S01E04: Transforming Operations with AI and Automation

You are listening to 'Ops Game Changers', the new ActiveOps podcast where we share real-life stories from remarkable leaders who are revolutionising the world of service operations. In this series, we explore some of the key challenges faced by service operations as they strive to deliver more - more capacity, more productivity and more business impact. Host Bhavesh Vaghela (CMO at ActiveOps) quizzes his guests on how they went about unlocking significant value, adopting best practices, and experiencing some game-changing results. 

In episode four, we dive into the topic of automation in customer service and how to manage staff apprehensions and uncertainties around the impact of AI on their current role. To address this topic, we are joined by Ellena Bianco, senior leader, client operations at CoreLogic. CoreLogic is a B2B information service provider empowering the property services industry in Australia and New Zealand through technology, data and connectivity. 

This Ops Game Changer shares how the team at CoreLogic evolved their automation strategy, from being very rules-based some five years ago, to now adopting sentiment with AI to reduce human intervention and drive operational efficiency. 

Ellena shares her first-hand experience of how the team at CoreLogic went about identifying areas for improvement across the customer service element of the business, the targets that were set, and the impact these changes have had on productivity, staff wellbeing, and ultimately the customer experience. 

Throughout the episode, Ellena talks about the elements of resistance that were met along the way, such as the disbelief, uncertainty and apprehension of employees around how AI would impact their day-to-day work. Ellena shares how these challenges were addressed with honesty, understanding, and transparency. The approach that CoreLogic had towards AI implementation has enabled employees to fully understand and appreciate the improvements and embrace more challenging work, leaving the repetitive tasks to the bots. 

Tune in to this fascinating episode to learn more about CoreLogic’s experience in transforming its customer service teams to address customer requests in under 30 minutes, and why this has had such a positive influence on customer experience and team morale. 

Want to learn more about how to radically transform your company through the power of operations? Then don't miss the following episodes and hear more fascinating insights from other leaders in the field of Operations about how they have overcome challenges to drive productivity and boost performance at their enterprises. You can listen and subscribe to ‘Ops Game Changers’ on your preferred podcast platform and also on our YouTube channel, AOTv.

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Transcript

Ops Game Changers Podcast
S01E04 – CoreLogic 

Bhavesh Vaghela: Hello and welcome to "Ops Game Changers," the podcast that shines a light on the crucial role operations teams have in driving business performance and improving staff and customer experience. My name is Bhavesh Vaghela, I'm the CMO at ActiveOps. And in each episode, I'll hone in on the key KPI or challenge that a business has solved. I'll delve into how they went about doing this and explore the outcomes achieved. Now today we're joined by Ellena Bianco, who's senior leader client operations here at CoreLogic, to find out how they evolved their automation strategy, from being very rules-based some five years ago, to now adopting sentiment with AI to drive operational efficiency. Now, before we jump into this automation story, let's welcome Ellena to the show. So, hello Ellena, how are you? 

Ellena Bianco: Good, thank you, how are you? 

Bhavesh: I'm very well, thank you, thank you for jumping on the show. We're really excited to hear more about the automation story. Now, before we jump into that, perhaps you can tell us a little bit about how you ended up in operations? 

Ellena: Oh, thank you. So probably not that interesting a story, but I think it was the early or mid to late '90s where work was hard to come by in Australia. So I started just out in a call center as customer service for a large telco and just moved around departments in there and landed in what was then called business and government service delivery. And sort of worked there for a while. And I just noticed after a while, some teams were always, always struggling and some teams were doing really well, and it just fascinated me. And I just think from there I learned, I wondered, and I was curious about why that would happen. And it was probably at the start of when the internet boom really, like it became, the internet, it needed to be a primary service, not just phone and fax line, and the demand for internet services for business was exploding. And so many changes and we just couldn't keep up. So that sort of piqued my interest and I was really just attracted to the concept of, and I now know that if you can measure it, you can manage it, at the time I didn't understand that. And just how that change was managed and how that was impacting different teams. So that's how I got started and just progressed my career through different organizations within Australia, both telco and banking. 

