Are Robots Taking Over Your Job

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  • May 11, 2021
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Are Robots Taking Over Your Job?

Steven Booze, VP of Solugenix Corporation

Naheesh: Hello everyone. Thank you for all coming to today’s webinar. My name is Naheesh (0:45) and I will be your main host for this presentation. Just some general cons (0:49), please utilize any questions you may have by using the Q&A function on your Zoom option below and our guest speaker will do best his best to answer them at the end of the presentation. Now with that being said, for today’s presentation our guest speaker today is Steven Booze, the vice president of Digital Innovation from Solugenix Corporation. Steven uses his 20 years of experience in building and scaling technology-based firms to support client enterprise initiatives and digital transformation. His unique work style helps guide his executive and project strategies in working and guiding organizations in using digital technologies to create new and modified business processes and customer experiences. For his presentation today, Steven will talk to us about robotic process automation or RPA and how it is transmitting (01:31) how business operate. Now with that being said, I will now pass it to Steven who will begin the presentation.

Steve: Alright and thank you very much for that invitee or rather, introduction and excited to be here with everyone. So again, my name is Steve Booze and VP for digital innovation at Solugenix. So just a little bit about Solugenix. Solugenix has been helping companies with their technology services for about 50 years. We’ve been the back-office support behind many large names for decades and help make businesses more efficient by providing services like business process outsourcing, contact centers, application lifecycle management, talent acquisition service now, and of course robotic process automation. And that’s what we’re going to speak about today.

Agenda

I don’t know about the rest of you but I’m originally from the West Coast and right now I’m in Manhattan. And I am looking out over a significant blizzard and I know some are you in Canada so it’s kind of normal but for me, this is really amazing. Hopefully I don’t lose connection or anything else like that. If I do, we’ll just have to figure that out. So, the agenda so today as discussed, I’m going to be going over RPA. I’m going to talk about what it is versus other technologies along the same spectrum, talk about some news cases, tools and vendors and how RPA might impact the future workforce. I will show a demo in there as well as showing as opposed to telling is going to be a lot stronger. At the end, I’ll also have some links and some other additional information about RPA that may be helpful.

Simple Definition Of RPA

Okay, let’s get started. So, this is a really high definition of what RPA is and I’m not going to read it all the way through. In subsequent slides, we get into more detail. But again, RPA is an acronym for robotic process automation. The robot part in RPA is software robots running on physical or virtual machine. This software is programmed with business rules, workflows and steps to do repetitive tasks across applications and systems. RPA can be used to automate processes which are time and/or labor intensive, so functions which are onuris (03:51) and do not require human intelligence to make unexpected decisions are perfect candidates to be automated. RPA allows workers to switch their energy to more thoughtful and meaningful work by eliminating these tasks. To better illustrate this, let’s go ahead and let’s take a look at this short thing (04:10).

START OF VIDEO

Throughout the day, your team spends a lot of time gathering and transferring data from different computer systems including spreadsheets, emails and various software programs. This is time-consuming. It could take hours, even days to complete. Wouldn’t it great if your team could spend that time on higher value and less mundane activities instead? With robotic process automation or RPA, they can. All thanks to bots. Bots are virtual employees that can be taught to replicate the tasks of your team. Like moving data from one software application to another, performing calculations and quality checks. And emailing you with the results when completed. A bot needs no new technology or process changes within your environment. It works with your current IT set up and software applications and keeps an audit trail for security compliance purposes. It’s fast, accurate and works 24/7. RPA removes bottlenecks and improves the processes within your team. Providing your employees with more time to focus on the things they do best.

END OF VIDEO

Automation Maturity

So, even though it’s shown on the cartoon, right, to my disappointment RPA really isn’t some form of cyborg or autobot, no Skynet sort of thing that is happening as the video showed. But again, it’s a software designed to imitate human actions on a computer system. RPA always follows fixed rules and execute repetitive operations as coded. And that’s important because I want to talk equally about what RPA is not. Because often, when I discuss RPA, there’s a lot of confusion and it gets rolled up into a lot of different other technologies that are out there. I want to call out that RPA isn’t machine learning or artificial intelligence. They’re not substitutable but they can become complimentary. For example, machine learning or ML, if you’re not familiar, it’s a computer system that is taught to accurately predict with data. So, in this case, computer programs access and use complex data and algorithms to recognize underlying patterns and make decisions. These algorithms that automatically get better as the program collects more data without the need for it to be reprogrammed. Some everyday examples of ML are online prowl (06:41) protection. So, if I use my credit card and it’s out of my usual buying pattern or out of my geographical location, I might receive an alert from my credit card company, for example. Another one I take a lot of [inaudible] (06:54), not so much here in Manhattan, is traffic apps. Things like Waze (07:00), they gather current location and speed data from our GPS navigational systems. They use location, speed data from our GPS and use this data for congestion analysis. So, they tell you to take this road and not that road. Probably the one that’s most famous is Netflix. I read that Netflix has just a 90 second window to help viewers find the movie or TV show before they leave the platform and visit some other service. Consequently, their recommendation engine is key to their success and it’s estimated that 80% of Netflix viewers and views come from these recommendations. Of course, that’s huge because that translates into one billion dollars a year from customer retention. So that’s ML.

