Latest / Make It Real / How AI simplifies complex systems with David Anderson
Transcript
- David Anderson (00:00): Be prepared to take risks. In other words, can this be applicable to, I don't know, our legal organization? We're looking at documents. Can it be applicable in different parts of different work streams? I think we want to make sure that we're leveraging proven technologies while everything else is evolving, Shirley Macbeth (00:25): You're listening to Make It Real, brought to you by EXL. I'm your host, Shirley Macbeth, and on this show, we're exploring how artificial intelligence is reshaping workflows, industries, and the way real work gets done. And yes, we're going to make it real. Implementing AI often gets described as a project, but we all know that AI is actually a journey, and that's why I'm so excited today to welcome to discuss his journey. I'm excited to welcome Dave Anderson. He is the Senior Director of Operations and Vendor Management at CNO Financial Group. Dave already went around this journey. He has moved AI from concept now into reality in the everyday customer service agent operations at his organization. So we're going to dive right into a discussion to learn from Dave and understand the opportunities, the challenges, and then obviously the lessons that he has learned along the way through his AI journey with AI and the workflow at CNO. So great. I'm so excited to have you here. Welcome, Dave. David Anderson (01:30): Yeah, I'm excited to be here too, Shirley. Shirley Macbeth (01:33): Awesome. Well, before we jump in, let's talk a little bit about CNO. Just give us a little bit of a background on your organization. David Anderson (01:39): Sure. Well, CNO provides insurance, financial services in the health arena, income retirement, and we're really here to protect the needs and support the needs of middle income America. We do that in a manner that's traditional. We have voice response systems, we have self-service websites. We also sell through field agents, D2C, and then my organization is really responsible for policy administration for all of our enforce policies as well as mail operations, both inbound mail and outbound mail. So that's a little bit about CNO and a little bit about what I do here. Shirley Macbeth (02:19): That makes sense. Well, thank you. And then when you think about ai, you've mentioned a lot of different areas that you work in. How did you first think about embedding AI into this complex system that you manage? Tell us a little bit about what you were thinking, the benefits that you saw as a potential when you were considering it. David Anderson (02:36): Well, in operations, you're always looking for driving, timeliness, maintaining or driving quality, reducing costs. So as AI began to evolve, those were the ticklers that really caused me to raise my eyebrows on what can AI do for us. In the past, it's always been around robotics and automation or changing process flows. So that's where our journey began and my thoughts began wrapping around AI. I saw the potential internally, CNO’s taking a very conservative approach with AI, but when you look at things like Copilot and things that can help you in your day to day, it's very intriguing to get that applied to your process flows. Shirley Macbeth (03:21): Absolutely. So was there one specific business challenge or one area of opportunity that you saw that you wanted to focus on initially? David Anderson (03:28): Well, I mentioned that we have various channels for our customers to engage us, and I saw the need immediately in bringing in and ingesting our mail. It's unstructured formats, sometimes structured formats. It could be a handwritten letter and the opportunity not only to use old fashioned OCR, but to then really enable that to enhance our process flows through AI really is where I began to look at Extracto as the opportunity to again, just drive timeliness, promote quality, but then begin to look at things from an end-to-end process scanning all the way through to production for our customer inquiries. Shirley Macbeth (04:15): Now, you mentioned things like mail and you mentioned handwritten things and you said you have a conservative outlook at the organization around AI, justifiably so. How did you help people take that leap from like, "Hey, we're going to bring this in and we're going to automate something in a very different way?" David Anderson (04:33): Well, we had to show it and we had to prove it right, and that's where EXL was so impactful for us through mockups and proof of concepts, the intriguing opportunity that they presented me, I still had to take that and show our program management, show our developers, show our IT and our leadership that there's potential here. So it was really through the partnership with EXL that enabled me to bring that show beyond just a proof of concept. Taking data from one of those forms, bringing it through Extracto and presenting it back to a user here was what really opened our eyes. Shirley Macbeth (05:18): Dave, when we've talked before, you've mentioned that there was kind of an aha moment. Tell me about that aha moment with your stakeholders