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This data is probably one of the most critical elements in so foundational to not just our but so much of how business is ran today. It's a challenge for a lot of companies. There's a lot of gaps in data. There's a lot of quality issues.


What happens when the world is forced to hit pause when cities, states and entire countries come to a screeching standstill as the world struggles to combat an invisible virus? Companies around the globe are fighting back. The wheels of innovation are already turning.


Faced with adversity, companies are turning to intelligent automation to not only help them overcome these obstacles, but to ensure they're prepared to fight whatever's next. Today, robots and machines are helping humans in almost every workspaces activity. Airline industries use them to fulfill cancelation requests at scale. Pharmaceutical companies utilize these tools to ensure customers can refill their prescriptions on time. Intelligent automation is a combination of robotic process, automation and artificial intelligence, and it's fundamentally shifting the way we work.


Today's guest is Marissa Cogan, our the head of automation advisory at Cognizant, one of the world's leading professional service companies that is helping change the fundamental ways that we work. Marissa and her team are spearheading the future of work. She joins me on today's episode to discuss how data is serving as a foundational surface for these technologies and where automation is headed.


In today's episode, we discuss robotic process, automation, data, machine learning and how businesses can best think about and utilize these technologies. Let's jump into today's interview with Marissa Kogan.


Our this season of Hidden in Plain Sight is brought to you exclusively by our friends at Splunk. The Data to Everything platform Splunk helps organizations worldwide turn data into doing its time for data to be more than a record of what happened.


It's time to make things happen.


Learn more at Splunk Dotcom or by clicking the link in our show notes. Marissa, welcome to the show. Thank you. I'm excited to be here right back at you. So I would love to get started and just learn more about what was your origin story that led you to the work you're doing today? When do you feel like it got kicked off? How did you first get interested in technology? Take us back to the beginning, if you would.


Yeah, absolutely petrified. Little traditional two than maybe some others. When I was younger, I was always into science and technology. Those were the my favorite classes in school. So my degree is actually in engineering. But when I got into the workforce, I was more into operations, a lean Six Sigma process improvement, and I found a real passion for it. And really what got me into that piece was I liked making things better and easier for people, because everything about that is how do you make things leaner, simpler, less waste in a process.


But I always remember there was always this list of things that we wanted to tackle that needed technology to do it. And as I continue to go through different roles, I started to get involved in those types of projects with the technology teams and even picked up a program where we were driving data and analytics across the entire enterprise. And I found a real passion for it. And I started also noticed there was a bit of a gap between the business view and the views.


But if you really looked at both sides and brought it together, there was just a really great opportunity to apply technology and get business outcomes. And that's how I almost stumbled a bit over into the technology space officially in the company that I was in. And we started putting this automation into practice. We started bringing to the table and I saw the impact that could really be made from it. And that's what drove me to start looking into opportunities to do that.


More at the start up for about a year was a tech company. And then I started to talk to Cognizant and I realized that it was exciting to get the opportunity to go help others, put this into place for their organizations and really be able to bring business together to get some really positive outcomes for them and drive value for the organization. Right.


And so your title now is head of advisory for the automation practice at Cognizant. And when some folks hear that they might be thinking just robotic process automation. Could you unpack that title a little bit for us and explain about your role and what it entails?


Yeah, absolutely. And it's funny because they actually just started a little bit with robotic process automation, but it is so much more than that. So for those listening in this robotic process, automation, it's really using technology and code to help be able to do work that the people would typically do other rule based stuff, downloading reports, uploading data entry. A lot of the what I often call the things that you probably don't like doing in your role and you wish you didn't have to do those are a lot of spots.


We go we try to target with technology to address them, but intelligence automation takes it even that next step further. And you're starting to look at processes end to end on how can we apply technology to help lift people out of the process that doesn't require decision and strategic thinking and put technology. And to think of that is if I give a simple process almost anyone can relate to. If you were to buy something in a company and you get this invoice and you have to get your product in, receive everything, look at, make sure it's right, you then submit things to go get paid.


