I am super excited to have this group, together with me today. First, Clark Patterson. Clark, welcome. Clark's the head of product marketing for Snowflake. Snowflake is a technology partner, of Coveo, and super excited to have Clark here as a host, to help bring and introduce, the data perspective to this conversation. So, Clark, welcome. Thanks, Steven. Great to be here. And we have Bruce Buttles, and Eric Emerman. Bruce Buttles is the digital channels director for Humana, and Eric is the practice director for Searching Content and Proficient. And they're gonna walk us through a real life example of how Humana is thinking about their digital customer journey, and how they're thinking about creating more relevant experiences. So Eric, Bruce, Clark, again, pleasure to have you guys, and I'll turn it over to you. Thanks, Davis. Excellent. Thanks for having us. I think, Clark, did you wanna open, with a few words here? Or I'm sorry. Or do you wanna jump right in? Yeah. Yeah. Let me just jump on in. I think, just for for the for the attendees here, I'm sorry about that. You know, we we've got an excellent, presentation here by Bruce and Eric in in terms of, you know, digital transformation at Humana specifically. And, know, as you as you go through the presentation, we encourage you to think about a a a few things. One is, you know, current times and and, as we all are. Right? But, like, how how are we, impacted by current times? How is it changing how we think about our business? And there's a good good conversation that that's gonna come out through that. The second is, like, directly related to that, from a technology standpoint, what is your organization doing to to drive transformation? And, we're gonna talk about the cloud here a little bit and and kind of the role that it plays and and a little bit of a dialogue on that front. But, I know there's a lot of hesitation in a lot of cases to to make the shift to the cloud in particular due to, data sensitivity. So so, you know, think through your your specific situation and what we're gonna learn here. And then, of course, there is as Steven kind of mentioned, like, be engaged. Right? These conversations are made better through an engaged conversation. We are the three of us are gonna interact as we go, but we would love to hear from you as well. What are the questions on top of your mind, that that we can answer and, make this session most impactful for you? So, with that, yeah, Bruce, I'll, I'll pass it over to you. And sorry for the the false start there. No worries at all. You know, I I really just wanted to start the story here with this this kinda quote that I that I share often with my team. It says, you know, changing lives for innovation now more than ever, this has to be our focus. You know, it it's not a surprise that this might resonate with with many of us, especially in light of the coronavirus global pandemic. You know, I I feel like most of us have always made strides to reach and serve our customers, our patients, our constituents, you know, and and but now in the midst of this historic, event, it's really an an evolution in human history that I think we've never experienced, certainly not in, I think, most of our lifetimes. So as I reflected on our journey over the last, you know, six or months or so since COVID set in, what I found is there's really three major driving forces that together are really requiring us and even enabling us to to innovate like never before in history. So I thought I would just share what those three things are that are really triangulating those three forces. So So let me let let's dive in and I'll I'll share a bit on those three, and then and then I'll welcome in Eric in a minute to, join the conversation, and we'll we'll drill down in even more detail. The first force that's really been is this rapid evolution of customer needs. You know, COVID nineteen is changing, the the needs and expectations of our customers from, social isolation to food scarcity, even, you know, limited access to health care, to even just an overwhelming just a general sense of fear. You know, the the health and human services, folks, published a recent article, a study where they said, in July that is, that telehealth has actually increased fifty percent since the pandemic. Think about that. Telehealth has increased by fifty cents fifty percent since the pandemic. Probably not a huge surprise because maybe many of you have actually used telehealth for the first time ever. But I would say, you know, the adoption of telehealth is something that we had on our road map over, like, a three to five year program, and it's almost been ubiquitous overnight. So that's just one kinda key indicator. I don't know if you knew this. I I I included, mason jars there under food scarcity. You may not know this, but there's actually a global shortage of Mason jars right now as more people realize, hey. I better, you know, start canning my food, because I'm not sure, you know, tomorrow if we're gonna have, you know, enough food. So these are all pretty scary things, but all of this combined really has has resulted in the need for innovation. Shall I even say an innovation imperative? You know, I think in our careers, we've all seen oops. Apologize. Let me go back one. We've all seen, you know, a rapid, you know, expansion of customer needs previously, but but not at this pace and certainly not at a global scale. You know, if we're familiar with the idea of kind of swift changes in customer demands, but, however, this time, it's different. I think we all feel that. You know? So so this is the first force that's really happening as consumer needs are evolving very quickly. You know, the second major force driving this hyper demand for innovation, is acting to really supercharge our ability to actually innovate, at now at speeds and scales we've we've we've never seen before. So my guess is you'll be surprised by the second, force, and I wonder if you'd be surprised if I tell you it's actually our federal government. Okay. Before you turn off the t the the screen and you you go back to your business and stuff, stay with me for a second because I need to explain to you why I see the second big force is actually our federal government. Just like the needs have been changing, public policy has been changing very rapidly from executive orders to changes in health and human services policies. We've seen and tracked, changes in the center for Medicare and Medicaid, their policy changes. Even the Social Security Administration is reducing restrictions on things like telemedicine. So, really, you combine all three of those forces together, and it's it's given us the opportunity and really the the need to innovate, you know, at a pace in a in a way we haven't before because some of these restrictions that we had previously are now been lifted. So, specifically, the, the center for Medicare's, actually released a a waiver authorizing under section, eleven thirty five of the Social Security Act to lift geographic and site restrictions allowing telehealth services to be delivered wherever the beneficiary is located. And that that new clause in, section eleven thirty five is what allowed, telemedicine to be adopted much, much more widely. Without that, it wouldn't have. You know, another thing in, that that the Center for Medicare has done is is added one hundred and thirty five new services that are now authorized under telemedicine. A hundred and thirty five new treatment codes, if you will, are now available for health, telehealth, which weren't before. So that's, yeah, another force that's it's allowing