when they sort of were able to grasp how this could transform your business. David Anderson (05:29): It's really an extension of what I just went through. It is when we saw for the end user displayed on their screen and side by side on the other side of that screen was a snapshot of the form. We have thousands of different forms from each state for each customer need, and to see a form side by side to what an end user sees. And then what will go into our administrative system was that aha moment that said, we can take this again unstructured format and put it into usable data, and then from there is where the future really begins. So that was the aha moment for us. Shirley Macbeth (06:12): It's seeing is believing, I would say, right? Yes. It's the concept to reality and then seeing how that could really change the day-to-day of your insurance reps. That makes sense. On the phone, you've mentioned that there's so many stakeholders and so many groups, and you're kind of at the hub of that. Let's talk about how, and you mentioned this a little bit, but how you were able to win them over certainly seeing was believing, but what were some of the other concerns and maybe barriers that you had to overcome in convincing and getting along this journey? David Anderson (06:42): Well, you have the traditional concerns, right, the financials, and then anytime you mention AI, that will raise the hair on the back of the neck of legal, privacy, and even architects. "Well, how do I bring AI into our environment and then share it across another environment?" Shirley Macbeth (07:01): So it really took the establishment of a set of goals that said, "We're not going to bite off more than we can chew. Here's the magnitude of it. Here's what the customer impact is and the impact to our agents in the field." Once you buy off on those goals and then you realize that it's also cost-effective, then you're able to align those disparate groups, which also includes operations, program management, the vendor management. You bring them and you align around those goals, and then that's how we move forward. (07:38): When you think about when that first kind of conversations happened to how long it took, maybe you can give us an update of that. How long did that journey take? David Anderson (07:47): Easily a year. I think it took about a year from EXL’s proposal, the proof of concept review all the way through contract conversations and then team building. And then I think we implemented 13 different, what we call use cases or production workflows through Extracto in a period of, I think the shortest amount of time was just once we got everybody on board, everybody just moved forward and within five months we had our production and implementation tasks, but end to end over a year. Shirley Macbeth (08:27): Over a year. Interesting that it's sort of the upfront is the alignment piece that really is important. David Anderson (08:32): Upfront is where you want to spend your time, you really want to spend the time upfront getting alignment, getting the buy-in and building the right players. Everything from, again, you're RealSoft. I never even knew what a JSON was until this project and just the ability to feed the data across the two companies is critical. So you have to build the team and spend the times upfront. Shirley Macbeth (08:57): So now flash forward 13 use cases, would you be able to maybe just give us an example of what one of those is, or a couple that would be amazing? David Anderson (09:07): Yeah, absolutely. So a lot of our payments are premium payments or auto draft. Okay. So we've got the customer's name, bank information routing number, bank account number, address. Anytime a customer wants to change that, they can mail that in, mail the form to us. That's one of the examples. And basically we extract the content off of the form, we bring that into the Extracto world. Those data elements are pulled out and on a lot of forms, there are so many data elements that are unnecessary. We extract out what's pertinent today, we're presenting that to the end user, and they're reviewing it and looking side by side. But the future is basically enable Extracto to bring that through a high degree of confidence in the information and send it on to the admin system. So changing bank information, we can also bring in instructions if somebody needs to process a withdrawal or surrender on their policy. We're even doing that on a limited basis through the extractive tool. Shirley Macbeth (10:16): These are major systems where you're taking this handwritten content in some ways or other things that probably maybe you could say what that would've looked like to manually then enter many steps along the way to now really making that so much faster. How do you measure that? How do you quantify the change? David Anderson (10:34): Well, that's the process we're going through right now, day in and day out. It's good old end-to-end timing right now that the EXL operations team is doing. We established a baseline going in and now we're monitoring the progress as Extracto matures. And so again, ultimately our objective is we have the human in the