Most of that process is just entering information, keeping it in, moving along this value chain and then ultimately paying your vendor. The end of the day, almost all of that could be automated. Instead of people helping to move everything left, right and key information, we'd rather put them in a position where they can add value back to their customers. Look at how do you enhance a product? How do you add more value back new products, new customer experiences and more strategic thinking.


And so that's what we really help our clients do and we're helping them think about how do you, one, connect these different technologies to make this happen? It is very thoughtful. We have to think about the ecosystem there and we have to think about what's the outcome you're trying to achieve. So we work with our clients on how do you make those connections through data intake, getting that information. And like I mentioned, our I handling exceptions, you typically need data to do that.


Machine learning technologies. You're going to have to add in analytics so that you can actually get objective data and information and then looking at how do we move people along. The journey is something we spend a lot of time doing. That's actually what my team spends a lot of time working with clients on is how do you think about this enterprise wide perspective? How do you ingrain this just into how people work? So people think of automation and this technology is another tool in their tool set because there's this top down piece we can have.


You say this is an initiative we want to do. But if you really want that stickiness in an organization, we have to also think about how you bring the people along, get that grassroots piece of the. And we help people think about where are you at today, where do you want to get to, how can we either make you more efficient, maybe even think about disrupting the market you're in, and then move you along that journey by using this technology to do so?


So many people are familiar with terminology like digital transformation. I'm curious, when you start working with clients, this is basically like an automation transformation. This is a mindset transformation. What are some of the steps or processes that you and your teams do to get this started? Yeah, absolutely.


So there's a couple of things we do. We always first look to see where they add both from people. So people used to working on technology. What's the culture of your company? Current infrastructure? As a question we need to ask, are you on Prem? Are you using cloud technology? What do you have in-house today?


And then as you start to move through this transformation, it's about connecting those dots for them. How do you apply that technology in a strategic way for the organization? Because if you just go and you put the technology and that's step one, but you need to drive the adoption, especially what we do today for digital transformation. It's a very business process, focus of a two. So you have to have the people who are doing the work in finance or doing power delivery.


If it's an energy company or if they're working clinical trials, we're going to have to bring them along and make that connection for them. And as we move this through, it's applying that technology in a seamless way. What is the art of the possible? Where do you want to go? Let us find those technologies, the right fit to your organization and what you're trying to solve and implement them. How do we then lay that plan for the people?


This is a new way for people to work. Technology isn't new for people, but having to have a call bot or a digital worker. So digital work of being something they use is maybe RPK plus an OCR technology, maybe plus an analytics combining those technologies through this digital worker, alongside your other employee, and maybe they've been handing off work. You have a person working with a digital worker and now a manager that has to manage this worker and their employees.


We have to also lay that plan for them. How you to move the people and really critical. So what we're doing is we're working with our clients on what training programs do they need? How do we help scale from a technology, but also a process standpoint is important. How are we going to make sure that if you're going to upscale an employee, you also think about your digital workers and even laying out plans with our teams because we know in the future career path is going to look different for people.


They're going to have to have different skill sets as part of their resume when they're coming in or we're going to help them get there. And for the most part, it's a lot of helping people get there and thinking about what those new roles, what roles need to look like in the future and then bringing both of it together for that digital transformation for the clients. So when it comes to robotic process automation, where is this at in terms of awareness?


And are most enterprises familiar? Are they implementing it? How far along are they on this path already? If you could just kind of tell us where you feel like the industry is at right now. That would be very interesting.


Yeah, for sure. The industry it's interesting. This has been a really hot topic. I stumbled into this automation space back around twenty sixteen is ARPA really started to get some legs and start sprinting at this point. And you'll see a lot of companies in the industries that are all touching it. Every industry has our in their conversations. They're realizing now they need to move to intelligent automation, just not robotics, the stuff that they're pushing for, that enterprise wide digital mindset.


