Seeing the Work You Shouldn’t Be Doing: Process Intelligence, Hidden Factories and the Future of CI with Paul Rudge

In this episode, Liam O’Neill speaks with Paul Rudge, Process Intelligence Manager at RS Group, where he is helping to bring together nearly two decades of continuous improvement experience with a new generation of process intelligence capability.

Paul has spent most of his career in Lean and Six Sigma roles, working hands-on with teams to drive improvement across complex operational environments. More recently, his focus has shifted towards using data and process mining to understand how work actually happens at scale, particularly in the context of RS Group’s SAP S/4HANA transformation.

This is a practical and grounded conversation about what really changes when you move from traditional continuous improvement to a more data-led, process intelligence approach, and why greater visibility does not automatically make improvement easier.

They discuss:

• Why process intelligence can be “almost too powerful” at first, and how insight overload can slow you down rather than speed you up
• The shift from improving hundreds of small things to focusing on a handful of changes that genuinely move the needle
• Why most organisations underestimate the scale of variation in their processes, and what happens when you finally make that visible
• The concept of the “hidden factory” and how process intelligence exposes the rework, manual touches and workarounds that traditional reporting never shows
• Why years of well-intentioned customisation can make processes worse, and how standardisation can be a counterintuitive improvement
• The gap between what people think the process is and what is actually happening in reality
• How process intelligence supports ERP transformation by revealing complexity, reducing variation and identifying unnecessary work before migration
• Why governance only works when accountability and visibility are in place together, and how making processes visible can drive behaviour change on its own
• The importance of validating data with subject matter experts, and why even the best tools can produce misleading conclusions
• Where AI is starting to add value in process and CI work, and why it still depends heavily on human judgement and critical thinking
• Why continuous improvement as a discipline has been slower than expected to adopt AI, despite its potential

Paul brings a pragmatic perspective shaped by years of experience delivering change in real organisations. If you are working in continuous improvement, process management, transformation or ERP delivery and trying to make sense of how process intelligence and AI fit into that world, this episode will give you a clear and honest view.

Host: Liam O’Neill, Managing Director at bpmd
Guest: Paul Rudge, Process Intelligence Manager at RS Group

Transcript

SPEAKER_01 0:01

Welcome to Work in Process. We are Liam O'Neill and Sam Lewis. This show is the leaders who are responsible for improving how their organization actually works. If you lead process, transformation, IT, enterprise architecture, data or operations, and you are accountable for turning strategy into execution, this podcast is for you.

SPEAKER_00 0:22

Across the organizations we work with, we see a lot of investment in teams and tools, in programs, different softwares. You get dashboards built, processes modeled, programs launched, but that doesn't always translate into real business outcomes, into bottom line results, into something you can point your finger at and say, yeah, that's worked. If you are serious about building a structured, data-led and outcome-focused approach to change, we are glad you're here.

SPEAKER_01 0:51

This is work in process. If you get any value from this episode, please subscribe. You will get a brand new episode before anyone else. The views and opinions of our guests are there alone and do not represent those of the company.

SPEAKER_00 1:02

Welcome to another Work in Process podcast. And with me, Liam O'Neill. Today I'm joined by Paul Rudge, the ProSt Intelligence Manager at RS Group. Now, Paul has a fantastic background in continuous improvement and is increasingly growing into the process and process intelligence space. So I think today's conversation you're going to find very interesting as it brings together those two different worlds of CI and BPM, seeing where there's some conflicts, some synergies, and where it all works together really well. So without further ado, I'll hand over to Matt himself to give you a bit of an introduction. Paul.

SPEAKER_02 1:33

Hi, I'm Paul Rudge. I work for RS Group and have done for about eight years now. Process Intelligence Manager, as Liam said, this is a fairly new role as we go to a new phase within the RS strategy going forward as we make some changes. My experience is all within continuous improvement historically. I've been working within the continuous improvement space for about 17 or 18 years now. So I've been going at it for quite a while. And this is kind of like the next leg on the journey using Datron transformation to turbocharge CI for the future for RS.

