Customer Success | Clay Wesener from Microsoft and Keith Kirkpatrick

Hey everyone, it's Alan Shemel from Techron. You know, we're going to continue with this fantastic series we're doing of sessions between some of the leaders at Microsoft as well as analysts from the Futurum Group. In this next session, we're lucky to have Clay Wener.

Clay is the partner for GPM Power App Studios at Microsoft and FU analyst Keith Kirkpatrick. In today's, uh, session, it's really a customer success story where Clay joined by Keith are gonna delve into a real world customer story and this case Wells Fargo offering a blueprint for leaders ready to scale success in the age of intelligent apps. You're gonna see how power power platform is being used to modernize complex regulated workflows with copilot studio agents and power apps.

This session will highlight architecture, business impact, and lessons learned from deploying intelligent apps at scale. I think it's really a great session you're gonna enjoy. Let's go to Clay and Keith.

And, hi, I'm Keith Kirkpatrick, research director with the Future Home Group. I cover enterprise software and digital workflows. Hi, my name's Clay Wena.

I look after our low-code developer experiences on the power platform. Well, thanks for joining me today, clay. Maybe Clay could talk to me though a little bit how power platform can actually help these organizations balance that, that agility to handle these types of, of scenarios with their compliance needs that often come up when you're dealing with things like banking or insurance or, or any one of these regulated types of processes.

Yeah, absolutely, and it, you know, we, within the product we sort of refer to this as managed platform because it is very much a feature of, of the platform, of how you can govern at this scale. And, and this has come from, you know, not just, uh, us deciding exactly what's gonna be in there, but really for folks and customers leveraging low code over the last 10 years and evolving to have a really, really strong governance because I, I think we learned very early on in the journey that if those guardrails are not there, people are just inclined to wanna turn it off. Um, and, and we are very much, I use the, the word guardrails deliberately, and a lot of the things we do in a managed platform is focused around how do we give you the right control so you can still enable these types of tools, whether it be building apps, building automations out at scale, but do it in a way with the, the right sort of controls and guardrails on it.

And so, like examples are things like data loss prevention. So I can set rules around what connectors and what data you can access versus someone else. And so I can also say how many people you can share an app or a workflow or something with, so I can sort of mitigate the risk that you might be able to, to have working in low code, thus someone that's received more training or onboarded to the platform.

And so typically what we see customers do is sort of implement this zoned approach of, you know, their, their zone. One is everyone in the organization and they say you can build apps for personal productivity, you can connect to your office data. Um, you can sort of work with those well-known sources and you can go and share apps and flows and agents with up to 10 people as an example.

But once you want to go beyond that, we want you to engage a little more with it. We wanna make sure things are supported, we wanna make sure that you know what I mean, we have the right controls, whether that be accessibility on apps or the correct support path. And then what typically happens is we'll then have a zone two, which is potentially some more sensitive data, potentially, you know, a ability to share with more people within the organization.

And what folks might do then is they might say, well, this is for our divisional leads or our champs within each group that we've onboarded, we've trained, they understand the platform a little bit more. And then that final zone would be your it, your dev center who's working with your really critical data around things like finance and, and hr. And what we've just started to make sure we do in the platform is give you the right controls that someone can still come to make power apps, make power, automate and start building, and they're not going to fall into a trap there.

They're gonna fall into the pit of success because we've, we've put those right guardrails on what they can access and what they can do. If you look at, not just if we're talking about, let's say gentech technology, but just everything, if you look at the development of the smartphone, everyone expects sort of a consumer great experience throughout all facets of their life. And, and I guess that, you know, do you see that sort of pushing or helping to evolve kind of what 'cause customer success might look like, you know, not just now, but into the future?

You Know, again, earlier in the, the low-code journey, it was always IT departments, development teams that were looking at the low-code platform. And more and more these days as we're talking to customers, it'll be their employee experience team. You know, it will be folks responsible for actually healthy and and, and productive employee experiences.

And that's what I mean, it's not just about cost saving, but you know, it's about bringing the right tools in. There's the SNCF, the French railway are actually a really good example. They run PowerSchool, which is an onboarding school for the whole power platform when any new employee starts.