Bhavesh: Well, I mean, I think that's a very common story when we talk to operations leaders all over the world. It's often the case that you've grown up through the operations ranks. So it's fantastic to have you at the show to kind of talk through the automation journey. Now, before we would jump into that specifically, perhaps just tell the viewers a little bit more about CoreLogic. Who are you and what's the role of operations for CoreLogic? 

Ellena: Sure. Well, CoreLogic is at its core, a business to business information service provider with platforms that fuel property decisions in Australia and New Zealand. So we gather a lot of data and then we package that up for, for people to make property decisions. So we really pride ourselves on our data and our services, helping people build better lives. And every team and every way has that connection to what we do, that's their unique way of delivering that. And it really does help the end user find a property, whether it's residential or commercial, acquire one through mortgage platforms and then protecting through insurance data. So it really hones in on the property universe in Australia and New Zealand, so that's the core of what we do. And our service delivery or operations sits within client experience, and our role really is to deliver on what the customer needs. So our platforms really do the bulk of our grunt work, so we rely on our platforms to present this information, to be up to date and to really help these businesses make their decisions. Where that doesn't happen, where customers need help, that's the size of our operations. So we do that and we also do a lot of the research of that data. So finding out more about data, finding out who's connected to certain projects that are happening within the commercial and construction real estate segments in Australia. So that's primarily our operations within CoreLogic. But again, it really is there to support the platforms that we provide our data through. 

Bhavesh: So Ellena, I guess when you are thinking about customer experience then, it drives some key challenges for your operations team. So could you share a little bit about the challenges that you face? 

Ellena: Yeah, and I think we wouldn't be unique in the challenges that we face in having to deliver on what the customers are asking for. But I think when I think about the challenges, I think my answers would be very different had I been, like, when I was a team leader, I would've said absolutely, it would've been SLA and KPI driven, and I would've said it's about having enough resources to do that. But now as I've progressed and I sort of sit back and have a wider scope to be worried about, it really is that balance, I think, the challenges of exceeding that client experience, making sure that they wanna stay a customer of CoreLogic, and by the same time enhancing our employee experience. Why do they wanna work for CoreLogic? What are they able to do? 'Cause so many people now wanna be connected to that purpose of CoreLogic. And that other part of that triangle there is how do you stay ahead of the technology so that you are not staying behind, and that you are able to deliver our products faster and just keeping up with what's going on. Because to our customers, they're not interested in what's happening behind the scenes. So how do you balance those three key pillars daily and you just can't stop. And I think the pace is the challenge, that's how I would answer that question now. 

Bhavesh: Yeah, it's a very good answer and thinking about that pace, when you first introduced yourself, you talked about that pace of technology change in the operations teams that you were working with at time. I guess in some ways we're experiencing that rapid change now. 

Ellena: Absolutely. 

Bhavesh: It's constantly changing, in fact, it's probably faster than it's ever been. And that kind of jumps into the topic, right? So the idea of automation and automation I know is a journey that you've started probably five, six years ago. So what were those drivers at that time? Why did you embark on starting this automation journey? 

Ellena: Yeah, I think foremost, we're not shying away from that, was the cost of the work we were doing. So we were able to work out how much time and effort we were spending on processing or data entry, that it seemed like there weren't decisions needing to be made, or the decision was quite easy. And we would sit back and we would watch people, and we would look at ways that we could reduce the time of the task, we were constantly going, if it's one and a half minutes, how hard can it be for us to look at it, or from the employee's point of view, how boring is it for them to have to continuously do this all day, every day? So we looked at what can we do, we went to product and we said, can you stop us needing to do this? This queue of work was actually work that needed to be done, it was a fulfillment request, it wasn't a product initiated queue. And so we then had very brave executives at the time who said, let's see if we can automate this. And so it was a very small scale, we reached out and we targeted about three or four different processes that we considered high volume, low value. So the decisions to fulfill that task were easy, and that's how we started. So we literally just reached out to a couple of suppliers, they showed us some prototypes, we said, yeah, let's try this. And it really was about how can we just not have this task? And we definitely needed people on the task. 'cause around that time, the SLAs, well, the turnaround time for that work was around 30 minutes. So you could imagine a 30 minute turnaround time if you've got a couple of people off, or lunch breaks. that's how we had to, we were so timely, we were so closely monitoring their time that it was quite stressful, stressful for everybody involved, so that was the first one we looked at. It was a really easy process for us to say, yeah, this is right for automation. And when we looked at these processes, it was, could we automate 85% of the work? We always knew that were gonna be exceptions, and we were more than okay with that. Could we do 85%? And if it was yes, then let's have a look at that. So yeah, that's how we started. And it really was rudimentary keystroke replication. We didn't look at redesigning the processes, that wasn't part of the scope. It was just, can we replicate what the team member is doing? 

