ServiceNow, Inc. (NOW) Earnings Call Transcript & Summary

Thank you, Jack. That was a great overview of what we perceive for hyperautomation, what we see in the market, what analysts see in the market. And we want to step up a notch and see what have we learned in the last roughly 2 years that I've been working with customers implementing ServiceNow's RPA, things that hopefully help you to be faster when you deploy your own RPAs based on the ServiceNow platform. So we'll go through a couple of points of best practices, good practices that we have identified. We'll start off by identifying the right processes that actually varied an RPA. Jack already mentioned that everything is RPA just because it looks like, right? So we'll look at that. Secondly, we will look at a maturity model for RPA, right? As you start, you might not be the best expert in the first step, but you want to grow into it. You want to scale it up. How do you do that? What are the next steps to do? And third, we will look at how can we use the RPAs in the broader context of a digital workflow. Having a ServiceNow platform on the back of your RPA engines will open up or does open up a lot more opportunities and possibilities that make it useful -- make it even more useful. And lastly, we'll drive into how you can monitor your RPAs and get to that ROI or measure that ROI that we've been talking about to get back your investment into the whole program. Well, let's have a look about identifying processes to apply for RPA. ServiceNow has RPA bundling, what we call the automation engine. The automation engine consists of 3 different application packages: RPA, APIs via integration hub or even intelligent document processing. These are 3 different capabilities bundled as the automation engine. RPA is a great tool for everything that's UI-led. Anything you want to do on a user interface level where you actually remote control a screen, a form onscreen, clicking buttons, entering texts, things like that, that is where RPA really shines. And we can automate these repetitive tasks for people swivel-chairing between different applications and things like that. That is a great use, at least, for RPA. Anything not UI-driven, anything that can be done using APIs, back-end integration, as we definitely would say, use integration now don't use RPA. While you can do it, it's not the best choice to do it. And the third pillar is when we talk about extracting information from unstructured documents, right? Typically, it's PDF files. You might get them from maybe your suppliers, your vendors, from your customers, whatever. You get PDF files, forms basically, and you need to extract information out of that to make a process. That's when we talk about intelligent document processing. [ Another ] capability, all of the ServiceNow, and you can combine these to make a really powerful growth. So if there's something you want to take away from today's webinar, RPA is great for anything UI-led, that is really its strength. And what can we do with that? We can use RPA to connect to legacy systems, right? In enterprises today, we still have quite old systems that have been around for 10, 15, 20, maybe even more years that don't have an API. Maybe you don't want to upgrade or you don't want to pay for the APIs. It's too expensive. That is a great way where we can apply RPA. Maybe you have a homegrown, home-build application that just doesn't serve modern needs anymore. And front face there with a ServiceNow modern user experience and use RPA to actually back [indiscernible] into the system like mainframes, for example. We can automate legacy system actions like anything that is somewhere in the back-end. For future pay being a great example. You get stuff you procure, and you need to get that into your finance system to unlock the payment. That is, to me, a very manual task for a lot of customers, copy and pasting information from one sheet to another or one system to another, so we can bridge that, get up using RPA. With all that, we actually enhance the work of the humans, right? We take away the mundane, manual repetitive things and unlock their work time to more valuable work. That is the whole idea of hyperautomation here. So these are good examples of when to apply RPA and how to find good processes in the enterprise. Let's talk about a maturity model, where do we start and how do we grow that? If you've been with ServiceNow well, you know that we like to talk about crawl, walk, run, fly, these kind of maturity levels. When you start with RPA, you'd most likely start at the crawl phase, right? That's the first time you set it up. You need to get the infrastructure ready. Robots are basically installed and machines in your environment. So you need to set that, these ones up and make sure they are maintained and owned and things like that. You have the first processes that you implement. Most likely, they are relatively simple. We kind of see request-driven processes as a good example. So you get a request coming in, maybe through a service catalog. And the RPA is automating the fulfillment of that request, right? Or some of the departmental routine work within a department with what, so far, 4, 5 people have been working on, on excel sheets, [ group sharing ] staff, that is good examples where you can apply RPA and start automating and learning. You need to build up the knowledge in your teams, how does RPA work? How does the connection to ServiceNow work and things like that in the process. Once you have that, you go into the work phase where you start to expand the use cases. So you find more scenarios that you can apply RPA in your environment. You define some common rules, how do you want to maybe deploy, maintain, operate these robots as you have them as they grow as you get more in your environment, right? You start building up maybe more developers on RPA. Maybe you're handing over some of the tasks to the businesses, right? There are applications like UI or their capabilities like the UI recorder, where