And this is becoming a really, really common practice that more and more folks are, as they join an organization, they're getting training on these tools, not as something they have to use to do their job, but as a benefit to them to be able to do their job in a more productive way. And I think again, the, the consumer push and acceleration of AI is, is just accelerating that within the enterprise as well. Right.

When you're talking about human in the lube, uh, you raise a really good point because ultimately this is still new technology and you wanna make sure that particularly in, you know, you're dealing in a commercial environment that you don't want this agent technology to sort of run wild or unchecked. So I'm just curious if you could talk a little bit about, have you seen other examples where customers have actually deployed their sort of checks, uh, and, and balances to make sure that their technology does what it's supposed to? Yeah, absolutely.

And there, there's a couple of ways we're seeing folks doing that. One is just in how we define and build the agents and the tools themself. While that agent has the ability to issue refunds, it can only do them up to a hundred pounds.

So it has very specific guidelines built into it that once it goes over certain criteria, loop in a human, send them an approval workflow so that they can approve this, review the details. So that first one is just very structured, giving the agent details. Um, the other side, and, and this is where we've sort of really seen how apps have evolved in the last couple of years, if you've been looking at what we've done with power apps, we've introduced this concept of an agent feed, which is really about in the same UI that you would come into the app and, and do your day-to-day work.

You start getting this feed of activity from the agents that are in your digital team effectively. And so you can start seeing where they're completing actions, where they might need assistance or where they're getting blocked. And so what we're starting to see there is even our UI patterns of what we traditionally thought an app was, is starting to bring in this age agentic behavior to give, you know what I mean, that human in a loop and that oversight capabilities.

So I still want someone to have a really clear view of what tasks are being completed by the agents, what's being completed by ai. And in that view get, be able to get into the reasoning, understand the logic and sort of the thought process that the agent followed behind it. So it's not a mystery of why something progressed or why an action was performed.

But as the, as the human responsible managing that team of agents, I can effectively go in and see why it did something that might be then come a teaching moment for the agent where we correct that behavior or change it for future cases as well. Well, you know, it, it's really interesting you mention sort of the generational shifts that are going on. You know, we're seeing the, you know, entry of these, I guess you'd call them AI natives coming into the workforce where they don't know anything other than a world with ai.

Uh, and I guess, you know, that kind of begs the question, you know, we've heard so much about AI in the past, you know, particularly the last couple of years. Can you talk to me a little bit about, you know, what role can AI actually play within customer success? Because, you know, it's a wide, you know, AI has so many capabilities, but I'd just be curious to see if we could boil it down to this function.

Yeah, I, and I think it honestly depends on the customer, how they're approaching it. You know, one of my favorite examples of I think sort of scale and pace pg and e here in the United States, um, they're a big power platform user, and we, we talk about scale. I think they estimate since they started their journey in 2021, along the lines of like $38 million in savings that they accrue to the power platform.

Like huge in, in, in terms of scale. Um, but so much of actually what they've implemented is not just, you know, uh, cost efficiencies. They introduced an agent called Peggy, and they actually have a nice avatar for Peggy that they, they introduced across the organization and Peggy now handles, it's between 30 to 40% of their IT help desk calls.

So built in co-pilot studio, Peggy has access to their knowledge base, all their policies and documentation, and just Peggy one agent they estimate saves them about $800,000 a year. And it's, wow, it's absolutely transformational. And so even with the savings they were getting on the power platform between apps and automation, there is a limit.

Mm-hmm. There's a limit to how much productivity that that can drive a gentech, you know what I mean? Tools and, and, and what people are able to build in copilot Studio has really just broken through that, that barrier.

And, you know, you look at, again, someone like pg and e when they implemented Peggy, it was very simple looking over knowledge bases, access to information. It helped a large volume of sort of tickets that would come through the help desk that used to be a human replying to an email or replying to an im. Those humans now are actually providing much higher quality support on a, on more technical cases.

They're not helping someone log into Citrix for the first time or, or point them to something that's really well documented. Peggy's able to do that, but then they've also continued to evolve it over time. And so, again, one of my, one of my favorites that Peggy can do is getting folks that get locked out of their SAP accounts.

