#14 9 Great Use Cases for RPA - Part 1

With Robotic Process Automation, your business can automate processes and tasks that are typically carried out by your employees. There are several ways to use Robotic Process Automation effectively in your business. In today's podcast, we will go through a couple of business areas to see where RPA is especially useful. Hello and welcome to our episode Great Use Cases for RPA. With RPA, you can work across different application— applications, platforms, and departments to automate your business processes and to free up your employees from manual repetitive work. Also, RPA can integrate very well with existing IT infrastructure and it doesn't require any additional installations. And the best is that companies don't have to invest heavily to automate essential processes. And there are several ways to use RPA effectively in your business. And then in the next minutes, we will go through 9 use cases. And yeah, with me here is Arno again. Arno, which one— which one would you like to kick off this episode?

I think we should start with the most popular one, Sasha, which is customer service. It's obviously one that's close to the hearts of many businesses to make sure that your customers are satisfied. Of course, you know, modern customers are very accustomed to quick responses, you know, from customer service centers because, you know, there's all of these options, these engagement channels that's available. So, you know, it is possible using RPA AI to deliver these quick results that customers want, you know, from their customer service journey. So, you know, automated customer service assistants can do all sorts of things for you. So it could sort out initial queries, for example, and offer initial responses to customers. So where you ping a customer service help desk via a chatbot, or a sort of any automated route. It could even be using telephony. It's good to take those queries and really sort that and actually put that to the right department. So the tech department could deal with something that relates to any technical queries, the service department for anything relating to service delivery, and so on and so forth. And it just really ensures that the queries sort of reach the right customer care agent for a very quick resolution, rather than sort of transferring calls between, you know, one customer service operative to another. So, you know, a lot of the rules within site customer service and the way that the customer service journey is routed, all of those rules are generally predictable. And, you know, according to recent research, I think it was also McKinsey that did this, you know, over 70% 80% of customer services queries are rules-based. So, you know, these processes can be automated. So it is a really, really good starting point and an excellent use case for RPA to get started with, you know, this particular customer service automation.

Wow, this is amazing, 80%. So it's actually for every business who is currently doing it manually, it's basically losing a lot of capacity, isn't it, they could use somewhere else. And, you know, I think we discussed as well recently chatbots, and I think combining that RPA with chatbots, I think, yes, this number can potentially go even higher.

Yeah. And I think, sorry, yeah, I think this is also where you see the winners and the losers in this space, where if you look at somebody like Amazon, for example, or somebody like Apple, I mean, there's a lot of other examples as well, Their customer service journey is extremely effective. It's very light touch. It generally gets to a resolution very quickly, and it leaves you satisfied. You could debate whether or not the product or the service is affordable or not, but I think with some of these larger corporations, it almost becomes irrelevant, you know, what the service costs and what the product costs. It's just these value-added services that, you know, that if there is going to be a problem and you do need to return the iPhone, it is extremely easy to do so. And, you know, that all is driven by automation, and, you know, that equates then to huge levels of customer satisfaction and levels of satisfaction Interesting.

I think another one which is really, really popular and seems like it's always current. Sometimes I think, okay, what are companies or what have companies done for such a long time that invoice processing is still a big topic for automation? But invoice processing is really like a top use case, and I think that probably is because some companies they not always have been around for so many times, isn't it? Some companies are just at the journey where automation probably starts to make sense for them because the invoice volume gets larger, or maybe there was a merger and acquisition, suddenly that might be a reason. But for some reason it is a very hot use case. Even with some— yeah, we built something a couple of years ago, the Intelligent Capture Cloud, just for that sort of purpose to really process that large volume of invoices coming into companies, and very often they end up in mailboxes and then will be processed, usually manually entered into ERP systems and so on. So I think this large volume of invoice processing, very repetitive, very manual, can delay a lot of payments. And because they have been entered maybe incorrectly into the ERP system, or they not even entered correctly into any kind of system, so they're sort of lost. So this obviously produces a lot of, yeah, I think a lot of, not grief, but unhappy suppliers. And this is something you can avoid easily. And yeah, with invoice processing, I think Usually the challenges are with the formats of the documents, but now with RPA and combined with AI, you can now extract all this information from these invoices easily. So you don't need to be a human employee to just make sense of that invoice. Invoices are generally quite structured, so there's an invoice number, there's a total, there's a VAT number on there, so the system can check check on those things very easily and verify that maybe with a purchase order system at the same time, was this invoice a proper one which is okay to process further? Or yes, all that stuff now can be done in combination with OCR and AI and OCR. OCR suddenly is very, very sexy again, around for so many years, but now with RPA. OCR is really, really, really cool. Basically the eyes of the robot going in this new modern world. So yeah, I think taking all the data and put this into structured format and validate on that data, finding out if there's some errors and then processing it end-to-end really into the systems. I think that's the power. On invoice processing. And if you have huge volume, I think that's, that's becoming very clear that you're just wasting a lot of time doing it manually.

