This post includes the full Transcript of from Ashling Partners Webinar Introduction to Robotic Process Automation (RPA) – Part 1 on May 28, 2019 and the YouTube video of the entire educational webinar: Introduction to Robotic Process Automation (RPA) – Part 1

This is the first in a 4 part series that helps educate you on the value of process automation.

Introduction: Transcript from original webinar recording

Hello, and thank you for joining our webinar on an Introduction to Robotic Process Automation. So, quick walk through the agenda today, we’re gonna kind of talk at a philosophical level, a higher level about how we got to where we are about the future of work, how RPA impacts that, then we’ll kind of walk it back a little bit defining robotic process automation, discussing the value and promise of RPA going through how to determine use cases, and then some specifics on how to get started. 

First, how did we get here? Many people will tell you that this is the fourth industrial revolution, and that this is no less impactful than moving from an agrarian economy to an industrialized economy to moving to an assembly line and the mass production of items to the internet, generation and internet industry, and then now really the process automation industry. And so this is going to have a very significant impact on work. Historically, to date, the business model has been that you build high barriers of entry. In essence, use the walls of your castle, if you will. And that’s been to improve price elasticity, which therefore creates better profitability and gross margin for your organization, or at least the opportunity to have that. And really now in today’s market, it’s quite the opposite. Instead of building your castle, you’re now trying to be more pragmatic and flexible and having lower barriers of entry as you move from one area to the other. And this change can be difficult. And so reading the quote here, the CEO of HubSpot talks about his morning, and there’s six companies that are identified in this quote. And the commonality of those six companies are that none of those companies existed 10 years ago, they’re all in somewhat commoditized spaces: mattress company, music company, eyeglass company, taxi company, or like taxi company, clothing, razors, these are all basically considered commoditized goods. But all six of these companies are killing it both from a profitability and growth perspective. And that’s largely because they’ve created a low friction experience, or what they call frictionless experience for their customer. And so it’s no longer about having the high barriers of entry. It’s about the ease and speed at which you can transact with your end customer, as well as move into and be pragmatic and dynamic into new spaces. Furthering that topic, if you look at 2001, not that long ago, only one of the top five companies from a value perspective, were technology companies. Now, in 2016 and beyond, all of the top companies are technology companies. And so what you’re seeing is that more and more people are leveraging not only the value of technology, but also turning that into an infinitely scalable model at a significantly lower cost point as well as the ability to, like I said, pragmatically move from area to area. Now, how does this impact the future of work? As we start talking about how people will be working in the future, we like to start with this quote from Google, the book How Google Works. And beyond the quote, it’s really talking about in the book, how workers will no longer be doing data entry and data manipulation, that really starts to go away, and really is perceived as kind of a giant waste of time for the worker, even though that is, for some organizations, the majority of what the worker does today. It’s really about critical thinking. It’s about analyzing that data not entering and manipulating that data and reacting to that data. And that’s really the going forward work.

Using two quotes. The one on the left is from Oxford University. The one on the right is from McKinsey. They both stayed roughly the same. thing from two different perspectives. The Oxford University one on the left talks about 47% of employees will be at risk to have their work impacted by automation. The McKinsey quote on the right talks about 50% of the activities that workers do. So one is activities on the right, and the one on the left is the employment or actual roles. Either way, you’re basically talking about 50%, roughly, half of the types of work or workers will be impacted by automation. So it’s a very significant area of impact. But as we talk about this, a lot of people jump to, we’re gonna lose our jobs, and we’re not going to have work to do and we’re going to take away all this stuff. We actually don’t believe in that idea. We believe that this is really meant to empower workers to do more meaningful work, and that there will always be the value of empathy, storytelling, creativity, collaboration, etc. And so the value will be that workers will no longer be spending their time doing that data entry data manipulation that we talked about, and more focused on actually solving the problem in a creative manner or telling a story about what the data means, making people understand that connection to the data, and providing empathy to the customer and storyteller. 