And it's really exciting because I guarantee you, every company probably think about on a daily basis, whether it's in retail or grocery store. You go to an airline in an airline that we used to book more flights with in the past and hopefully in the future. All of them are thinking about this and applying it today. And so it's a really exciting spot to be in. But at the same time, there is still a lot of growth. Most say they haven't felt like they would really say they have scaled their program yet.


And a lot of that has to do because it takes a lot of effort to not only get the technology in, but then move an entire organization, like I was mentioning before, that change management, the education pieces of it, just if I were to add as well, and this technology, one of the things that I would notice a lot of times the conversation will start with this is it's a nice gateway to all things intelligence, automation, and especially in the business process, automation, space, because it's a little different than if you're going to go put it into a system or put in a data lake that's a little bit more into the side of the house.


When you're doing business process automation, you really have to bridge that gap between your I.T. teams and those business teams. And ARPA is one that the business side has really taken a liking to because they understand it. They could see the application. It's quick. You could put some production just days. And then something people really looking for such a really nice lever to also really increase the speed of your automation journey. Fascinating.


And one of the examples I want to dive into is recently wrote an article called How Intelligent Automation is Solving Unforeseen covid-19 Challenges. So let's kind of unpack one of these examples here about the airlines, about how they're using our tools to handle this pandemic. If you could kind of help elaborate what's going on there. I think that would be fascinating for our listeners as well. Absolutely.


And so we we're working with this airline for some time, actually. And when it happened, we just saw this massive impact to them. They were probably one of the most hit industries out the gate because everyone was stopping. Travel orders were just being shut down. And we also then happened naturally is just this massive influx of cancellations, requests for schedules, wanting to get a credit depending on how people had purchased flights. And to do this, the team looked at the volume and they said, we just don't have the manpower.


They had over a hundred and twenty thousand requests come in in just one day in the past. Used to clear about three per month. Well, that's a four thousand percent increase basically overnight. And the change is that I don't we can't get through all this fast enough. And even in this space, there's actually some laws they have to follow. So they actually need to respond in a certain period of time back to their customers to. On top of being, how do I handle this volume?


They're also trying to make sure they're able to meet the regulations that they have to follow. So we sat down with them and said, look, we work with you. We know the system legislative plan to get this automated for you. And what we actually been told him is, look, give us less than a week. Give me like five, six days. We can get this built. We can get to these 80 percent, 90 percent of the way there.


And then we'll work on the last final, the exceptions piece of it once we get it into production. But they'll give you the lift that you're going to need to be able to respond back and address this issue with the clients. And we were able to pull it off. We it was nice because our teams were in multiple locations. So we did a handoff, almost like sprint relays. You're doing handoffs day and day and night to keep this going.


And we put into production in six days for them. And what's really cool about it is this one. But in a couple of days, actually now there's the volume in one day that used to take an entire month to do. And so the team is thrilled because they're going to use this moving forward. But the other thing it was those people doing that work got redeployed on to more value added work for for that company. That airline needs a dozen other concerns that they were facing.


So they're able to put those employees into other spaces to be able to address that work. And we've actually continued to expand even past that article. We're helping with other areas like named information updates, because a lot of those to be actually be able to go back and reissue some of these for future use to make sure your profiles are updated online. So we've helped them address other concerns as we got this first one going to be able to continue to add that value back to this airline.


Really, really interesting.


And I think to when it comes to data, I want to get your take on how do you go about assessing where a company is based on their data. So are you obviously you're looking for how they're collecting it, cleaning it, arranging it. What can companies do to kind of be very savvy about their data so that they're ready for RPA or they can allow RPA to better work for them?


Data is probably one of the most critical elements. So foundational to not just there, but so much of how business is ran today. And to be honest, it's a challenge for a lot of companies, a lot of gaps in data. There's a lot of quality issues, a lot of that driven by different things, some of it's manual. And think about when you type in an email how many times you get the little red squiggly for an auto.


