The Process & Automation Podcast Episode #15 - Great Use Cases for RPA - Part 2

So you probably, yeah, if you have customers and lots of customers, there's lots of information about your customers you might want to store in your CRM. System and sort of every kind of activity or event around your customer you want to store and react to it. Because yeah, you can, the basic stuff we all aware of from what we would store in a customer information system, CRM system, is a typical contact information. But you also would like to potentially store purchase history, any kind of preferences on product, type of service, product category? Is it, is an RPA product they're interested in, or are they more, more into case management, that kind of stuff? So, or birthdays and anniversaries, I think company anniversaries or personal anniversaries, this kind of information is, is really important for, for businesses because we always need new sort of touch points, more touch points with our businesses, and we're really work on that client relationship and to either sort of maybe reward your customers or really supporting a deal which is currently in your pipeline to close it. So all that customer information or prospective customer information is really, really important. And yeah, so there's lots of that activity what we do manually. And again, with lots of data sources out there, doing all that stuff manually, this will be very time-consuming. It wouldn't be very accurate either, potentially. So we are humans, we make mistakes, right? So with RPA, we can really get that information and the huge amount of information we have around our customers, we can really store that in all our systems easily. And yeah, so that kind of repetitive tasks, I think we could really reduce that by 80%. This is what research says. And states.

Yes, no, absolutely. And I think, you know, a centralized customer information hub or a client knowledge center or a customer knowledge center is, is such a key capability for a business to have really that know your customer sort of mantra with inside the business. And I mean, you know, we've, we have built client knowledge centers before, very successfully using RPA and low-code, and it is such a great tool to have for sales executives, top executives, so that they can actually see, you know, a 360 view on the customer, including business development, what's in the pipeline, account management. You know, you talk about personal information, we call it 50Q. So 50Q is is 50 questions that you, you know about a customer, you know.

That's good.

Not, not necessarily, um, who's their, who's their favorite football team, but it could be things like that that really gives a personal touch and, and really promote the, the fact that you, you understand and you know your customer. Um, you know, of course, if you don't have the automation in place, what tends to happen And what we see is every account manager does stuff differently. You know, you have account managers that uses a combination of spreadsheets, SharePoint, PDFs, different types of PowerPoints that they want to create aggregated information of that particular customer. You know, different formats of organizational charts because org charts is a very key thing in a a customer information database, you need to understand the organizational chart. So you understand who's the decision makers, who's the influencers, who reports to who. So these are vital information for account managers. Of course, with something like this where you automated using RPA, you can constantly go to Salesforce, scrape the chatter, what's the latest chatter on this account, surface this in your customer information database, with a low-code overlay that's accessible using, you know, mobile, tablet, browser, offline capability. You know, we had something that's called the Taxi Report, and it was literally something where a salesperson go from one meeting to another meeting. They just want to sit in the taxi, have a quick report because they're always running around, they're quite busy, but they just want to have that quick go-to report to almost 5 minutes before the meeting to give them that insight. You know, where are we? Are we red, amber, green? You know, what's on the horizon for this customer? How does this customer spend compared to other accounts, etc.? So it's a very key one as well, and I think that's why we decide to put this at number 6 in our RPA use cases.

Yeah, very important.

Yeah, so the next one that we'll touch on as a top use case for RPA is back in the realm of HR. And in this instance, what we're looking at is, you know, processing and storing HR information. Now, what we mean by that is that it takes a lot of time to actually aggregate huge amounts of employee data, you know, from things like, you know, employee history, payroll reimbursements, the training an individual has received. So these are all data points that are associated with an employee. So to have that that one sort of 360 view of employee can sometimes be a very challenging thing because you have to source data from so many places and it can take a lot of time and it's a very tedious process and of course error-prone because there could be multiple sources. So this is a big headache for, you know, for HR departments and, you know, if you have a you know, a need for, for a really deep insight into your employee records, you know, it is something that, that you would probably need to automate. And RPA is a very, very good capability to do this, where RPA system can go and collect information from various systems. It can then organize all of that information, you know, bring that employee employee's history through from, from a place. The payroll data can come from the payroll system, the level of training they've got. So you can aggregate all of that into, you know, in, into one place, um, and that really allows HR to have a sort of a one-stop view of the employee. And, and again, it's, it's back to the same old where rather than HR executives actually doing the data capturing, the sourcing of information, if that's handled automatically, then what HR people do is what they do best. They focus on human aspects of HR, right? And I think that's the key here. And they can then work to improve employee productivity and work culture and all of the rest can be handled by automation.

