In this episode, ADJUSTED welcomes Sam Neer, Group Product Manager with Berkley Alternative Market Technology (BAMTECH). Sam discusses how technology and claims work together, and the ever changing landscape that is technology.
Season 5 is brought to you by Berkley Industrial Comp. This episode is hosted by Greg Hamlin and guest co-host Matt Yehling, Directory of Claims at Midwest Employers Casualty.
Comments and Feedback? Let us know at: https://www.surveymonkey.com/r/F5GCHWH
Visit the Berkley Industrial Comp blog for more!
Got questions? Send them to marketing@berkindcomp.com
For music inquiries, contact Cameron Runyan at camrunyan9@gmail.com
In this episode, ADJUSTED welcomes Sam Neer, Group Product Manager with Berkley Alternative Market Technology (BAMTECH). Sam discusses how technology and claims work together, and the ever changing landscape that is technology.
Season 5 is brought to you by Berkley Industrial Comp. This episode is hosted by Greg Hamlin and guest co-host Matt Yehling, Directory of Claims at Midwest Employers Casualty.
Comments and Feedback? Let us know at: https://www.surveymonkey.com/r/F5GCHWH
Visit the Berkley Industrial Comp blog for more!
Got questions? Send them to marketing@berkindcomp.com
For music inquiries, contact Cameron Runyan at camrunyan9@gmail.com
Hello everybody and welcome to adjusted. I'm your host Greg Hamlin coming at you from beautiful Birmingham, Alabama and Berkeley industrial Comp and with me is my co host for the day, Matt Yehling.
Matthew Yehling:Hello, everyone. This is Matthew Yehling coming from St. Louis, Missouri along the banks of the Mighty Mississippi.
Greg Hamlin:So glad to have Matt with us today. We actually have a special guest with us. That is with Berkley. Actually it goes by the acronym BAM TECH but Berkley alternative markets technology, our special guest for the day is Sam Neer who is our group Product Manager at Berkley alternative markets tech. So Sam, could you say hello to everybody?
Sam Neer:Hey, everybody, very excited to be here, Greg and Matt. And again, I'm based out of Raleigh, North Carolina, where it's a little bit warmer, not as warm as Birmingham, Alabama right now, but it's still there. And I will say no one wants to say Berkeley alternative markets technology over and over. So we might just call it BAM tech just for all of our sanity if that's okay.
Greg Hamlin:I think that's wise. I think that's why it's so the topic today, this is something we've never really tackled in the nearly three years that I've been doing adjusted is claims and technology, and the role that it plays in helping us do our jobs. So I wanted to bring Sam in today to talk to us a little bit about that since he is part of the Berkley company that manages our technology to help us be successful. Before we dive deep into the topic. Sam, I wanted to ask you a little bit about yourself. So I'm sure that you knew you were going to be in workers compensation, right?
Sam Neer:Greg knew it is again, coming up as a small boy, I would say to my dad with a glint in my eye one day dad, I come to work and workers compensation and a quippy line I'll have is either the way I ended up in the industry is either I found my way into making great technology products with great organizations and really effecting change, or I follow the goal of becoming the most stable, uninteresting version of myself one of the two. And again, maybe, maybe it's a little bit of column D.
Greg Hamlin:there's a lot of stability in worker's compensation insurance. So that's the one positive right.
Sam Neer:That's it's something to be accounted for. So with the 32nd background, again, I've been working in digital technology for the last 12 years and product management, started off in PR and analytics then moved to telehealth right at the height of the pandemic would not recommend trying to jump into telehealth at that time, and have only been in sort of the insurance industry for you know, for a couple years now. But at the same time, it really just a baptism by fire. But I've learned a lot. And I think insurance is a great area, insurer tech, that's having a lot of new frontier, a lot of legacy systems upgrading. So it's a great time to be alive. And again, my specialization is claims I'm beginning to dabble a bit more on the policy and underwriting side. But the trends are out there that are happening impacting all of us, and really excited to talk those through. That's awesome.
Greg Hamlin:Well, I know the headlines right now, when you hear about technology, you hear about the mass layoffs of companies like Twitter, and Facebook and everybody else, Google. So there really is something to what you know, as you were joking, there's some civility that comes with insurance and worker's compensation, it might not be as glamorous. That's definitely not the Silicon Valley dream, right. But there's definitely opportunities for stability.
Sam Neer:And glamour is in the eye of the beholder, right. And I will say that the impact and the scale of which we're being able to operate here at Berkley is enormous, right? And so that's what I do enjoy that. And you getting to build technology that powers really a lot of what happens in the workplace is really awesome. So I'm thrilled. Okay, I tell my wife, I'm the coolest guy ever. And she doesn't believe me yet, but she'll get there soon.