Bhavesh: Got it. 

Ellena: So that's how we started. 

Bhavesh: Fantastic, so, I mean, I guess, it's again, a very common story as to why operations teams go down the route towards automation where it's all about, hopefully reducing some cost and improving the customer experience at the end of the day. And as you say, a 30 minute turnaround, you've got a very short window to make sure you deliver against a customer requirement. So, looking back, what'd you think went well and what would you say your kind of key learnings were at that stage? 

Ellena: I think what went well was the process was quite easily defined and mapped. So the process we started with was quite, no, I don't wanna say easy, but there weren't too many exceptions. There was one system to go on to, and the scope of success was quite easily defined because we knew we could do 80% and that 80% was successful. The more difficult ones, we didn't even try, and that was still processed by the team. So I think the scope of the project worked well, we tackled what we should have tackled. And the team really quickly, it caught on because that pressure valve was released. So it worked and it was successful. However, I think some of the key learnings were to ask, to make sure that you understand every process along the way. We had a service provider that did the development for us, to make sure you understand every, not every bit of code, but understand how they've designed or how they've delivered on what you've asked them to do. So even if you have a BA that can interpret the business requirements, actually understand how they've done it, 'cause if those people move on, it's your business, it's your customer, you need to be able to understand that. So I would say ask questions and then really ask more. And the other one was, I think, looking back, is try and preempt as many things that you think could go wrong and preempt them and be prepared for that. So if the product changes the log on page or moves a checkbox, that's going to impact. 

Bhavesh: Of course it would. 

Ellena: So try and preempt as much as you can, if you can, 'cause if you think it can go wrong, it probably will happen, and be prepared for that.  

Bhavesh: Yeah, and I guess, Ellena, we kind of hear it a lot at the moment with the whole AI revolution, that there is this fear for people's jobs, right? I mean, people are scared in some ways of bringing the new technology, like particularly, the new levels of artificial intelligence that are available. But in some ways, even five years ago, five, six years ago, when you were starting this journey with automation, I would imagine it's the same sort of fear from your teams and people. Did you encounter resistance at that point? Did your staff fear that, oh my God, I'm gonna lose my job as a result of this? 

Ellena: Yes and no, I think the resistance came in the form of, I wanna say, disbelief, like there's no way you can automate this. And I'm not sure if that comes from if a bot can do it, what am I doing? I'm not sure if that's where the thing comes, or even for me, sometimes, I'm so surprised at what is able to be done from a technology point of view. In our instance, because the volume was so high, and we had so many different teams with volume pressure, there was no talk of your job not being here. It was always around that reassurance that, hey, you're not gonna be doing this, but there'll be this other work to do, or this work's gonna take away those repetitive tasks, and what you'll be left with is a challenging work that we can't automate. The resistance, I think that in the beginning, was maybe fear, maybe no one quite verbalized the fear, it was more of, I don't think a bot can do that. 

Bhavesh: Yeah, it's not possible, right. 

Ellena: It's not possible, yeah. And so when we asked, hey, can we watch you do a task? There was always like, see, a bot won't be able to do this 'cause I have to go over here and do it. And that's when we sort of looked at our mapping process and changed that concept of not so much keystroke replication, but outcome focused. What are we actually trying to do in this task? Why are we even doing this task? 