it's very easy for someone to record a robot that can be handed over to a business to start off with things like that. I mean, in that stage, you typically get to little more complex applications that you automate, not really complex. We'll get to that in the next stage. But on this one, you start maybe with a customer application that drives the process. It's not a simple request anymore. It's a full-blown application, let's say, right? You start using things like Flow Designer. Maybe you integrated the integration hub and things like that where you expand your usage. Once you have that, the third stage when we consider a run is, we actually scale it out. You add way more robots, automation and things into it. You'll probably start out building an automation center of excellence that purely handles RPA request, right? Demand coming in, there will be more demand coming into your team. More people ask like, hey, I want the same things like that. And that's where you kind of structure the process around that. You're building way more complex integrations where there might be a bidirectional data exchange between legacy system and ServiceNow going better in and out and things like that. So it will get more complicated from a process perspective, but not from the technology way. By now, you have to learn how the technology works. The last stage here, which I called fly is basically when we talk about monitoring and harvesting on your investment, right? And we'll come to that in a moment, how can we actually make that visible what you get out of the RPA world. With that model, I want to basically give you an example of where RPA fits and maybe where RPA doesn't fit. The example that most of you probably have seen or heard us talking about is an employee onboard. Quite complex process in modern organizations, right? It starts with paperworks handing to the new employee, creating batches, provisioning laptops, maybe access to systems. There's a whole bunch of tasks that need to be executed until an employee at day 1 can actually start really working. And we have been -- we do have our employee onboarding process already in the platform ideally, right? It's there. But there are quite a lot of back-end systems involved. And you can see them here at the slide at the bottom where it says T-System. Well, maybe not all of these applications have proper APIs that we can probably integrate with. You see like a homegrown there for batch as an example. And if we talk about fully automating that whole journey, that's the idea of how hyperautomation get as far as you can with a reasonable effort. And we want to also automate that homegrown piece, right? And that's kind of where we start talking about which capability is fit for purpose in a given scenario. You can see that at homegrown remark here as RPA as an example versus on the left-hand side, where we talk about documents being sent to the new employee, like maybe the bank account that they need to fulfill, so we can pay the salaries. That might be a form of PDF they have to supply, we would use IDP, the document processing to extract that information versus on system access. We probably use an API to provision roles into environments. So use the different capabilities that we have as part of the automation engine highlighted, they're now in blue, for the right purpose. RPA is not great everywhere, but where we need it, it is a good and a great capability to use. Another example that I've been working with in, yes, the last year is one of my customers in the range of higher education. They have a process when a grade of a student was wrong in their system, right? Let's say, maybe the student came out and say, "Hey, you graded me. You made a mistake in judging my test there. Something has been wrong." At that point, their legacy or the previous process was that the teacher actually need to go to a portal, request a grade change. That grade change request on the portal would actually be sent to kind of a faculty master to get some rules in place. Like is it from the current semester? Is it from the right student? Is it from the right teacher? Things like they have some rules have to be applied mostly manually, right, that people checking data. And if approved, that portal system would actually generate a PDF, which would be sent to a back-end operator, an agent of a secretary worker to update the real back-end system where the grades are actually stored, right? So somebody would need to swivel-chair from that PDF into the back-end system; change the grades; and lastly, when finished, ideally, they would even send out an email say, yes, we have changed the grade. Now it's all good. This manual process obviously is kind of a big error-prone, right? Because we are sending around. We get a lot of manual steps in here. It's time consuming. They would even have sometimes maybe grades of a whole class would need to change. So they get 20, 30 of these grade change requests in 1 day, maybe towards the end of the semester, even more kind of a high work volume, right? So we worked with them to automate that piece with RPA. And we actually use the combination from ServiceNow request-driven process where we replaced that portal with a ServiceNow catalog, get into flows and use RPA to update the back-end system. That's a great example to start off with as a request-driven process. And as we do that, some things you can really leverage as we get integrated RPA into ServiceNow. ServiceNow knows about all the environment. We do have a CMDB in place. On that CMDB, you can see the lines here. We have configuration items for all the robots, all the applications that we need to act with for the service that the whole thing runs on. So we know all that environment. One thing we can do, for example, is when there's a change coming in, maybe updating your back-end application, we know that this application is touched by a robot, so we could stop the robot while that upgrade or change is happening and we don't run into some error