Courtesy of Presidio's Mladen Milanovic, below is a transcript of his speaking session on 'RPA & Customer Service' to Build a Thriving Enterprise that took place at RPA & Intelligent Automation Live.
This session will talk how Robotic Process Automation can answer on major challenges in customer service industry today
Robotic Process Automation is changing the world and a way how we work. Advanced RPA technologies and integrations are able to address major customer service’s industry challenges. During this session we will cover major customer service challenges and how RPA can address them.
He's coming from Jacksonville, Florida today, the vice-president of engineering at Brasilia. And I'm talking about Milena Malevich Mulla Then please do join us.
Milan: Milan which is the vice-president of Engineering Responsible for Procedures, RPA, Program, at a global scale.
He has immense experience in customer service as he was running engineering for procedures, national Center practice working with large size customers Will either it's a real privilege to have you with us on this on such an important topic on how we deploy implant, implement, intelligent automation, in customer service. So thank you for sharing your expertise. On behalf of our global community, we're all very much looking forward to your presentation.
Well, thank you for opportunity. I just, it's going to be good session, so looking for it.
So, all right, So just, let's just get started the real quick.
We put together a little bit of packed agenda and as, as Joseph pointed, I'm coming from Presidio. So I spend a couple of minutes really introducing you guys.
We'd Presidio, and what we do, and then we're going to get into the crux of the presentation or meat of the presentation.
Are we going to talk about the, what is the customer service today, and really how RPA can respond on those customer service trends that we're seeing across the different customer base today.
We'll talk about a couple of, a couple of different use cases.
A couple of examples, so we're gonna give you a couple of examples as well as, for, for technical audience that are listening to this, this presentation, we're going to just give you high level of high level view RPA platform architecture and how that RPA platform can interact with the, with the Contact Center, and how really, really can help independent of all different of different customer care or contact center solutions, right?
So Presidio Presidio is a global IT System Integrator, with a very, the revenue of $3 billion. We the one thing that is very important for us, the client relationship.
So, we are 50 top clients, have tenure of over 10 years with us, so definitely, our 97% of clients are making a repeated purchase.
Over time, in the last 20 years, we build a the largest contact center practices in the world, and in the last 20 years, we probably over thousand Contact Center customers, and we deploy over millions of Contact Center agents across the world, mostly in the United States, but we did the significant amount of work outside of ... as well. Interesting thing, that that's something that differentiates our approach, is really a understanding and focusing on business outcomes.
We believe that technology is transient.
and definitely, definitely different technology solutions that are coming and going and go, but what stays there if the customer need, and the desire to implement a solution that meets their clients' needs. So, it's definitely what we are focused on on Piece Mealing, or creating a technology solution that is going to meet and fulfill that the business outcome.
So, when I was preparing this presentation, I can a couple of recent statistics.
And on the left-hand side of the screen pick up a couple of interesting numbers that the Zendesk recently reported from survey more than 90,000 customers or companies across the 175 countries.
What we are seeing is at 120, as we all know, and that becomes, they pay back, customers, 20 20 was, was really something that, that, that changed the way hall our customers are interacting with the brand, and there is a 33% of the customers during the 120 that use the alternative channel, for the first time in majority of those alternative channels were, in fact, a messaging chin.
The next question and this is something that we usually get a lot, when we are talking with archives like URL.
We know that during the 2020 are the Merced start reaching us out more towards messaging channels or alternative channels, but are they going to continue, and the answer is yes, 74% of those customers answer yes, and they are going to confusing messaging to interact with brand.
Additionally, we notice that 81% of interactions.
We're all our chatbots.
And that's a very important point, because that's something that is bribing the automation and interaction we and contextual integration interaction with the, with chatbots is something, they really deriving the engagement and driving that need for self-service.
On the right-hand side of the screen, there are some numbers about the RPA.
So robotic process automation is a hot topic today.
And according to the markets, watch the CAGR until 20 24, it's around 20%.
So definitely the, the need for that process with the nation and the desire of the customers that kind of looking at the ways how they can deploy robotic process automation is significantly growing.
The Lloyd recently published a very interesting survey where they did the survey 523 executives in different range of industries across the 26th grade.