Correct. Or at least I do say that, yes, you type fast. I also think texting and having the shortened speak that we use sometimes also throws up, throws us off in our typing. And when that's what you do day in and day out, it's easy to make a mistake and have a typo and miss a number or spell something wrong. It's just human nature. But with that it impacts your data. And the other piece of that is, is that there's still a lot of information that's manually scanned in because some of these organizations that have a manual like mortgage document that they had to have signed or even when you're joining a company, you've just download scan with a signature back in.


That's a lot of extra information that someone has to read, find information and then keep it. So it also leaves a lot of room for gaps in the information. A lot of companies have been growing by acquisition and merger. With that comes the need to be able to ingest the systems from that other company. Merge the information, clean it, synergise it, a lot of times things aren't called the same things in both companies, so you end up with a massive undertaking and a lot of companies also chose along the way not to always do that.


They actually run multiple systems. That's how you go and you speak to some of the bigger companies out there. They're going to be running two, three or four hundred systems. And that's a lot of information to have to get through. So when we're working with companies on these data platforms, we do assess where they are at on that journey. Are they still using data in warehouses? Have they gone to cloud? Most are trying to shift. The clocks are trying to get more seamless in how they're able to ingest and use data.


And a lot of people are looking for that real time frame. That's that's what people want. Is that real time in the moment, almost in the instant that you click the button, you want the answer. And so that's what people are trying to get to. And so we look to see where you are today, how many sources of information, how good is your data? And then we lay that plan for them, because what we want to try to get to is the ability to look into it and find opportunities.


We want to be able to use data insights, have objective conversations on where do we need to target for either cost optimization, maybe how to generate revenue, maybe also really by revenue leakage because of a process not working the way it should. And then as over to apply more intelligent technologies like Emelle and I, a lot of times you need data to feed those models to get the insights. And so do as we see where you are today, what kind of gaps we need to fill and then lay that plan for you on how to improve the quality of data.


How do you get more data? And even at times you can use our data, feed back information into your process to fill some of those gaps. So you're able to use that information in a way to go back and improve the quality of your process to.


Are there any other examples of companies that you're working with or maybe cognizant where you see a data modernization happening or type of best practices emerging that you think is worth sharing and kind of amplifying?


A couple of things is the best practices plan, the plan to address it a lot, try to still kind of muddle through with the Excel files and data downloads. One of the biggest things you could do and let me give you an example where I see some best practices of that with a client is is doing this with automation, actually is that as we were building their automation program, we actually put in metrics for them right out the gate to see where how was the data coming in on the bots that we put in?


Because what happens is if you're missing data, the bots not going to be able to run. So it's going to cause an exception. So we built a command center, so they're able to see that information and then they select a view then for their business stakeholders. So they're able to go back and either say, I have a process gap, let me go work on addressing them, or I know I have this exception. Can we use the bot to actually take and feed that information back to that?


Information was not coded, right? So you end up finding a way to fix the process and then you're tracking to say, I have a theme here. Let's go back to the root cause of the problem, which is very important. And then we feed that information also into the IT teams because the teams are working on that data strategy. As we move into especially data lakes and and cloud, you're able to actually look to see where do I need to work on improving my data and where it's coming from, the source and the quality of it.


And so by linking those teams, we're able to see that impact. And using the last piece of that is it's important to actually use that information. A lot of times you'll see this information get put into dashboards and then people say, well, I don't agree with that, no, because I've always seen it this other way and an excel over here, it's important to go back and use the data at the source so that you actually start applying those fixes at the root of it versus having to have teams go and massage information on the side.


So that technology to help with that, too, that we can talk about. But really, the idea is you want to be able to find it and fix it so that you're having this objective conversations and are able to lift people out of that annual exercise of having to go back and clean and cleanse data. Right.


And when it comes to some of those technologies or developments and machine learning to assist in that regard, are there any recent developments that you are particularly bullish on?


Yeah, there's a couple of really good spots. We've actually been using process mining discovery tools pretty aggressively now. That's very new in the market, putting that into place that we can see where there are opportunities to improve. We're even using it and some of the data we have from our programs to be able to look for opportunities in the life cycle of development and say, you know what, here are things we can go and work on. Here are things we can go and do that can make this better.