Yeah. And you mentioned just from a startup business that start with invoice receipt to payment, which is sort of generally called accounts payable. You know, perhaps they start with a shared inbox, and from a shared inbox they use an Excel spreadsheet to track it. From there on, it gets emailed across to various people to, to process it, approve it, and then to do the final payment. But I think what we're seeing is that even for smaller scale invoices, you know, not even thousands, but I think sort of in the hundreds or even high tens, you know, it is very, very easy to use desktop automation tools I mean, even something like a UiPath attended robot or even something like Power Automate, you know, these sort of things are brilliant at actually looking in shared inboxes, identifying document types, which is, you know, classification engines that could say this is an invoice or, you know, this is some other document. And then from there on, string that into your— or actually feed that into your accounts payable process. So it is, it is also, I guess, you know, a lot of people always talk about the volumes. I think the, the fact is you can also start with smaller volumes because of course what you would see is increase in accuracy. And, you know, and I think sometimes You know, a lot of people again promote the sort of high volume, low value transactions. But I think that there is a case, especially for something like invoice processing, where, you know, it should be something that should be in your business, you know, as soon as possible, really.

And I think if we discussed this a while ago as well, isn't it? If it can be automated, it definitely should be automated. Yes, exactly. I think a startup or any kind of business these days should have an automation first kind of thinking. That's, that's what I believe. With growing pressure on organizations to operate at digital speed, low-code development has emerged as an opportunity to more quickly transform. How do you know if it's right for you? So if you're forced to accelerate operations, improve the customer experience due to continually evolving expectations, Visit our website, theautomationguys.net, and download our low-code guide and learn all about the secret of low-code success. Just never come into that situation that you have to use your valuable capacity on, on these really tedious admin tasks. And there's certainly the really rule-based ones. Yeah, absolutely.

Yes, so that brings us to the third use case for RPA, which I think is quite an important one, which is to do with sales order processing. Now traditionally, data consistency, you know, within site enterprise system is a very tedious task to get like a really good consistent data set. And you have scenarios where sales representatives spend a lot of time actually entering this data into CRM system, and then they go to ERP system to enter the data there. So there's some duplication there. Financial analysts then go and replicate data into perhaps other modules to get some good visibility into reporting, and this results in obviously a lot of duplication. It's prone to errors, and, you know, it affects productivity of all of these people that's involved. So with RPA, you know, we can automate these sales activities end to end by automating tasks like the sales order entry, for example, or invoice creation, you know. And all of this helped to maintain a really good database where you, you know, remove that duplicate data entries. And of course, you know, you improve customer experience as well in the process. And you also, you know, your sales team, you improve their productivity You're going to improve their employee satisfaction because you're removing these time-consuming tasks like double data entry from their day jobs, right? And then they can start to concentrate on, you know, their actual main task, which is, you know, prospecting, lead generation, and actually going out to generate more business.

Absolutely. Yeah, I think that's a very, very key thing for salespeople, isn't it? They want to earn, they want to do more sales to earn more commission, and they don't really, they I think it was even very early on when we introduced CRM into the sales process. I think they said, I can't be bothered to enter everything in here, so I just want to get out and do the deals. And clearly, yeah, absolutely understand them. They shouldn't really dealing with this stuff. It's just not their thing, isn't it? So lots of salespeople are like hunting. So this is just admin stuff. They, yeah, they will be your best friend if you start automating this.