And that, they find out, in those responses, that the expectation from those executives is that RPA will increase their workforce capacity by 27%.
So basically, executives today are looking, as the RPA, is a tool that is going to help two way, increase the ability to handle the volume of different transactions, as well as increase the productivity of their existing workforce.
Additionally, the organizations that are combining RPA and AI is growing significantly.
Out of all those companies that are implementing the Automation at scale, Switches 51 or more automations. 47% of them are already implementing something that, we call Intelligent Automation.
So, let's, let's look a little bit in a customer service trap.
So, the thing is that, over the last 20 years, we build a successful contact center business unit, and we did the deploy, lots of different contact centers for our customers.
Currently, the customer service industry is the other major disruption is the new technology companies are creating a new ways to communicate and to engage with a client.
Uh, so when you look our traditional clients, they are not competing anymore with the peer groups, with the P, If we are talking about the hospital, or be it, we are looking at the financial organization, like a bank or or insurance company.
From a customer experience perspective, or customer care perspective, they are not competing with another insurance company with another hospital system or a bank.
They're competing with Uber or Amazon because their clients expect the same level of interaction they are receiving from a technology company that they're receiving, from Uber, and or for Amazon, or from any any other disruptors that we are seeing today on the market.
When we are talking with our different klein's, we were able to identify several major customer service, these trends, that are really impacting our industry today.
The first one is intelligent self-service. If you guys look at the, at the numbers, and especially the ones that were on the left-hand side, that talk about our interactions with the chatbot. Chatbot is one of the ways of all for delivering that sales service self-service channel, if you want, so, there is a huge pressure from a client that they want to take care of their problem by themselves.
So, uh, most of the customers are hearing from their clients that clients are trying to do as many transactions as they can via self-service, without really getting the getting interaction with a, with a human.
They want to be able to complete simple tasks, more complex tasks, but as their ability and adoption of the self-service channel is increasing, they want to have that comfort on the more complex transactions. And that's the reason why we feel that the self-service channel is just going to continue to grow.
So another thing is agnostic customer service. So we saw that the volume of messages jumped significantly. But when we are talking messaging, we are talking about different messaging channels.
And then we are talking about e-mail channel, we are talking about Voice channel.
So what we are seeing is a trend is that, Hawaiians, they want to interact with the brand or the channel of their choice at anytime. And they don't want to be forced to change a channel.
So, what that means is we have the client interacts with the brand via their why, our brands webpage. And there is a some transaction that cannot be completed.
Or there is a some question the customer need to do, customer has, he or she wants to engage with a bot or with the human leveraging the online chat. And if that's not available, then we need to do the switching channel. And then we have to our cell phones or phone calls.
So, so this is something that we definitely, the customers, definitely do not appreciate it, the switching channels.
So additionally, you know, when we are talking about a rapid and flexible feature deployment, there is that pressure from the client is coming from the clients to add new features and new functionality.
And today, you know, it is really difficult for traditional commercial customers, go have a large squad, all full of developers to be able to deploy those features. So that's where we feel that rapid and flexible ability to rapidly inflexibility, deploy a new features, develop those features, pilot the features. And pest features is very important in, in, in a cost there today.
From the, um, formula can contextual and personalized customer service, that the buzz word that is, that became through, especially during the 2019, in 20 20.
And the goal is really to what customers want is the ability to understand what their client clients do, what they how their clients to engage with the brand, and how those clients are served, and how they would like to be inserted.
So, Bill, this kind of, first half of the trends are really something that is putting the pressure on technology.
Another trends, and that's, like work from anywhere, and gig work, and engage and empower staff and increase the age and efficiencies are hitting in heating directly into the overall workforce transformation motion.
And talks about the ways, how we can empower employees and polkas them, and enable them to be more efficient during the customer interactions.
And instead of thinking how they are going to use technology solution to solve the customer problem, they need to be focused on our customers.
So, we, on our side, as a technologist, and as a, as a people that are building or bringing those technology solutions to our clients, we need to ensure that aging population is able to with effectively and efficiently use those, those applications, and being focused. Not on the technology, not on an application, but on the client.
So, when we talk with our client, we are seeing that lots of clients, internally, and consultants are trying to really throw different solutions in order to understand what, in order to address those customer service trends. So, we're seeing proliferation of the API infrastructure, especially on the rest side.