One of the most common things that it apparently happens thousands of times, um, and now Peggy using an integration between copilot Studio and Power Automate can actually open up SAP and go and unblock that person's account for them after they interact with her on teams. And so this was something that was critical to an end user to get unblocked really, really quickly. Peggy's able to do that for them fast, but it wasn't high value from an IT support team and what they were really providing them going and opening up an accountant unchecking a blocked checkbox.

And so I feel it's a really good example of where they started simple. They focused over sort of knowledge base examples. They evolved it into actions, but it's something where they've gone for a, a high volume, you know, cost inefficient area.

They've applied agentic AI to it, and that's something that go back three or four years ago would've been an extremely expensive tool to go and implement leveraging LLMs and leveraging copilot studio. They've been able to do all that in low code, which is super impressive. I, I'm curious, you know, one thing, clay that you alluded to earlier is if we think about how apps were pre, you know, previously developed and rolled out, it was it who gotta manage that?

Now what it sounds like what you're saying is we're getting to the point where, you know, business leaders or even folks who are, are working within departments may be able to actually launch apps or launch agents, obviously with that human in the loop and with those, you know, specific guardrails, are you seeing any kind of patterns emerging in terms of, you know, uh, customers who successfully scaled these, this agent automation for more of a grassroots approach as opposed to springing from it? Yeah, and you're absolutely right. I mean, we sort of see an approach from both directions and some, some customers very deliberately approach it from one or the other to start with, I actually then of all the examples I I I've sort of talked about today, do quite well balancing both spectrums and I both ends of the spectrum, sorry.

And I think that's where you start getting the real value multipliers. PG and e, great example, I talked about Peggy earlier. That's an IT or centrally LED tool.

It was about optimizing a process within the IT team, but at the same time they have thousands of developers across their organizations. And when I say developers, I mean low code citizen developers that are enabled to go and build apps to go and build agents to go and build automation across their, across their team. And they've sort of very deliberately focused their center of excellence, their digital transformation team on a few core objectives.

So that's the team that sets their governance policies, make sure it's scalable, and then they also support and train those different sort of divisional leads across the company. Pg e actually again, I think they're on the spectrum, the end of the spectrum where they're doing this, you know, in a really amazing way. They have a conference every year called Level Up now where they actually get together all their citizen developers and, and, and those divisional leads from across the company to come together, share stories, share learnings, and sort of explain new technology.

But it starts becoming a real cultural tool in that they're enabling people to go and solve these problems, make themselves and their teams more efficient. And there's, there's reward that comes from that. You know, they're getting folks together, they're getting a lot of learning.

And so I think, you know, while lots of companies are enabling citizen development, the ones where we see it's truly being successful, they're bringing this level of evangelism to it. Well Clay, maybe you can talk a little bit about some of these platform features that, that are kind of critical for managing customer success initiatives, because it really seems like, you know, they're obviously you have the human component, but there's also the technology side in terms of making sure there are the right tools in place to help organizations, you know, address all of these issues. There Is, there's obviously the human, the technology component.

I would also say there's just the practices and, and, and sort of learnings and we actually have some good documented platform guidance out there of like, what are the best practices in, in thinking about this zoned approach that I was talking about, and in how people, uh, can sort of apply different levels of control to different parts of the organization. I would say then we start looking at the specific technology one, a lot of those guardrails just light up directly in the product. So as a new citizen developer, as a maker, when I go land at any one of the power platform tools, I can get welcome guidance with links to internal learning explanations of where I can go to support.

I get routed to my own personal developer environment. So I actually have a sort of controlled, dedicated environment for me to go explore in to experiment in. I'm not sort of working in prod I'm, I I have the ability to be controlled and then things like pipelines, which effectively are a low-code a LM tool so that once I do build something, I can either use it for my, myself and my personal environment, but if it gets to the point where it does make sense for it to be deployed somewhere centrally leveraged by others, I can go through an automated deployment process where the right checks go.

I have an AI advisor that reviews my code, make sure my apps are secure and performant and accessible, and then get the right approvals before that gets deployed. And it's really that mix of, you know, we want to democratize, we wanna make these things available to everyone across the organization, but then have these right built in tools so that you don't have to go read a wiki to find out what's the process that you should follow. It's built in to the developer tool.

