engineering going over the course of the next few years and, you know, how is how do you see that incorporate this digital thread that you described and really bring on some of these new disruptive uh capabilities as as we like to say at AWS to really continue to reinvent digital engineering? I'll group it into three areas, kind of get our heads around it. The first one I'm going to say real time digital twins. And we're starting to see that from our customers and experience that digital twins are getting a lot of return on investment. So So what is a digital twin? A digital twin is a a uh a virtual representation of a physical asset that's in the field. So if if I have a tank that's fielded, right? I've got a digital twin. I've got a some portion of that tank is modeled in some kind of computational model or some real-time status dashboard. Uh and it's mapped to serial numbers, right? So, um, so having real-time digital twins, being able to monitor, you know, in the case of the DoD, what's going on as we're fighting a war, so we make decisions, um, for for for any kind of situation where we've got assets deployed, uh, being able to use that information, uh, and then to combine it with AI to do performance-based logistics, right? or or look at the data and say, "Hey, maybe maybe it's cheaper to spare this a little bit more often than to go and actually redesign the part, re-qualify it, and then install it." And that gets into the second thing, which is AI for DE, artificial intelligence for digital engineering. As we start to add more and more sources of truth to the digital thread, we can leverage AI to turn that onx engineer into a 10x or a 5x engineer. Right? Meaning, you know, today I can only do so much, right? But tomorrow with digitized data and maybe Agentic AI, I can start seeding models faster or making better decisions or reviewing my work. So before I get it out to review, shifting further shifting my defect detection curve uh to the left. Uh and then the the the third one is is a little bit of a play on words, but I call it digital engineering for AI. So I flipped it, right? How do I get AI to the edge where the end users are? It just doesn't show up, right? I know I know the cloud, right? But the reality is if I'm going to the moon and I want to leverage AI, I somehow need to get that software, those algorithms to the moon, to Mars, to the battlefield, you know, to the bottom of the ocean, wherever we're doing the work. And the data has to come from somewhere, too. So long before you can you get there, you have to engineer a system. And I like to call it system engineering mastery. And I think digital engineering can provide that system engineering mastery to allow us to bring AI to the edge, right? Kind of bring that complex system together. Yeah, that's fantastic. And I I love the play on words, right? where you're using the technology that's adopted AI to really then go build um what that new framework needs to look like to get these technologies uh really into the hands of the end users um in all the different austere environments that they they face challenges. Uh this is an area clearly you didn't wake up you know yesterday and say hey we want to be in the digital engineering area. SEIC's been doing a lot of investment over time. Uh but you did mention uh the DoD instruction right so just recently came out you alluded to this earlier but I I maybe wanted to get to a more concrete example we hear from customers often that they want to get both these new capabilities but they really want to drive also the efficiency and uh you know perhaps not at you know the existing budget but they're actually looking to say how can I be even more efficient in my delivery of these capabilities um and so can you give us an example of how digital engineering ing is being used to drive efficiency uh and what kind of outcomes customers are are are getting from uh these changes of how they'd be able to go develop and and create these new systems. Sure. Can't mention the customer's name of course to get prior approval but a great example I think really illustrates uh the efficiency and the power of digital engineering. We had we had a customer that was maintaining a a many decades old facility that was doing testing for critical equipment for one of the branches of of defense. And it needed to be updated uh just to handle more throughput to keep up with the technology of the systems that were coming through that facility. and they had purchased a whole set of equipment to upgrade, but it but over the years, right, that facility expanded and grew and it was a patchwork of things and they didn't really have any good documentation of how anything worked. So, they they'd spent a lot of money buying the equipment and they were nervous that if they started to replace this critical equipment, they they could if it didn't come back online correctly, they would go from just having not enough throughput to no throughput for a period of time. And so they brought our team in to go and model those systems and we modeled the using digital engineering techniques. We modeled the the ASIS. Mhm. And then the 2B with the new equipment. We created a digital thread between the system architecture models and the performance simulations to show that they were going to get the performance. It gave them the confidence to then go forward and actually change that out and increase the throughput of their facility. Oh, that's a fantastic example and sounds like you you've