So those are more up and coming technologies. We actually have gotten quite a few folks trained in it now because we think that it's one that's going to be very impactful as we move forward. And the other thing we've been doing is looking for tools that give a bit of the power to the people in some ways is what I'll call it, is the. A lot of times teams want to be able to have their hands on this, they spend all day doing these models Excel and PowerPoint and databases and access and everything.


And so what we've started to do is also as we give tools out there, you may have heard of citizen development and self development. Yes. Because we give them that power to go and work on with these tools. We also want to still see what are they doing, what are they having to fix? What are they spending their time on? Because not only can you empower people to give them efficiencies today, which everyone wants, but you look for themes in that data and that information and you can lift it back into the organization.


That's really key. That's how you're going to find some big swing wins. That would be hard to identify if you're just sitting there looking at a valuation map because you're getting down into it where the Sunnis are doing the work and you're going to find those opportunities very, very interesting. And I would love to just take a step back for a moment. One of your pieces of your career and your background, I think is fascinating is that you're a graduate of GE's operations leadership program.


And any time we start talking about GE or a company that's been iconic and existed for so long, there's there's a lot to learn. So I would be really interested to know, what did you learn in that training and working at such a large and established company?


Yeah, it was a phenomenal experience. I am so thankful I got it. I was as I was a graduate, their operations management leadership program and also the corporate audit staff, and they have some similarities to it. I think if I think about some of the takeaways that I had from those programs is one, I love the ability to see a lot of a very large company very fast. It helped me create some very good practices. I had to get in to learn how to execute fast because you were rotating every four to six months, depending which program you were in.


They also had a very big focus on process process improvement. Lean Six Sigma was just how you worked in that company. I even think it was Green Belt certified as an intern with them because it was such an early on thing they wanted us to do. And I actually think that's part of what got me down even this path of wanting to get into this technology space, because that was when I was doing was Caucasians in Nien. We were doing these big events and there was always this list of stuff in them that I wanted to go work on, but I needed to go and put them into this big list of projects.


And the tools weren't really available back then to be able to go and do what you can now with ARPA. And the focus is coming on this intelligence mission space. And so that was another element that I think actually put me on this path that I was on even back at that time. And I think that if I were to say a third thing that I honestly treasure out of my experience, there was the exposure I got not only to just so many industries.


It really gave me a perspective on what was unique. But what also you can actually make a lot of synergies across industries. There's more similarities than I think sometimes we realize when you're in the day to day of it. But if you're able to find them, the system, you can really learn from each other. And I thought that was something that was really impactful that I took away. And then just the focus on empowering as well. And what I mean by that is in those leadership programs, you're pretty junior and you were getting exposure to a lot of things.


Running teams are going to shop floor with 90 plus people. At the time, you were getting to go and do projects to redo an entire propulsion for one of our business units. And it gave me a viewpoint on how important it is to empower teams, find ways to empower clients. Also, it's when the heart of what we do actually now is even it's not about us doing it for you. It's about how do you teach someone to fish?


Because if you can do that, what happens is everyone lifts up around that person. So if I think back, those are some of the things that come to my mind right away. I make you a whole list of things, but those are ones that came to my right away when I think about what I walked away with and I'm so grateful for in those programs for sure.


And I think when we start talking about the conversation around I machine learning, the automation of jobs and processes, it can be territory that feels pessimistic. However, you're someone that's at the front lines where you see a lot of toil and repetitive tasks that, you know, let's be honest, they're not enjoyable for folks to do day in and day out, you know, every week, every month.


And a future of Kaisa and like you mentioned, of continuous improvement is one that should really be exciting for folks. What your thoughts on this? Because I'm sure you hear some of the pessimism and doom and gloom sometimes. How do you address that?


I think is a couple things. And this actually does go back to the lean Six Sigma days. The challenges are actually quite similar with slightly different nuances to them. Is that when you. When you talk to folks, one of the things about automation is it is absolutely going to be something that changes how we work. But I do think much like Lean Six Sigma, if we think about it as another tool in our toolkit and something that we can help bring people along with, it makes the conversation very different.