Yeah, absolutely. I think that's, yeah, it's key to see where your employee is, isn't it, in the organization. If you have a small team, I think that's easy, but as soon as you have a couple of hierarchy levels in there, yeah, absolutely key to have that. So the next one, coming nearly to an end. Processing of fast refunds. So again, when it comes to customer satisfaction and company's reputation, I think when we think about an insurance company, for example, or so like a big retailer, if you can't handle your refunds efficiently, your customers will become quite upset. Or if you claim UK claim processing, that kind of stuff is just very slow. You had an accident and all that kind of stuff and it takes ages, then you become very, very unhappy. So, so with RPA, you can make this process to be, to be really quick and seamless. And yeah, so I think by, by just having this sort of this, this mechanism of RPA, you can tap into all sorts of different, different systems to come up them with a specific answer. You can use AI combined with RPA to come up with the right answer for that specific complaint or that specific transaction which was wrong. So you can collect all that information automatically, pull that all in, and then do these steps, these next logical steps, which are again very rules-based activities very often. You can really just sort of do them semi-automatic or nearly 100% automatic if there's no real exception coming up and everything is sort of ticked and fine in general. RPA can process this whole refund automatically and then within a couple of minutes you might have already your money back in your account. So I think if you have a huge work queue of that in your organization and customer services and you have to go through every kind of request and case and meta manually, then yeah, yeah, it will be very, very likely the refund processing will be very, very delayed. So I think it's very key in customer service to deal with those kind of requests.

Yeah, and I mean, just on refunds, I think for me it's putting the right type of process for the refund against the value of the refund in the right place. And, you know, and it's back to that sort of 70/30 rule or 80/20, you know, depending how sophisticated you are. If it's a refund on a low value item, you want that to go through almost instantaneous because the cost of actually doing that manually is probably more than what the item is worth. So what you want to do is you want to create a scenario where you've got the different levels of refunds, all with various types of automation. You know, on the one side of the spectrum, fully automated, it's a very clean-cut case. The customer's got a fault on a product, maybe they engage with a chatbot. The chatbot actually uses RPA to do some inquiries in the background. 5 minutes later, the customer's refund is processed. Happy customer, you know, very, very good boon for the reputation of the company. Satisfied customer, they'll probably stay with you. On the other end of the spectrum, you might have a very complicated refund, or can be insurance claim, where you could do some of the initial data gathering using a robot. The robot could actually engage the customer through, let's say, a chatbot. That's a very popular channel. And then once all of that information is aggregated, that can then be handed over to a human in a very convenient format where the robot's done all of the initial checking, security checks. It's, it's laid out what the refund is about. It could perhaps be a high-value item, so they perhaps needs to be additional, additional inquiries. It could be a bit of a workflow. But are you deploying the technology in the right way? And you're deploying it and engaging the right type of stakeholders at the right time? And because of course, if I'm gonna return my Tesla because I don't like it anymore, it's an $80,000 car. No, it's not gonna be 24 hours or you know, 8 hours later, refund in my account, you know, uh, it's gonna— the expectation is that there is going to be somebody that, um, you know, on, on, on the, uh, the refund side from the business that would look at it. And from, from me as a customer, you know, that, that is an expectation I would have because, you know, it's a high-value item. Not that I'm saying you're going to return your Tesla, um, you know, and obviously other electric car brands are also available, but I think if, if you use the same type type of process to return a very low-value item. And that's silly. That's, I think, where the cost to your business then increases. And I think RPA could do you a massive favor here by automating those sort of high— low-value, high sort of volume type refunds. So the next one we'll look at is recruitment. And RPA can be an absolute godsend within the recruitment space. Of course, recruitment processes themselves can be quite complicated and long-running, and RPA can really streamline this process considerably, you know, from initial, you know, placing a job role to the whole HR process. And beyond into the onboarding process. Now, of course, you know, with recruitment, you know, you will have resumes from a lot of platforms and different sources, and you have to sort through spam, and you have to discount obviously undesirable applicants, and there's loads of other factors, you know, where you want to, you want to take a lot of stuff and you want to discount a lot of things and you want to just deal with the things that's important to you. So by deploying RPA, you could have that capability with inside your business and you could really streamline your recruitment process considerably, even as a first step, by just automating that initial noisy part of it where you have to go through a lot of information just to get to the, the things that you want to pay attention to. And of course, you know, if you're a recruiter, I know it's quite a stressful job, I can imagine. You know, you want to be able to spend time finding the right candidate and bring that candidate through the right sort of interviews. You don't want to actually, you know, spend a lot of your time sifting through things that you don't want to pay attention to. So, you know, all of the screening, assessing, You know, I mentioned onboarding as well and the administration beyond that. All of that can be automated with RPA. And I think recruitment is— and this is why we put it on the list— it's one of those processes as well with inside a business that's got high degrees of automation abilities. You know, we look about what we sort of in the 90% range because the process is so predictable, and that's extremely high. So, so You know, and that's, that's one of the key reasons why we think it's a very, very good use case for RPA.