and opening up the door to much more digital innovation. You know, I I don't know. Just to put some numbers behind this, about fourteen thousand people typically per week prior to COVID were getting telemedicine care in within the Medicare world. So fourteen thousand per week. Now we're seeing about, you know, globally across the US, that is for all Medicare, about six hundred thousand sessions of telemedicine every week. Think about that. Fourteen thousand to six hundred thousand sessions in telemedicine a week just for Medicare recipients. So I hope you can see now I'm not just bone smoke. The truly, the policy changes have have helped free, you know, innovators like you and I to be able to meet our customers' needs. Alright. So the third one, that I thought I would share and and that I'm seeing is really this rapid adoption of new technological platforms. You know, it's one thing to have needs change is the one another thing to have, know, regulatory changes be lifted and and and change to open up new opportunities for digital innovation, but it's another thing to actually have the platforms to actually deliver in speed. So I thought I would just share really just three key themes that we're seeing, that are, you know, platform wise that's driving our ability to innovate at paces we've never seen before. But it really takes us as leaders and as innovators and digital folks to to adopt the use of these platforms. The first one I'd say under the heading of just kinda automated software engineering. You know, Gartner has a a, study that they released earlier in the summer where they predict by twenty twenty four, sixty five percent of all enterprise wide software development will will be done via some type of low code. Sixty five percent. So I so I you get the positive, well, where are we today? If it's only basically three years from now, how are we gonna get from where we are today to sixty five percent of what we do is automated through things like low Coveo? And the second one, which probably is not a surprise to many of us is cloud computing, is really just this dynamic elasticity to, computing capacity. You know, I I mentioned a minute ago, fourteen thousand sessions a week to six hundred thousand sessions a week. I mean, we've all experienced the, explosion of Zoom and sessions like this. It simply is not possible without the elasticity and expansion and the the the computing capacity capacity of cloud. So that's another, big force that we're adopting at a much, much more rapid pace than I think ever before. And then the last thing I would say is AI machine learning models, is when you when you combine all three of these and top it off with, you know, the cherry on the top of machine learning, again, it gives us this need for innovation, this ability to innovate, to react quickly to our customers' needs. So those so just to kinda recap, you know, the three forces we're really seeing that are coming together, they're triangulating, allowing us to innovate like never before are, you know, the need, the customer demand. It's the second is public policy evolving and changing, frankly, at a pace that I know I I haven't seen in in decades, out of necessity. And then lastly, the thing that's really, you know, supercharging innovation are these three teams here is the rapid adoption of new platforms and technology that automate our software engineering, that give us the computing capacity that we need, and the intelligence and the machine learning, combined together to really, help us, I know at Humana and many companies to meet our customers' need and innovate at the pace of we've never seen before. I have another question, is, before we transition over to Eric here. On the on the rapid evolution of customer needs specifically, can you talk to, like, the data accessibility dynamic that comes to play there? Like, I think of the the the fear dimension in particular, and and part of, over getting over that hurdle is, like, just having information. Right? And and and data at the end of the day. How should people be thinking about factoring that into to part of their innovation and their transformation here? As a matter of fact, one of our major initiatives, the set of data products that I own, is related to search. We would literally in the last, I'd say six weeks or so, have made the strategic shift to almost focus exclusively on data, and and and getting the data aggregate into a place where we can make it, we we call it democratization of the data, liberating the data, making it, open and and accessible to any application that we might have, whether it's, you know, customer service, whether it's a back office, or it's the, you know, the customer themselves through self-service. You know, data is just what we're finding as as we're we're innovating faster and faster in our digital channels and our customer experience, it's the data that is now becoming kind of that that funnel, that limiting factor a bit. So, I couldn't you know, for for us right now, it's becoming probably our number one imperative from an overall solution perspective. Yep. Yeah. Yeah. I think the other interesting thing here on this slide in particular is in addition to dynamic computing capacity that's afforded you when you when you're using the cloud, the same applies for for for storage and data effectively. Right? So there's there's we're only constrained by the limits of the cloud with regards to how much information and data we can get our arms around. And so, you know, I think the the the thing to think about there is, are are we using as much as we can? And are there ways that we could could use, cloud technology specifically to, expand the the universe of accessible data, in our unique, environments. Yeah. Great point. Is there any other questions maybe from the audience or whatnot? Because we're we're gonna start to drill down into our our journey a little bit. I thought I'd pause for a second if there's any other questions or comments. I'm not seeing any in the chat. It's okay. Well, I'll welcome folks again to, you know, feel free to to chime in, and and and jump into the conversation. So, what what I what I wanted to just, as as as, I'm gonna ask Eric to, you know, kinda double double and triple click actually down on some of the details of how we're, using Coveo in in different technologies to to really meet our customers' needs. I wanna tell you our story a little about our journey. You know? So how how do we get to where we are today? So let let me just start by saying, you know, back in twenty eighteen, you see on this diagram here, this is a rough timeline. You know, we had Google Search Appliance, and we have been using it for our enterprise wide search, for, you know, customer facing, internal facing for quite some time. However, in in twenty eighteen, we realized, hey. This is end of life. So Google pulled the plug on that product, and we, you know, had the imperative, we need a new search solution. So, we went to the market. We looked all over, and we did a a bunch of evaluations in in Coveo one, and we, became a customer of theirs officially in twenty nineteen. And we began there in twenty nineteen really just focusing on, you know, basic site search. So we started deploying Coveo to power, you know, the machine learning and the AI that's built into Coveo to power basic site search. So we we set it up to, you know, ingest, if you will, all of our site content from each of our major digital properties. And that was kind of our first step. In twenty twenty, our focus has really, been much more specifically on what we call finder experiences. So, think