Then there is something else called artificial intelligence that we hear a lot about, or AI and that goes a step further. So, AI represents the ability of machine emulate the natural intelligence or sensing ability of humans. So, where ML uses the data to patterns, AI uses data and experiences to acquire knowledge and apply that knowledge for new environments. In other words, it’s the ability for a computer to imitate intelligent human behavior. Intelligent being the key word of course. The difference between AI and regular programming is that regular program defines all the possible scenarios and then only operates within those defined scenarios. AI is designed for specific scenarios but is allowed to explore and improve on its own. Good AI figures out what to do when it’s met with unusual circumstances or situations. As an example, Microsoft Excel software can’t approve on its own. It only can do what is coded. But something like AI facial recognition software can get better and recognize faces the more it runs. Couple of common AIs are autonomous cars. AI algorithms are fed with real time data and centers GPS and cameras and so on. It produces control signals that are used to operate the car. You’re seeing a lot of that. But probably the most familiar are digital voice systems like Alexa and Siri. These are real applications of AI that are increasingly integral to our daily lives. I know I use quite a bit. These devices rely on machine learning to effectively operate and perform better over time. Natural language generation, NLG, which is a computer’s ability to create content in either written or spoken language so that it could be understood by humans. And really the goal of the devices is at the very end, a user can’t distinguish between a computer and human. This is known of course, as the Turing test. This is where a person would judge a conversation and be like, “Yeah, I can tell that’s a computer, or I really can’t tell who’s saying that”. I think we’re all in agreement that we’re pretty far from that right now. We can tell whether a chat whether it’s a chatbot or something else over the phone is a person or computer at the other end. But it is getting better. Personally, I’ve even noticed the natural expressions coming from Alexa. So, I ask something like “Alexa, what’s the weather?”. She usually responds like “The current weather is x, y, z or the high will be and low will be expected today”. But every once in a while, I’ll get something thrown out and Alexa will say something like, “Have a nice day!”. It always throws me off and sometimes I even catch myself saying, “Thanks, you too!”. To be quite frank, when I do that I realize that I need to focus on getting some friends and building some relationships skills [inaudible] (10:53).

Evolution of RPA

So, there’s the aspect of those three things. So, there’s RPA, there’s ML, there’s AI. And again, with all technology nothing is absolute right, and RPA rather is no different. So, RPA has advanced to mimic human behavior. You’ll hear this and you’ll especially hear this from you know, the software vendors and the tool sets. And this is something called cognitive automation. So, it’s combining the technology such as speech recognition, natural language processing, text analytics and data mining. It’s combining them and placing it into RPA making that richer and giving even better results. So, result, it helps better organizations you know, extend automation, more processes and makes the most, not only structured data right, but especially the growing volumes of unstructured data. So, we’re seeing these things starting to converge. But they are very still distinct technologies.

Benefits of RPA

So, some of the benefits of RPA you know they’re virtual employees as discussed. And as a virtual employee, you know we’ll see benefits and you hear like, “yeah, they never take a day off; they’re available 24 by 7, 365 days a year.” Obviously, there’s the scalability of it, the reduction in human errors. All of these things are very, very key in why companies are moving over and using RPA. To say that, do they break? Are they brittle? Yes, you know. Are there situations to where RPA will stop working? Yes. If it comes into a youth case (12:40) or business decision that hasn’t been defined. Again, it’s you know if it’s not a sky note (12:46) situation where it takes over and does what it wants. It can only do what it’s defined to do. But even that being said, there’s ways of programming and such to make it more robust and more elastic. So, benefits of RPA we’re seeing it grow. It’s growing tremendously. There was a research that’s released, and we see these things all the time. You know Grant View research (13:10) estimated the value of RPA at $1.4 billion a couple years ago. And it’s estimated to reach $26 billion by 2027. And this isn’t a surprise as many of our leaders are looking to focus on continuous improvement, efficiencies, analytic capabilities. And why is this? Well, RPA delivers a couple of things. As discussed, it’s faster in execution so a bot works fourty times faster than a human. Again, 24 hours a day, 7 days a week. Never gets sick. Never calls in. Never goes on vacation. And all this increases productivity and efficiency. But there’s also predictability with a bot. A bot can run with 100% accuracy. Again, it does what it’s told. And this reduction in human error provides a lower level of operational risk. It’s scalable and because of this, bots can be fully compliant and provide an audit trail every step. And of course, there’s the cost. So, by automating tasks, cost savings of 30 to 50% or higher can be achieved. And a software robot costs less than an employee. There’s no changes needed in the infrastructure and because of quick development, there is a short ROI (14:22) period. So, a lot of benefits that are coming to RPA and why we’re seeing businesses switch over and using RPA.