And I think a lot of good salespeople are quite diligent in maintaining CRM systems and ERP systems, but I think they— it also causes a, a great degree of frustration. It takes time away from them that could be used selling. And of course, not everybody is very consistent, so you might have somebody that's very diligent that actually sit down and do these double data entry, but then you're going to have other people that's not really interested in it. And also the process breaks down because you don't have a consistent process. And of course, that's where if you do reports on your figures or you need to go into the CRM system and see what the update is on an account, it can produce inconsistencies if you don't have a streamlined automated process. So you can remove a lot of headache takes from your, your sales process by deploying RPA, and that's why it made number 3 on our list.

Fantastic. Yeah, so the next one we picked is payroll. So also a very, very time-consuming activity which happens once a month for all the employees of your business. And in some organizations this is done really still manually, depends really on the company size. But I think we, when we look back last year when we went even started, suddenly payroll got far more complex and, and then it got even more, more time-consuming to work out what is the right payroll figure and how to calculate all that stuff. So this is just an example how complex payroll can be. And if you, if you, if, if you have some form of automation in your payroll process with RPA, you can just verify that stuff, especially if it's a lot of workers. You suddenly, for example, had on furlough, then I think you could do all this in sort of in a bulk processing and with RPA and update your systems accordingly and just make sure it's all proper and validated. I think without that, things can go wrong. And then I think the big problem is there if something is wrong, employees will become dissatisfied, really, isn't it? So if something is wrong with the pay, I think is one of the worst things which can happen. So this is why payroll automation and calculating benefits, reimbursements when they have been on business travel, all that stuff needs to go in as well. They potentially get some car allowances or expenses paid back, so that needs to flow into payroll. So I think checking all that stuff with different multiple systems in place, I think that's— yeah, I think this is, this is a big one. We will probably see more and more coming, coming. Going forward.

Yeah, I think number 4 on the list, definitely deservably so. You use the word employee dissatisfaction. I can think about harsher terms rather than dissatisfaction if you, if you don't get your, your salary at the end of the week or the end of the month. But yeah, I think, you know, it, it is one of those things where you want to get it right. The numbers needs to be spot on. I think consistency here is king, and there's no reason why you shouldn't have a fully automated payroll because it is very predictable. And, you know, these are, you know, some of the things that as a business, you know, and, you know, you, you did mention employee satisfaction, dissatisfaction, but yeah, it is a key driver for it. So the next one that made our to the top RPA use cases. At number 5 is price comparison. Now, a lot of businesses out there that produces products tend to bulk buy components and to provide these products or services. And, you know, obviously the cost of these items can impact a company's revenue or its profits. So companies always, you know, do research online to source these products or the components that goes into their products and to source for the best prices and also to make really good informed decisions. So this research process into, you know, finding the right components to put into your products at the right price is very time-consuming and quite complicated. So, and this is one of the reasons why a lot of companies are actually starting to use RPA to automate that research. You know, you can train a bot to be able to go to different vendor sites, you know, download price lists, do comparisons automatically, and then make recommendations. You know, and it's not just comparing prices from these different vendors, but it can also, you know, compare product attributes, its quality. So you could really, as a business that manufactures something, you know, can buy that, you know, that best product or the best resource you need at the best price possible. And you could really automate and streamline that complete process. So that's a really important one as well for us in terms of a use case, and hence why we put it at number 5.

Yeah, I think sometimes there's a bit of a negative word to going to websites and finding that information. I think there's this word scraping coming up, isn't it? Scraping that information with the bot. I think it comes across a little bit negative, but basically that's— this is how we get this information from going through websites and extracting that information, that structured information like these attributes. I think there's a very interesting project currently we're working on. It's all about change and climate change. So if companies want to purchase stuff, so they could say, okay, I want to buy this Samsung TV, but that has a specific set of energy attributes. And just finding somewhere, wherever out there, you need to to maybe compare on that energy efficiency going forward. I think this becomes a topic more and more, and I think this is where the bots can then help as well to help businesses to find the right products to support the climate change agenda. Yeah, that's— even the scraping sounds maybe a bit negative, but there's lots of positive in the outcomes. Great. So I think the next one we picked is storing customer information as a use case. So 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]