about health care, finding a doctor. You you may or may not be surprised, but finding a doctor is in the top three most frequented, journey for customers on all of our digital properties. Simply finding a doctor. Top three things that customers do. So, when you when you think about it, you say maybe it's a medical doctor or dentist, maybe it's a a a clinic, it's a hospital, a vision doctor, a pharmacy. So it's a broad scope, and now it's even COVID nineteen. We we're gonna talk about it a bit, but a COVID nineteen testing locator, we built very, very rapidly, to meet that acute need back in April. So these quote finder experiences, I kinda took it to the next level. It's not just website content. It's this is, you know, data content. This is databases and huge, huge data sources of, you know, hundreds and hundreds of thousands of different, health care providers. And then and then going into twenty twenty one, we're gonna it's kind of the the the the final phase to bring the experience full circle is customer service, where we're going to be able to integrate the the search and the find experience all the way into the call center so that, you know, the call center will be seeing the same type of results and searches and have the same type of insights as do our customers, and stitching that all together. So regardless of how our customers interact, they're gonna get the same quality, responses and answers whether asking a call center rep or whether they're doing it themselves online. So it's a quick quick overview of, our journey and how we came to where we are today. Any before we jump over to to Eric, dive into the the details here, do any questions on the journey here? Again, you can enter your questions directly into the chat, or we can ask them live here. Actually there's a couple here. Let's see, he kind of touched on this a little bit, Bruce, but, interested in how search can be implemented for, experts in the enterprise like you know, doctors as opposed to patients, you know. I think we are definitely kind of thinking of this through the lens of the customer, to to a large degree. But but how should, like, other other folks within the organization be thinking about this? Actually, that that is our strategic goal is that it truly becomes the kind of one search to rule them all across the entire enterprise. So, if you know, a little bit about Humana's history, it's it's been very interesting, over, you know, a very, very long time. But in in the most recent three years or so, three or four years, you know, we've been primarily a health insurance company, but, over the last three years, have been pivoting to be a more of a, you know, a health care company with insurance. Whereas before, it was kinda switched. It was an insurance company with a little bit of health care. We're almost at a point now where about half of our staff are clinicians, doctors, nurses, etcetera. So, that is our goal, absolutely, is to is to use the power of that that platform to power the search experience for all audiences even, you know, our own doctors or other doctors and providers. Yep. And I think there's a lot of interesting ways to to think about collaborating on on data, in in in different ways. We see a lot of, companies using our Snowflake platform, for example, that in they are just in different industries and but but they come together on on common types of information because they think that it can augment and solve their problems as well. So so in addition to like the individual roles that are kind of partaking here, it's also like how could I use, you know, data and information that maybe I didn't think I could use before. Could be something like weather perhaps, in in a in a manner that, it could could help me see around the corner like I couldn't do before. So there's a lot of different ways to enable both the individuals, but then also access the information so that they can kinda see their, different trends and patterns. Wonderful. So, when we look at kind of the the overall picture that Bruce just, shared of of kind of that timeline, We're going back now to kind of the initial goals at the beginning of, that were kind of laid out to my team at the beginning of this implementation. Right? First things first, goal above all else was a consistent user experience, customer experience. One of the major challenges that we were looking to try to solve here is, you know, depending on different ways that we talk to the organization, we wanna make sure there aren't different answers that are being provided. Right? If I call customer service, I should get the same answer as if I'm on a a digital, a digital site, or if I'm on an app or I'm on some other sort of way of interacting with the organization. Right? I want to get rid of the information silos accordingly to do that. Right? There can't be numerous different places where information is living that are alone in in holding that information if we're going to have everybody being able to answer kind of consistently across the board. We also wanted to make sure that we were getting a full understanding of how customers were interacting across all touch points. Alright? So, obviously, I might go to the website first. Then if I can't figure it out, I might call the call center or I might look on the finder. We need to know we're losing Bruce again. We need to know all of that. In aiming for that, and I'll share my screen now if we can go this way. In kind of going through that, that process, we're making sure that we are kind of capturing that information through things like Coveo analytics in order to make sure that that we can answer, you know, consistently and and intelligently kind of across all all points throughout the organization, as well as help our content authors make sure that they're understanding what is being asked in what areas. And you'll see a couple of examples of this, but we can kind of make sure that we're actually able to answer the questions that customers have in our content, in our ways that might not require a call center call in the first place. Alright? The next piece is gonna be modern architecture. As Bruce mentioned, it was kind of the Google search appliance. Historically, it's, you know, an on prem device that lived in the data center. Humana is now cloud first. The goal is how do we start using SaaS services? How do we start using auto scaling? How do we stop you know, get out of this cycle of having to manage and scale servers, and instead just have an end web service that can be used for rapidly scaling up new experiences like the finders we're talking about. Now you'll see a couple examples of this in a second. How do we provide a free form customer focused or clinician focused or employee focused search experience where they don't have to know exactly what they're looking for. They just give us a question, and then we'll get them the answer back by doing the hard work on on our end. Right? I mean, how do we unify all of these datasets that that answer can be provided from everywhere and not just the specific zone or area that the user is in? Lastly, focus on outcomes. Right? Leverage feedback loops using things like Coveo analytics. How do we get those feedback loops to make sure that if somebody got a good experience, the next person's gonna have a great experience as well, learning from what that past user did. Right? How do we know how do we use the information we have about the current user to help personalize their experience and give them an individualized answer back for them in a way that's going to solve their problem quicker? Alright? We wanna double