Bhavesh: Yeah. I mean, I guess it's one of these things that's always evolving, it's never a static thing. So you're constantly moving from the next operation or try to tweak accordingly. So five years on, what's the perception now? How has this automated, have you hit the 85%, how has this impacted the business? 

Ellena: Yeah, I think when we look at certain processes and we really tackle some ones that have got a lot of decision points, it takes us longer to get to that 85. So that's our benchmark, we need to be able to do 85 for it to even be worthwhile for the time to invest in the process and the developers developing it.  

Bhavesh: Yeah, I think it's a key challenge for any type of change really is, well, it's not gonna work for me because my work is very complex and very different. And actually a technology or a bot, as you say, or a AI is not gonna be able to do it. And I think, as you say, the rate of change of technology is so fast and so advanced now that things like ChatGPT as you described, are revolutionary in some ways, and the sorts of things that it's gonna enable you to do. So I guess it kind of brings us very much into today, in terms of where you guys are today. So you've been on this automation journey, where you started with this kind of keystroke, the basic processes that you've evolved, and you're now certainly moving more towards adopting some more sophisticated technology to deliver that sentiment and the idea of tackling some more of the complex type of processes that you have. So perhaps kind of talk us through the sort of things you're doing today. 

Ellena: Well, I think it is, before I just jump into that, I think it's really possible because the cost of this technology has come down, it is accessible. 

Bhavesh: Yeah, that's true. 

Ellena:  I think to most people. So that gives us a bit of leverage to be able to be a little bit more courageous, 'cause it's not a huge financial commitment to be able to try. So what we're looking at now is really more report deliveries. So taking different pieces of work and creating reports for customers around property. 

Bhavesh: Got it. 

Ellena: And we are looking at, so when we receive customer inquiries, having it run and presenting, it would say, this is what I think the customer's asking. And if you look at it, you can then say, yeah, and it can give you suggestions about a response, and you can pick which one, which you can pick that response and it can say, hey, this is a formal response, this is a less formal response, this is a very casual response, which one do you wanna select? So that's really exciting for us to be able to deliver. Again, going back to that turnaround time, saying, exceeding that customer expectation. If they've got a customer wanting to list with them, and you wanna be able to make sure you are providing the best data for them, you don't wanna wait four hours, even four hours is a long time now. In our banking and finance, four hours is half a day, that's too long. So if we can do that very quickly, and that turnaround time is reduced to half an hour or an hour, that's what we wanna start looking at. Or even if we have a whole heap of documents and it can recognize that someone might have put something on there that's considered a personal document, like a driver's license or a passport photo, we don't wanna have that information on our system. It could flag it and say, we think there's something here that you might wanna remove. That sort of speed and accuracy will be a game changer for us. Absolutely, a game changer. Before if we to do that, we would've had a had to add teams of people to be able to do that, now we don't have to. So we can keep our workforce, we can keep our existing workforce, not add to it, but deliver this exceptional customer service. So that's where we are at and the potential is huge for us. 

Bhavesh: Yeah, and I think, as you described where you've got this AI bot, taking the customer inquiry and then trying to figure out what the response should be. And you are putting that option in front of the, I guess, the teams in terms of well, what you wanna do? Which way do you wanna go about? This is what I think, things you should do. Do you see a world very soon where the bot will do it automatically and you won't even have to have somebody eyeball it? 

Bhavesh:  And when we think about AI and we think about a machine doing something, that's the biggest hurdle that we as individuals have to get through, is whether we trust it. And if we're able to trust it, then we would probably advance it. So I guess no doubt in in years to come, that will improve. But I think we're in that phase right now for organizations, where we're in that middle. We'd like it to do a lot more and we know the capability of it is to be able to do a lot more. But actually, how much are we prepared to let it do it as well as trust it? And I think that's a really, really interesting challenge. and probably a period of time that we'll go through where we'll evolve. I guess in some ways very similar to your journey you started five years ago where it was it's very simple and individuals, of course, a bot wouldn't be able to do what I do and all of a sudden to now thinking, okay, we can take that to the next level. So it's really exciting. So, I mean, what's your, from a CoreLogic point of view, what's your view on AI? 'Cause I know you talk about digital first, human where it matters. Do you kind of see this whole evolution as something that's gonna become more and more central to what you do? 