Matthew Yehling:So when we talk about technology and claims, you know, claims is been around for a while, what do we mean? What's the role of technology in claims?
Unknown:I think that's a great question. Again, I'm gonna start off with the buzzword, because everyone needs a cool buzzword to begin, but I'm gonna say the technology and claims the word of the day is augmentation. Right? So with this, as you know, the claim experience is a very human one, right? You're in the moment you're in the accident, how are you basically getting through that process? And that's why at least how I view this is how can technology assist in that process to augment the adjuster and the humans who are very much interacting with that claimant at that moment, and that experience, and also with the policyholders, and also with agents again, there's a whole spectrum right here. But with that, as some people just tried to say, can we automate it? Can you just talk to a computer? Can you never interact? And yes, there's going to be the small paper cuts or the report altogether, there's going to be some subset that can be automated. But the way that I've been viewing against leaves my time here at Berkley is how can we use the best of technology to augment the best of humans to really attack these problems? So that's where I believe that most places will say just throw Our computer or machine learning model at it. But in reality, how can we leverage technology to leverage humans is the way that least I've been trying to approach it.
Matthew Yehling:Can you give an example? You know, a recent example maybe of how you're using technology to augment something in the claims industry?
Unknown:Way too many Matt and again, this is what keeps me on my toes, right. So with that, for instance, sometimes again, we will use machine learning or what some people call AI. So ML is the buzzword machine learning, which is sometimes people call it AI. It's all these different cool terms, right, just saying, hey, the, you know, Skynet is doing something in the background. So from there, we at least some of our Berkley time will say, hey, when a new claim comes in, based off the first report of injury, how do we get some of these early details to identify whether it's going to be a large scale claim, or just, you know, just the paper cut, right. And again, when it's the smaller ones, we're saying, hey, adjuster doesn't need to do 17 of the normal steps, again, all the regulatory and must have requirements we're always doing to meet the laws of the land, but some of the stuff of the process all the follow ups, we can reduce some of that, on that when the machine learning or AI or Skynet identifies and you don't need to do everything on this one, right, and we don't get it 100%, but directly that save some time. So just do the human steps, the augmentation where they need the plug in and reduce some of that early. So that's a good example where we're saying, hey, technology will identify some things that reduce some of those steps, but we still have the human doing the must have steps in that process.
Greg Hamlin:I think it's really key one of the things you're highlighting there, and that we're not in a state where we're looking for technology to replace human beings. But if we could redeploy some of those efforts, so we have time to do the things humans are really good at that's, that's one of the things that can make us special if we allow computers to help us and technology to help us improve the processes. Sam, what are some of the misconceptions? You see, when you start to hear about how technology can improve claim processes? You're dealing with a lot of claims, people who probably don't all have high levels of technology background? And so what are some of those misconceptions you sometimes hear where there's some, you know, maybe they don't align with what's actually what actually can be done? Well, yeah,
Sam Neer:I think that's a great question, Greg. And, but it will say it's, there's two ends of that spectrum of those misconceptions, right. One is that technology, hey, anything that I don't like doing right now, technology can solve it can solve world hunger, just with a single flitch. Sam, here's the idea. Just go make it happen. wave your magic technology wand. And you know, it's just like, my parents, when I go home for Christmas think that i is because I work in technology can solve all of their router problems and printer problems. Some people think that, hey, technology can solve anything you want. They're just like the printers, the TV's broken, can you fix the Roku? Right? It's like, I can't do everything, folks. Okay, so that's one end of the spectrum. And the other one is that misconceptions is that technology can't do some of the cool things that humans historically could do. Right? And some of those, which when you actually talk about it makes sense. Like, hey, we want technology to catch mistakes or errors, right? Oh, yeah, of course, I would like that. Or could it reduce mundane, repeatable tasks, so you're doing like think work, and not just, you know, just click work, right. But the two ends of those spectrums are always fun, and especially insurance, some tends to gravitate towards, oh, technology isn't gonna be able to do anything. So that's the fun conversation. And I'll actually flip the question back to you. How have you all seen? Like, what are some of the misconceptions you found? We're working in this industry longer than I have that, you know, that come up a lot as well? Is there any different ones? Besides from those two extremes?
Greg Hamlin:All right. Well, I was just gonna say the one I've seen the most, in my experience has been that often technology can do things, but what's not being calculated as the amount of time and effort and resources that would have to be deployed to get there. And so often, I feel like adjusters managers, supervisors have the want list, and the want list might save them five minutes, but it might take 10 years to accomplish it today. So then the prioritization and becomes the issue. It's not always that it can't happen. It probably could. But is it really worth having that happen for what it's going to cost?