Our customers are investing in a boat. You can see castle and to empower that. That's remote workforce. There is a lot of buying, and acquisitions, or, or customization of CRM side, building a knowledge and inside the product. And the building and creating voice and chatbots that have a natural language understanding, and ability to communicate with the cloud, with a client, using B and L use.
But, when we look, all of those efforts, we are, we feel that those efforts are very siloed.
And they are just addressing one or couple of the challenges or trends that we are seeing today, and what we are seeing is that that labor is not balanced, right? So, they cannot, they are not making a difference in the world.
Oh, Presidio, came, came out with a Workforce Transformation Framework, where recombined this kind of unify the different approaches around that, the Workforce Transformation Framework. And the center of that the Workforce Transformation Framework is robotic process automation.
So, let's just kind of briefly look what, when we are talking about RPA, what we are alone, what we are expecting from the robotic process automation platform.
And how that a robotic process automation platform, I can really respond on them or service challenges.
When we double click or an on path, the robotic process automation, we expect that the, that RPA platform has a low code, or no code development environment.
Has the ability to bring into the automation loop of practical AI. We do not expect Skynet.
We do not expect the robots that are going to completely remove human and human decision making process, but we do expect a platform that are going to be able to bring into the automation, workflow, machine learning, natural language, understanding, computer vision, document, understanding, and such.
And, at the same time, there is that, that notion around a human, in the loop. Because, again, we do understand that, those algorithms around the practical AI have certain limitations. So, we want to be able to leverage majority of the automation potential.
And then, we doubt, decreasing automation potential, although the human, and that human intelligence, into the decision making process, where it needs to be, and then human, can make that decision. And then, again, hand over the automation back to the robot, and the robot can wrap up the process. So the goal, really, is that we want to have the flexible automation platform that is going to be able to really have continuous automation journey, with, potentially, a looping in the human and and leveraging the what humans are better. And humans are best in making those those decisions. Right?
Again, unattended and attended automations are must, because, especially in a customer care or in customer service, tended automation has its own place because then we can see a, a really good co-operation or collaboration between the robot that is going to do those structure, mundane tasks, And the human that is going to provide input, or additional activities for attended the robot to perform.
It will look a little bit deeper and kind of double click on each of those components, and see how every every component is addressing those, those customer service trends.
This slide is trying to really summarize, and, again, we touch on now, on the low code or no code.
Development environment, they're extremely important, because finding skilled labor, or skilled developers that are going to be able to enable brain to add new features, is very difficult and very challenging. So, in order to empower businesses to make new features, make new, really seized, and make those good workflow, we need the environment in which they are going to be able to build this very quickly and deploy very quickly. We already touch on a practical AI.
We already touched on the on the human in a low and an attendant automation as well.
But it definitely, working together, especially from a practical AI perspective.
And human in a loop, can really create a collector of deaf, different use cases that we can expand And provide a true selves ciao for our end customers, and from that perspective really increase significantly efficiency and increase the customer experience with the interaction with that specific brand.
As I said at the beginning of the, of the, of the, of the presentation, there is a There is, yeah, brief diagram for more technical team team members to kind of look how that robotic process automation can interact with the different, the different components in the contact center. And so, what we are seeing is, let's just kind of start from the bottom of the slide is, cab unattended automation that we usually use for Doze backend processes.
And where that on a $10 donation from a customer service perspective have a huge impact is infecting the self service.
So what we can do is that we can, we can leverage A We can leverage the ability of RPA platform to integrate with external chatbot, boycott, e-mail, phone platforms or communication flattens and triggered those processes and basically have a robot execute an impact with the third party application in order to fulfill the requirement or request.
That was, it was pushed by a client that is interacting with the brand.
On the opposite side, there are a candidate automation, as I mentioned before.
Abandoned information has that power, too really M power contact center agent to be more focused on customer. Right?
Because I attended automation can scroll through the multiple pages, or screens in the application, too, get the information in front of the center agent eyes, or it can faster do a screen pop, or it can facilitate faster and more accurate, the completion of specific task, if that's a closing an account, or something like that. So, that's honestly the the selected the platform. And we do lots of business with that with the UI path.