SPEAKER_00 2:04

Super. So you've had a long time with RS Group. So moving from that continuous improvement role, from that continuous improvement business partner space to taking on process intelligence. What have you felt as the biggest shift in the way of working, in the kind of work that you're doing? What prompted the move and how are you hoping to move differently on that?

SPEAKER_02 2:22

I think there was a couple of key drivers as to why the move happened. So the first and the biggest, and something that'll be familiar to many in our sort of industries, is the move from SAP EC6 to a SAP 4Haler integration. So, like a lot of our organizations over the years, I think we've customized our SAP quite a bit. We quickly realized that in order to make this move as smooth and as seamless as possible, we needed a better understanding of our processes, especially around the amount of variations that we have within them. So a large part of this move is focusing on understanding that variation and hopefully aligning and simplifying as much as possible to allow for a cleaner migration to South 4 Hannah while reducing risks along the way. Coupled with that, the data intelligence side, the data mining element that we are bringing into the organization also helps to take the continuous improvement background to a whole new level because we've always been very data focused. We try to make data-to-use decisions, but the data mining and what is available today just takes us that little bit further than what's been available in the past and allows us to get a much better understanding of what's going on and hopefully a better foundation for making improvements for the future.

SPEAKER_00 3:27

And in that vein, making that foundation for the future. And before process intelligence, you're in lean, you're in Six Sigma. How does that ground in foundational competence here, how does that form your personal approach to driving improvement, to driving process intelligence work?

SPEAKER_02 3:42

I've been doing lean six sigma in various guises for about 18 years now. I think over the last few years as well, we've played around a little bit with Shingo, which some people may be aware of as well, is that kind of an ideology, if you like, a set of principles. And both are great, have some great principles, some ways of working, but both have their limitations as well. I think over the years I've very much been a fan of a contingent approach to continuous improvement. I'm a huge believer in horses for courses. And I know that in the past, within RS, but in other organizations that I've been to, sometimes CI can almost be seen as stuff that people have to do on top of the day job. They don't always see it. They see the improvement, but they struggle with the journey there. So I think this is a moving for the contingent approach and trying to really focus on what makes a difference. I think this will hopefully allow us to focus that a lot more accurately so that we can really be just working on the smaller number of things that are going to have the bigger impact rather than whereas in the past it was a bit more of a scattergun where you might try to improve 500 small things. I think it's really having that ability to focus on some of the uh big needle movers, if you like, that are going to drive us to do things differently.

SPEAKER_00 4:44

And when you say the contingent approach, that is what you mean by that, right? Raman going big bucket, everything, just taking the biggest, the most impactful changes and focus numbers.

SPEAKER_02 4:52

A little bit of that, but I think a little bit in the past, we've been, and I think a lot of organizations get this, especially with the Six Sigma and the Shingo approach. Sometimes it feels very prescriptive. It feels, oh, you've got to do this chart, then you've got to do this graph, then you've got to do this piece of work here, and then you've got to do that. From a contingent approach, we've tried where possible to streamline that. I mean, there's a difference between people that are going through training and certification. There's obviously a level of rigor up and above that you would go to for that. But where we're just doing day-to-day projects, it's doing that right, it's having that kind of lighter touch of not necessarily being completely wedded to some of the more complex tools, just to tick a box and meet an ideology. We've just used the tools and the principles that would matter for a specific project rather than going through that tick box exercise of making sure we've done this, that, and the other all the way through. If it makes sense, we do it.

SPEAKER_00 5:40

If it doesn't, we tend to not. It makes a lot of sense. Is that something you're bringing into process intelligence as well, rather than sticking to all the bells and whistles of formal approaches, just trying to find what works and what's a good fit?