Matthew Yehling:Yeah, my example would be the first notice of loss and automation of that, and triggering, you know, maybe keywords, you know, given the example of highlighting, you know, more serious claim, so you trigger in on words like amputation, traumatic brain injury, and those go to a more experienced high level claims person versus you have something where it's like contusion laceration, and those things get assigned to a newer person or somebody, maybe that's less experienced. I mean, I've seen some examples of that through automation and augmentation, I guess. You know, the word we're used And so that would be an example I've seen of where it's been applied in, in the industry versus having it go basically, across the spectrum. A new claim comes in and always goes to Sandra, because Sandra reviews every new claim, it's like, well, you know, if we can identify, you know, things, and you might, you know, identify 80% of the stuff, and then Sandra just gets 20%. And then that time that Sandra is freed up, is now able to go in and do some other tasks versus all she's doing is reviewing new losses coming in. That's a recent example I've seen.
Sam Neer:I love that example of that. Because I will say it's like, it's a combination of routing rules saying, hey, and we picking out words, but this is where technology like we say can assist is sometimes when you have to write the exact if then rules and then you forgot a derivation, right? Some people call things very similarly, there's also this idea in technology called stemming, or, you know, he's like do plurals or ing or things like that, right. And that's where you can say, hey, technology, with natural language processing, called NLP, come up with all variations of this type of word, or even recommend words. And that's what it's getting crazy right now. It's like, Yeah, I'll just recommend these 20 other words, should these route to this type of adjuster who's going to handle this type of catastrophic claim, for instance, or this cat claim? So that's where it can use the combination of an if then rule set this kind of basic, but it's good and technology, but then can technology, figure out a few more examples around that, to help escalate that? I love that example. And again, it's one we're even looking Yeah, we utilize here to some degree, and how can we expand and enhance that as well?
Matthew Yehling:And it's small things, and then you can continue to build on them too, right? Yeah, it's nice to have the home run. But every time you know, it's a lot of times it's a little singles, and how do you gain little efficiencies, the 1%? Better improvement, and then that becomes exponential improvement over time, right? So now has, you know, 80% of her time freed up to do more meaningful other tasks? You know, we're not trying to eliminate her role. It's we're trying to elevate her role into like, okay, let's, you know, you're you're better utilized in this capacity. versus, you know, breeding. Yeah, I mean, that's another example. I mean, the difficulty I work with a lot of attorneys and nurses, you know, the difficulty here, I get a little pushback from them, as I'm in the show me state. I'm in St. Louis, I'm in Missouri. They want to see everything. So that's some of the difficulties I experienced on the kind of the reverse. I'm like, no, let me review the document, give me the document. And
Sam Neer:one of the fun things about the changes in technology is sometimes under the hood, it is not easy to decouple with machine learning and AI and insert buzzwords, and you know, joke Skynet from the Terminator back in the day, right? But to that end is, it can't always show you that way. So that's where sometimes again, the idea of a buzzword back again, augmentation where you could say the computer, or ml or AI recommended this, do you want to take action on it? So it's not basically making the choice all the way, but it's allowing those to say, hey, oh, I want to double look at the document the Show Me side, I want to Okay, let me just double check to make sure the computer got it right. And if it does that 100 out of 100 times, or 99 out of 100. Maybe you start trusting it. So that's the idea is you don't like you said we all want to using a bad sports analogy. We all like seeing the long past bombed Randy Moss at the end, you know, with a touchdown, I don't know why I'm going to the Vikings in the 90s. But, but in reality, the teams that just chunk it forward to like five yards at a time, five yards at a time, the small incremental gains can eventually really get you there. And it's not as glamorous as the star play. But that's really what's gonna move the needle in the long run. So okay, so
Greg Hamlin:one of the questions I had Sam is what is technology good at in the claim space?
Unknown:Yeah.
