April 8, 2020

Episode 10: Alexis Paul & Kerry Wang of Humana

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Description

On this episode of The Handoff, Dan speaks with Alexis Paul and Kerry Wang of Humana’s Intelligent Automation Center of Excellence. They shared the inspiration behind the center of excellence, as well as its mission to reduce complexity and make life easier for Humana’s 45,000 associates and more than 14 million members.

Alexis and Kerry talked about Humana’s realization that its associate experience lagged behind its member experience, and how that has guided the team is looking for ways to automate repeatable, mundane tasks like refilling prescriptions. They shared how they involve members and associates in their process, as well as Humana’s “citizen developer effort,” which allows associates to define and build their own automation processes.



Podcast

Transcript

Kerry:
Thank you.

Alexis:
Thank you. Glad to be here today.

Dan:
So Kerry, we'll start with you. I would love to hear about your background and what got you into starting Humana's Intelligent Automation Center of Excellence.

Kerry:
Great, thanks. Yeah, my name's Kerry Wang. I've been at Humana a little over 17 years, almost 17 and a half years. About three years ago, maybe three and a half years ago, I was tapped to start the Intelligent Automation Center of Excellence, primarily because we'd been doing automation here, specifically robotic process automation, desktop automation, for over 15 years already. But it was really isolated. It was isolated to specific business areas, and we really felt like intelligent automation combined with RPA, so machine learning plus RPA, was really going to be a transformative capability for us. We really wanted to focus it and scale it across the enterprise.

Kerry:
So they asked me to start the Intelligent Automation Center of Excellence a couple years ago, in order to really get good at it and to build that competency, in order to build it across the enterprise to really be able to change the experience of our associates and get rid of some of the mundane work that we've been doing over the past years and years and years. More recently, the Intelligent Automation COE has moved to Alexis Paul, and I got moved on to work in digital human resources, really focusing on the overall strategy, how we are approaching digital, and creating better associate experiences so that those associates can then create better member experiences.

Dan:
Awesome. Thanks Kerry. Great background and very interesting work. And you handed it over to Alexis. So Alexis, we'd love to hear kind of how you picked this up and what you're doing with it now, and some of your background as well.

Alexis:
I have been in data and analytics for the last 15 years with a focus in healthcare in the last 10, and more specifically at Humana for the last five. And throughout my career a lot of what I've been trying to do is figuring out how you can find the right data to solve problems that are affecting different parts of the business. And when it comes to automation, a lot of automation is really a data problem. Is the data in the correct systems? Is it where we need it to be able to make decisions? How hard is it to get to it? As we are looking to mature the processes that were established at Humana, I was tapped to come over and lead and bring the advanced analytics, AI, ML components, and really scale and mature them across the organization so we could figure out a harder set of tasks that we can tackle to help clinicians, operators, agents, and associates across our organization.

Dan:
Before we dive in to the awesome work and some use cases that you all are doing at Humana, I would love to understand a little bit more about how you define automation. I think when I've talked to people about automation, they automatically go to people eliminating jobs, which is like the extreme, to robots in hospitals, to bots that are automating some of the mundane processes. It kind of runs the gamut. So I would love ... And maybe, Kerry, you can take this one on first. How do you define automation from the perspective of Humana?

Kerry:
I think automation is all those things that you talked about, and we approach it across all those spectrums. So automation is this huge catchphrase and companies have been doing automation forever and a half, including us. We really look at automation as what is something that's painful that a machine can do for you. Be it those digital assistants that we utilize today, Siri or Alexa or whatever your preferred platform is, that's automation to us.

Kerry:
We look at utilizing that and how we can deliver healthcare differently in order to allow members to speak through Siri or Alexa and give us information. We're doing proof of concepts from that all the way through robotic process automation, which is a part of the Intelligent Automation Center of Excellence. Really attacking those repeatable, mundane tasks. So automation is all those things to us. We really look at it as what can we utilize with a machine to do repeatedly, consistently well, and how can we use those machines to reduce the complexity and pain that our member or associate has to go through.

Dan:
Alexis, I'm interested, there are some levels of automation that I've heard as well, including unattended automation, attended, and then intelligent automation. Can you help differentiate some of those terms that have been used in referencing automation?