RPA Terminology

            I just want to pause briefly and talk about terminology because a lot of things just like every other technology, there’s a lot of acronyms thrown out and there’s a lot of terminology. This isn’t the end all or be all but just to make sure there are some sense of understanding, if this is unfamiliar. So again, a bot we talked about that. You know, a computer developed to run on a business process. It’s on a physical or virtual machine. And this software is programmed with business rules, workflows and so on and so forth. But bots run process. And a process is an activity or task that an individual is using their computer system to do. So again, the bot is a virtual employee that’s taking over the task that this employee is doing. Sometimes called swivel (15:21) chair type of activities. So that being said, there’s a couple of things right. A bot, it’s important to know that a bot can only run one process at a time. Essentially, the processes run in serial not parallel. So that’s important. Just like a human individual, right. I can’t, it’s going to very difficult for me to cook and swim at the same time. I’m going to do one or the other. However, one bot can run multiple processes and even different processes when available. So that’s what this image over on the right-hand side with the circle is attempting to show. And what it’s showing is we have one bot there. And that bot can run as many processes as allowed within that 24-hour period because it’s available for 24 hours. So, for example, if there is a process that runs from 9am to 9:15am, for that 15 minutes. After 9:15, that bot is available. It’s not that there’s that only one thing that can run on it and that’s all it does. So, another process, a different one can be scheduled right after that and so on and so forth. We continue to be loaded so you get a good utilization of that bot. And you know, rule of thumb is you never want to utilize a bot to 100% because there will be situations where there are exceptions or there are errors that happen where the bot may stop. With that being said, it’s important to note again, one particular bot just like an individual can do multiple things in serial, one right after the other. I say that but like everything else there’s nuances (17:00) for every rule. So, you know working with your different vendors and different tool sets out of there. You can run processes at the same time because sometimes a bot can trigger another bot so that they can run in parallel on another machine right. That’s an example. Or an environment can be configured for density. Something called density which allows multiple robots run on one machine. So, there’s things that can done around that. But you can think of it again as in that terms of virtual work, virtual employee and if you need multiple things done at multiple times, you would get multiple employees that they can work in that kind of parallel type of environment.

            You also hear things; you know in terms like unattended and attended. So, as the name applies, an unattended bot operates on a schedule or is triggered by a specific event in a process flow. So maybe it’s unattended and this bot turns on when an email gets sent to it. And it knows, “Okay, I just received an email so I’m going to start it.” But nobody is starting that. That’s a trigger to them. While attentive bots are activated by employees whenever they’re needed. So that’s something to where maybe I do a certain process. And when I get done with my piece, I want the bot to take over from that point, I would start the bot from there. So that would be an attended bot. And that’s basically and there’s something called a hybrid of course. And the hybrid is just combining those two. So maybe a situation where you know, I do something that unites you know, or basically starts an attended bot and I manually start that, and it does a process. And that process kicks it over to a scheduled bot or unattended bot and it also runs. So, there is the ability to use that hybrid type model. And so, an employee can work with different tasks simultaneously. So, those are just some of the terminologies you will hear just in general.

Demo

            Okay, so I talked about you know, showing and not telling. So that was a lot of information but the best thing to do is to actually see a bot in action right. So, this demo I’m going to show, this demo was created by a vendor UI path. It creates an extra (19:22) tool. And it shows a bot interacting with multiple software systems. This bot can perform screen scrape (19:26), and sorting (19:29) data and updating data. It’s going to create records and push information out via email to the business. So, there’s a lot going on with this and the real, the genesis behind showing this is just showing you know, some of the attributes that a bot can do. And that being said, let’s go ahead and we’ll get started.