Sam Neer:And that's where I think, you know, the unglamorous sides of technology is the piping right? Technology is a good thoroughfare of information connecting different systems, facilitating seamless and easy communication interactions, a couple of ideas that come to mind that, especially in the claim space, especially as we as adjusters need to be more easily contactable or basically reaching out to claimants, things like digital payments, don't go send my old school check to my grandma, like my grandma did. Can I get something in? You know, Venmo? Right. We've heard that or texting, right? Like which kid under the age of 25 wants to have a phone call they dread it that's like, is that a punishment? Right? Am I being grounded? Because I have to answer the phone. So everything from the piping to also thinking about where can identify patterns, right? technology could say I'm seeing a lot of this problems. Let me just take this as a problem. What should we do with it? So it can't always say the what to do with it. That's the million dollar question. For instance, one of our partners at a similar company Midwesterners employers casualties have this idea of identifying problematic claim notes, hey, we've seen a bunch of these claim notes. This one is flagged for attention. Or another operating unit at Berkeley is also saying we've seen claims like this, you might want to go check those out. So these are the ways that technology can find those patterns to then surface it and then at that point, the adjuster or the human can take it there. And so again, the reticence is Sometimes that technology is not as good as humans and everything, it's like, well, that's majority clue we truly have a brain, we have the ability to think. But it can also look at 10 million claim notes, and come up with some groupings of problems and say, Hey, I've seen similar ones that a human would never be able to do. And so and then data validation, and anything that we said earlier, it's not think time, it's just checking a box. Because computers, they do make errors. Trust me, I've got a backlog full of bugs to try to tackle. But at the same time, it's much more consistent in humans at that part, but trying to ask your computer or even this newfangled chat GPT, I tried to you know, that's the buzzword nowadays, I tried to ask it to write a haiku about claims adjustment, and it failed miserably. So anything once respective, but it did actually have a good song two claims. This is one aside about claims, I asked it to do song about claims adjustments to the tune of Baby Got Back. And it did says I like small claims, and I cannot lie and it actually went there. So it started. It's getting closer. But the huge nuance, you know, is not there's where it needs to be.
Matthew Yehling:Great points. Yeah. So when you're working with obviously, individual adjusters, you're working with injured employees, you're working with different components? What are some of the challenges and managing those expectations of the claim staff? When it comes to technology? What comes to, you know, enhancements and things like, you know, Greg alluded to earlier, like, and you alluded to when you're like, fix all my stuff, like what? What are some of the, those expectations like how do you how do you normalize those?
Sam Neer:That's great. And that is like, it's the idea that I want it all. And I want it now, right? Like that's the the problem that we're dealing with right here is like, there's so much that we want to fix. Greg, you made a great point earlier saying, Hey, we don't always necessarily know the size, this will save me five minutes, but it's going to take Sam six months to build. Right. So this like some of the misconceptions that I wanted, when thinking about this question, it's a really good question. Is that one you hear about it elsewhere? Well, we can do it right away. Hey, I've heard about my friend who works at similar insurance company, they have this cool button that you know, brews and coffee and does XYZ for my claim process. Why can't I do that? Right? So misconception is people don't forget out all the piping all the underlying architecture that goes up to make that right. Another is like the response times, like we think that everything in every system is supposed to be blistering fast, right, which should be like my iPhone starts up in a second, I can't wait a second, give something pauses, even briefly, we're like what's happening. So the challenge is, again, these are misconceptions that are out there. So the challenge is trying to not just address them, but then overcome them. And that's where again, product management comes in my entire profession is to say is, hey, we understand that your iPhone can boot up in a second. And we understand that your friend can do XYZ at this other carrier, here's how we're different. Let's work within our sandbox, and let's create amazing things within there. So it's really us trying to overcome those by doing the quick explanation, because it can't just like not, we can't do it, then you're just feel like either you're being talked down to. But at the same time, our role is in product management, and even within technology is to explain what we can do. And then we partner with again, Great Plains groups who are coming up with amazing ideas to figure out what we can do. I'll actually turn this question back to you too, and saying, you've seen a lot more of these mismanaged expectations over time. And I know, Greg, you said earlier as a mismanaged expectation of sizing, what do you think on technology, technology teams can do better to help in that conversation? Like what is we as technologists, what do we need to learn, when actually engaging in that back and forth?
Greg Hamlin:Great question, I think, on are end, sometimes we don't understand how hard certain things are not maybe how difficult but how many hours would be needed to accomplish something. And so that wish list we've talked about can get really long, because we can all think of things that would make things easier. Well, if I just clicked here, then I wouldn't have to do these five other things. So I think sometimes understanding also what other things are being worked on that are competing for that same time. So we could spend five weeks adding a new button to the screen. Or we could do this other thing that would allow us to automate small claims. And so understanding the impact, I think, on both sides, sometimes maybe the technology side might not understand the lift that would come from something. And then that's our job to make sure we're speaking up to explain that. And then on the other end, I think understanding how long it takes so that we're prioritizing the right things. I don't know what your thoughts are, Matt?
Matthew Yehling:Yeah, something similar. I think spending enough time with the people doing the job is a lot of times the difficulty and making sure like when I say I want this, like that five button example or like I have to click on these eight things to have this happen. Instead of these eight things, like would it make sense to click on it once and then it jumps to eight. What is that? Up to 234567 doing? Are they doing anything like? Just, you know, sometimes maybe it's the, you know, the Data Architect, or maybe it's the person that's actually, you know, the business analyst. Do they understand? And then sometimes the claims people really don't understand well, the reasons you have to click on steps three, seven, are this like that triggers this piping like that, like Sam was saying, like, I think there's definitely roles on both sides. Like, the reason the phrase that everybody hates is like, Well, the reason we do it that way, is the reason why it's done that way. Right? Yeah, yeah. Because an x ray over come over and hey, can you just cut out this process?