the lie down on those delightful user experiences by surprising people with this is exactly the answer for you, as well as make sure that we're giving kind of consistent and rapid touch points at all scenarios. Can you there's a good question here around, information consistency, which I would assume is, like, kind of, you know, governed data, you know, that type of thing. Or, like, like, how do you how should people be thinking about that in the in the context of, of search here? So I think in in the context of search, you're right. That that, you know, there's information consistency is is a broad topic. Right? Where you've got, you know, master data management and information governance and all those various pieces. With search, one of the benefits of the ways that we can attack it is we can start with where the customer already exists. Right? We can we can plug into all of those various information silos even if the information isn't perfectly taxonomized or consistent across the board to begin with, and start providing answers. And, obviously, there's some tuning that needs to be done and some tweaking we'll need to do with the search engine side to make sure we're not giving, you know, conflicting answers to the same question, those sorts of pieces. But one of the benefits we're getting out of the search implementation at Humana is lots and lots of analytics about what questions are people searching for and what answers are they clicking on and how are those answers helping them. Right? What are they going to, and it's and it's solving their problem. They're not coming back and looking for more more, you know, answers to help them solve the problem in the first place. So it's helping drive kind of the efforts on that consistency on the knowledge management side as being almost that I'll call it that, that that North Star for where they're aiming for. Right? We know what our customers are looking for. We know what they're telling us what they need. Where they're saying we can't find something, or the data is saying we can't find something, Now we know where we need to put our efforts to make sure we have a more consistent and managed data experience and a more consistent, or or a more precise answer to solve that user's question. Yep. Awesome. Awesome. There's actually there's a kind of a a related question that I'd love to just gonna answer quickly, which is around, you know, curating content is a challenge for a lot of folks. And how can we take the least effort approach to getting trustworthy data? From a Snowflake standpoint, we solve this through the notion of a marketplace. And so the idea is is, you know, it's like an app store or iTunes store for data effectively, and we'll evolve it over time to be, like, data services as well. And the idea is, you know, you as an owner of data can can build a trustworthy data set and and the insight that you believe is a value to, you know, your internal stakeholders or perhaps people outside your organization, and the marketplace is that vehicle by which we can expose it. And so the discovery process gets dramatically simplified when, you know, you as a consumer can go out and actually see, what's what's accessible to you and go in very rapidly, enable and engage on that data. But then as a provider of information, it it speaks to a lot of the things that that Eric just mentioned, which is you have great visibility and control into, like, what's actually being used and in what ways, where are the gaps, and how can you tweak and tune moving forward. Absolutely. Absolutely. So if we jump into see if I can move our slides. Some of the actual implementations and some of the results we'll have. And, Bruce, I I think I've seen you speaking, but you've been muted. Are you back? Hey. I see your mouth booming, but I don't hear sound. So I'll I'll go it alone for a second, but if you jump back, feel free to jump in. So first thing that we we did, or the first implementation is or set of implementations, as Bruce mentioned, was really just site search, digital websites. Right? So this was, at the time, kind of, I'm gonna call it a a replacement for the Google Search Appliance. Right? That it was powering digital site search. So Humana has a wide variety of properties, and we started with really four main ones to start. Alright? We started with providing site search, so website results back on humana dot com on, you know, CarePlus and Humana Military and MyHumana, right, which is the internal member portal. But it wasn't just site results. It was also, doing things like using the existing q and a, sections of the website, or the q and a, kind of answer pairs that that existed within the organization to provide direct feedback or direct question answers for end members or end customers who are looking into Manus properties. Alright? These questions weren't as simple as just you ask this question, here's the answer. There's branching questions. Right? You ask this question, give me some context about yourself if you're an anonymous user. Are you coming for on an employer plan? Are you you coming for Medicare? Are you looking at these variety of things? And we have the ability to kind of help customers branch down into the answer so that they're getting a direct response and not purely just a list of ten blue links. Instead, it's kind of here's the result for your your question in the first place. Alright? Now in doing this, we went you used Coveo and we, you know, went live in kind of an iterative approach, a pretty standard way that you're implementing Coveo. Right? We first rolled it out to the sites into iteratively, and this is an example from Humana dot com. Right? Where we first rolled it out, and there wasn't a lot of data and machine learning yet. So we kind of did some initial tuning, rolled it out, and then kind of started doing some, you know, manual tuning by hand as the machine learning models kind of gathered really robust set of data. Right? So some examples from this. First thing I learned, you know, I'm not from a purely health care, perspective myself, but the first thing I learned is that no one knows how to spell HIPAA. Right? Everybody goes h I p p a not h I p a a. Put it simply doing something simple like putting a synonym in there helped a huge amount of the content gaps that users were seeing because there was a a very simple way to kind of fix that. Same thing happened when kind of COVID hit, where it was COVID dash nineteen, COVID nineteen, coronavirus. There are many different ways things are being referred to. Doing little tuning tweaks like that allowed us to kind of bump that just click through rate from, you know, fifty percent to about sixty percent manually pretty quickly. Then we enabled the machine learning. Right? We enabled advanced relevancy tuning or automatic relevance tuning. We enabled query suggestions. And in about three day process of of enabling that from it being enabled to actually watching result, we were up to about a ninety five percent click rate click through rate on search results for humana dot com. Alright? So ninety five percent of the time somebody searches for something, they find a result and go there. So this is really kind of where we kind of started to start seeing the value of this and where kind of I think that conversation started kicking off throughout Humana saying, hey. Look. We're getting some great results here. Where else can this can this be used? Right? This started as a Google Search Appliance project. Right? We're simply replacing site search. Now we have this corpus of data that is being found very, very easily. How do we expand