RPA in Action

            So, again this demo, this bot can work with 7 applications. It’s going to work with Excel, it’s going to work with terminals, it’s going to work with Salesforce, it’s going to work with Word, PDF, email and SAP. So, the Excel file contains the name, email, SAP number in an individual code for each person. The robots first going to read this data then open up the terminal, input each person’s code and get all the information from the terminal. The emails from this CSV that we look, will put input into Salesforce to find every employee. And then the expense data from that terminal will be added to the expense row. Afterwards, this bot is going to create a Word document from a template with the status for each individual. It’s going to take that Word document and convert it into a PDF document and it’s going to send it out as an email attachment. Lastly, the bot will find the employee’s position in SAP with all the above data and it’s going to go back to that original CSV or Excel file and it’s going to populate it from the beginning.

So, this is the bot starting. And what we can see is the bot is starting by opening up terminals, Salesforce and SAP. And it’s logging into all three of these systems, preparing for the applications that it’ll work with. Then the bots will browse the pages of terminals and find the ID of the first employee that was on the Excel file and the same thing in Salesforce based on their email address. The expenses are then added then to expense IT. Then, the Word template is going to pop up and it’s going to fill in that template and convert it to a PDF. And then it’s going to send it as an email attachment. And now it’s looking at an SAP and it’s going to move onto the second person, looking for their ID in the terminal. It’s going to do the same thing in Salesforce. But in this particular case, it notices that there isn’t a record for this individual and so it’s going to create a record. And after doing that again, the PDF from Word and the email gets sent out. It’s going to move onto the third individual. It’s going to the same thing and now as you can see from the original CSV, it populated all the information, and it has sent all of those out. So, all of that happens pretty fast. It’s slowed down to a certain extent. And again, this isn’t a specific use case where you go like, “Oh, I get the end result”. But it’s really to show you, okay. A lot of applications that it’s working with, a lot of different things that it was doing; it was inputting, it was screen scraping, inserting records, converting, emailing and that’s the power of a bot. And this may be something an individual does you know throughout, maybe in HR or some other process. And it’s showing this is what the bot can do and there’s very specific business rules behind that.

RPA Use Cases

            This slide just shows you know, using that as examples. So, that was just a lot of different applications. But RPA is used in pretty much every type of industry and every type of department or business units. So, you’ll see it in finance and accounting which really is one of its stronger suits. And why is that? Because finance and accounting has very strict business rules already imbedded in it. Systems are such that they’re structured, and it makes it very, very kind because the same repetitive tasks happens over and over. But you also see that in HR right. And maybe onboarding or offboarding where certain activities have to happen. Maybe they’re even time sensitive. We see this in IT processing. Some of the things that typically happen over and over again when a certain trigger event happens. Bots can do, they also can help with data transformation and data, you know, manipulation, things of that nature. And we’ve seen too, many cases done where maybe short term there isn’t a, you know, ability to do the coding and any kind of use of API are nowhere to make sense (24:08) to talk to each other. Bots work well for that too. And we’ve talked about other things like compliance right. So, when you have these types of things, it’s going to define (24:18) it as and you have to make sure they happen every single time, and maybe there’s, you know, a whole set of compliance that have to be adhered to. Bots are good at that. And it can, you know, number one, they’re only going to do what they’re told. Number two print that audit trail. So, it makes it really kind.

RPA Vendors

            So, RPA vendors. So, I mentioned a few but you know, I’m just going to briefly mention on the vendors. So, there’s a lot of them out there. If you look at the image on the right. This is from last year; Gartner did a Magic Quadrant and I think it was last year. This one might be from the middle of the year. And in it, like I said, there is a lot of vendors. But in it, you see Automation Anywhere, Blue Prism, UI Path and WorkFusion in the upper right-hand corner, so that’s in the leaders section. And typically, whether you’re looking, you know, at the Magic Quadrant from Gartner or Forester or when the research reforms (25:12), you’ll typically see, you know, these individuals up in the leader, kind of the leaders every time. And that’s not necessarily by coincidence as these are also the market share leaders for RPA. That being stated, if you look on the right-hand side, this one shows over 50 RPA vendors in the market case and that’s growing. And that’s because RPA is an emerging technology. There’s not necessarily one tool that is best for all companies. So, you have to choose a RPA software vendor, make sure you understand the vendor landscape, and prepare these vendors to choose the one that’s most suitable for your business and obviously, an implementation partner that you can trust to work with. And again, I’ll stick a link at the end of this just so you can take a look and get more information.

Might Your Job Be Automated?