Sam Neer:Love those phone calls, we love this one goes. And I'll actually add something out there. I think it's great to say as we as technologists need to get better at actually going and sitting down next to the person saying, walk me through instead of just saying, I want XYZ at the eighth step, like skipping steps two through seven. Let me see why you don't need those. And then again, that's where the dialogue can occur, right? Hey, step number three. And I need to give a shout out to my amazing team who thinks through all these things. So again, we have a team called claim to fame where we really focus on claims shout out to that group, what they'll say is, Hey, you forgot about regulatory reporting here, or you forgot about NCCI will have these different plugins of different steps, we may need it. But that doesn't mean we can't, we may need steps now. One and two, but we may not need 345 and six, right? So I think it's a good back and forth to be able to explain but too many times, we just hear I want to go jump from one to eight, we write it off as technologists can't do it. And then that dies, and you lose that potential savings over time. So rolling up the sleeves and getting in the trenches important, it just just takes time. Right.
Matthew Yehling:So how would you tell Greg and I are both in claims management. And we manage you know, the claims adjusters and claims analyst and examiner's etc. So, you know, we have in our prioritizations that are important to us, you guys obviously have prioritizations that are important to it and to technology. So what's the best way to manage that those prioritizations in the limited resources? Because, like the example Greg gave earlier, how do we manage something, when there's only a limited resource, you know, IT resources and technology resources? Unfortunately, we've mentioned, you know, Google earlier, like, we don't have Google money, we're not gonna like, you know, how do we manage those prioritizations?
Sam Neer:Oh, this, these are the questions that make us happy that we're asking these questions, right? Well, the there's a simple answer, actually, man, Greg, I will tell you the way we prioritize his liquor and guessing I wish it was that easy, or just a dartboard. It's like, close your eyes. And that's no, I completely joke. But I think a better way of like, for lack of a letter buzz phrase, it's basically like, It's the voice of the tactical combined with the insight of the strategic, right. So with that, as we need to do, anytime you ignore us, or the people who are living this day in and day out, we talked about that dialogue earlier, then you're not going to get the things that will actually impact people in the day to day. On the flip side, for all you're focusing on some details in the weeds, you will miss the bigger strategic opportunities out there. So the first thing we need to do in order to prioritize the chaos, that is a huge backlog and seems like 15, new things have popped up in the last, you know, 30 minutes, since we've been talking is combining those two, get those two inputs. And then after that, you need to basically then narrow it down quickly, because there's always way too much that you want to do. Just like my wife has 15,000 home projects she wants me to do. We can't talk about 15,000 projects, we need to talk about five, right? So first is get the inputs, do your homework, again, with targeted homework, you can't boil the ocean, narrow it down, and then pick a direction and go. I think, you know, it's sort of the idea that a lot of places have analysis paralysis. But again, there's a show called Prison branco TV years ago, where the guy Wentworth Miller, who played one of the characters there had said, There's only for four roles you need to remember, make a plan, execute the plan, expect the plan to go off the rails, throw away the plan. So even with that things will go wrong at times. It's not any point. It's not perfect, but you need to make it and you need to start executing, right? So take those inputs, Nora down and then go. But in reality, if you're not thinking about the strategic, then you're missing out. And Greg, I'll actually ask you as basically, as a, you know, a claims leader, what's important when we on the technology side should be thinking about the strategic should we be coming to you with the ideas, should you become the US or is there some better forum for us to make sure we're not missing that voice of the strategic?
Greg Hamlin:Yeah, I felt like that conversation has to go both ways. But I do think you're right. It's really important. You don't want to have your technology department, so focused on just fixing the brakes, that they're never ever thinking about the strategy, and the bigger things that could really move the needle because if all we're doing is keeping the car running, that's great, but we haven't actually come up with new innovative ways to do things better and our competition is going to be looking for those way is to do a better, we're all trying. So if all our attention is just trying to make sure that the car runs, that's great, but we're gonna miss out on some really important things. So I think talking back and forth and creating that dialogue of what's possible versus what can be dreamed up is, to me some of the first steps to really coming up with that. That's what I would say. Anyway, Matt, thoughts on your end?