loop, so to speak right now, but we're gradually reducing that commitment of the human in that transactional loop. We would rather see that very highly skilled, very motivated individual shipped over and begin to do other things and let these production needs just flow all the way through. Shirley Macbeth (11:19): That's amazing. And so when I hear what you're saying, it's providing a better customer service for your end customer, certainly. But there's such an interesting moment as well for your service agents to really transform how they do their jobs. David Anderson (11:34): Absolutely. It's an opportunity for the associates to grow. It's an opportunity for them to contribute. A lot of this is transparent to our customers and even transparent to our field agents, but once you begin to take that processor, the associate that's keying the work, once you remove them from that keying and you enable them to do things like supporting the customer and our field agents directly, instead of spending the time keying, that's where our benefit really grows is that we're able to spend more time fixing customer problems. An agent may come to us and say, I have a client that has a house closing. Some of the money they're going to get is going to come from the cash value of their policy, but I can't wait three days for that. Well, we can expedite that and put it in the hands of a human to expedite that, but we can't do that as effectively in today's world because we're still in that production line mode. So it's like going from production line to customization is how I've always looked at it. Shirley Macbeth (12:46): That's incredible. What a change. So you have 13 workflows now or 13 use cases. What does the future look like? Are there just so many new ideas that you're thinking of now to automate? David Anderson (12:57): Right. We are. We're looking at other areas across the enterprise that have similar work Right now, again, I'm in force administration, but maybe claims processing, maybe putting together new applications, but also that workflow represents, I don't know, about 30% of my overall throughput. So we're also working as a team to look at other opportunities within our existing work streams to kind of grow the capacity while we grow the capabilities of extractive. Shirley Macbeth (13:30): We talk a lot about on this podcast around concept to reality and that journey, as I sort of led off with what might be maybe your couple pieces of advice for others that are going on this journey. David Anderson (13:41): We mentioned it earlier, do the work upfront. Don't make any assumptions that everybody's bought in. There's skepticism. There are also challenges. There's the change management challenge, the concern that folks are going to lose their jobs or that their jobs are going to be highly downgraded. I've been around a lot of evolutions and operations, and I just haven't seen that, whether it was robotics or even going from paper to email way back in the day. So you've got to be prepared for objections. Again, financial objections, resistance to change, and even there's a concept out there of change fatigue. Be prepared for that. For example, in order to meet that five months where we went from use cases to releases, production releases, we probably had five release streams stacked on each other. Be careful about change fatigue because that's a lot of work for folks, so make sure you're resourced appropriately as well. Shirley Macbeth (14:45): When you say change fatigue, is it the agents? Is it the people implement? David Anderson (14:49): That's a great question. Shirley Macbeth (14:50): It can be both? David Anderson (14:50): It can be both. I think we were so successful because we took our end users, the agents, the processing agents from the beginning. We just didn't rely on subject matter experts or operations management. We brought the end user into the use case developments. Okay, the UAT, the production validation, and now they're into what we call hypercare, where we're training the system. So there's a lot that the people go through that the folks go through. So there's times where you have to take a break and take a step back and look forward a little bit, but breathe a little bit so that we don't burn folks out. Shirley Macbeth (15:36): Right. I think sometimes, like you said, the change management from the people and getting all used to this, that is a journey in itself. So I think important what you mentioned there, to recognize that. David Anderson (15:47): Absolutely. Shirley Macbeth (15:48): Well, we have a part of this podcast that we call the shout out, and we've talked a little bit about this already, but it's around people. It's around change management, and Dave, I think how, if you get any specific additional advice around getting the people thinking about that customer service agent and the day to day, how their work was going to change and upskilling, helping people understand how their work is going to be different. Any takeaways specifically on that? David Anderson (16:16): You have to paint the big picture so often, and I'd do it to this day. I think that, okay, these next two hours