SPEAKER_02 5:52

Yes, and it wasn't necessarily how we started. So it was one of our early learnings for those that have dabbled in the space of process insights and process intelligence. They're almost too good sometimes. They can give you so many different things to go and work on. When we first turned it on, you'll get raft to raft of KPIs that look like they have opportunity and things that you could go looking at within them. You almost get blinded by it, you can't see the wood for the trees. So, one of the things that we started doing originally, we'll go and we'll pick the top 30, 40 activities and we'll go and sound them all out and do a bit of work and understand them and then go and work on the best ones. The problem with that is it's actually quite a lot of work to do the validation piece, to do the tie-kicking that you need to do before you really get going with some of this activity. And the businesses, as a lot of businesses are at the moment, especially with all of the other stuff that's going on, was quite busy. So it's we don't have the resource to do all that checks and balances. So we then started, and a bit of a recent development was to turn that around slightly and go, well, don't mean wrong, we'll still look at some of that in time and we'll work through some of that stuff that you might not have thought about, but actually we'll focus the process intelligence to look on the stuff that you know you're gonna have to put resource against to go and fix. We'll just turbocharge those fixes and then we'll move on to the next thing. So it's that way of thinking of rather than going after the 30 or 40 things that are out there, it's it's what are the five that are really going to move the dial and are already on the radar and are already important to you. How do we help you do them quicker? How do we help you get to the root cause faster and implement them?

SPEAKER_00 7:15

That's a brilliant approach. A lot of the BPM teams that you see, a lot of the BPM teams I work with, there's a lot of good you can do with process platforms, process intelligence, process modeling. But unless you're solving a specific problem, it can be really difficult to get that sponsorship. So boiling it down to a handful of problems that people really know, they really feel, it's always a really good way to get that buy-in. In terms of getting leadership on board and getting sponsorship behind the intelligence program, have you found just boiling it down and focusing on the five or six key problems, has that really helped to bring them on board? Or is it still a bit of a journey to get that awareness at the sponsor level? I think it's still a journey that we're on.

SPEAKER_02 7:49

I think they understand the value. I think they absolutely understand the value. They funded the investment for us to go and start doing this work. I think, as with any business, they will now be the payoff, if you like, will have to go and now really, really prove its worth. Every change that we have ever made, every modification that we have put into a process has always been because it comes from our wider thinking and our core value, which is that we want to be first choice for all our stakeholders, whether they are our internal stakeholders, our customers, our suppliers, etc. So where we've actively made modifications and put customization within our systems and our processes, it's generally trying to make things better for one of those sets of stakeholders. I think what we're trying to do now is come at it from a different point of view, is understand that it's almost counterintuitive in that by putting all the customizations in, you actually cause other problems that then take away from some of that uh later on down the line. So by simplifying and standardizing our processes by removing the variation, we'll actually make our lives for our people, our customers, and our suppliers better. That change in thinking, that change in philosophy, if you like, was a key driver, and we knew we needed tools to help us do that because the sheer breadth of processes that we have within the organization means that it was necessary to have that starting block to really have a good understanding of what processes we have out there and what the true variation is. For anybody that's worked in the CI space, how it always is, is there's what people think the process is, and then when you actually start to dive into it, there's actually what the process really is. And they tend to not necessarily be the same thing a lot of the time, as is the case with us.

SPEAKER_00 9:15

I've worked with quite a few centralized organizations, once you've grown inorganically, they've bought different units, brought them into the family, but it's still got a centralized view of the way the processes work. This is how we do onboarding, this is how we do invoice management. And then as soon as you asset test that go to a region, a different business unit, it starts to fall not apart, but it's very different. There's so many different variations, so many different product lines. So, in terms of getting that visibility of all the different variation within RS group, and obviously that's supporting the S4 program, has it already started to support some of the CI programs as well and started to enable you to move forward on unlocking some of the quicker wins?

SPEAKER_02 9:52

Yeah, so alongside the alignment and the reduction of variation, at the same point, we are identifying core activities from a CI point of view. Are we going and looking at certain core processes and ironing out problems within them? So it's not just then about aligning variations, it becomes more about actually, do you know what, there's a physical problem or a bottleneck or something that we can go and we can tackle? So we have a small list of core activities that we'll use essentially as proof of concept. I mean, we're still fairly early in this journey, and we'll go and tackle some of those and hopefully get some good returns to help the bind from that side of things as well.

SPEAKER_00 10:26

Perfect. Has there been a specific process you've found yet a specific area where you've used intelligence and then you've been able to see what it looked like, whereas your previous experience from CI or previous experience from other exposure to that area had told a very different story? Is there anywhere where we've got that kind of anecdotal difference of what the data says versus what people say?