Alexis:
Yeah, absolutely. I think actually touching on this as an important part of telling the automation story and demystifying what it is, what it isn't, and how it can help us. I'll talk about it in terms of how we approach it from a maturity perspective. Attended automation is really the types of tasks that can be done in terms of ... I have a personal productivity assistant, right? We've been doing automation in corporate America forever. If you've ever used a keyboard and a shortcut key that's control C instead of going to copy, or control V instead of going to paste, and finding those mouse clicks, you yourself have found ways to take a shortcut and make things a little bit faster. So within robotic process automation we think of attended automation as a set of tasks that you as a user or associate can kick off yourself to help you speed through a couple of those really mundane, repetitive type tasks.

Alexis:
Unattended automation is something that doesn't require me as a traditional worker to kick off. It's something that can be scheduled or triggered by a set of actions or events that are happening in the background. What that means is if every day part of my job is to go in and open up a fax queue to see how many different faxes we've received and route them over to the different people to handle, a bot can be scheduled to, say, open up the fax queue, identify if it's something related to claims denial to go to this person. If it's something related to reviewing clinical notes going over to this person. And so unattended is the set of tasks that we can do based on some sort of a schedule or a predefined set of rules that it's going to happen if this happens, and we don't have to worry about having somebody kick it off.

Alexis:
Cognitive is really a combination of the two and it allows us to really ... If you think about attended and unattended automation as being digital workers, there are skills that used to be performed by a traditional worker that now can be performed by your digital personal assistant. Cognitive is upskilling. So if before it was copy/paste, if it was data validation, if it was opening up four applications simultaneously so you didn't have to click through and go through to those, what cognitive allows us to do is increase the diversity of tasks that are able to be done.

Alexis:
So that means reading that faxed document to look for some pieces of information that say how to route that document to the correct queue. It means reading a prescription that's coming in and being able to match it to the standard formulary language in our pharmacy systems so that we know how to fulfill that prescription faster, without having to have a pharmacy tech or pharmacist open up the document and read it. So cognitive is really the evolution. If you think about it in terms of my first bot might be straight out of high school or straight out of college and on the job training, you're going to increase the kind of things that they're able to do.

Dan:
Does the cognitive one actually create like a super power for the workers? Is it enhancing the work that a human is doing, or is it more about learning itself, learning and evolving and getting better as a machine?

Alexis:
Yeah, there's really both components. So the first one is what we would really consider sort of that human-centered design or human-in-the-loop. How do we take five different types of documents, highlight across them using computer vision and natural language processing, pulling up the relevant information for a clinical case worker and saying, "Okay, here's five 10-page documents. We're highlighting all of the words that might make sense to you, presenting them to you, and allowing you to then enter over your case notes or make a determination on what next step you need to take in a process."

Alexis:
So it's automation in terms of speeding up information delivery. It's cognitive because it's finding interesting things, but it's bringing it back to that clinician or that associate to say, "You're the person who knows the best about this. Make the best decision how to go forward."

Alexis:
Over time, however ... And I will be totally honest, this is part of the maturity curve with cognitive. Over time, we hope to be able to say not only are we speeding up the information delivery and giving it to you so that you can make a decision, but we might also present to you a set of typical actions that are taken. So think about this kind of like what happens with Netflix, in the early days of Netflix, where there was a recommendations engine in the back that says, "You watched this, we think you might like something like this."

Alexis:
Well, you're not necessarily going to get that easy of a case determination in healthcare, but it might say, "The last five times we looked at a claim like this that was denied, we actually went on to go ahead and pay it. So let's just automatically pay it and put that good value and experience back in the member's hands."

Dan:
Got it. No, that's a great distinction there. It sounds like you have a really great vision for where you want to go and the work that you're doing. So, Kerry, I would love to understand what the inspiration was behind the Center of Excellence. Not many healthcare organizations, I don't think, have a Center of Excellence for Automation. So what speared that?

Kerry:
Really what speared it for us was that we believe that the member experience really cannot exceed the associate experience. And as we look at so much of our investments over the last five or 10 years, we were so much focused on the member and really looking at their experiences, and looking how to digitize them and make it better and better, to meet them when they want.