that out into other areas of the organization as well? Right? Another success result here is when, you know, we actually kind of got into, I'm gonna call it the the COVID pandemic. Right? In late February, early March of this year. Questions that were coming back to digital leaders like Bruce and his teams, from the c suite, from the executives where we need information. Right? Obviously, there's a lot of fear out there. There's a lot that's going on. How do we actually get information that's gonna help us solve this problem, and solve our members' problems more quickly? So one of the first sources that was used to help with this and help make those decisions was a system like Coveo, where we brought a put an analytics dashboard together that was searching for specific terms or specific topics. And it's able to start saying, here's what customers are actually coming to your website and looking for. Right? Here's the volume of customers that are coming in. Here it is broken down by state. Here's the what we're providing answers to or what we're not providing answers to. You know, free face masks you'll see on here as a top one. I just know just from talking to Bruce, you know, you'd be surprised. Humana's given out, I think, over fifty million free face masks at this point, kind of across the board. It's one of those kind of big things that's happening as, you know, a health care, you know, company in order to make sure that they're assisting their their, members, assisting their their constituents with providing services in order to to help meet the needs of a very kinda clearly, unprecedented pandemic that's really affecting the industry in a in huge ways. On on that topic, there's some can you just tell about the Coveo analytics specifically and just kind of, like, monitoring it as the term I'm gonna use? But, there's a lot of information obviously coming through at any given time. What is kind of the best best, approach strategy in terms of, like, keeping on top of, the the data as it's it's flowing through? It's an excellent question. So I think the the first there's multiple strategies that have been in use here. And we've been supported, on the Humana and the Perficient side by by, you know, customer success managers from Coveo who are working with the company to kind of help answer that question. But the first thing that that we're really doing is making sure that we have a a baseline set of of, you know, reporting and dashboards and informational areas that, we're essentially able to give just an overview that allowed enough drill down to kind of make it useful. Right? Where there are specific areas of interest or topic areas that come up or new applications that we wanna focus on. Right? Then we can spin up additional kind of, I'm gonna call it point in data sort of dashboards or point in data sort of visualizations to drill into those specific areas. And then the after that, it's more of almost a process loop or a process feedback loop of, okay, we have all this information now. How do we rally the appropriate content teams, the appropriate knowledge managers, the appropriate folks internally to kind of, you know, revise the content that's on the site or to kind of, respond to these needs? And that's through things like, you know, manual tuning through Coveo, which through the back end content systems or web page authors that are being created. And it really ends up being this feedback loop that's not only you know, we talked about feedback loops before is Coveo to customer. Right? And how do we use that to gather the data and kind of automatically respond? But there's also feedback loops of the data to internal process and internal organization to proper appropriately kind of make sure that the best content is out there and we're solving needs in terms of what exists in the first place. Awesome. Yeah. You know, that's can you all hear me now? We can hear you now. Oh, thank goodness. Exciting. So, Diane, I was like, oh, wait. I wanna add some stuff. Oh, great. So you're getting you kinda touched on it a little bit earlier. I think this goes back to the whole idea. Eric, you remember this. Some of the challenges we found was just simply identifying, well, who is the data owner organizationally? Who owns the data? That was one of the epiphanies I had as you know, I we went we leaned into this and did various efforts and whether it be website content, who owns it, whether it be, you know, data about providers and medical doctors and whatnot, who owns it, or vision doctors who owns it. I just assumed that that was very clear thing and then it was gonna be easy. It wasn't always easy, you know, to to determine, well, who who owns it? Forget about digital. Who owns this information, period? So I I can't stress that enough as as you start to venture into these things, you think about data quality and consistency and whatnot, is is be very intentional up front as early as possible to identify those key stakeholders that, own actually own the content that you're going to be searching. And there's a Monica asked a question about liability a few minutes back. Is that ownership carrying the liability dimension as well? Yeah. And and if it's, it could be a co ownership, but, without a doubt. I mean, much of what we we have on our websites have to be, and and mobile apps, etcetera, have to be passed and approved by the Center for Medicare and Medicaid. So, from a legal compliance perspective, we're one hundred percent. Excellent. Okay. Now jumping along the digital journey, timeline a bit more, we're now jumping over to the finder experience, which has really been a lot of the effort for this year. So finder experiences, Bruce kind of gave a high level overview before, is essentially an experience that we're building that is locationally aware, right, and helping you to find something in the real world near you. In Humana's case, there's about five different things we're looking to find now. Right? There's, doctors' providers. There's dental providers. There are, pharmacies. There are optometrists or vision providers, and there are COVID test sites, which is a recent one we'll talk about in a second. Alright? Right now those tools, or previously those tools at Humana kind of they were limited a little bit by technology in a way. Right? You had a whole wizard you had to go through in order to to search for a provider by, you know, putting in your zip code, putting in, you know, specifically what plan you were on. And you can only see a very, I'm gonna call it, limited subset of the overall data, just due to kind of technological limitations across querying across millions of providers potentially, right, in a a very large geographic space. What we're looking to do with this new experience is, a, is going to be limit you know, expanding out the capabilities of what can be done and how easy you can interact with the data. Right? So show up at the site, we'll pull your location and automatically show all the providers around you without you entering a thing in the first place. Right? You don't have to enter a network. You don't have to enter a location. It'll just it'll know it. Right? Then if you wanna change it, drag around. Search around in a different area. You're gonna be moving. You're going down vacation. You wanna see who's available. Where else? Go for it. Just drag up and now you see those, providers or pharmacies or, you know, whatever you've got, in that area. Now if you have a network you can put that in and now start seeing more information about those various entities. Right? What services are there? Are they covered by my insurance? Are