#2 Demystifying Hyperautomation PART 2

Welcome to today's episode of the Process and Automation Podcast brought to you by The Automation Guys. This is part 2 of our demystifying hyperautomation episode. If you have missed part 1, we recommend that you get started with the previous episode. So let's get started.

So let's, uh, let's have a chat about process mining. So we just mentioned that early, uh, earlier, uh, early on. So shall we maybe go a bit deeper into this one?

Yes, I mean, what's your view? In my view, it's the new kid on the block, but not so new.

But yeah, so yeah, we started 2 years ago with process mining, but before, obviously, the, the, the, the extent how it has developed and what kind of use we can get with, with it these days is much different than to what we, what we did before was process analytics. So yeah, process mining as a technology is new, but effectively is looking at lots of data which is collected in systems, isn't it? So timestamps, event data, and then just trying to figure out how processes are really running. And all that stuff we have done obviously for years in a different way. It wasn't called process mining, but the cool extension these days is, yeah, they bring in AI and machine learning into these into the mix as well to get even more data out of it as well. Later on, suggesting specific actions based on the data which has been uncovered through process mining. But effectively, yeah, it is not really, really that new. So we have done process analytics and looking through data on how long a process has run, where was the process at a specific time, who has processed it. So all that stuff is not really that new, but I think it was the AI and the machine learning in the mix. We now can really get lots of insights we haven't seen before. So yeah, we're using this mainly now for our SAP customers where we take in all that data from accounts payable, and you can really see all the different variations the process actually is taking, which was not that easily visible beforehand with just process analytics. Now it's really, really uncovering the truth there that some processes are running with like 30, 40, 50 different variations, and then clearly can't be, can't be a good one, especially if you're working in a large global organization. If everyone is somehow treat the process slightly different. And there are good reasons for that here and there, but very often it is just people do not understand the process correctly or as it has been defined. And yeah, that will all come out of a good process mining project, and it's eye-opening for lots of managers out there. So this is why it's currently quite an exciting topic.

Yeah, and I agree. And I think it's, you know, for some of our listeners, it could be hard to actually visualize exactly how that looks like because, you know, we talk about process mining and conceptually what it tells you is, you know, where to spend your time to actually go and look at those processes that's critical, that needs some attention. I think in a, you know, I think You know, from a process mining perspective, ideally that's what it's telling you. It's telling you a lot about how your processes perform, and it gives you the bad apples. It gives you the ones that you perhaps need to pay attention to because, you know, you could apply monetary cost to how much your cost, your process cost per hour to run. For the different people that participate. So process mining gives you that ability to say, well, you know, this procurement process, you know, costs X amount every time it runs because all of these people are involved and these are the gaps in it, the waiting times. So it gives you the ability to find that And the nice thing about the good process mining tools is that, you know, you could plug it into your enterprise resource planning software, your ERP system, you know, perhaps like SAP or JD Edwards, perhaps Oracle, and it can crawl through your data and very visually tell you, you know, give you a list or a candidate list where problems are. And it is incredible how you can, you know, go through, drill into the details, and also to try and unearth what is going on. And also, if you have, let's say, a multinational company, of course, within that company, there's going to be similar processes, let's say, for procurement. And, you know, what you could do is understand for each country you know, who are the people that's really good at it and who are the people that's not really good at it. And perhaps learn from, you know, people in a different country. Well, how do you guys do it? Because I think sometimes people use a system.

Yeah.

You know, the people in a different country might be really, really efficient in how they do their process. But if you compare the same process with somebody, you know, a department closer to home, it might be totally different.

Yeah, there might be good reasons for it as well, isn't it? So it's good to understand it.

Exactly.

Yeah.

And, you know, if you go down, you know, what's the lessons learned here? You know, who can we talk to to ask them how you guys do this sort of thing? Then that's a good, quick win that process mining gives you. And it's strange, you talk to— we work with multinational companies, and you talk to the different stakeholders in different geographic regions, and sometimes it turns out that somebody has got a process and they've deployed RPA and nobody even know about it because it was just a department head that had the authority to do that. And they kind of just, you know, almost on their own did that and improved their own processes. And it's like, well, that's great. Can that work for us in this country? 'Yeah, okay, let's collaborate, let's have a look.' You know, that's one example, but I think it's kind of, you know, looking across the board.