SPEAKER_02 10:47

So I think one of the core areas is a common one across a lot of businesses, is order placement. How much of that order placement is automated versus manual work? We had a way of cataloguing this, but it was a little bit manual. It wasn't even one of those where it was uh opinion versus data. It was bad data versus good data because the data logging was manual, there was data that was being logged in correctly for all good and valid reasons. But this allowed us to actually see what was really happening out there, what the process really was. The other thing was just on the variation side of things. It was a shock. And talking with other customers that have used these tools, it's always the same thing. It's when you start to see that initial outlay of the amount of variation, it's always a shock because there's always more than you think there is. But it actually going back to one of your previous points about the buy-in for senior leaders, etc., one of the things that process intelligence does very well is it takes the variations within a process and it visualizes them for them. Now, what it does from a day-to-day point of view of trying to use it proactively, it limits it down and it says, okay, I am looking at your top kind of 40-50% of your process to make it into a manageable bucket. But you do have the ability to show me on a single page every individual step that could happen through every variation and then map all of the variations through it. I've always found that a really great visualization. You can't read it because there's that much on it. And I always made the joke that for me to show this to people properly, I'd literally have to go out at night and project it onto the side of a building. But I've always found that's a really good way of getting buy-in because it's an instant visualization of the complexity of your processes when you put human beings into the mix and then you start to really see where the opportunity lies.

SPEAKER_00 12:20

Yeah, definitely. The process goes from being a single string of spaghetti to a bowl of spaghetti ball and A's. So one of the things I think a lot of process teams struggle with is being able to articulate what the role is in an ERP program. Creating visibility is great, but how does that actually support the ERP program? What practically should they be doing to help those moves from ECC to S4 or from dynamics to Oracle, whatever that may be, but what is that process intelligence role in transformation?

SPEAKER_02 12:49

So for us, there was a couple of elements. So I've already talked through the variation piece at length, and that is obviously an enormous part of it. The fact that you can start to visualize that from our point of view, we know the process that we want to move to. We want to move to a, for example, a standard ordering process. We can overlay that over our current estate and we can see where we are working in different ways today. But a level above that is the ability to really understand the manual touches. I think historically, with a lot of businesses, a lot of business reporting tends to be outcome focused. So, for example, historically, I could tell you how many orders we place for what products, for what quantities, at what prices, etc. What process intelligence is very, very good at doing is it will then go a level below that. It'll go, okay, well, let's look at that particular order. Well, on that particular order, you placed it on this day and you placed it manually, and then you did something on this day, and you then somebody else went in and had to do something. And in order to get that delivered, somebody else had to touch it over here. And what you start to see is all of the little hidden factories that happen within a process. And then you can start to really understand which one of these hidden factories are generating the most work, and then you can start to go, well, how do I take that hidden factory away? We have more than enough work that we don't need to be wasting time like that. We want to be using that time that we're wasting on little busy work in order to be providing a better service to our customers and our vendors. So that ability to be able to see that rework and manual touches that you have within process is enormous because what it starts to show you is the stuff that you just shouldn't be doing. There's just no requirement to do it. And so you can start to look at what you do differently, and there'll be some quick wins throughout that, I'm sure. Definitely.

SPEAKER_00 14:27

Yeah, I think from experience it's slowing down up front, getting the processes right, getting them clean so you can speed up at the back end. But a lot of companies I've worked with who have done the ERP programs are in a space where they want to get the ERP program done and fast. Maybe we're already a little bit behind. Maybe it was the system ECC has been discontinued in 27 and they've got 12 months left to go.

SPEAKER_02 14:48

In RS group, how did you manage that tension between wanting to move fast the ERP program, but also wanting to take the time to get the sponsorship to get the process foundation set up from so we've always been aware of various time constraints within us, but at the same point, I'm lucky in that I have a leadership team that are passionate about doing it right rather than doing it quick. I mean, for those continuous improvement professionals, you've got the cost time quality triangle basically. You can't have it quick and good quality without it being really expensive. You can't have it quick and cheap without it being poor quality kind of thing. So we're lucky that we've got a leadership team that understands that. We know we're not going to rush this, we know we've got the time to do it properly. Where we had time challenges, we've mitigated the time challenges so that we're not having to jump too early and what have you. So I'm lucky in that front, but I understand that that's not always the case with some organizations. And now, like I said, it's about putting the groundwork in to really allow us to move forward as we go on to the next stages of the transformation. But we're still quite early days in the grand scheme of things.