Ellena: Absolutely, so I think when we look at, so digital first, human when it matters is something that we absolutely wanna fulfill. So as I mentioned in the intro, our platforms and our products really do need to take the grunt work of helping people make decisions. So when we say digital first, it means if you need at any time of the day, seven days a week, you should be able to do what you need to do. If at some point, that's not possible, and there are always exceptions, we wanna be there to be able to help you through that. Obviously, we can't be there 24/7, but during business hours, we we wanna be there and help you through that. So almost like the agent, the chat bot now, every time you go somewhere, you'll always start out on a chat bot. And if it can help you, great. But if not, it's great when they can transfer you to somebody. 

Bhavesh: Totally. 

Ellena: But if there's no transferring to somebody, that's generally an experience you don't wanna go through again. And in the back of your mind you think, I don't wanna do that because I don't know if I'm gonna get a response. So we have to be here to be able to deliver on those outcomes that a customer is looking for. And we want to be there. So if you wanna go online and we wanna be able to help you through a knowledge article that says, hey, why is this value coming up a particular way? Or why is this valuation taking this long? And there's an easy answer for you, we wanna be able to do that digitally. But if there's something more complicated that you need to talk someone through or explain something, we will be there for you. And it's as simple as that. So technology takes the grunt work and we'll be there to finesse whatever it is that needs to happen. 

Bhavesh: So yeah, that's a great way to describe it actually, to be honest with you. I think that's, yeah. us as consumers, if we put our consumer hats on, that's exactly what you want. We want to get our response sorted out as quickly as possible. And in some ways we're not that fussed how it's done so long as it gets done quickly, right? 

Ellena: Correct. But you always look for that, how many times have you been on a website when you haven't got the response and it says, was this helpful? No, and it takes you ages and ages and then finally you get offered up a human chat or a phone number. So we don't wanna make it that difficult for people. 

Bhavesh: Of course. 

Ellena: Yeah, we wanna be there, but by all means, please help yourself first. 

Bhavesh: And you're right, it's actually a very difficult balance. Because companies will go down that path that you've described and we've all been there as consumers where we've really frustrated that we can't contact the organization, 'cause we're kind of going around the houses with these automated bots and conversations and so forth. And how frustrating that is for us as consumers and the negative impact that has on a brand. Whereas, and we all know that driver behind that is cost in terms of the most companies, it's about taking as much cost out as possible under the guise of it will make the customer experience better. And the reality, in some cases it doesn't, right. Because the customers get even more frustrated. So it's a really, really challenging balancing act of how far do you push it, where you still enable your customer to feel like they've achieved or had a great response or great experience as a result. So I mean that's quite interesting in terms of the impact. And so you've been on this journey for five, six years. You've obviously got more and more sophisticated in the usage of automation and and AI as you are now. What impact has it had on your customer experience? Have you seen any positive signs around that? 

Ellena: Yeah, so if I use an example in our banking and finance space, we were always struggling with the reactive nature of how we respond to customers. So a workflow would trigger something in that they would call us. So we've automated a lot of those queues, which was easy enough to do because they were generally email responses. So we were able to do that and we were able to schedule it throughout the day where we needed to, or even overnight to capture everything that was happening in that day, we were able to do some at night, but by and large we were able to keep on that throughout the day. And that freed up our team to be able to change from inbound to outbound proactive and using that AI, looking at particular jobs that said if this has had five interactions, we think there's something that we need to follow up here. So we created a queue that these are the jobs that we should be calling on. And we started that quite small by targeting our key clients. And we said, we are going to do this for you, we're just going to see how this goes. And we started noticing that the inbound calls dropped because we were being able to be proactive. 

Bhavesh:  Got it. 