Yeah, you mentioned a good point actually with RPA, that someone is taking some action. I think that's the key. Once we have identified all these things with our customers, then it is really key to take action based on that. So otherwise it's just great to have all this visibility, And if, if, if you can actually take action automatically based on that, even better. But I think another, another important point here as well is that it will uncover sort of a lot of areas in the business where you can then look for improvement and use automation. So, so some, some businesses sometimes struggle to find out actually what to do and what initiatives is really the most relevant one. But very often, as you said, so sometimes there's just this department view, which is great, they want to improve their department, but maybe in the grand scheme of the business, actually energy should be, or money and time should be put on Project X there, because this has real, real benefits after looking at all the process mining results. And this can actually help, so process mining as sort of the precursor for building this huge pipeline of automation initiatives. Because it will tell you, okay, we have these 30 different variations, but if we would automate this one here, so suddenly we are down 15 variations of the process. And then here we can do this and here we can do that. Suddenly you have a list of 30 different initiatives and then the results after implementing all that. Yes, it's immense. So I think with all these technologies like process mining, we need to really take the data in and take action. Yeah, like I say, as always.

Yeah, yeah. And I guess just to visualize this further for our audience, so a typical process mining tool will you know, look at an end-to-end process. Of course, it won't just look at one, it will look at all of them and then come up with really interesting stats. And, you know, it will tell you for each step in that particular process, you know, what are the waiting times, you know, because you could have a process which has got several steps and you know, after a particular step, there's a 10-day, 15-day gap where nothing happens. Well, why is that? You know, can we actually shrink that gap by deploying an automated solution when we understand what's causing that gap? So that gap could be that there is a delay between an invoice being send out and the payment being received. Well, how can we speed that up? Is there a training issue there that people don't know what to do? What is fun? And that's where you can then make that objective decision to say, well, we see what's happening here. Let's deploy a solution that bridges that gap. And then the good thing is that once you've got that solution in place, Because of the nature of process mining, it can be real-time. So you should see the effects of that pretty soon. Were we effective in plugging that gap? Yes, we were, because now we've got new cases that comes through on average that takes 4 days or 3 days to transition from this one state of the process to another one. And I think that's the key for You know, if, if you're not going to deploy all of the, the really progressive AIs and the RPAs, if it just unearths that I need to actually give people more user training there, or actually that area of the business is understaffed for that period of time when it's busy, maybe we just actually apply more resource. So these are some of the really important insights it provides you. Of course, you, you can deploy this standalone as well. I've seen where people create real-time dashboards, SLA indicators, where it actually looks at your real-time data, and then you could set up service level agreements against that and then measure, you know, the, the, the, the progress or the performance against your process performance against those SLAs. So, you know, and that's a really good— for operations manager or some managerial person that manages a team, that's great, right? Because it's like, you know, to find that information actually in your ERP system, you know, would probably involve writing a lot of reports and, you know, a lot of technical things that, you know, only perhaps IT can do or the vendor of your ERP system, whereas with the process mining tools these days, it is actually easy to assemble these dashboards and these alerts to say, you know, there's a problem here. You know, what should we do to tactically, you know, remove that, you know, and continuously monitoring it.

Great. Yeah, yeah, it's fascinating what is available for us and businesses these days. So all this part of hyperautomation has so much in it. So what do you think should we give out as a tip to sort of get started on this? Because this sounds all great, I guess, for some. So for some of our listeners, they think, okay, oh, process mining sounds great. How should I get started? I want to start with everything at the same time. Probably not the best advice, but so what do you think is like a good takeaway from this episode?

I think be curious, look at things, and if it is something that you feel is repetitive activity that's done manually, even something very small, that's a place you could start. Dip your toe in it. Hopefully this episode has provided you with some insight into what all of these terms mean. But I think the message is that you can start small. Of course, you know, you could reach out to myself or Sasha if you wish to discuss a particular problem you've got. Just to size it up and say, you know, how would you guys deal with this? So I think that the advice is really don't be scared to start small. It doesn't have to be something big from the start. It can be as big as you want it to be.

Yeah, that's a very, very good advice. I think that the small start, this is what we indeed also think is very, very valuable. So this is why we we work a lot with these labs, so where we offer everyone who wants to sort of try things out without they making the big step to just see how it works. Yeah, sort of hands-on. So a little bit like, yeah, it's a lab, LabWorld, and where you can— people can just experiment with small problems they have and then take it from there. Because sometimes, yeah, it's just very difficult to understand, especially over a podcast, what is process mining. But to to really grab it in a little, in a little lab is really, really useful, and I can recommend that.

Yes, no, I, I would agree. Um, you know, and don't, don't be scared to take that first step. Um, there is a lot out there that needs to, um, that needs to be digested in terms of the, the automation, hyperautomation space, but there key elements in there that I would say is fundamental to get going and also to start your culture of automation, where when problems come in, you see it differently. You know, rather than saying, well, I'm going to use a spreadsheet and start emailing people for their views, perhaps there's a better way to do that. To take that manual activity or the nature of that manual work out of that particular problem that you want to solve. And again, there's a lot of information out there. Hopefully by continuing to listen to these podcasts, we can tell you a lot more stories in the future. We're going to share a lot more. And, you know, Hopefully that, that would give you the confidence and the insight to, to start your journey.

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