This isn't something that should just be done to somebody. This is about how we're going to work different in the future. And that's what we spend a lot of time helping do that change management portion. And a couple of things we focus on. One is explaining it and you really take the time to learn this technology. It's exciting. It's not the movies. It is actually something that helps make people's lives better. It makes your job easier. It takes all the stuff that you don't like doing during the day anyway, and you have it built into the system.


So it just works for you. And you spend your time on where you would want to spend your time in the first place. If I'm someone in finance, I want to go and analyze this data. I want to figure out what are different strategies that I can do to improve my my cost position or my operating margins. I want to go look at that information. And if I'm working with one of my business units on, how do I help them improve?


What are levers we can work on? Maybe think about how do I bring in different products with my sourcing team or think about different vendors that can also partner with that's where people really want to spend the time. And so we continue to work with them on how do you bring people that way, educating and explaining how do you help them be a part of the Six Sigma? People know how to use the tool and even then that was about simplifying process.


So it's a similar mindset. If you actually educate folks and say, hey, here's how this works, what are your ideas? Do you want to help be a part of building them or do you want to learn this technology? Do you want to make this a part of your role? Much like the black belts and master black belts became roles that stood out and companies do we want to create those roles within these organizations? Because it's not going to be done just by one core team that the centralized team is going to offer the guidelines the best practices in place and make sure people are able to follow and understand a process to follow.


But if you really want this to become something that's a lever that drives transformation, that helps move that strategy needle for a company, it has to be ingrained in how people work. And that's from the bottoms up and the top down of the organization.


And when you are working to set digital strategy, which is one of the things that Cognizant is obviously known for, are there any type of insights you can share with us? What can folks that are listening, how can they start to think about digital strategy? How can is there any low hanging fruit that they can start executing on today?


Yeah, absolutely. So when you think about your digital strategy, there's a lot of things that's going to come into play there in this phase with the process, business process side of the house. You think about where are you at today first and be really honest with yourself, is your organization excited about technology? Are they a little bit more maybe legacy in how they do their processes? Where are you at at the moment? Where do you want to get to?


What is that that mission statement you're going to put into play because it can be crossed out? That's fine. I would also always a challenge, folks, to think even bigger and broader than that. Maybe it's a new market you want to get into. How do I maybe think about my position against my competitors if I want to drive revenue? Like what? But what does that battlecry that you're going to want to put around this entire transformation program?


Because people need to know why they're doing this and people will get behind it if they understand it. So that's one of the first things we actually always sit down with. And then as you start to lay it out, look for what those quick wins are, because some of the bigger, longer term plays, they take time. They're going to take months and even maybe years sometimes do the full implementation, but look for how to take it and break it out into pieces so that you can get benefits today.


You can get those outcomes, you can get people bought in because they see it working and then move it forward for tomorrow. If I were to even give an example for some of the automation programs that we were doing, and I even did this with myself when I was leaving the automation program, what we would do is we'd often look for some of those quicker wins that people with submitted. And we'd say this one, if it's going to drive this benefit or we think this is great for innovation because this team hasn't done this before, why don't we give them exposure to it?


And it's their idea. They're excited to be a part of this. Spending time on those is important. And then what we also did is we said, look, we know we want to go tackle some of these other areas, but you balanced it. People, if they had a chance to see how it worked, they had a chance to be a part of the solutions and actually enable that bigger, broader digital strategy and journey. The folks wanted to go on because they said, you know what, this does make sense.


I see the benefit. I had benefits. And then this really powerful thing tends to happen because word of mouth is probably the most powerful way you're going to market anything. They start talking to each other. They start saying, let's submit ideas for this. And then I always encourage organizations, be very transparent on your journey. Let people see the ideas that are being submitted, show them the videos, do analytics and data dashboards, put things out there?