Matthew Yehling:Yeah, like, Sam put it. I'm a big games clear fan, where you just have to start something. Stop, you know, ultimately, like, you're always great to have the plan. But sometimes, you have to start and something. Yeah, keep worrying about that being perfect. When, because then you'll you'll never get anything started. And you're gonna never never finish anything. If it's always got to be, you know, 100% accurate. There's going to be little glitches, like you said, there's going to be little bugs here. Having people understand like that, you know, we're going to do that. And then Greg hit on it, too. Like, we can't create something that is also so bad, though, that it's great. I see people and technology, people want to work on new things, right? Unfortunately, like claims, a lot of times it's like we're on legacy. There's a lot of legacy stuff. There's years and years, there's there's legal components in this component and, you know, reporting upward components. So there's all that that needs to be factored in. And sometimes that, you know, that minutia that's not glamorous, and nobody wants to work on that stuff. You know, it's all the fun, new things that everyone wants to work on. Right? Yes, very much. So.
Greg Hamlin:I've heard it said that objects in motion tend to stay in motion. So I think there is something to getting started and just getting moving. Yeah, Sam, I know, on our end, our claims people, we're pretty good at understanding a lot of medical terminology. Now, we're also pretty good at learning a lot of legal because we spend a lot of time in both of those worlds. But when we start to get into the technical side, I think maybe I'm the only one but I do think sometimes we struggle a little bit. So what are some of the challenges? Or what do you do from your perspective, to break down some of these concepts and help the folks in claims understand what it is you're trying to accomplish?
Sam Neer:Yeah, I think that's a great question, Greg. Because just as a technologist coming into insurance, it's sometimes your kids, it's actually going both ways, because insurance is not the easiest and most straightforward at times, right? And I had alphabet soup for my first like, when I first joined, I was like, Oh my gosh, let's play this game. Which acronym is this? Is this the insurance companies acronym? Berkeley acronym? Is this like state acronyms is? There's two acronyms for the same thing. How do I survive it? Right. But I think that idea is like, hopefully things like this podcast where you're explaining things like in metaphors or analogies. This is like XYZ or even my bad analogy of my wife giving me the honey do list, right? How do we break this down into a shared understanding that we all have a checklist as well, but try to talk a similar language. And that's what product management does usually trying to take stakeholders, and then developers. So first of all, talk things something out. And if it makes no sense, try it again. And then say, explain it like you're explaining it to a five year old, and everyone seems to kind of like roll their eyes like no, okay, I can try to explain that. But in reality, amazing if you to simplify it, and they get to a way that you understand it. Another thing that we do in our team a lot is basically a diagram, diagram diagram. Big Box is like you're going to a whiteboard. And again, we use a digital tool called Miro, there's other versions out there. But how do we just like there's a box here, and it goes to this box? And let me get this process to this box. Right. So that's how sometimes we explain the intricacies of API's and batch jobs and all you know, buzzword soup, when you hear again, I'm sure when people hear our technologists talk to like, their eyes are rolling, what are they talking about? And so this is why at least what one of our goals is to under explain what we're doing and why is I say, let's make it stupid, come up with bullet points, not long paragraphs and explain to it like in a common language. And then if there's follow up questions and Nepalese like, well, let's, I actually care about there's that one person in the room who's like, I want to ask the detailed question to be the teacher's pet. Right? At that point, then you say, Let's sidebar this, and let's go to the huge deep dive sames ideas, I think on both ends. Also, when adjusters like you said earlier matters. Like, they may just say, I just wanted to do this, but need to break it down that way. I think both sides need to say, explain it simply, and then have the follow up questions after that.
Greg Hamlin:That's really easy to forget all of the things we just assume we know. And I could say, well, we denied the TTD because of the IMEI but we need to keep in mind CMS and somebody who's outside this world if you just say somebody in claims understands every word I just said. Yes. And I do think it goes both ways.
Sam Neer:I love that Greg and I think especially because like again, a lot of developers sometimes they're not even having that interaction. So again, if you ever get a developer on a call Have, you will rattle that off? And they'll just be completely like they're like, I understand none of it. So I'm not even engaged. Right. So I think the goal is is saying just like, you know, I've seen great on this podcast, people will explain what, you know, what are these terms? Let me explain the context, even if it's baseline, or, you know, most insurance adjusters or people will know, how do we here's it, we all understand what we're talking about. Yes, yes, yes or no? Okay, let's explain. 30 seconds. There we go. Now, let's move on. And I actually finally understood like, it took me a while but actually understood exactly what you said. So that's where us as technologists we're getting there's
Matthew Yehling:so I when I was in college, I worked in a restaurant. And you know, most people paying credit now, right credit card. So periodically, the credit card system would go down. We still had the whole, the old. You know, Swiper makes? Yeah, yeah. Sam's probably too young to even have seen any of those. But Greg and I aren't, you know, but no one knew how to use it. And then there's occasionally credit cards don't even have those raised ridges anymore. So then you have to write it down. And people are like, What do you mean? Anyway? What happens when when technology goes down, and it's all hands on deck for you guys?