like connectivity issues and things like that. While as we know that, we can do that kind of thing. Or the other way around. If the RPA robot fails for some reason, something wasn't right, maybe grade was out of -- was too high, too low or something like that, the back-end system gets an error that this can't be saved, we can use that information back in ServiceNow and create an incident for support staff to follow up. You don't need to send an e-mail to somebody say, hey, robot failed, maybe you should look at. We can use, there is no platform to actually do that and connect the different disciplines on the platform. That's one of the big benefits of having RPA as part of your hyperautomation landscape, not as a stand-alone tool. And in that aspect, you can explore the benefits of having that together, right? RPA ServiceNow, as the manager of your robot, does know how many tasks do we have. How many robots do we have? We can talk about the queueing in managing and distributing the world load of different robots. If you have a lot of processes running, you can manage a whole farm of robots. You can also use features on the platform to use other integrations, like we mentioned, IDP for extract information from PDF or using an API integration to do an update on another process so you can really build powerful end-to-end processes in one go. You don't need to kind of hand over to yet another application. Yes, we can also store configuration and credentials information in the platform versus having them on the road. With those things to change, you have potential place that automatically distribute to your robot. And if you look at from the robot execution side of things, the robots run on a Windows machine in new environment, right? They need to remote control the screen. That's why they run in new environment. These robots have access to ServiceNow. They can leverage all these features as mentioned. We can actually offload complex steps into ServiceNow and say, "Hey, you do it for me. And once you're done, give me the answer." So you can leverage these 2 different disciplines, let's say. And lastly, although on the robot side, we have our UI recorder, which helps you to fast out really the integrations and build shells out, something you can actually give out to your business users and they can start building shells or somebody else can follow on. With that, I'll give it over back to Jack for the last part of the best practice.

Perfect. Thanks, Daniel, for walking us through some of those best practices and how RPA, as deployed in a broader digital workflow, is truly powerful in kind of reducing those manual tasks and mundane activities. So let's talk about the fourth best practice and specifically how establishing a centralized framework for monitoring business value and ROI insights for your RPA bots is essential for scalability and continual optimization for your RPA program. So as we talk about briefly with the maturity model, once you're in the run and fly maturity stages, you'll likely have set up an automation center of excellence to manage the growth of incoming automation requests coming in. And as we see today, the average automation COE is faced with this growing backlog of automation projects as automation has become a larger priority for C-suite leaders and organizations in this current economic climate. And so as a result, teams are forced to prioritize among the already prioritized list. So there's challenges there, and ultimately, it leads to slow development overall. Next, we're seeing that there's too many automation tools out there today, which need specialized resourcing for each tool. And as we know, in today's environment, resourcing can be a challenge and not something you can address overnight. And lastly, there's often no connection between automations and the business impact that they're driving. So that makes it difficult to scale up your program and really prove that some of that business impact is being felt, driven by these automations. So with these challenges, there is a an opportunity to create a new automation COE with streamlined and efficient development focused on reuse of automation assets versus creating new automations for every process to accelerate that velocity of your automation journey. And as multiple COEs will continue to exist, you can unify them by providing a single platform for governance and central operations to track the overall life cycle management of your automation. And you control how they are being deployed across various lines of business at your company. And lastly, as touched on, with this new automation COE, you can have continual optimization as you continue to identify new processes as well as have goal tracking as well to monitor and manage how your automations are performing and where you may need to adjust. And so with the Automation Center, we've introduced this as part of Automation Engine last year. And this is a centralized workspace that enables you to really gain complete visibility over your entire hyperautomation landscape and enables you to subscribe to not just ServiceNow automations, but third-party RPA automation data to have really that unified analytics. And that full view of your whole hyperautomation landscape with real-time insights into ROI and goal tracking, you're able to see how you're your RPA automations as well as other vendor automations and see how they're tracking in terms of your business goals and ROI as well. And with that unified view, you can also predict and proactively prevent bot failures and downtime via the CMDB, as Daniel mentioned, as well as a dependency viewer. And so with automation center, you're able to really centralize your visibility of all your automations, how they're performing and really continue to scale automation based on tangible business goals. And so with that, I'm going to pass it off to Aditya, who will share with us a few customer examples of how they're seeing success with their RPA implementations. Over to you, Aditya.