            So, let’s get down to RPA and the impact on the work force. So, I did want to discuss that, and will there be an impact? Yes. So, let’s just, you know, kind of define it. RPA allows those businesses, you know, our businesses to leverage the benefits of increased productivity and efficiency. And it does free up time for employees to focus on value added activities. And I state that and a lot of times it’s kind of like, you know, we all kind of like yeah value-added activities. But no, I’ve actually seen that multiple times in real life where these types of things were just people were just doing it because they just had to do them, and they were just scheduled and set aside. I’ve actually seen it where has been the best of what RPA has brought and it has allowed these individuals to free up and really focus on how do we make the business better, how do we make our jobs better. So, it wasn’t a way of eliminating positions and this is also detailed. There was a research paper that came out from the London School of Economics and Political Science and they noted and acknowledged that knowledge workers didn’t feel threaten by automation, but rather they embraced it and viewed the robots as teammates. Right, and that’s kind of the best-case scenario. Another thing that we’re seeing that’s happening with the automation in the introduction of the RPA is with some companies a lot of the routine activities that may have been outsourced overseas we’ve seen that. And now what we are seeing is with RPAs some of these organizations can repatriate these jobs and are bringing them back over or there may not be the need to outsource those. So, you know. There is a study by McKinsey & Company and its suggested by 2030, 75 million to 375 million workers and that’s 3 to 14 percent of the global workforce will need to switch occupations. Occupational categories because of automation. Additionally, all workers will need to adapt working with alongside robots and we’re starting to experience that, I think we are seeing that now. That this is something that we are going to be working in conjunction with. And those numbers are devastating, there’s no question about it, but the report, the McKinsey report also goes on to suggest that the real story was that jobs won’t simply be lost. But there will be new occupations created that didn’t exist today and we’ve all seen that and experienced that with newer technologies as well. So, will RPA threaten your career job? Well, yeah it may. It depends on what you do for a living, how old you are, where you live, educational credentials, and things of that nature.

So, if we look at the slide here. That’s basically what it’s showing. So, if we take a look, we can see that there is a threshold and there’s from, left to right. So, occupations that are more on the right side have a lower risk of being automated. And as you migrate over or rather, to the left-side and as you migrate over to the right-side, you can see the risk increases. And you know, this is, you know, there’s plenty of things out here. This is one from Bloomberg. But there’s tools out there that you know, again to see will this actually impact my job. Here’s another one that, hopefully you all can see my screen. And you can enter in any job you want right. And this is kind of at the, this is also a link I put in. So, if I put in statisticians, you know, there’s a 22%. So, looking down the risk is extremely low. It talks about the growth. It talks about things like that. So, I always go back and see, you know, information is the key on this. Will there be automation? Absolutely. We’re seeing this now. Will that increase? Yes, you know, it will increase. Will it impact you? It depends on what you do. But also, I think a key to that is, you know, it’s a situation to where we can future proof our careers right. And that’s something that we want to do. So, it is a possibility but the answer to that is agility. So that’s the key. We have to be prepared to change our old ways in doing things. That’s always the case. And I think all of us as technologists have seen that. And good thing to do, and I highly suggest is to learn more about RPA. Because the more we understand about what RPA does, we’re going to understand what are good jobs, what jobs are good candidates rather, to be automated. And which ones are really good for humans and how we can work alongside RPA. And so, one of the things I included at the end as links that go out and there’s plenty of training, very simple and very geared towards business users and technologists where you can learn more about RPA. You can even do these things on your own if you want to. There’s a lot of free tools out there, like I said, especially from the bigger vendors. So, I encourage you to take a look and just, you know, all of us to be prepared. Again, nothing to be, you know, like “Oh my gosh, doom is coming”. But you just have to be aware that this is another technology that’s going to enter our workforce. Just be aware for you to work alongside it. So, I’m going to take a pause there and open it up to see if there any questions.

Questions?

You can either place it on, in the chat or you can probably easier just to audio question if you have any. Alright, going once. Going twice. Okay, so I was planning around 40 minutes and 10 minutes for questions. So that’s what I wanted to share this afternoon. So, hopefully you got some value out of it. If there’s any questions or anything at all, you can always reach me directly by email or you can get a hold of me on LinkedIn. And like I said, there will be some, I’ll look to share this some different links that you can go to for understanding and getting a little bit more information.

Naheesh: Alright, perfect. Thank you so much Steven for that excellent presentation and showcasing your expertise in that field. And with that being said, just some general note. You may notice a short survey that may appear on your screen after this webinar is ended. So, if you could kindly fill that out, that will be greatly appreciated. And if there are no questions, I’d like to conclude the webinar today and thank you so much Steven for taking the time to come out and present today. And thank you for all the things that came out. And we hope you have a rest of an amazing day.

Steve: Alright, thank you all very much and have a great day.

Naheesh: Thank you. Take care.

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