Ellena:  And then we were then able to talk to our suppliers and say, this is how much proactive work we've been doing this month on your jobs, so then they had a benefit of saying, well I don't wanna be on that list. So they started using the system in the way that it's intended and keeping customers updated so they didn't need to call us. So it sort of had this flow on effect by us being able to free up the capacity of the team by not having to send the reactive email and being proactive and saying, we are gonna touch this before it, we are gonna get to this before they call us and then feed that data back to the suppliers. We've sort of created this continual loop of improvement. Nobody wants to be on that list, they don't want us to call them. But our benefit is that we're not then needing people taking those inbound calls 'cause they've got tight SLAs on those and they're contractual SLAs and we have to make sure we hit them month after month. So that's sort of taken that pressure off. The team members enjoy the proactive 'cause they get more control in their day on who they're calling. So we've changed it from getting an angry phone call inbound to making the proactive call on behalf of the customer before the customer's even asked for it. 

Bhavesh: That's fantastic. 

Ellena: Yeah, so that's been a huge change, the pressure's out of the team. You are in control, you feel like you're making a positive difference because you are calling before anybody's had to call. We can then tell the customer, hey, we've already called on these jobs, you don't need to call us, that's where we say we've improved that customer experience. 

Bhavesh: That's fantastic. That's really is a very real use case in terms of the sorts of things that you've been able to achieve. Now when we first talked about at the start, when you started the first part of your automation journey, we talked about people and the team. Obviously, you've had an impact on the customer experience perspective. And we talked about the idea that individuals thought, well, bots couldn't do that, so there's that whole challenge around that. Now with AI that is much higher, in terms of the fear factor. Have you seen anything with your teams or with your people? Have you done anything with the teams and people to bring them along this stage of the journey? 

Ellena: Yeah, I think we've kept them abreast of what we're doing. We've often needed their help in designing the workflow. So we've had to go to key people on the team and say, explain to me how you do it. Don't miss any steps so that we can capture everything. But it's also, they've noticed the relief. And so we've been able to do things like career progression planning, which before we probably paid a bit more lip service to than actually did. But now we've got the capacity to be able to sit, go learn other skills or do some training or have really strong conversations. Not just about performance and productivity and output, but about where do you wanna go? 'Cause we want people to stay at CoreLogic and we want them to have fulfilling work to do, not just data entry or repetitive work. And so they can see that benefit, they can see, well, you know what, some of our associates are becoming more relationship type roles because we've been able to take away that work. So whilst we're by no means near the end, like we've still got quite a lot to do and look, that email automation is gonna take a big chunk of time to get right and progressed. But we wanna make sure people are not just under pressure all the time because that just creates a lot of stress. So I would say definitely, we've felt that relief and that the team have noticed that. So then now they're open to other ideas. So when we say, hey, this bot's gonna, from your three dot points, gonna write the notes, and you don't have to write a full paragraph. They go, oh, okay, that's easy. So it's the things like that we've definitely been able to breathe a bit of life back in by having these bots work. And they tell us now if it's not working, we think something's not working, 'cause our queues have gone up. Or they'll quite tell us and they won't say in a way like, oh, I told you your bots weren't working, but oh no, they're not working, what's wrong? 

Bhavesh:  So it becomes part of the process, it becomes part of them, isn't it? The whole- 

Ellena: Yeah, absolutely. 

Bhavesh: Process that you're into. It's just fantastic. It shows that the journey you guys have been on is one where you've brought everybody along the journey with you. 

Ellena: Yeah, and that's not like, because people come and go, so new people come and we have to continuously be on that journey. So I think the minute you rest and say, I think we've done it, something will come and shatter that. So you just continuously have to tell the journey, like stay the story, why are we doing this? What is the purpose? Why do we wanna invest time and money to developing these bots? You can never just rehash the same presentation, it has to be timely, things change, and the bots can get better and better. So that 85% could become, 90%, can become 95%. So that is just never ending. And I also think from a business point of view, we get new product managers and different products or we acquire new businesses. So to explain to the business as well, that this program of automation and optimization is not competing with anyone's roadmap, but it needs to be complimenting, and that's exactly the same for the team. It's not competing with you as a person, but it's gonna compliment your role. So keep that in mind, it's not there to replace you as a human, but it's there to take that repetitive task away. And if you wanna keep doing that repetitive task, which I don't think anybody does, then you can. But as soon as you take that task away, they don't ever want it back, no one's ever screaming to do that repetitive task again. I think it is just being open and honest about what you're doing and why you're doing it. 