Thank you, Jack. Hello, everyone. In this session, we are going to talk about a couple of customer success stories and their RPA journey with ServiceNow. So the first one is Hancock Whitney. The ServiceNow journey has been pretty interesting as they were able to build and deploy 4 bots in production in span of 3 months. They were also able to eliminate manual repetitive work by deploying RPA bots to integrate with their core banking platform without using any APIs. They had a few business challenges like manual data entry, improving data quality and reducing backlog of requests. So they wanted an innovative solution to resolve these challenges. With the implementation of ServiceNow RPA bot Hancock Whitney was able to minimize the need to scroll through multiple screens for data entry, 30 screens to be precise, which now helps them process 23,000 customer requests per year. What it means is employees can now focus on more value-added and customer-centric activities. The next one here is Inmar Intelligence. Inmar Intelligence is a leading data platform company. As Inmar expands and buys [ new firms ], scaling manual processes had become very expensive. And hence, there was a need to automate these manual processes. With the help of ServiceNow RPA, Inmar build bots to automate traditional custom billing processes such as downloading of EO, entering crucial data into SAP and automatically construct a purchase order in Oracle Ariba, which actually saved them around 1,100 hours per month, an estimated of $2.1 million cost saving per year. Inmar at present has 21 bots in production and new ongoing RPA development and support, which has been built and deployed by 36 citizen developers. So these were a couple of customer success stories, and now we need more of such amazing customer stories from everyone attending the webinar. So now we want to help you all get started with RPA and would love to offer you our enablement support, which includes RPA installation. So with that, our RPA experts will help you install RPA hub and RPA design studio in your [indiscernible] broad environment. Our next offer is development support, where our RPA experts will guide your team on how to build your first automation. And once your bot is ready and tested, our experts would help you deploy your bot in production. With that said, I hope everyone here is excited to build their first automation. Handing it back to Jack. Thank you, everyone.

Great. Thanks so much, Aditya, for walking us through some of those customer examples and how you folks today can leverage the onboarding program to get started with their RPA training. And so as we wrap today's webinar, why don't you remind everyone to submit any questions you might have at any point during this webinar and what we covered via the Q&A panel. And if we didn't answer your question live in our content, we'll make sure to answer them after the webinar. And be sure to access and download the resources over in that Resources Panel at the bottom end of your screen to access some of the resources pertaining to the content that we cover today. So just kind of walking through some of the key takeaways from the content that we discuss today and some of the best practices. The first one is to identify the right process to apply RPA as part of one tool in your overall hyperautomation toolkit. And so it's really important to really evaluate the different processes you have across your organization and which ones are most fit to apply RPA and to automate using RPA bots as well. Next, the second key takeaway there is to build and deploy RPA bots as part of an end-end additional workflow. And so as Daniel will share in some of the use cases we looked at, it's really important to not just deploy RPA as a catch-all automation, but really identify the different systems that are needed and where there may be legacy systems or manual processes that need RPA to fit in. And really having that broader digital workflow is important to achieve end-to-end automation and not just for one portion of your process. And lastly, as Aditya touched on, we have many platform experts here at ServiceNow that can help you kickstart your RPA implementation. We understand that it could be challenging to get started and to figure out when and how to deploy your first bot. So we love to help, and we really recommend to have you leverage some of our platform experts to help you in your journey. And so as we leave today's webinar, here are just a few next steps that you can take as you get started and as you begin to deploy RPA on the ServiceNow platform. And so if you visit that link there, you can access our NOW learning courses, and we have a few dedicated courses for RPA and learning core RPA skills. And so we really recommend you check out some of the courses there and see which ones are helpful for you and your team. Next, visit the Automation and Community Forum. We have a dedicated forum for all things automation engine, and that includes not just RPA Hub, but also our integration solutions and some of our newer capabilities. And so if you want to join in the conversation and ask questions about your processes were any challenges you might run into, feel free to visit that page and start interacting with fellow developers on that forum. And lastly, if you want to learn more about what Aditya shared today with the RPA Hub onboarding program, please visit that link. And one of our sales representatives will be in contact with you to explore ways to get started with that program. And so with that, I just want to say thank you on behalf of all of our speakers today for joining us and for taking the time to just learn more about a few best practices for RPA Hub and specifically, how you can get started and find success with RPA at your company. And so to wrap up, we just have a few slides on Knowledge. So if you weren't able to attend Knowledge this year or if you want to catch up on some of the on-demand content, you can visit that link, where we have over 150 sessions recorded, so you can take a look at some of the exciting content that we talked about at Knowledge, specifically around generative AI and some of the exciting innovations there. So feel free to visit that link as well. And as always, if you want to check out more of our on-demand webinars, you can visit that link provided there to access all the content. And just a friendly reminder, if you could submit the survey after this webinar ends just to see how we did. And if there's any way we can improve, feel free to submit that survey. So with that, thank you very much, and hope you have a great rest of your day.