they in network, out of network? You know, what sort of capabilities, does this provider provide? As well as what are their hours? How do I, you know, get navigational directions to them via Google Maps or similar. Right? As well as, you know, is there a way that I can directly interact with that provider, as we'll see in kind of the COVID test site, scenario? So this was stood up, and and the initial, if we go to the technical slightly of it. Right? The initial digital experiences were all done with the Coveo JS UI. It's a framework provided by Coveo that allowed us for to rapidly implement this by essentially implementing one interface and then bringing it across the variety of different sites with just some minor theming differences between them. Right? Some CSS, but that was a huge benefit to us because it means that there's really one major accessibility pass, which is critical in health care. Everything has to be very accessible for all end users. Right? You know, one major kind of development cycle, and then the integration are kind of a minor effort that lets us kind of bring it in everywhere in a much, you know, a much more rapid way. Right? On the finder side, this is where we get back to Bruce's original, comment about low code. Right? Here, we're using, a platform called OutSystems as as an underpinning for for this, which is a low code environment that loves to use REST APIs. As such, we plug directly into Coveo's REST APIs that are available, and built a series of components of, you know, low code components that can be dragged and dropped and added to the page to develop a very, very, you know, capable experience, in a relatively short amount of time. Right? And so we've got the pharmacy experience that was up and ready earlier this year. And then shortly after the pharmacy experience went live, is when COVID kind of started up. Alright? So if we look at this COVID test site finder, you'll notice it looks very similar to the pharmacy finder. It's because we're able to reuse the same components. We're able to reuse that low code environment. And just some kind of examples about this, you know, within about twenty four hours after Bruce frees out to myself and my team, we had initial data in Coveo, you know, for developers to start working with to build out this experience. The total site to go live to production was under four weeks. Right? Which if we look at the development of kind of large, you know, have to be accessibility tested, you know, production websites at at Humana, that's a incredibly short amount of time, to kind of get a brand new capability available for everyone. And since then, it's been continuously improved. And, Bruce, do you wanna talk about some of those changes that have have happened, improvements that have happened? I I will. And and, you know, I know you touched that briefly, but I think it bears repeating. So literally, in twenty four hours, we had the application that what, you know, what contained all the COVID nineteen testing data, integrated with Coveo. So Coveo was able to ingest, using the APIs that we exposed from the back office system, in really less than twenty four hours. We were exchanging the data and it was being pumped in to Coveo. I think that it goes to the I see one of the questions there about team size, and then I'll talk to you about some of the features we're adding. So team size, I think it's more about, kind of we we look at it as two separate worlds. One is just the application development. You know? So as we built the front end for, you know, COVID nineteen pharmacy finder, etcetera, Think of that as kind of a traditional scrum team, development team. So whatever that size would be at your company, you probably expect the same thing. The differences here is that the the Coveo APIs allow you to integrate very, very quickly. So you'll need some expertise there. Maybe that's, you know, somebody like an Eric to help guide, you know, the best implementation of the utilization and patterns for using those APIs. And then the other side of the coin though is the the more the digital business operations. And there right now, while we're searching, you see kind of all of our various websites. We've got the different finders. And really, we have a small set of folks, maybe three or so, that, have access to the Kavayo back end. They look at the analytics, they analyze the trends, they do the reporting, they pull out those insights like what are people looking for and what can they not find. You know, those types of things, helping to tweak the machine learning models as needed. It's really probably what would you say, Eric? Maybe three people or so that Yeah. Go in time. But, you know, they'll go in periodically, maybe a few times a week, that sort of thing. And some of the unique features for COVID that's been really a pleasure to be able to adapt quickly to are things like, when we started this, we didn't realize that, there are gonna be different types of COVID-nineteen tests. The term antibody tests back in April wasn't a thing. So, you know, we were able to once as the world evolved and the situation evolved, we, you know, capture the data and we're able to present it and and ingest it in the search engine very quickly. Literally, some of some of these things were, like, on a same day turnaround, a twenty four hour turnaround, a two day turnaround on some of these features. Perfect. And then I know, Bruce, you've done a lot of work with the team recently about integrating with the bot framework and integrating the ability to reach out to providers directly. You wanna talk about that a little bit and how it's kind of built off of the finder experience to build it kind of into a more I'm gonna call it integrated holistic, you know, user focused sort of experience from from a to b, you know, a to z, end of end of the spectrum. Yeah. That's a great point too. So, again, it goes to the whole, the the need the need for us all to be, like, what I call hyper agile these days is, you know, when when COVID started, end of March, we said, hey. We gotta do some things. So me and a few other volunteers said, we're gonna help out. What what do we need? And that's when we realized we needed a testing locator like this. So we started building it. Over the course of a weekend, we built the very first kind of minimal viable product just for our call center. But, you know, quickly, well, as it evolved so we we were one of the first applications to go live in this whole suite of, COVID nineteen programs that Humana now has made a priority, things like masks and, you know, food delivery and all sorts of things, apps like this. Well, one of the other things is it was being built in parallel just behind COVID nineteen was a health bot that, it was a symptom checker that launched, I think it was like in early May, a symptom checker bot that would walk you through the process of process of determining, do I need a test, do I not need a test? And then kinda, on the on the far end of the experience was a sign up form. Like, I wanna be able to sign up for test, get an appointment, and then go in and get a test. Well, it was pretty cool. We were able to actually stitch it all together, all three components. The the help bot that checks your symptoms, finding a testing location, and then lastly, signing up. We were actually stitched all three of those together very quickly, to be able to really complete the full experience. And, you know, who knows what's next? I mean, some of what we're talking about next is, you probably won't be surprised, but what about vaccines? Soon as vaccines come out, people