So I kind of just as I start building, get guided to the right environment, I get guided to use the right data, I get guided to share it and deploy it in the right way. And all of that we bundle up and sort of leverage within that managed environment, which gives the, the admins, the it, the central digital teams that control centrally to sort of set up those tools and that content that they want available across the organization. It sounds like all of these tools, you know, really underscore what you were talking about before, which is this culture of trying to utilize technology in a way where it's deployed at the right time, uh, in the right space and with the appropriate guardrails, but while still fostering a culture of experimentation and, and ensuring that people feel empowered to use these new tools.

It you're absolutely right. Like the cultural, I think when we talk about your, your first question about like what's the new definition of customer success, you know, I think it's the customers that have implemented the right culture and it feeling like it is a culture of empowerment and experimentation, not, you know what I mean? Not something that they have to fight really hard to get access to, because that's where a lot of these examples where we have customers turn around, they've built something that's ended up saving them millions of dollars.

It came from the expert that was involved in the business process. It didn't come from a central team. And to get that creativity and get that ideation, you need to give people access to these tools.

And you know, we, we sort of regularly, uh, sort of ref or I, I regularly reference, you know, Jurassic Park Life will always find a way. Uh, and I think, you know, so will users, so will makers, they will find a way and to restrict these tools to, to hide them. Folks will go find a tool on the web that can help them be more efficient in their job.

The companies that are doing this right, are making it part of their culture to provide those tools and just really enable people from the get go. The technology is probably going to be more accurate over time if you're talking about trying to, you know, really assess, you know, images and differences between them. But, you know, one of the other things I'm really curious about is how can agen AI and and all of this technology be used in regulated industries?

I'm thinking in particularly financial services, banking, insurance where, you know, there's a lot, lot of complex process, but you also have to be mindful of all of the, uh, regulations that are, uh, attached to those industries. Yeah, It, and it's actually quite surprising, I think in, in this technology shift with AI compared to when we moved to the cloud compared to internet, compared to a lot of the others. I think actually the regulated industries have, have actually been quite a lot of the front runners on this.

Um, you know, uh, EY for example, built Power post, which helped them with their financial processing sort of end of month processing. They built this as a, as a sort of typical low code application. They're already looking at how they bring agentic checks into it to make sure that things are being posted into the right period that they write, they have the right information.

Again, time consuming sort of manual checks. Wells Fargo have rolled out agents to a more than 4,000 branches, you know, meet a huge, huge number. And they targeted a process that was around their branch forms and procedure management.

And this is something that was particularly time consuming. So if you went into a branch and said, I need to set a power of attorney, or I need to open an account and, you know, under a, maybe a non-traditional circumstance, there's a huge amount of internal documentation around those procedures. The right forms, the right information to collect.

And before that would mean as a customer is standing there with the branch member, they're looking up that information, trying to go find the right procedure going in, right, going to find the right form. So a heavily regulated scenario, but also really impacting a customer who's literally standing in front of you waiting, you know, maybe on their lunch break, uh, trying to, trying to get through the bank really quickly. And so they rolled out an agent, you know, across all their branches to actually manage that forms and procedure scenarios.

And so that now in the branches, those employees are jumping straight onto an agent talking about the scenario that the customer has and working with this agentic AI to basically get guidance on the right forms, the right procedures to follow. Even in these regulated industries, they're seeing the value in ai and I think it's more about how they do it, making sure they have the right checks in place, making sure they have the right guardrails rather than what they probably would've done five years ago where they just tried to turn it off. You know, we, we talked a little bit about, you know, potential friction there, but are there any other sort of potential hurdles that organizations need to be wary of?

Uh, and and what, what's sort of your take on a solution? Like most things, we talked about human in the loop, you know, making sure you introduce this technology in the right way to organizations is really, really important. I mentioned EY earlier, they were really, really successful in after building Power Post, which helps them manage their, uh, their sort of end of month financial processing.

It simplified it, it brought in some mag agentic behavior to Val validate quality, and it, they had like huge gains in efficiencies in both, I think it was 70% in, in sort of the time or 95% in lead time to get things posted and about a 35% cost saving for them. So like real, real sort of impact to the efficiencies of their users. But what they did really well was once they built that tool, they told that story, they evangelized it, and so they helped people understand that this is how this technology was helping them, this is how it was implemented.