Kerry:
When we took a step back and looked at the experience our associates themselves were having with the tools that enabled them to help the member, we weren't exactly thrilled with ourselves. So we really felt that we needed to, we had to invest in and really be conscious of the associate experience, and invest in things to digitize their experience to help them. To help make their day easier, to help their tasks that they have to do every day a bit easier so that they can deliver better and better service to our members.

Dan:
In my previous experience at a large healthcare organization, I think some of the associates in the member services department had to open something like 17 applications in order to answer one question about benefits or care or whatever the question was. And it seemed to me, not being in that space, being more of a clinician, it just seems incredibly inefficient to have to open that many applications to actually answer just one simple, "Does this cover this?" So it seems like a great use case. Alexis, what are some of the innovations that are coming out of that center now as you're ramping it up and getting more intuitive to where automation can help the company?

Alexis:
There's a couple of ways that I would describe this. The first is that we're really continuing to scale and expand on where RPA can bridge technologies. So what you just described is the fact that many healthcare organizations are large, they've grown large through acquisition or through partnerships, and healthcare in and of itself requires many disparate relationships between provider, member, and healthcare entity. Whether it's member/patient that you're using to describe that middle term.

Alexis:
And so we're looking at how can RPA streamline that experience for the patient, for the member, but also for the associates. You're not opening up 17 screens. You might have a bot that's working in the background that is pulling up, as soon as the member is on the phone, some information to verify that it is the member. If they're calling about a prescription, here are the prescriptions that we filled for them most recently, or the prescriptions that people call about the most often that are typically covered by our plans.

Alexis:
And so we're using RPA to bridge the old legacy systems that don't talk to each other, to make that experience more seamless. What cognitive is doing, on the other hand though, and this is probably where more of the R&D is coming into play, is saying over time these bots should somewhat be replaced by more modern and elegant interoperable systems. The whole effort that's happening to make buyer-enabled applications so that our electronic medical records and our payer or provider spaces all talk seamlessly. We know that's coming. We know that that's going to help to provide a better clinical experience or care experience for our members. But until then RPA is a really great way to get there.

Alexis:
Cognitive, on the other hand, is saying even as we get those answers to come faster through the call centers, or those answers to be more available for our clinicians at the point of care, there's still going to be a whole body of tasks that are still somewhat mundane or are taking time away from those customer-focused interactions. So cognitive, by helping us to find ways to automatically fulfill a prescription ...

Alexis:
Right now, there's a technology at Humana that allows a member to get a prescription refilled by sending in pictures of those pill bottles. They go into an email queue, and then a pharmacy tech is looking at it and entering it into our systems. Cognitive can actually say, "We see this pill bottle. We see that it is this formulary and this prescription. Let's go ahead and automatically refill that because we can see that they're eligible for that refill." Really the way that we're pushing the envelope is how do we improve that member experience through intelligent automation, both in terms of the way we're providing service when they're calling us, but also how they're receiving some of our other products and services as well.

Dan:
And you mentioned the experience of both the associate and the member, also some human-centered design. We talked about it a little bit earlier. So what's the role of members and associates at Humana in building these processes? Because I think one of the things that I learned in the innovation space is that if you put technology on a broken process, it just breaks it faster and it frustrates everyone across the board. So I wonder how you include both the member and the employee in creating these new, more efficient processes.

Alexis:
This is something I'm really excited about that we're doing. It really stemmed from Kerry's original focus in terms of how he stood up our Center of Excellence. There was a very intentional push, in terms of the technologies and processes that we adopted, to enable our associates to identify opportunities themselves. And what that's become is what we're calling a citizen developer effort, where we are enabling our associates to build and define their own automations.

Alexis:
We still maintain some governance and oversight to make sure that it's not going to be a breaking change that they're building. But we've really accelerated, especially in our healthcare services operations, putting the tools in the hands of the associates who are closest to the members, to build the automations that will make the most sense. And we've seen an incredible adoption rate. We just launched, with healthcare services in our citizen developer space in August, and they've already self-built 37 automations that are focused on the clinician's experience feedback from, "Hey, these are the friction points we have with our members. These are the things that make me feel like a robot during the day. Help me become a human again."