are gonna be asking, hey, where can I get a vaccine? And what type of vaccine is it? Do I need an appointment? Should I get a vaccine? See what I'm saying? So between the health bot, the locator, the sign up, we're gonna be able to quickly evolve to not just finding a testing location, but next I believe it's going to be finding a vaccine. Absolutely. Awesome. Alright. So then continuing forward, and work's already started on this, but, you know, we'll probably be going live with it in the, the not terribly distant future. But that's going to be as as kind of Bruce brought up before, is customer service experiences. Right? Integrating with, you know, agents' native environments in a platform like Salesforce. Right? Where, you might have an agent focused around, you know, retail, that are interacting with chat, yeah, users. Right? But you might have a similar agent that's working or interacting with phone users. You might have somebody in Medi who's focused on Medicare. We're talking, you know, large numbers of of call center agents here, tens of thousands of people, that are spend all day every day interacting with, Humanis customers and Humanis members in terms of making sure that they're getting the right answers, the right the best experience at all times so that they can have a frictionless health care experience kind of across the board. Right? A big part of this is making sure that we're able to help those agents get answers quickly. Right? As we talked about content silos before. Right? You know, they what we're trying to get away from is, you know, you ask a question, to to an agent on the phone, and they have five different systems they need to look at. Right? Or a very complex scenario they need to look at. How do I now take that information from all five systems at once and put it right in the agent's view inside Salesforce, so their application that they're using, to allow them to actually, you know, get a curated answer immediately? Then how do I go step beyond that and use the machine learning that Coveo is providing and and the AI capabilities to look at what answers have solved members' problems in the past and make sure that the right answer is getting at the top every time. If you can do that, there are a whole variety of different, benefits that come out of it. Everything from reduced average handle to handle time. Right? Reduced amount of time that that, members are on the phone waiting to get their their problem solved. Right? You get, higher number of first issue resolutions. Right? First time we call, we give the right answer because we've learned to know what the right answer is looking at past experiences for very similar cases. This has been the right answer. Right? You get an easier ability to train, up new call center agents and to have a higher quality, of answer coming from newer call center agents because you don't have the same amount of, I'm gonna call it, onus put on that agent to know exactly what system to look in and what area and all of the steps of processes that can possibly go through for a question. The system is absorbing some of that and able to kind of start providing those answers back more quickly. And because of that, there's some huge benefits to be gained here. Now all of the stuff that we've done previously, the digital sites, the finder experiences, that can roll into this as well. Right? So if you have a finder experience on the website, the agent in their console can have the same finder experience or maybe something that's slightly modified for the way they search or to give them a couple additional options that lets them see that information and give you a link directly back to your finder experience and make this a bit more of an interactive process. Right? They're able to go and potentially see what customers have done previously. You know, I see you've been searching for, you know, eligibility for diabetes screenings. Right? Is you know, you've looked at these five documents. Here's one you haven't looked at that I think is actually what's going to satisfy your your need, and here's a link to it so that you can hopefully go and kind of get your problem solved as quickly as possible. Right? So we're we're doing this not only in that, I'm gonna call it the the customer centric world, but also in clinical. As Bruce mentioned, Humana's had a a huge pivot in the past few, past few months for a few years on on moving towards more of a health care first company as opposed to an insurance first company. There is a large new initiative around just purely clinical and having clinical call centers that are are there to help the, you know, the doctors, the nurses, the clinical workers, and, you know, provide a back line support to them as well. And the same technology is going to be integrated there to kind of help support those that user base as well. And then finally, pharmacy. Right? You know, as as Humana has a a mail you know, online pharmacy, mail order pharmacy business, How do we support those customers who are coming in through a retail sort of channel as well or something similar to it in order to help solve their problems potentially with a whole different class of use cases. Right? Ordering challenges, payment challenges, so on, but have the same technological backing so that if there is a a question they ask that happens to be about some other area of the organization, the information is still there, and we can make sure it's getting put put in front of those, agents, in front of those members immediately as quickly as possible. Alright? Bruce, any other comments, thoughts there? Just one thing that I personally am super excited about, that last bullet there on pharmacy. The reason why is because I for the better part of this year, I've spent probably seventy percent of my energy, leading the digital transformation for our Humana Pharmacy ecommerce business. Yeah, if you if you don't know this, but Humana Pharmacy is is one of our divisions, and it's a full fledged online digital pharmacy. And, you know, it's it's purely digital in mail order, with with a few brick and mortar, but it's really all all digital. But the point being is that we're we're rolling out a whole new, ecommerce platform, and one of our main goals is to start to surface in the natural search experience for customers, for call center reps, for clinicians, if you're doing a search where it's relevant to be able to actually pull in things like over the counter medications, pharmaceutical products that we offer, etcetera. So that while you're searching for something, that maybe there's a tendential, almost like Google does, is the vision is, you know, Google will maybe pop up ads that are somewhat relevant to what you're looking for. Well, imagine the same types of things where you're getting the search results, that you're looking for, but, oh, by the way, we may suggest you know, vitamin e or that sort of thing because it's it's relevant. And and and while if you stop for a minute and start thinking about all of this data, all of it being aggregated into a singular search engine, you know, one of the things that I knew we would run into quickly was this desire to mix and match information, is to be able to kinda segregate when we wanna segregate certain types of content in context versus making it more expansive. So if you look at these four boxes, there's cases where we really only wanna serve up clinical. We really only wanna serve up website information. We really only wanna serve up pharmaceutical information, etcetera. And there's other cases where it's a mix and match, where it's a little bit of website