As we’ve kind of now painted that picture of how automation is going to significantly impact the future of work and kind of where we believe directionally, it’s headed, we now wanted to take a step back and really help define RPA. So here’s a book definition on what robotic Process Automation means from the Institute for RPA and AI of which we are members. But really, at the end of the day, the synopsis of this is that robotic process automation takes the mundane repeatable tasks that people do over and over again, and automates them, software has now kind of become more intelligent, where you can take repeatable rule based activities, transactional type activities. And you can automate those empowering those people to no longer spend time doing data collection, data entry, data manipulation, and more time analyzing and reacting to that data. So the other thing that you will hear quite frequently is AI artificial intelligence, where that RPA falls within AI, everything’s kind of included in AI, it’s called AI white washing, nowadays, everybody wants to be part of AI, because the valuation goes up significantly. We really see it as a journey. And so at the left side here, you talk about desktop automation. And some of that stuff has been around already for quite some time. And then you move into more of that process automation. So instead of doing specific tasks, you’re doing a series of tasks. But really, those two things are very process driven, and you want to first and foremost, improve the process to be efficient. And then you want to look at tasks or series of tasks, and automate those to create a kind of fully paved road for an automated process. From there, you’ve got to then look at machine learning and artificial intelligence. If you do that too early, if you jump into ML and AI too early, you spend way too much time trying to do data cleansing activities, and understanding the data. And it’s kind of garbage in garbage out rule. So you first want to focus on the process, improve the process, make sure that the data that’s going through this process is clean, and the data that you’re looking for, and then take that data and start to become more of a data driven organization.

the future of work

So what RPA is not. It is not a physical robot. We talked to many organizations and you hear robotic process automation, and you think about robotic arms on an assembly line, or physical robots like pepper here on the left. It is also not a direct replacement for custom scripts and integrations. It’s certainly not the end of work as we discussed. And most importantly, it’s not a zero sum game or bottom line thinking. We believe it’s a positive sum game where both sides can benefit. What we mean by that is, it’s not a situation where for every robot to add, you’re going to remove a headcount. It’s really more about empowering your employees to do more effective and efficient work than it is about replacing employees and not having worked for those people. So as we’ve kind of discussed the promise of RPA, here’s some now more specific value of RPA. So we start to get into the value metrics, how do you define value for process automation? Some of this is coming up with your key performance indicators. But these are areas that we typically suggest these five buckets. So there’s certainly efficiency and productivity gains, doing things better, faster, cheaper. There’s clearly some bottom line from that, but also beyond kind of the obvious ones. You look at risk management, and start to think about the benefit of compliance, the benefit of auditability, the benefit of that transparency, and making sure that it’s done 100%, the same way every single time. So there’s a lot of compliance benefits there. There’s also the benefit of innovation of being able to drive things faster, your regression testing, your test case scenarios, in rolling out new product offerings, these things can be done over and over and over again, via automation, and roll out your innovation faster. It also improves your employee engagement. So it takes out those mundane repeatable tasks that people have to do, and then empowers them to do more meaningful work. And as they do more meaningful work, they feel more engaged as an employee, and a more engaged employee actually, therefore, then does an even better job at work. And so it kind of becomes a multiplier effect. And one of the things looking at the cost savings bucket, one of the other things that we see a lot of organizations now starting to do is really bringing back in house, some of their offshore BPO activity. And so things that they would have offshored due to cost reduction, and they’re now looking at that and saying, “Well, if the only value is labor arbitrage opportunity, I now have an opportunity to bring that back at even lower cost than the outsourcer.” And in almost all cases, offshore outsourcing is already heavily leveraging process automation within their internal processes. 

So what are the primary drivers for getting involved in RPA? It really first and foremost is improving optimization, reducing process error, improving performance, reducing costs, as well as improving the processing errors and improving the quality. Secondly, it’s also enabling those workers to then focus on more important activities. If you look at the right hand side, the primary drivers, as I mentioned, most people are looking for optimization of operations are better cost efficiency. And then secondly, that reduces process errors as we talked about. And then you can, you can see the other values here as it starts to scale down. This is from a forester engagement study of honor and five managers in January 2018. When we talk about RPA being part of AI, we really see it as the first step of that journey towards AI. So when people fill out the survey, again, January 2018, this is Harvard Business Review. A majority of those companies that are doing something in the AI space are actually doing RPA and then that moves into other areas of the business. But it really is that first stepping stone of getting a locked down qualitative process with the right data, and then becoming a more data driven organization as you first have a good intake process and in processing of that data. 