Bhavesh: I think Ellena, it sounds like the journey you guys have been on at CoreLogic has been very pragmatic and you've taken every step, thinking through the impact that it has on your customer experience as well as your internal staff. So based on reviewing then where you started and where you are now, what are you most proud of? 

Ellena: Oh, I think that the program is still going. I think easily some of those challenges, especially around the legal and the InfoSec and what happens with data, and I think that the program is still going, is a testament to the support we get from our executives. When an initiative takes a little bit longer to deliver some of the impact, I think other companies could have just said, nah, scrap it. 

Bhavesh: Pull the plug. 

Ellena: Pull the plug. But they've persevered with us and every time there's a little win, it's celebrated probably more than what it should. But it has built that concept of we're not gonna rest on our laurels. And I think that's probably different, tying right back to that initial conversation about operations and how far we've come. 

Bhavesh: Yes. 

Ellena: Change before 15 years ago would've been that's the way we do it and we're not changing that way. But now I think no one is really okay with just standing still. And even our teams have had to be on that journey with us, products have to be with that journey with us, that we cannot, we cannot just keep doing what we are doing. So even if we do have a process and we put a bot on there and we develop it and we can only get 18 months of benefit and then something else happens, that's okay. It doesn't have to be a long, it doesn't have to be a five year plan. If we can develop it quickly, and can spin up processes as quickly as four weeks. So we were asked just I think in May, could we have something rolled out by June 30 in preparation for end of financial year for some taxation purposes? And the team worked really hard and got it ready, July the first through automation, it was ready. Now that product need to deliver the ongoing solution for that. But for this year, for the first six months, from July to December, we were able to produce something that's not gonna be a long-term solution, but we did it, we can test it, you can practice it, and then build the right thing in the product. So we're able to do things like that. And it doesn't have to be a forever process. So I think, the long answer to your question, that's what I'm most proud of, that it's still going. 

Bhavesh: That's fantastic, Ellena, and I think, as I said, definitely a pragmatic approach towards delivering this. And I can imagine that operations teams all over the world are grappling with this challenge, this automation challenge with the advent of the more advanced AI. So the incremental things that you guys have been able to achieve, seem to have delivered the value that you were looking for, which has been fantastic. So, I mean, I guess one final question from me to you Ellena, is what's next? What's next on your horizon the sorts of things that you will do with automation? 

Ellena: I think for us, really nailing down that customer interaction. So, where we've done, we've proven ourselves in the processing, that's not a live interaction or a customer interaction. We've got time to put it through a queue. I think the next thing would be how do we have that email or whatever the new way to talk to us, whether it's an agent bot, which becomes a live chat, which could become a phone call, which could then become document sharing, I think that is that enhanced customer experience. So when you start to when you finish, we'll be able to resolve it and you don't need to then follow up anymore. I think that's probably where we need to head to. But designing that would be have everything integrated is gonna take a bit of time. So that's where we need to head to. 

Bhavesh: Yeah, and I think Ellena, that's the exciting thing about the phase we're in, in terms of the impact technology can have on what we do day to day. And I think, if we had this conversation in five years time, we'd be amazed at what it's able to do and what you've already been able to deploy within the organization, similar to the same conversation we would've had five years ago to now, you wouldn't have thought that you would've achieved as much as CoreLogic has, using automation and the journey you've been on. So listen, thank you so much for taking the time and sharing a fascinating story with us, 'cause as I said, every operations team is going through something similar in terms of how do they use these technologies that are available to them in order to deliver a great experience for their customers, but also while doing that, trying to make sure employees come along the journey. So it's fascinating to hear the steps that you've been through and that I guess, the dilemmas that you've experienced along the way. So thank you very much for sharing that story. So also thank you very much to our listeners for joining us and please do check in some more episodes of "Ops Game Changes" to hear more fascinating insights from other leaders in the field of operations about how they've overcome challenges to drive that productivity and boost performance at their enterprises. So thank you for listening and bye for now.