content, some clinical, and maybe some Medicare information that we want to be in the domain of this context. So that's a really unique perspective to be able to very quickly, adapt and pull in the information that's relevant for the context and not always have it be, like, just Google. You know. So we can we can very much tailor, the domains that we select that information from based on what the customer is is doing. And, Bruce, just to to add on to that, it should also be noted just as a not as an afterthought, but as a core piece of this. All of the data that's being indexed here is also secured if it's secured in the source system as well. Right? So we can feel comfortable about mixing those domains together and not have not accidentally, you know, sharing data that shouldn't be seen by somebody, with them in search results because they're going to get back the exact same search results as they would get in the original system where that data lives. Know, some of this information is public. Everybody can see it. Others could be, you know, internal. It might be about a specific patient, for example, or about a specific customer, etcetera. All of that needs to be, you know, fundamentally secure. So we're on, you know, Coveo's HIPAA cloud where everything is security first here. But because we have that underpinnings, it gives us flexibility in in how we can share because we can trust that, okay, where security is handled, now what ability do we have here to kind of mix and match and share as well? Yes. We got about six minutes to go here. I think there's probably just a little bit of a is this, do you have any kind of wrap on the slides here, Eric? Or did you wanna just kinda go and kinda get the rest of the questions that we've got up here? I I think that's I think that's the slides. I think we're at the, let's go to the go to the chat and go to the, you know, general roundtable conversation. Okay. There's there's so kind of there's a question around like, journey. So like when you think about all of the opportunities, and you talked about this a little bit Bruce in terms of, vaccines, like it's kind of an obvious choice, Right? Like, we need to stand up some services to support, that that need. But but generally speaking, how do you think about, like, the the journey to to develop the, you know, the the total platform for Humana over time and prioritize all the different options that are available to you and, you know, pick pick one choice or another near term and, you know, strategically implement others down the line. Thanks for that. Yeah. And I I would say that, you know, times have changed, but, fundamentally, the yeah. The fundamental still remains. So things like just having a good business strategy, having a good digital strategy. Now I I would emphasize guide. You know, it's our vision. It's our it's our this is where we believe we need to be heading. But what we found is that I I keep using this phrase is like right sizing our efforts in real time. So right size in real time because we we need to make sure that while we have our strategies and we have our vision, we we know where we we want to go and we believe we need to go, we also need to be much more open to that today to being responsive to those, needs that are just simply net new that no one could have foreseen. So, I think that's one of the biggest changes is is us kind of responding in real time and kind of not not being reactive, I would say, using our strategy, but at the same time, you know, adjusting our processes, a little more real time to adapt to the entirety of the challenge that we may be facing at the moment. Yep. And I think it Coveo back to that hyper agility comment you made earlier too is when when we're in that mindset, we can kind of, you know, try different things in a really rapid fashion. I think the, you know, the fact that this is all in the cloud really gives us a lot of opportunity to try things without a massive, you know, effort and expenditure and everything else that would have come with with traditional legacy systems. Right? So, there's definitely a bunch of dynamics at play there. There was there's this question, around, like, buyer side of Humana. So we've talked obviously a lot about kind of the the the customer experience side of things. Are there some things that you're doing, like, similar kind of trades here that that are happening kind of on the bar buyer side that, you could touch on really quickly? Yeah. I'm more on the b b. So, I mean, just a just a little bit of context on Humana side. So the majority of our customers are kinda re quote retail. So Medicare. So those are individuals that are retired. They're coming to us. They may or may not be part of a group. We do have employer groups as well to your point, in current side, but also in our wellness business, go three sixty five, dot com. But, so, yeah, we we absolutely do. So that comes more in the shape of, from a buy side perspective, you know, content and materials that help folks understand, you know, buyers, employers specifically, understand our offering. But, you know, like, you know, help them get into the funnel. We're doing more in this way of local search as well, like, localized search, getting content and information out into even things like, you know, various, you know, Google Places, etcetera. But but also is is, the back office for employers. So not just you know, once we sell an employer group is what is their administrative experience? How do we make it easy for employers to manage, their plans and their employees, in the back office, as well as not just always assume that, oh, they're gonna just log in to our website. Sometimes we may need to log in to or or integrate with their platforms, if if if they so need it. So it's, you you can't always assume that I I kinda joke and I say, don't let's not be so myopic to believe that everyone is always gonna come to Humana dot com. They they may not. You know, we may need to get our experience and our content and our capabilities out into their ecosystems instead. Yep. Excellent. Well, I think that, that brings us to time. So, you know, Eric, Bruce, this is great great content. Thanks everybody for joining the session. Lots of great questions out there. Thanks for helping, us keep it engaged and and, hopefully, we did an effective job of giving you some things to think about, you know, answering specific questions that you had and, you know, you walk away from the session today with some great ideas of how you can start to drive innovation, with, within your organization. So then I'm gonna pass it back over to Steven. Any any parting thoughts here as we kinda transition out of the session and on to the next? Yeah. Thanks to all three of you. Thanks, Bruce, battling the tropical storm in in Charlotte. So appreciate the the continuity, Eric, that you're able to to continue as as Bruce navigated that. Clark, again, appreciate, your efforts to host and to guide the conversation. And for everyone that's jumped into the session as well, appreciates, your time, your engagement, the questions that you've asked. And, again, this session will be recorded. It will be shared with everyone that, is in attendance. If you join maybe a little bit late, and only caught a portion of it, we'll share that that full presentation with you. But again, to Eric, to Bruce, thank you for telling the Humana story. Truly a a very interesting one with all the dimensions, that you discussed. And, Clark, again, thank you for for hosting and sharing your unique perspectives, from Snowflake as it relates to g and, data cloud. So thanks to everyone.