got this capability increase um as well as you get confidence that you could actually execute and deliver it. Uh maybe what are some of the other dimensions of uh capability enhancement? One of our our products is called ready one and that is an integrated digital engineering ecosystem where we take uh some of the best digital engineering and engineering tools out there from any vendor. We connect all of those sources of truth together into a digital thread so they can have a digital thread right out of the box and they can start making inferences on their data making sure like I said earlier their solutions are consistent complete and traceable um and it's available to all of the players 247. So that's another thing as the systems become more and more complex no one organization is doing all of the work anymore. That's right. So how do we break down this the organization of silos through these digital engineering collaborative ecosystems? And uh I should mention that we use AWS GovCloud as uh one of the key tenants of our ecosystem that allows folks to access it from anywhere. That's fantastic. I mean, that's really what we talk about when we talk about mission innovation and and what we want to get in place and, you know, appreciate the the perspective about how we've been working together with AWS to help support your teams. Uh, SEIC and AWS have put together a very strong partnership. Maybe could you explain, you know, how does that partnership and the collaboration with AWS teams uh help you deliver those digital engineering capabilities? Yeah, we have a we have a great relationship working with you guys at AWS and it's been going on for for probably a good four years now or so. Um we probably talk a couple times a week uh with your teams not just to say hi but to actually solve continually solve hard problems. I had mentioned ready one earlier that's our uh rapidly deployable digital engineering ecosystem and we were just at a point in sic's evolution where we had to upgrade our servers and our infrastructure where our digital engineering tools resided and we said hey let's go join the the new century and instead of going buying more equipment that may or may not meet the demand over a certain period of time we we decided to move to the cloud we decided to go to AWS uh govcloud and like I said we've been working with your team for for several years now. Uh and it's it's a it's a home for where where sic does their engineering work. Uh and and and then we also can bring it to our customers gov cloud space as well so they can have that collaborative uh session. And then we've gone so far to do executive visioning sessions with you all. We went out to your your headquarters out in Seattle which was a uh a really enlightening experience where we we started to unlock where we could go jointly. um to to take our digital engineering and our our ready one ecosystem to the next level. Uh sometimes folks, you know, the hardest part is getting started. What advice would you give to an agency? They've they've heard you kind of talk through the outcomes, the benefits, um you know, where the future is going, but um they're not there yet and they're they're ready to get started. Uh what's the first step? I think the the you know, selfishly the first step would say give us a call, right? Uh but if it but uh you know just at the at that higher level look for look for those proof points in the industry because there are there are some out there now. It's not like five or five years ago where everybody was thinking about talking about doing digital engineering, right? And with a few companies that were actually doing it. Now there's there's a lot more companies uh that have proof points. So so seek out those bonafide proof points or or look for customer testimonies. there's no shortage of of information of people that have uh you know either rightly or wrongly claimed benefits of digital engineering uh for their organization, right? And like I say, find folks that have experience using digital engineering in anger. Um and you know, whether you're reaching out to us or someone else put from our drive, don't recreate the wheel. I mean, one of the reasons that we're doing what we're doing is to help um elevate the entire industry for the benefit of our customers. So don't don't recreate the wheel where it doesn't need need to be recreated, but from the drive. Yeah, that's that's fantastic advice. Um, you know, don't don't suffer in silence to try to learn this. Um, it's been a real pleasure getting an opportunity to hear from someone who's grown up in the field uh and is now leading and being able to create the future of it in digital engineering. Uh this is exactly the type of capability that we get excited about here uh with our mission innovation powered by AWS because we're we're seeing uh the technology be applied to really change outcomes uh as you said in all the environments um that the end users are looking for and particularly with um the focus that the department of defense has uh it's we've got a great set of capabilities we've worked together with and uh we have a great part for folks to get started uh so they don't have to go at the but they can learn from all that experience uh that the teams brought together. So really excited um we'll be able to share with folks how they can get in touch with SEIC, learn about ready one and uh take that information uh to begin their journey in digital engineering. Thanks again Chris. Thank you. Appreciate it.