We have the ability to leverage the CTI integration with the Contact Center, and IBR stand, and chat and voice bots, and attended an attendant estimation in order to really accomplish that goal.
At the same time, upended Automation and attended the robots that are leaving and work together with a contact center agents. They can and they should interact with the third party applications in order to complete task And wannabes closing the account, opening the account.
Taking that away waiving that there's some kind of late fee or something like that.
So the deferent, that there are so many different use cases.
And the speaking of use cases, this is the, this is the one of the use case, That this is one of slide, that we were trying to summarize different use cases that we are seeing. And we are addressing with RPA. So the first one is the self-service. And that's kind of given.
And from the self-service perspective, again, majority of the traditional self-service approach is like, hey, where's the API for integration?
We all know that that's a first, that we definitely want to leverage API infrastructure, if it's available.
However, there a situation where, as I pointed out, APIs are not available, or APIs are very expensive to get.
Soon, destination, Robotic Process Automation platform can really help us on a backend, leverage, maybe UI, or leverage some of those native integration, where our platform already has in place in order to complete selfs therapy.
Additionally, through the different the, let's say document understanding, leveraging the AI models, robotic process automation, give this opportunity, really on the reach, self-service experience for our customers, and provide us that we can expose more features or more functionalities through the self-service channel as well.
From the agent efficiency perspective, multiple applications. and this is not something that we are, that this is nice for one type of client or another across different industry verticals.
We are seeing contact center agents should be rolling Chair Swiveling between application one, CRM two, the internal app, in order to provide a consistent view of the customer, or to provide a to collect information in order to communicate with a client.
That's where we feel that attended automation has an ability to a cow, because all those swiveling from one app to another, from one document, to another, is something that robots can do efficiently, and much quicker than humans can do. Human can poke. When interacting with a client? While Rob on a background? is collecting the information or collecting the specific?
Information about the previous transactions or previous interaction and presenting that income?
In front of the contact center agent.
We don't want to forget the, another technology stack in a contact center, which is the center operations. So, there is just so many different, the different stakeholders within the contact center business. That can benefit from the automation on the traditional onboarding and off boarding.
And, and kind of keeping up with the volume of all those tickets, if, if contact center is experiencing the hiring or, or, or attrition in a contact center is very high.
That's where we seeing that RPA is really benefiting customer service as well.
Same story around the complex applications, and that kind of complex applications in agent guidance go go hand in hand.
So, when we have a highly structured process, and I mean, we want to have a contact center agent, the train faster, we want to give them those call outs or kind of guide the agent through the how to complete the transaction. How to interact with the customer.
The best, the best example for that is the contact center claims, so we see that there is a high propensity of automation.
And in a customer service team, intake from our insurance claim intake perspective, where we can create a call outs, we can create the next best action based on the, on the ... of the selected church or a customer record and such.
And lastly, upselling cross selling.
It's it's something that we are seeing in the context that are more sales oriented, so in that situation, we can we can have, again, contact center agents will talk to the client.
But in a background attendant, the robot will pull the information across the different accounts, all previous purchases, and based on that leveraging machine learning algorithm that is developed in house and upload in the in the in the RPF Platform.
The, the contact center agent, who's going to get the information of what our product?
Or services that customer might be interested in. And then, he or she can pitch that to the customer, that it's already on a phone, or on a chat, or, or, or whatnot.
And let's not forget, again, my favorite, favorite thing is best thing now.
You cannot have a, you cannot have a successful implementation of the contact center or implementation of any of the new features unless you will have a, everything is tested and avenues that is operating as is, and especially when we are now talking about the comprehensive testing across the multiple channels.
You have two options.
Option number one, having the people do that and go through each one of those call flows across the chat, e-mail and messaging.
Or you can leverage RPA platform to do autumn's self-service testing application testing, and that, and do that, that testing across the each channel by and making sure that all those test cases are path. And we, we have something that we call proactive contact Center testing, which is every morning. There is always some contacts, tenant admin, that he's going to call number and kind of try to get to the agents from that everything is working. That's something that we can proactively work with the robotic process automation platform.