Next here is a shared services industry survey. From January 2019, it says the Intelligent Automation part of your operations, you’ll see kind of where people are on that journey today. So about half have at least started in that journey. About half have not. And then where AI RPA has run into trouble – what are the challenges? First and foremost, not enough process understanding, or the process isn’t mature enough to actually become rule based and scripted. And that’s, that’s really first and foremost, the biggest area for you to have to focus on is making sure that you understand your process, making sure that you can document and create a rule based process with somewhat minimum exception handling, and then being able to make sure that that is as efficient of a process as possible. So, no surprise, the industries that have already most utilized RPA are companies that have high transaction volume, so banking, financial services, insurance, Telecom, utilities, media, healthcare, retail, as you kind of go from the bottom to the top. All of these are organizations that have common themes of high transaction volume. So if you’re doing something over and over and over and over again, then that’s a great area for process automation. 

So how do you? How do you figure out how to get started, how do you even determine where RPA may be a good use of your time? We believe in creating heatmaps. And so for us, this is an example that you would want to create for yourself. But this is for finance and accounting, which is where many people typically get started. Look at all of the activities that you do within your process, and then break that down into the activities, the sub activities of that activity. And then can that be automated or not. And if it is automated, How valuable is it to you to be automated? So this is what’s considered a heat map, and can show multiple areas where process automation can create a lot of benefits. When you’re thinking of areas for automation, these are the characteristics that are valuable for process automation. And some of these we’ve kind of talked through at this point. But you’re looking for manual repetitive data entry, basically doing the same thing over and over. Ideally, you want something that touches more than one application. If it’s all within one application, there’s probably tools within that application that could also automate that in a spreadsheet, uploaders. And these kinds of things, if you’re only using one application, the more different items you touch, you’re touching Excel, you’re touching an accounting system, you’re touching a CRM system, you’re touching a website, the more items you’re touching, the more valuable the platform becomes because it’s now doing all of those different areas. You definitely need high volume to justify the investment in scripting it and automating it in the first place. Areas that need quality control or data validation, areas that you have compliance needs, is a great area. GDPR is a great example where you don’t want that data to leave the country, you don’t want other people to have access to that data. HIPAA is another example where you should have limited access and who has access to that data, all great areas for scripting and just having the software, access that data and then remove any kind of residual data aspects of that process. And then it’s got to be business rule driven. So it’s got to be something that you can script out, you can write down on a sheet of paper how the process works. If you can do that, then you can automate it.

Here are some example use cases. Ten example use cases that I’ll just kind of highlight a couple here, you can read and read them on your own. So onboarding a customer onboarding a vendor, you think about the forms that people need to fill out, like about when you go to the doctor’s office, and you fill out forms, and you fill out kind of the same information three different times? Well, that’s because they have siloed data in different applications, and they need to re enter that each time. Automation does that for you, in essence, takes that swivel chair data entry and says okay, for every vendor, I need the same information and I have the same form that they need to fill out. I’m just going to scan those forums, take that data from the forums, and I’m going to upload it into the various applications that are required to be able to do business with that vendor, right. Same thing with a customer. AP invoice scannings – another great very common example where you receive an invoice via email. You have software that is monitoring that inbox. As soon as you get an item that comes into that inbox, it opens up the email, it opens up the attachment, it validates that that attachment is indeed an invoice. It scans that invoice for all the relevant information, it logs into your accounting system, it enters that information from the invoice and then attaches a copy of the invoice. Very similar to expense receipts, you take a picture of your expense receipt, you email it, maybe with some specific information in the subject, if necessary, like project code or something like that client code. And then it does the same thing. It logs into your expense entry, and it does all those things from scanning the receipt, third party shipment, emails, Excel uploads. Number six here, we’ve got a client that goes and scrubs competitors websites and gets any product information and pricing information from the website and downloads it into an Excel for people to analyze every Monday morning. But other things like working 24/7, providing a kind of extension to chat bot where a chatbot might be communicating with you and then you requested to do something. While the chat bot doesn’t do that an actual RPA would go behind the scenes and then make those updates from any kind of help desk, chat bot type information. Also doing data entry, data manipulation, providing those analytics scorecards, demand planning, etc. 

So how do you get started? How do we move forward here after you understand the promise of RPA and understand that this is going to have a significant impact on your organization? How do you even start to get started? So for us, we see it in three categories. In the first category, you’re really talking about doing that process discovery, and benchmarking your data. And we’re gonna go into more on this in the second series here, the second step of a series. So this is the first one just kind of introducing you to RPA. We’re going to do a deeper dive on use cases and business value in the second one, I’ll talk about that in a minute. But really, this first phase is about understanding the business value, understanding the benchmark data understanding process discovery, and then identifying the tools that can help you with that. Then you move into a build phase, that might be a prototype, proof of concept, pilot, whatever kind of a crawl, walk, run, but you’re you’re certainly starting to know build out value and demonstrate that value. And then lastly, you want to make it sustainable, you want to make sure that you’ve got a Center of Excellence, focusing on change management, focusing on the operating model, data governance, data ownership. And all of the ways to make this scalable. 