Sam Neer:You just You just panic? That's what you do. You just can't? Just like I don't know, it's like, I never want to claim home. Exactly. Just like as a shutter down for the day. I guess no one else is doing any more work. Right? Like those are? Those are the good old days is like snow days or stuff. It looks like it's gonna stay I guess they just shut it down. Right? But unfortunately, we were not in middle school anymore, right? And I'll have to ask at the end bad how you survive those fun, probably the teachings and people like, you know, customers, I'm sure love that and love taking time. Right? What I will say is like anything like any types, you've got an emergency on claims, whether it's technology, people forget that the techniques that you use, whether and you know either on the claim side, when there's a fire, whether it's at home, whether it's via whether anything is you just want shut out the noise and focus, right? The problem is with technology is sometimes it's very hard to diagnose the problem. But you'll hear Hey, the system's slow or something like that, or something's not working, right. And then of course, everyone trying to be helpful is like, Oh, and this other thing isn't working and this thing, and then we have to like, okay, there's a lot of noise. How do we focus it? You start decoupling these things, breaking it down here? Oh, yeah, that thing has been broken for the last two years. Okay. Thank you for that help. It's not helping right now and the panic or the fire. But I think communication is also key. Because when something breaks, just like you had, there's, you know, the difference is if you put up a sign and saying, Hey, our credit card machine is broken, it's going to take us a little longer to process payments, people like oh, okay, they know, they understand at least I'm going into it right you see those sometimes i Big fast food addict. When I go in, someone had put the sign up saying we're understaffed today, please be patient. I'm like, Oh, okay. This is why the lines taking so long. So communication is is also a way during those panic moments, to try to communicate it there, right. And finally, send consistent messaging. And then, at the end, give a wrap up or summary, we had technology called a buzzword retrospective where we get in a room and again, most people have retrospectives. But we get in a room and say, Why did everything go so badly? Right? And it's never a fun conversation. You don't want to be having these. But you really need to have the tactical discipline say, Here's everything that went wrong, summarize it, and then send it out to your stakeholders for accountability. I've had this in Greg a couple of his emails last year. And they're not fun to descend. But I'm hoping that it gives the visibility saying, Hey, we're taking ownership for what did break. And here's what we're doing to solve it in the future. Right. Greg, when you get those emails for me, are you you're not happy to see them. And I hoping you're at least liking that we're taking ownership that we broke something, right,
Greg Hamlin:absolutely. And I think some of the things, you know, we don't have these types of problems very often. But when they have happened, what I really appreciate one is just the regular communication, knowing, you know, sometimes every half hour hour, this is where we're at this is what we're working on, this is what we're doing to fix it, updates are going to follow. And then at the end, talking about this is what we found out, this is what we learned, this is how it happened. And this is what we're going to do so it doesn't happen again. I think that's a big part of it. And luckily, we have a company culture where we can accept ownership. And there's not a lot of finger pointing that allows us to get better. So kudos to Berkeley for developing that. But that's a big part of the success.
Sam Neer:This is what I love working about this organization. And why I think we are the leader in like our respective insurance areas is the fact that we've got a great product. And again, like I said, it doesn't happen often. But no company is perfect. It's how the company responds, and we take ownership. And then we say how do we not make sure this doesn't happen? Again, a lot of places that have worked even passcode has tried to sweep it under the rug saying, hey, there was no problem or let's just cross our fingers and toes and hope it doesn't happen again. We actually take the methodical time to really not just figure out what went wrong but enhance so it doesn't happen in the future. And that's why we're always pushing forward which is appreciated.
Matthew Yehling:So that's awesome. I mean, how many problems mobile down to communication, right? When it's like a like you gave the example like put up the sign tell people, you know, we're moving slower today because we're understaffed or whatever. We know this is down, hey, we know, emails responding slowly, or we're not able to get outgoing things or in going things or whatever. So just that communication, I think it's critical. And hopefully, this never happens at our industry. But that's why I had to give the restaurant analogy, right. But yeah, when those problems go down, you know, we have the after action review, or whatever you wanna call and, and, yep, and we are able to able to improve the process. Right? Very much. So.