Yeah, you mentioned onboarding there. I think, I think not just for, for finding the right candidates, onboarding is such an important thing these days too, especially now with being virtual a lot. I think getting, getting, getting that experience for new employees right is very key. And if If your process, your automation is already making sure things are happening 14 days before someone is starting the job, getting the right information out, requesting the right information, I think it feels like a really nice, very well organized onboarding process. The experience is much better. You have people turning up for your first day of work very excited instead of hearing nothing on the first day. They are bombarded with massive amount of forms, maybe not even well-structured, I think that's such an important thing because retaining your recruits while we're going through all that stuff, finding the right recruit, I think the onboarding experience is one of the key things to actually set off with the right sort of mindset and energy into your new job. So I think it would be quite pointless if you get those things wrong as well after going through a very brilliantly automated recruitment finding process and mess, mess, mess that part up. So yeah, very, very key focus has to be on the onboarding. Yeah, yeah.

So it just falls off the cliff then. So you've got a really good— and to be honest, you could have a recruitment process where if you don't deploy a lot of RPA, you would potentially, you know, have the recruiters doing a very good job at making sure that the process is very streamlined, the experience from the prospective employee could be really good. Then, of course, the handover to onboarding, that's where the problems start. And then the employer might think, wow, this went so well. Now the onboarding is really messy and not very consistent. And, you know, they forgot to do certain things. I don't have all my system access that I need for day one. You know, there's so many examples of things that would really start things off on the wrong foot.

Absolutely. I think another, another interesting aspect about recruiting is, and the automation element is, you can find candidates very unbiased. I think this is what we hear a lot as well. So if you do the manual sifting, so there's, there's some bias in going through CVs. So, but if you now let an AI looking through a huge amount of data. Sure, it really depends a bit on the AI and how it might, might have been processed, programmed. But in general, you, you would look at CVs differently because you're not going in with your subjective view on things. So you would effectively find candidates you might have not seen before or sort of, yeah, rejected before. So that helps you as well to to be more diverse company. And because you're purely looking at the level of talent and qualification and that kind of stuff and not any other factors. So yeah, very, very, very good point there as well. So yeah, so that was number 9. So as we said, we will have 9 really good use cases. Shall we overdeliver one more, Arno? I think there's a good one Yes, space for one more.

So do you want to tackle it?