is doing email or it's watching chat at the close of a month or a quarter. Your processing team, your customer service reps, if you don't continue to paint the big picture, they begin to get very compartmentalized. Their world becomes extremely small. It's just that transaction. I've got my, I know I can do 50 of these a day, so I get next work and I process it. If you expand the view and make it a more holistic picture of, Hey, you're playing a critical role in addressing the needs of our customer, we may alter your transactional role, but you're still playing an integral role in the process, the end-to-end process of taking care of our customer. So you can kind of help make that shift if you're consistently refreshing the boundaries of your teams, just making them, enabling them to see the picture that they're playing in a larger picture. Shirley Macbeth (17:31): I think that's really helpful, and it ties back to how you described CNO when you first started talking about the organization. You're there to help the constituents that you serve, and if this helps make that even easier, that fits with the values of the company. That's amazing. So I'll disclose with one sort of look ahead. Where do you see this in three, five years? I mean, I think when we talked before, I feel like you said pace is changing, the pace of change is so fast. Where do you see this all headed? David Anderson (17:59): Just looking at my operations, I see just continued growth and capability and growth and capacity. That's a roadmap we've already set in place and we're already working on. But I just think the evolution and the pace of change with this sort of technology is, it can be great, but I'm a little concerned that it can be too much. There's a lot of that looking for the shiny ball out there, and so I'm hoping that we focus on leveraging technology that might be very different two or three years down the road, and being mindful of what that difference is while staying on a parallel track of what we have right now. Let's just continue to try to make it better and then leverage it in other sort of life areas. And then I think the final thing is over that time period, be prepared to take risks. In other words, can this be applicable to, I don't know, our legal organization, right? We're looking at documents. Can it be applicable in different parts of different work streams? I think we want to make sure that we are leveraging proven technologies while everything else is evolving. Does that make sense? And protect your downside too. That's always the important thing when there is so much change, right? Shirley Macbeth (19:26): Yeah. I mean, what I hear you say is that it's not about chasing the shiny objects to say that it's around the use case, right? It's the legal teams... David Anderson (19:35): Absolutely. Shirley Macbeth (19:36): Benefit from it. So it's not about chasing the tech per se. It's about looking and seeing the advantages to make a real concrete difference. David Anderson (19:44): That part hasn't changed in business in years, right? It's all about cost benefit, and you get a little bit worried sometimes that might go out the window because something new and shiny is out there, but it may not be worth it. Shirley Macbeth (20:00): Well, thanks, Dave. If I think back on our conversation, we talked about so many things. You have so many great tips and advice for others that are going along this AI journey, but if I summarize and think about some of the things that stood out to me, I would say, first of all, you said spend the time upfront to get the people aligned, pick the right use case, and really plan for success. That was integral. So that's one of the things that you said. You also talked about the importance of painting the big picture for the people that you're working with, and especially those who are having a new workflow and their ways of working are changing. So the importance of really painting the big picture, why this matters. And then the other thing that stood out to me was you really said, don't chase the shiny object. It's not about the shiny object. At the end of the day, it is not necessarily about the tech. It's what it's doing. That was a great piece of advice. How does that sound? Did I summarize it, Dave? Well, and is there anything you add? David Anderson (20:53): I think those are three or four components there that we've all got to focus on, and I know it's sort of our guiding light and working with EXL. Shirley Macbeth (21:02): Wonderful. Thank you so much, Dave, for taking the time. You're welcome. I think your journey is really so helpful to others listening, so I really appreciate your time. So Dave, thank you from CNO Financial, and we will sign off from here. Thank you so much. David Anderson (21:16): You are welcome. Thank you. Shirley Macbeth (21:21): Thanks for listening to Make It Real. We hope today's conversation gave you ideas, insights, and inspiration to help bring AI to life in your organization. Remember, big ideas don't drive change. People do keep learning, keep experimenting, and keep embedding AI where it matters most. Follow along so you never miss an episode.