Greg Hamlin:So Sam, this is the exciting part, I think, is where do you see technology going to improve claims outcomes in the future? So we've talked about some of the things we're doing now. But where do you think this goes in the next five years? Yeah,
Sam Neer:I think that's a really great question, Greg. And that's what again, exciting we don't always just want to be fixing the the bad things. We also want to be improving and really enhancing and making more fun for everyone involved. The technologists, the adjusters, policyholders, there's a lot that technology can do to really enhance. And so for instance, the research firm McKinsey recently had a report and again, they call it what it was called human in the loop. We've talked a little bit about this earlier, where technology can take some of the mundane heavy lifting, but then keep the human apprised of the steps, they need to stop or double click or click in or as you said earlier, find the documents read the document to show me they can the human is least tangential to that process, right. So they don't have to do everything, but they're in the loop. Another one is, again, the buzzword that was really big years ago, but you still hear it a lot is cloud computing. And most people don't even know what that means, or like, how does that impact me. But the better way to think about as the daft punk song from years ago, Harder, Better, Faster, Stronger. So cloud computing can make systems faster, more reliable, have better, you know, uptime, better, you know, just overall better experience. And so that's another shift to saying, hey, let's get away from the thing that's been in the closet, the server in the closet for the last 50 years, don't unplug, you see the signs, like don't ever apply this. More like we don't have to worry about someone tripping and just like, oh, gosh, the system's down, right. Another one is the idea of buying versus building. Some larger organizations like ours historically have been like, we got to build everything ourselves. We got to do everything ourselves and manage everything ourselves. But really the ones that the great thing about Berkeley, while we're leading sort of this insurance industry is we're thinking about what are we great at, and let's execute on that. And that's augment with other organizations that do their best that and then we make an ecosystem the best, right? We, at Berkeley are plugging the piping, that we don't have to build everything from scratch, sort of like, again, you're making your recipe, you don't have to do it the way grandma did, where you make every single ingredient. From there, I can get the best ingredient from here, the best ingredient here best and green from here, and still make that delicious dessert. And I'm making myself hungry at this point. And then the last one, as we talked about machine learning and AI, you're getting served with the idea of human in the loop. But where can we leverage those technology areas to really solve problems that we didn't even think about? Right? Like one of the exciting things that we in the technology are citing, go to the basic question, the job to be done of what are we trying to do here? And where can technology assist? So we're able to ask bigger and bigger questions, it seems like every year, but then again, we had enough to go back to the drawing board to actually do it is it you know, regulations. But it's exciting to having to be an insurance tech. So like I, you know, gets me up in the morning.
Greg Hamlin:I agree. And when I think back on when I started my career, you know, maybe four or five years in some of the data analytics was starting to, you know, really start to get into insurance. And everything was about filling out a field, right? There's a new box every five minutes. Here's a new box. Here's a new box, right? Because we have to capture the data. And so as a frontline adjuster, it was a nightmare. Because I was like, well, now I've got to make sure I find the 900 boxes, and all the data goes in the box. But I look at where we are now in some of the advances in analytics and being able to just cognitively not only read notes, but start to make inferences about what those things mean. That will allow us to do things that instead of having to fill 900 boxes out, we can actually get to that same place without having to do that. Which is exciting to me to think about, like where that goes next. I don't even know what that looks like, you know, 10 years from now. But yeah, it's very interesting to see very much, Sam. Overall, I've really enjoyed having you on here. I can't end the episode without joking. You know, our audience will never hear it. But in the middle of this technology episode, my computer had a blue screen of death and we had to stop the entire podcast because everything locked up and shut down. So even in those moments, the stuff can happen. But the show must go on. So we show must go on. That's right. We were luckily we have a great editor that will make the sound amazing at the end. But I wanted to end this season by asking each of our guests to tell us something that they're grateful for. I'm really a big proponent of putting good vibes in the universe. I feel like there's plenty of people doing the opposite. So my, my small contribution to the world is to make sure I put something good and every time I could think of it So, for you today, Sam, what's something you're grateful for?
Sam Neer:I love this question, by the way. And again, listen to other amazing adjusted podcasts, go shout out, please go back to the library with there's a ton of great episodes on Spotify, your streaming, platform of choice, great content there. But I have one professional and one personal. So the professional thing I'm grateful for is an amazing claims product and analysts and dev team. So again, I get to come on this podcast and tell everyone about it. But we've got a lot of great people who have been working for decades, who really get all the credit for supporting Berkeley industrial comp. And, again, our alternative markets are bamtech It's too much of a mouthful, even for me to say it on a personal level. I'll call it the five F's, right? So my faith, my family, football, film, and finally fast food. Okay, so those five really get me up in the morning and make me excited to so I'm grateful for all of those things. And, again, grateful for this podcast and the best cohost group product manager could ask for. So Vicki offer a great conversation.
Greg Hamlin:Thanks, Sam. Really appreciate having you as a guest today. And with that, we will wrap up this episode, and hope you'll follow us in future episodes releasing every two weeks on Monday. You can also catch our blog on the off weeks that is written by our wonderful Natalie Dangles. So again, remind everybody to do right think differently and don't forget to care. And that's it guys