Yeah, I think we touched on something of structured information and unstructured information and extracting data from lots of different formats. I think that's a very, very important one. As I mentioned, yeah, we purely, we built a product based on this, the Intelligent Capture Cloud, to just really extract that data from unstructured data sources. So I think data is really coming through in your business in all sorts of different formats. Invoice obviously is an easy one, but sometimes you have this lots of different price lists coming in, you have quotes coming in, you have reports coming in from different suppliers and vendors and employees, and all your stakeholders might send you all sorts of weird stuff. And and it's important for the process, for your business process to continue. And yeah, I think with going through all that stuff, this is again very, very time-consuming to find that maybe key information from these different formats. This is this time-consuming element, but with OCR, optical character recognition, combined with RPA, you can let the system really work through all these different things and different types of documents, handwritten notes, emails, contract documents, all sorts of type of documents, and find the relevant information you need. And then you can store depending on what information it is, classification. You mentioned that earlier. I think that comes in here as well. I think it was the power of RPA. You can just have that bot 24/7, 365 days a year, really work on on all sorts of documents and extract that valuable information from that document and populate the systems which need that information. And yeah, that will definitely free up a lot of man-hours to— yeah, and I think even the claims process is what you mentioned. I think that capability in general, unstructured data to structured data, I think that will help all of these RPA use cases in some way. And so it's a very, very important use case, an important area to look at to be really, really more productive.

Yeah, and they say what they call this is recitative tasks, is where you take information and you have to re-key it in or interpret it and key it in a different system. And it's interesting that around 10 to 20% of employees' time is spent on tasks, you know, like this. So, so that, that's a huge saving that you can immediately bring into your business when you need to extract data from different formats. And it's very easy to do that using robotic process automation. And that's why I thought this is a very, very good one as well. Very good use case that's worth putting on the list.

Yeah, that's great. So now we have shared 10 really good use cases with you. And yeah, as you can see, RPA can be implemented in really several interesting ways. It requires some practice, of course, and getting used to it. But I think once it is implemented in pieces, I think Yeah, I think your employees will easily adopt to this new way of working because you're freeing up your employees from these repetitive mundane tasks and most of them will be very, very happy so they can not do copy and paste in systems anymore and extract information. So they should be far more satisfied and really put the capacity in something which is really value-add and maybe speaking to customers more often and that kind of stuff. So yeah, Arno and I, we as the automation guys chat with lots of businesses and we encourage all of them really to get started with RPA. And Arno, I think we agree here, starting small and automate one process at a time and just see if there's a really good choice for the company. I think that's a good way to really get started. And yeah, so yeah, we have covered, I think, yeah, probably more than 6 or 7 episodes on— we covered RPA on the 6 episodes already. And the really good one in detail is the 9 Steps to RPA Success. So if you haven't listened to this episode so far, yeah, I recommend to have a listen. And of course Yeah, we'll add this link and we have this link into the, into the show notes. And yeah, there are 10 use cases, but there are for sure hundreds more use cases. And Arno, I'm sure we will cover a few more here in the future.

Yep, absolutely. Like I say, it's, it's hard to pick your top 10, but this episode actually gives you a bit of an insight into why we we chose these 10. But of course, like you mentioned, there are hundreds, if not thousands. And the best way to get going is to get started small and to really explore the art of the possible. You will be surprised how many other ones will become visible once you understand what this can do for your business. You will go into your business with a different pair of lenses on and see potential opportunities everywhere when you start with automation.

Yeah, okay, yeah, that's true. Yeah, also let us know what you like to hear from us more. Visit our website, The Automation Guys, and yeah, of course, leave us some feedback and suggestions for more of these topics. Yeah, thank you all very much for listening to our episode today and see you all very soon. Unfortunately, that's it again with this episode of the Process and Automation Podcast. If you like this episode, please give us a 5-star rating and don't forget to subscribe to this podcast so you don't miss any upcoming episode. We hope you will tune in next time, and until then, let's automate it! [MUSIC] [MUSIC]