This is some of the examples and in a contact center. So agent, in order to, kind of already talked to touch on those. Where agent needs to kind of deal with six or more applications saying the wall. At least 2 or 3 log ins per per work day.
So, we were able to really build some, some robots, that bill, that will help agent.
In general, we say eight minutes per agent.
Per day, per agent, on that specific specific use case. I'm not going to go through the trawlers, those, those.
Those kinds of examples are tricky, self explanatory.
And I believe that each of the customer service leaders can, that can find a case or use case or challenge that they are dealing with. That probably robotic cross function or intelligent.
The robotic process automation platform can, can address and provide a positive value.
So let's wrap up real quick. So key takeaways, perspective.
RPA is here.
I know that there are some articles where RPA is that, though, that are saying that robotic process automation is that kind of falling down the hype and everything. But the process automation is there.
In the end, when we are talking today about the RPA we are seeing is that.
Lots of companies and early adopters are not in, in, in a phase of scaling the automation program up.
But what is very interesting is that the today, a robotic process automation is strictly speaking, robots doing that transaction in and out is not the thing anymore. Where we are seeing impact on my May all major KPIs is really intelligent automation. So, again, it's not the hype.
We already have a data science, the scientists build machine learning models that have proven in the practice, or just comply for rubin RPA technology that and proven data science and the algorithms that we have and creating the automations that now can do more and provide more value to add to a client.
Omni channels, omnichannel is there.
It's increasing and omnichannel interactions are here to stay.
It was, uh, recent. I can see where, where Contact Center Executives, this expect that contact contact Center calls are going to drop.
I do not believe that they're gonna fully draw their complexity, are going to increase, because if customer is not able to a solve their problem to a self-service channel, or through the chat, or e-mail, they are going to call, and those customers are going to be upset. So contact center agents, or need to be on a on a top of their best game.
So, again, it's very important. So, omnichannel is there and we need to find a way how we're going to make our contact Center agent efficient.
Because they need to be focused on a customer experience.
Hi proclamation platform can have significant impact on entire customer service value chain. Because now we can harness all that data to be having a different CRM, is a different customer journey platforms in, a: in a, in a different report.
Because, now, we can do a couple of things.
We can build the models and believe our decisions.
Based on the data that we have, and, and based on my experience and Presidios experience, there's a lot of data stored in all those contact centers over the years.
We also, we also can deploy more features through the self-service channels, document understanding, we can leverage a natural language understanding. We can do computer vision and basically, M power, organization to provide those additional features. And the impact of the really low value calls or all the low value interactions to the agents, and have agents, when really, we need to have that.
So, anyway, hyper donation platform can positively impact agent productivity and overall customer experience by really doing this.
efficient, the agent, is more focused on the customer, and on a customer need less, and he or she will be able to provide, really a good customer service. So, I want to thank you for for being with us today.
It was really pleasure talking to you, and just say, I think that we can kind of kick off the the Q and A session.
Terrific megalodon, what a, what a, what a great journey and review of intelligent automation in customer service. Very good insights. Thank you for, for sharing that openly and being very methodical and the way you shared that.
Which is very helpful in understanding the challenges and the opportunities. I start with the, there are several questions from the audience, I'll get into specific ones, This is a general question, since you have been on this, and this side of customer service, and intelligent automation, for some time.
Has there been, have you done studies yourself, or other third party studies on the, on customer satisfaction related to bots?
And what, what that what that's looking like?
Because I'm gonna see a very biased opinion that I have because every time I interact with the bot, me, I mean, I, it's not a very good experience most of the times because it sends me to information that's not really related to what I'm looking for Or God says isn't like to the terms and conditions document of certain contract of some sort.
And I know there has been a lot of, a lot of development in this area.
two part question: one is that, what is the evolution on the quality of these interactions, And, in the end, what, what do organizations can do behind the scenes in creating this bots, to make them more useful?
This is an excellent question, and thank you for asking, because, again, it's a journey. So, when we start that a 2007 deploying, like natural language, understanding IVR, we did that thought that that's going to be a, the killer application for, for customer.
Sorry, I think that we all, both practitioners and consultant, tried to bite off more than we could off with the technology we have in hand, with the chatbot. And, what we are seeing with the organizations that didn't do the right thing, is A, decreasing the customer satisfaction when we wanted to put a more complex transactions over to Chad.