Alexis:
And so they're building those things themselves with my teams providing more of that Genius Bar experience. Ask an expert if they don't know how to do it themselves. We do more of the traditional IT tasks in terms of peer review, peer code, checking for all of the security vulnerabilities and those things. But we've dramatically reduced cycle times on some of the easy automations. And frankly that's the best way, because I'm information technology, I'm not at the point of care. So teaching our clinicians, this is sort of the art of possible, letting them test and learn themselves and build some of the systems themselves, we've also realized helps fill my backlog with the more complex pieces as well, because they start to see what's possible.

Dan:
Yeah, and that's a great point to kind of hit on for the listeners as well. You want the people at the frontline to be able to be a part of that innovation because they know the pain points, like you said, and to include them in the whole process from ideation to implementation to measuring it, I think, is a key best practice in innovation. It sounds like the center was built for that. That kind of leads me to the next piece of this, which is ... And maybe Kerry, you can give us the early definition of this, and then, Alexis, where your head's at now. But how did you think about measuring success with these automation initiatives? What were some of the metrics that were originally proposed as you stood up the Center of Excellence?

Kerry:
Some of the metrics that we originally stood up with were really around, I'll call it effectiveness and efficiencies, and then combined with associate experience. So let me break down effectiveness and efficiencies for a second. We had measurements around tasks, the time the tasks took within a process, and then the amount of effort that it took to accomplish each of those tasks.

Kerry:
So then as we started deploying bots, we started measuring the number of transactions those bots were taking on instead of humans taking that on. And then we had that as a measure of effectiveness of our digital workforce. Like how much work that they're really taking on. Combine that with ... Because we really thought that, again, it's not just the efficiency plan but it's really the associate experience quality.

Kerry:
So we combined that metric with, I'll call it surveying metrics related to, in essence, is your job getting any easier? Bit by bit by bit. Constant surveys around the amount of effort it takes an associate to get their work done. And as we looked at deploying more and more digital workforce in those given areas, whether or not that associate experience, and I'll call it that weight of transactions or the weight of the complexity of transactions that they had to accomplish, whether or not that was being reduced over time. So really it was the efficiency and effectiveness of that digital workforce, combined with did it actually make an impact on the people doing the work.

Dan:
We've heard that as well from some others that have implemented, that it's not only the efficiency piece but it's also the experience of the target that you're trying to make more efficient, or the recipient of that efficiency. I love that you got the process and the human touch in there. Alexis, where's your head at now as far as outcomes and success, and maybe is there an example of one that you're really excited about that's really just knocking it out of the park?

Alexis:
We have quite a few examples. Really where we're headed next is continuing this maturity journey in terms of the types of automation that we can deliver back to the business that have a significant impact on those customer-facing operations. Whether it's clinicians, or agents, call center reps, et cetera.

Alexis:
Just speaking to what Kerry was saying, a really great example of a very successful automation for us is, at Humana, one of the benefits that we have is an over-the-counter benefit. Many of our members call in to a call service desk to actually place those over-the-counter prescription orders. These are kind of high-level metrics, but the old process used to take like maybe 20 minutes per phone call, and it would take a couple of days to fulfill the prescription. We implemented an automation solution that was a combination of attended, unattended, and cognitive.

Alexis:
We actually had really small bots working in different ways as a sort of integrated solution that actually reduced ... What would happen is that our members would actually have to get put on hold. This happens a lot in call service operations. They'd get put on hold while the call service operator was looking up different information to see what's covered, looking up the different things they were asking for, helping them to place the orders. And then that would go into a queue where someone would actually have to go in and manually enter in the prescription before it could be filled.

Alexis:
By using this integrated cognitive, attended, and unattended solution we saw that hold times for these particular type of calls were reduced by five minutes. That's a big amount of hold time to not have to wait anymore to make sure that you're answer is getting serviced.

Alexis:
But, perhaps more importantly, the prescriptions were getting out the door almost a day faster. So when you're talking about really having a significant impact in a solution, it's this sort of multi-tiered approach of how can we use some smart RPA, or cognitive RPA, as well as some of the more simple repetitive task-based RPA to drive an exceptional member experience. So where we're going is, how do we continue to find more integrated solutions like that, that aren't just looking at high transaction type processes where RPA is a really good fit, but these really more blended innovative solutions that, at the end of the day, help to drive that better member experience. That help us to deliver that seamless integrated healthcare experience that enables us to have better health outcomes with our members as well.