And that not only made, obviously people a lot more receptive to onboard and leverage the technology, but it also started driving this ideation of other things to go improve within the organization and using similar technology. A lot of these companies are not coming in and doing a full low code approach of apps and agents and automation and reports all on day one. Where we're seeing folks be really successful is they're leveraging the composability of the platform.

You know, they're starting with, for example, they might have a, a legacy application that's inefficient for a user. So they go and use an app, they build more efficient, streamlined UI over the top of that, that's an incremental solution they can deploy, they can get out to their users and start seeing benefits. Then on that same app, they can go and add automation.

They can start getting approval workflows, then they can start bringing in agentic ai, getting that automation and that AI behavior incrementally building these solutions over time. And it's very much, you know, intentionally how we've designed the platform in that these are not all or nothing solutions. And you know, back to our earlier conversation, pace is extremely important these days and people don't want to go do a 12 month waterfall project of every requirement met.

They wanna find ways to incrementally build. And by leveraging a platform that has common governance, these tools are designed to work together apps with automation, with agentic behavior integrated into co-pilot with that unified platform. So essentially you're setting up a framework to enable organizations to really drive these best practices in terms of making sure that yes, you are implementing new technology, but you're doing it in a thoughtful way where you have the right checks in place and you know, you really are making sure there's, you know, other things that, that you need there.

You need the audit trails. You need to make sure that, uh, you know, when you do a project, you're going back and you're actually assessing, you know, does the technology achieve the goals that we set out to, uh, set out to you when we deployed it E Exactly. And I think it's that, you know, there's two parts to it.

One is that being proactive. So as you're releasing a new app or a new agent to the organization, do you have the right controls around it, the right guardrails from the beginning? And again, our goal is let's have the right framework, the right tools, the right guidance to go really enable that and let an organization tailor those guardrails to sort of accommodate their level of risk, what they're, they're comfortable with doing.

But then on the flip is make sure we just have the right visibility, the right auditability, so that as you're leveraging AI more and more within the organization, it's really transparent mm-hmm. About what it's doing. You know, I think one of my favorite things with, uh, copilot Studio, um, and Pets at Home is a great example of this as it's interacting with customers on customer service.

You can go into any step through any sort of run or action the agent has performed and see, understand its thought process. Why did it do this particular step? What were the inputs?

What were the outputs, what were the reasoning? Um, and not just understand it, but then also help teach it for, to handle sort of moments, uh, in a different way in the future. And I think having those, those sort of tools from a governance perspective just built in, again, you know, we talk about it being unified for the developer, unified for the end user, but also for the, for the admin so that they're doing in this sort of central and controlled way.

And even then, whether you're building an app, an automation an agent, you know, you've got that composability across the platform, but I don't think admins really want a super composable admin story. They, they want that to be a lot more unified and and controlled. So, you know, it's bringing the, the blend of those worlds of let's bring together multiple technology, multiple tools, but make sure then you sort of have one central view of, of how it's all coming together.

If you want to really drive the use of new technology, you need to do it in a very stepwise fashion. Using a platform that allows you to unify people, processes, technology, it doesn't make any sense to try to do it in a very disjointed way. You won't have the governance required to do it safely.

You'll confuse people in terms of which tool should I use, which approach should I use? Ultimately, it really does matter to make sure that you have a unified way of approaching the implement implementation of new technology. It's also really critical to make sure that as you go about your journey, whether it's implementing low-code processes, uh, implementing agent technology to have a clear understanding of your business goals, what outcomes do you want, how are you going to measure them, and then how are you going to take all of these different learnings and then streamline it so you can actually apply it and scale it over the enterprise, not just for today, not just for tomorrow, but well into the future.

And finally, I think the most important thing that kind of resonated with me today is you need to look for a trusted partner, trusted technology partner to help you through this journey. A gentech technology is very new, low code. Yes, it's been around for a while, but you know, there are still quite a few pitfalls that can be out there.

You know, to go out on your own can be very, very challenging because you have all of that risk of potentially opening yourself up for errors, missteps, and of course there's that, you know, we talked about it a little bit today, uh, regulatory concerns. It makes a lot of sense to, to partner with a company that has experience with other enterprises to deliver these types of benefits using that new technology.