What is our recommendation for all clients that are starting the chatbot journey, or voice blood journey is really start the smart, I don't want to even say small, but Touchsmart, where you are going to?
Canva, all the ah, more structured, Much easier interactions to a bot.
Now, if you, if customer is not able to solve or serve self serve Excel with the bot, you need to provide a handoff to a human.
But, most important thing is it needs to be a contextual handoff.
So, what that means is we are seeing lots of clients across the different industries are deploying a year siloed chatbot, frameworks without communication, or connection to a rest of the customer service systems or contact center.
So, when that contact center agent receives your chat, he or she doesn't know, what did you try with the bot, and that's the reason for frustration. Because now we need to go all over, it's the same thing, Just say, when you are up, when you are calling your bank, and they ask you to enter your account number, Social Security number, and date of birth, right.
And, then, you get on a call with the person, she asks you to verify your identity.
It's the same thing, You get frustrated even though that person, That's their SOP, right.
But, that's what we are seeing as a, as a main problem, and when we are talking with our clients, it's really crawl, walk, run, identity, low hanging fruit, push that, measure the effect, measure the engagement, measure customer satisfaction, move on, but always, always ensure that you have a reliable, contextual handoff to a human.
That's a very good example. I think Banks, healthcare, is also another notorious industry that you have to say the same thing 3 or 4 times.
And There's a follow up to that. I'm curious on your experience and development of the technology and the implementations in the industry, are their mechanisms for tracking the quality of interactions with bots? I'm into companies have a way of saying that, Yeah, you know what, this is really bad, I mean, and the, Or, Or, or, it was really good. But, is there a way of tracking what's going on in those interactions. Yeah. Yes, in the very technology, did, provide a way that we can, that we can track the efficiencies of the bots, both on RPA side, in both, on the traditional chatbot side, the natural language understanding. And those thoughts are nothing new, you know. The big thing for natural language understanding technology is, is here, since the late eighties, it was just very expensive to deploy in a commercial purpose. It, So, we'll start there.
The problem is, a, again, it's how the brain approaches to the initiative of automation, both on a bolt of both, in both, on, on, on a chatbot side, or, or, or natural language understanding bot.
So, we do have a, we always to recommend, with creating those personas, understanding your customer, and then, based on the experience, we create those dialogs and create those engagement ways, how we engage, how we expect that the customer is going to engage with the, with the bot.
With the, have a personal experience.
When we were working with the big utility company down, utility company, where we did the voice, the natural language, voice understanding platform, we're, we have a user group.
And we'll literally rain all those interactions with people and getting their feedback.
That type of engagement is something that you cannot get all these.
But what you can do, though, is based on the experience you can create initial dialog and then use it tools to see if they are on the any other utterances, bolter spoken or written that customers are asking because there's different. People will ask for the same thing differently and then do fine tuning. But that's a, that continuous improvement process, is very important in any automation journey, in general, both on a chat voice, and they're trying to Sandy. And the robotic process automation, especially intelligent process automation, because the more than a platform or IQ iPad, has those feedback loops where you can get your, get your Model three train when you're ready to make it better. Or document understanding data extraction, and such.
Excellent. There's a comment here that I should share with you, because I think reflects the opinion of a lot in the audience.
The way that you provided, you know, your vision on how RPA in customer service should be implemented, was very elegant. And in the end, I think that, as consumers, we support the vision that you share with us.
But there is a perception, that the way that most organizations, organizations are actually implementing it, is different from the way you propose hearing your vision.
I'm curious about why there is such a disconnect. What are the challenges, because I'm now that you're coming into those organizations and advising them to do the right thing, and then it seems like they're ignoring a lot of your advice and doing some other things. It's a dynamic that happens that organizations and they think they know better, but they really don't. And so how do you overcome that in your clients? Listen, it is a, it's always a conversation.
There is a, on one side, you have a, yeah, uh, there's a budget constraints, there is a different opinions, there is they are predefined technology constraints that you cannot, you cannot really overcome, but at the end of the day?
I have, I'm going to have a very good customers.
They take us as a trusted providers and trust that consultants, I would say.