Kerry:
Just to pull on that a little bit further, if you don't mind, is that a lot of people think of automation, especially as we're looking at automation in one of these big companies like Humana or something like that, as a way of where we're going to be more and more abstracted from their experience. The way Alexis is describing it, we're really looking at automation as an enabler for our people, our associates, to have more personal interactions and deeper human interactions with our members, those people that we serve. So instead of abstracting that interaction, we're actually using it as an enabler to make the interaction deeper.

Alexis:
I actually really think that that is at the heart of a big part of this message, is that we see automation as the way to give back time to our associates to spend with the members. So for clinicians that means less time searching for answers, more time providing answers. It means less time annotating over clinical documentation in five different places, but doing it in one place and having the bots deliver it to five places, even if they're not yet integrated. And so that means that the focus then can be on the things that are really going to win in the marketplace when it comes to healthcare, which is empathy, understanding, and being the advocate for the patient. So that's really what we're here and what gets us jazzed up to do this.

Dan:
What's interesting is sometimes it's hard to get that ROI of time back, or empathy and those skills, through the finance leaders' heads. They're like, "Well, where's the hard dollar savings?" Like, "No, the nurses can actually spend more time with patients. There's safety, there's reduction of error, they're happier people. The member experience is going to be better." And they're, "Well, where's the hard dollars?" So do you have any advice for healthcare leaders as they're trying to stand something up like this and balance the efficiency and the human part of this? What would you tell them to think about and really tackle before they start one of these centers?

Kerry:
That's a great question. We've been blessed by our senior leadership here at Humana, from the CEO, Bruce Broussard, on down. Really as we were standing up the Center of Excellence, one of the things that was pushed from our CEO, Bruce, was that associate and member experience. He was the one that pushed really hard to ensure that that associate/member experience was one of the key metrics that we actually took in to begin with, with the Center of Excellence, and that we measured all of our initiatives against.

Kerry:
So I'll call it that senior leader buy-in at that C Suite. We were blessed with our CEO plus his management team underneath him, really have bought in. Automation was not just an efficiency or [inaudible 00:25:23] finance play, it was a play to make our associates better in order to deliver better for our members as a whole. And really getting that, I'll call it senior level alignment, and that push across the management team, not just from the CFO, but across that management team, was a huge difference maker for us in that journey.

Alexis:
I'll add just a few things here on this. I think that what you're really asking is a broader question about digital transformation and what do you ... Automation's just one of the tools in the tool kit for digital transformation. Our leadership focus, as Kerry mentioned, has been very much on how do we make sure that we're appropriately building the culture, putting in the training, planning for how work is different through digital transformation. So when it comes to automation, what I see is that it's the ability for us to provide some capacity back to our workforce to pick on the next set of skills tasks, or to pick up the things that provide the most value as we continue to push forward. Business is only going to become more complex and the speed of information only continues to grow. The volume of information only the continues to grow.

Alexis:
And so automation is a way for us to really actually focus on how we get back to some of those really high-value things like human interaction and empathy. Like Kerry said, we've really just been very lucky in that the focus here has always been on automation. Really all companies are going to have to find a way to do automation, but the real winners are going to be differentiated by what they do with that capacity. So for Humana, we're keeping to our core values, which is putting our members first and focusing on healthy outcomes.

Dan:
To the outsider, it seems very complex to build a bot and make it do all these things, but as you dive deeper it's actually the future of business. It needs to be run by taking away those manual tasks and making the human interaction, and what humans are good at around complex decision making, more efficient. So I love those pieces of advice.

Kerry:
Yeah, absolutely, Dan. And to kind of pull this just a little bit further, one of the things that we haven't talked a lot about is, I'll call it the cultural change management. The efforts that we've put around that, we've had to put a lot more into, around introduction of automations. I would say that we've learned that the disruption at the user level is very low. The person that is actually using those automations, they embrace that really quickly because it's helping them do their day-to-day job. But what we've learned really over time is as the leader structure, the managers, the directors and things like that over them, automation is a different thing for them to think about as well. It's a broader scope of their ability as a part of their job, and they have to do a lot more with that too. So we really had to invest a lot more in that change management, especially on that middle layer of management, than we had [inaudible 00:28:13] ever expected to do.