SPEAKER_00 15:47

Oh, perfect. On some of the previous transformation programs you've maybe supported or seen, how well was the capabilities developed from that transformation program sustained afterwards, either the process angle or any of those other capabilities that kind of help make change happen?

SPEAKER_02 16:04

So I think from my side, I mean, most of my experience comes from the CI world. And I don't know whether some of this comes with luck, some of this comes with how we've always approached CI. I've never really had a huge issue with things going backwards. I'm not saying some of the really small stuff that goes through doesn't tail away in time. But the big changes that we've done, because we've generally run through the demaic process and we've always really been very open with the groups that have gone and done CI work with us on the importance of the control piece. And we've always made a huge thing. And actually, as a result, we generally, when we've done our CI work in the past, certainly of any kind of size, we will always have had change management involved. We've had control plans in place to try to make sure that we don't fall back into old ways. I think one of the things that we always do when we do training, there's a question that we always ask at the beginning, which is we get people to put their hands up, sort of who here in the room has at some point made New Year's resolutions. And most people in the room put their hands up. And then you ask the second question is keep your hand up if you've kept all of them. And instantly just put every hand in the room goes down, and we go, and that's because there's been no control in place at all. And this is why we really stress the importance of control as we go through the Domaic cycle, because if you don't, it all falls away afterwards. So we've really always tried to emphasize that, and I think we've been fairly lucky and consistent across that in the past, and therefore we've not really had a huge amount of stuff that has fallen away over time. We are in the process of rolling out an updated transformation system. Part of that will essentially be not just the control, but almost the audit. So this is something we haven't had in the past, and luckily we've not needed it, but we don't want to rely on that in the future. So if we are putting something in that is not a one-time fix, and what I mean by a one-time fix is there are some things that you fix that they are just fixed. You cannot physically do something a different way in the future. They require slightly less elements of control, but there's an awful lot of things that require controls to keep them in place. So it's going back six, twelve months later on down the line, depending on the type of change that you've put in, to make sure that we can go back and check that we are seeing the benefits flow through that we always thought that we would. So that is something that we're looking to implement. It's something we've not necessarily done in the past. It's not been an issue for us in the past, but we don't want to be complacent going into the future.

SPEAKER_00 18:17

That control element's really interesting, actually, because it's big and CI, but I think that's a really good principle across any kind of change, whether it's massive transformational, small, incremental, whatever it is, having that accountability to make sure it's followed through. You know, that change is sustained, people carry on working in that new way, you realize the benefit. How do you identify the right people to hold accountable when you're bringing those control measures in, when you're bringing the cane out if it's not stuck? How'd you get the person whose uh net goes on the line?

SPEAKER_02 18:47

So I've got a past and present answer for that. So from a past world where we were doing the CI, because these were probably smaller activities, we make sure that no CI project was allowed to happen without having spot the proper business sponsorship. And we would have a three-way conversation at the beginning of the process, which is where somebody from my area of in CI would sit down with the project lead and that sponsor and then have that conversation about accountability and how we make sure that change sticks and make sure that we've got the right people on the hook at that point in the process. Sometimes that will change because the nature of the change might mean that you've put in some a solution that's a complete technology solution and that accountability has to sit within technology as opposed to the business or vice versa, and that's fine. But at least from day one, we have that conversation with the sponsor who should have a certain level of accountability. Now, as we go into the much bigger world of ERP translations, full operational excellence across all of our processes, we are moving to a global process ownership model. So if we are making fundamental changes to any of our processes in the future, they will have to go through a global process governance model and be signed off by the right level of the process owner, depending on the level of the process that they are changing. So that is something that we are implementing. I would say it's not there yet. Like I said, we're quite early on this bit of the journey, but that is certainly what we are working towards and using the governance elements within the process manager and process intelligence to help do that for us.