So, majority of our clients that really take recommendation, my advice is for end clients, end users, do your research, even though making the chatbot or doing the robotic process automation is simple. It's something that you can do inside, in house.
There is a reason for hiring in talking to a consultant because of that journey that we just talked about, and those kind of tribal knowledge that we have across the different industries.
And from the users, like yourself, those horror stories that we can avoid by very by good implementation.
Milla, than we are out of time.
But I want to point out that we could go on talking about this for a long time because you're very down to earth very you're you have a strategic view of the opportunities here, but very tactful also in the way that you approach it.
And you do not sell to acknowledge your selling solutions. And the, and the, and I think that your approach, and the way that you weave it together, is very effective. And certainly a very compelling. So thank you for doing such a great job and articulating your vision and the implementation of what, what greatness should look like in customer service. When it comes to intelligent automation, thank you so much for taking the time to sharing your expertise and your insights.
It's a pleasure. Thank you very much, Appreciate it.
Ladies and gentlemen.
That's Latin, Milan, Milan, Milan of which I can see that my Serbian is not that good, I guess. And sharing his wisdom and expertise on RPA and intelligent automation, targeted customer service, wonderful journey really. I asked you to go back and rewatch this presentation and pay attention to the flow. There is lot of great insights there on how intelligent automation should be done in the correctly in customer services. Well, let's take a look at what awaits for us in tomorrow's sessions. We're wrapping up today, and tomorrow is our final day. I want to remind you of a few things that you will receive the recordings of all of these presentations in the next couple of weeks. I think most of you know that, at this point.
Also, remember that you can interact with our speakers, and and you can ask additional questions commentary on LinkedIn undermining Joseph Barrows. There was a posting on this conference, and you can see many of the speakers and the participants comments already in there. So, you can feel free to engage in that.
We also want to remind you, that the next conference, that we are going to be leading globally, will be, the Enterprise Architecture Live Conference will be done on this similar channel, but you have to register separately for that.
That will be on July 13th through July 15th, and there is a more technical aspect of that, of that, it's focused on enterprise architecture, but, as usual, we'll bring, Speakers will discuss the technical aspects, and also the organizational governance, cultural aspects of technology implementation, because you cannot do one well without the other. Now, as I look at, our final day together tomorrow, we have four outstanding presentations from industry leaders. We're gonna kick it off with the President for the Institute for Robotics, Process Automation, and Artificial Intelligence. And he's going to be giving his perspectives on the state of the industry. That's going to be followed up by a leader at Tech Mahindra, who's going to be focusing on conversational artificial intelligence. What are the trends were the solutions were the best practices that we are seeing in the marketplace today.
And then the final two sessions will be by industry leaders, global industry leaders who are in implementing RPA at scale. We're gonna first gonna have the Enterprise architecture leader from Mondelez International aura but try to charge you is going to be sharing with us the RPA roadmap for an enterprise architecture perspective. It's a good segue for the Future Conference we're going to have. That's going to be a deep dive in our enterprise architecture.
Again our leads on the Enterprise Architecture for Mondelez International, a major food company.
Now we'll wrap up with a major application in finance and we're going to be talking to the director of Quality and Transformation and Morningstar, financial services, and Morningstar Financial Services as being an incredible transformation that includes the implementation of RPA at scale. So Margaret tomorrow is going to share with us the control of his robots. The designing an effective RPA governance program specifically. So you do not want to miss the sessions. And you do not want to miss Margaret tomorrow's session if you're serious about real governance, effective governance, and implementation at scale in a large organization.
So, without further ado, let me send your wave for the rest of your day. Let me thank you for participating and engaging. The questions have been fantastic. The interaction is high class, as, it usually is expected from you, very qualified audience. And it's a real privilege to be here with you Wherever you are in the world. Have a wonderful rest of your day, and we'll see you back here tomorrow for the final four sessions. Thank you very much. Have a great day.
Vice President of Engineering,
Mladen Milanovic is Vice President of Engineering responsible for Presidio’s Global RPA Program. Mladen has 20+ years of experience in contact center industry leading presales, post-sales, project management, and custom application development groups. In recent years Mladen is focused on workforce transformation and automation.
September 07-09, 2021
October 12-14, 2021
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