Dan:
That's an interesting point. That middle layer of management, across multiple industries, tends to be the reason why innovation dies. And there's some literature about that now. In nursing literature, specifically, there's a study that came out that said the number one barrier to the adoption of change in a health system is the frontline nurse manager. I think there's some other literature as well that kind of takes that across different industries and different layers of the healthcare system. So to convince and get on board that middle layer is really key. As we wrap this up, I just have one question for each of you. What's the number one thing that you want to hand off to listeners about automation? What's that one thing they need to take away and think about as we move forward?

Kerry:
The thing I would say is I love my calculator. And I love my calculator, not inherently because I can't do math. I know I can't do it as fast as my calculator. I know I can't do it as well as my calculator. I know I can't do it as consistently as my calculator. I can do it by hand, but I make mistakes and it takes me a long time to do it. I'm a morning person and as the course of the day goes on, my work gets worse and worse and worse. It happens.

Kerry:
But in essence, my calculator is automation, right? So it is a function that's helping me do my job a bit better and it helps me be more accurate. It helps me focus on the things that I need to focus in on rather than doing the math by hand. So the thing I'd leave it with is that I'm not scared of my calculator. Maybe that's because it's been around for 50 years or so. Some of this automation today seems a little scary because it's a little different, but really it's here to make our lives better rather than to take over the world or something like that.

Dan:
Yeah, that's a great piece of advice. I'm sure you were the one on the Texas Instruments calculator programming the worm eating ...

Kerry:
You know it. But don't call me on that.

Dan:
Yeah, I was the one figuring out how to spell bad words upside down with numbers. Alexis, we'd love to hear what you want to hand off about automation.

Alexis:
Two pieces of advice. The first is it's really important to think about automation as your own personal productivity assistant. This is about how we take the parts of our day that make us kind of go, "Ugh, it's Monday again" and turn it more into, "Yay, it's Friday." Because maybe those are the best things that you do during the week. And the other part is that it's important to also start small. There's a lot of different applications for automation across the organizations. Sometimes we think we have to have that really big win that is super transformative, but most of the innovation successes start with small and incremental pieces that are built. So that might be very early on just finding a way to open up five applications simultaneously and copy and paste out of all five of them into a spreadsheet, so you can look at data in one place.

Alexis:
It doesn't have to be this big overwhelming thing that you're trying to go forward and tackle. And, because of that, the people who are doing the work are going to be the best source of inspiration for what they can do to automate. So really having a program that's focused on teaching the art of possible, showing lots of examples of how it's been successful in small incremental ways across the organization and other organizations similar to your own are really important. And the last piece here is at the end of the day, this is really, really about organizational change as Kerry mentioned. You have to start with the idea that tomorrow's work is going to be different than today's work. Just like 20 years ago, the way we worked was very different. So encouraging a culture that fosters creativity, curiosity, and sort of test and learn is going to be really important.

Dan:
Yeah, great points, not only for automation but for innovation in general and I really appreciate those insights. So, Alexis, where can we find more information if listeners are like, "Hey, I want to understand a little bit more about this, both from an industry standpoint and maybe from a Humana Center of Excellence standpoint"? Where can they go and find out and make contact?

Alexis:
Certainly we would be happy to connect with anyone via LinkedIn and answer questions. We have a pretty broad network of companies that are similar to ourselves. I know I participate in a number of conferences and product councils for the different platforms we use, Automation Anywhere, WorkFusion, as well as some of the other emerging technologies that are starting to make headway into this space. And outside of there, you can't hardly open up a webpage and type in RPA without a flood of options out there. So it's there if you want to start to interest yourself, and if you want to get a little deeper we'd be happy to have a conversation.

Dan:
Awesome. And we'll put links to all that in the show notes so that everyone can find your LinkedIn and get some more information about that. Kerry, Alexis, this was awesome. I really appreciate you taking the time to be on the show. I think we learned a lot about how large systems can institute automation and become more efficient and keep that human touch. You gave some great examples for healthcare leaders to consider. It was an interesting conversation, so I really appreciate it.

Alexis:
Thanks. Great to be here today.

Kerry:
Yep, thank you very much, Dan. It was great spending time with you today.

Dan:
Thank you so much for tuning in to The Handoff. If you like what you heard today, please consider writing us a review on iTunes, or wherever you listen to podcasts. This is Doctor Nurse Dan. See you next time.

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