So it's not just something that people hear once in a while in a meeting. It becomes a part of how people think, how people work. One of the things I always said about my time in GE was I never, ever had a question. If I thought integrity was a value for us, I felt it everywhere I looked in our emails, in the offices, it just we felt that you have to have people feel this is really important because they see it everywhere and they see that people are talking about it.


They see there's one hundred of these ideas. One hundred people's names I could write an email to if I wanted to, that are working on this. You know what? I want to be a part of this, too. Those are things that I would always recommend for folks because the technology is super important. And, yes, there's a lot of work that goes into it. But bringing those people along is going to be very critical also as you reimagine what your processes are going to look like in the future, for sure.


And I think to many folks out there, they're exhausted right now with the pandemic, with cultural with societal challenges. And yet we have these digital transformations that should have taken months happening in a matter of days. We have examples, like you mentioned, with the airline where a process is being, you know, really, really streamlined. This can't help but take us to a better place. What's the future of this? What makes you really optimistic and get you out of bed early in the morning?


This whole space is so exciting to me and I know a lot of stuff is super positive, but the pandemic. But I do think the push on the digital transformation is one that I would say I think is positive. A lot more people are talking about how do we go faster, how do we really get this working? Whereas a lot of times we were moving things along, but it was a little bit of a slower pace where now people see the importance of it in a multifold way.


And I think that's also because it's not just now seen as an efficiency. People see the opportunity for business resilience, that business continuity. And it's really important. And for me, what's exciting is that. I already thought this place was exciting, I'm actually asked about it, gives me extra excited about this is that if we're moving this faster than we're making a bigger impact for people and how people work differently because the audience there's a lot of stuff.


And I was on the other side, I was where I was an like running reports and digging into data. And then I was tired digging into all that. Most people I know, they're not working 40 hour weeks. They're spending a lot of extra time because they had to wait three hours for a report to download or they had to sit there and redo an entire Excel table because five of the sources out of the twenty five they were trying to reconcile changed.


And you have to go back and make sure everything's clean and fix all this information. And to me, what's exciting is about could you imagine if the work we did actually every night we go to bed and we say, I know I added value, I know I made a difference to my organization. I know I made this impact to my clients. And it's not saying that we don't today, but I think a big portion of the time a lot of us spend is on things that we wish we didn't have to do and we wish we could be spending more time on the value added pieces and the stuff that truly gets us excited every single day.


I feel like we're helping people to do that and we're moving that needle. And that's something that's always gotten very passionate, is being able to see that positive change.


Thank you so much for being generous with your time. I would love to throw the ball back to you one more time and just hear any final thoughts, anything else that you think more people need to know about. The mike is yours and take it away. Sure.


I think one thing I would encourage is folks to go out and really learn more about the space. This is a space that you don't necessarily have to have an engineering degree or a technical degree or at least learn more about and be a part of this. This is going to be a business and I.T. truly come together and meet. And there's a lot of information out there. There's free trainings. There's a ton of stuff you can read. And I am definitely convinced this is something that is the future.


And I think being a part of that is this really exciting opportunity that anyone can be a part of and even maybe raise your hand and ask folks, can I be a part of maybe the first group that gets their hands on this technology or gets to work on maybe putting one of these into production in this intelligence automation space? And I've always encouraged folks to be brave enough to do that change through organization. I'm the one that's going to push that needle and help others move along, because this is a really exciting space that can cause a lot of positive outcomes for you and your your colleagues and the overall organization.


So being able to raise your hand, drive that change and being that voice is going to be exciting also for you and your and your colleagues as well, especially now when we're at home. This is a nice opportunity to maybe learn that that new tool and technology and add that on to your to your resume and then obviously also helping your teams be able to advance this amazing wise words.


Mersa, thank you so much for joining us. And to everyone listening, we will see you next time. Paul. I'm Sophia Bush, and you've been listening to Hidden in Plain Sight from Mission Dog. This podcast is sponsored by our friends at Splunk, the Data to Everything platform. In today's data driven world, every company, big or small newworld, is sitting on terabytes of unused, untapped and unknown data. Splunk helps turn all that data into action.


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