The first five steps on how to get started for us. First step, define your transformation. So before you do anything, before you jump in and buy a RPA tool or or kind of dive into the deep end, you first want to really figure out what’s your definition of success. What are we trying to do? Are we trying to drive more efficiency out of some of our back office areas? Are we trying to improve customer engagement? Are we trying to improve employee engagement? What are the goals and objectives that we’re trying to do? And again, we’ll go into that in more detail. And in the next webinar. We want to align our goals to our business objectives. And we go into this in much more detail, but you really just want to make sure that automation is not being done for the sake of automation, that you’re aligning to overall business goals and objectives. You want to make sure that you establish the right governance, you want to plan for your transformation and crawl, walk, run, conduct pilot before you kind of jump all the way in. So that’s a good brief description on how to start to get involved in process automation. Some of the lessons learned that we have from having done this is think about scalability, you want to think about growing this before you start. So how are we going to turn this into an enterprise grade automation versus just all of a sudden you’ve got 5, 10, 20, 30, 50 bots out there. And now you’re thinking about well wait a minute, we’ve got to start to reel this in and make this more of an enterprise solution instead of pockets of solutions everywhere else. You also really want to focus on In the process mapping, that is definitely something that I’m hoping you take away from this. It is absolutely imperative that you focus on not automating a bad process, and that you first and foremost, understand the process, improve the process, and then look for various specific tasks within that process flow that you can automate. And really make sure that you’re continually focusing on the business process outcomes and the value and your definition of success. More so than while we’re gonna have 20 bots at the end of the year, it’s like, Okay, well, why not 15? Why not 30? It’s somewhat of an arbitrary number. And sometimes you need to have something like that just to kind of help understand the scale of how fast or slow you’re going to move. But certainly make sure that it’s aligned to business outcomes. Also understand that whatever you start with is not going to be where you end. There’s got to be some pragmatism here. So you may start with a very centralized, very small controlled Center of Excellence, and then that may become more of a federated or hybrid model, as you start to get other departments involved, and they have a seat at the table on how automation can and should be done. As part of that Center of Excellence, make sure that you certainly are bringing change management to the table, you really want to make sure that you’re focusing on the why, not just the how and the what. So it’s not just what you’re doing, and how you’re doing it, but why you’re doing this, right attaching that to business outcomes, attaching that to the future of work, attaching that to what this means to the workforce, and really treating this as a digital workforce. So you’ve got onboard the scripts and bots similar to onboarding an employee with Active Directory authentication, and password resets and setting up access to applications. And now there’s a lot more there than you may originally think. And these bots need care and feeding some maintenance periodically. So you want to make sure that you’re doing that just as you give somebody a review or a touch base. And by all means, make sure that internal audit and other IT security and internal controls are involved in the process. 

So I’d like to thank you for participating. I want to talk again, in summary here about how this is not about unemployment. This is about the future of work, and about really cross training your employees, retraining them, and making sure that people continue to become more efficient and more meaningful in the work that they do. And it’s really about that progress of moving forward for the future of work. As I stated before, this is really the first in a series of webinars, and I’d like to thank you for participating in this one. The next one we have will be a deeper dive on the business value, and use case development, a deep dive on how to do use, identify use cases, and prioritize those based on tying it to business value. I hope that this one was helpful, and I certainly hope that you will join us on our series. Thank you so much for your time.

I’ve also provided some links here for you if you’d like some additional reading. So there’s a couple YouTube videos that we have created. The first one being about how you can source your BPO activity. The second one’s kind of a deep dive on that source to pay or vendor management process. We’ve partnered with chambers from UiPath on that one. There’s several blogs, I picked two that are introductory level for you to look at, and then a couple introductory articles from Forbes calm as well. And then, if you have any questions, feel free to reach out. Otherwise look forward to hopefully having you participate in future webinars. Thank you so much for your time.

Length of Webinar: 29:27

Originally Presented: May 28, 2019

After RPA awareness is provided and high-level process prioritization is conducting via ideation sessions, we help organizations select high-level automation candidates that tie to business outcomes. These outcomes are used to develop business cases for funding and sequencing.

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