SPEAKER_00 20:09

Fantastic. I should say for us listening to that would be Signavio, process intelligence, and process manager.

SPEAKER_02 20:15

Yes. So we very much have three core pieces of the functionalities. We don't use the complete suites. I know there's a couple of bits that we don't have at the moment, but we very much use process insights as our very quick, dirty, gives us a really good overview of where we should maybe go and do some deeper diving in with process intelligence. We've got process intelligence, which is the full data mining capability that allows us to really understand the processes and really do it at a far more customizable and really get under the hood. And then we also use process manager, which is the process management software. So allowing us to map all of our processes and govern them. And there's sort of a subsection under that, which is governance, which is workflows around those to make sure that they are governed and controlled properly.

SPEAKER_00 20:58

And on that governance stream, so governance can be a bit of a challenge. Either it's not defined at the start and you're desperately scrambling to get it later, or it's defined, it might not be implemented, or it's defined and works well, or it could even be a bit too heavy. There's a lot of different routes it can go. It can be something that people know is there and work around, though, rather than properly engaging with, properly getting the teeth into the right way to make sure things are controlled, properly governed. From your experience, what makes the difference between governance that works and governance that doesn't?

SPEAKER_02 21:30

So there's two things that go hand in hand there's accountability and there's visibility. So accountability, as in you touched on it earlier on, is knowing where the box stops. Because if there's no accountability, it doesn't matter how much visibility you have, nothing's going to be done. But then visibility is huge. I think we've always been relatively good at the accountability piece. And this is where process intelligence starts to really come in is the visibility piece. That's a little bit of the hawthorn effect. It's if you make a process visible, you'll find that overnight, without changing anything on the process, it will become a theory too much. Better than it was when it was invisible. And that's just natural human behavior. So there's an element of that. And one of the things that we will be doing, and we're not there yet, and this is quite a long journey, and we are completely comfortable with the fact that it's a long journey. But as I said, we are going to be using the process manager suite to help map all of our processes. Once they are mapped and they are published, we will have a governance procedure that nothing should be moving away from those processes without going through the full governance, without going to the GPO, et cetera, for the global process owner for sign-off. But then the magic of process intelligence is you can join your process intelligence data to the processes that you have mapped, and you can start to see where those processes are failing, where you are seeing variation that you would not be expecting with process KPIs and not meeting what you would expect them to meet, et cetera. So you can start to build in that visibility of not just what the process is, but how that process is operating in almost real time. And that visibility will go a long way to making sure that there is the adherence to processes in the future. And it's always a current stick, right? We try to avoid the stick wherever possible it should be said. And like I said, the Hawthorne effect is so powerful. You make things visible, instinctively, things change. You'll get a 20% improvement just by making it visible. That's before you make changes to the process that increase the levels of improvement even further, kind of thing. So it's a long journey. It's not a simple thing to put in place. We're gonna stumble along the way, as I think everyone does on these journeys. But I think we know the direction of travel. We know there's a slog and a chunk of work to help get us there.

SPEAKER_00 23:29

And speaking of long journeys, I think everyone who's in any space affiliated with making change happen is increasingly exposed to AI at the moment. So, from your personal perspective, what is it in the kind of emerging AI space that's exciting you the most? And what is it that you think could be a real difference maker?

SPEAKER_02 23:47

AI is a bit of a pet project of mine in that I think CI on the whole, as a bit of an industry, has been very slow on the uptake of CIA. I think considering what I think CI could deliver within process improvement, I think we have been very slow to adopt. I've gone to lots of the conferences and everyone goes, oh, this is the next big thing. It's so important, it's so important. And then you go and you see what everyone's speaking about, and AI hardly gets touched on. I think that's starting to change, but I think probably not quickly enough. But from my point of view, I think there are opportunities but also pitfalls with the introduction of AI. I think there's a mistaken belief sometimes that AI removes the need for critical thinking. It doesn't, it just changes the way that that thinking operates. Uh, there's an old adage of a fool with a tool is still a fool. AI doesn't change that. If you don't ask it the right questions, if you don't work with it in the right way, if you don't understand how it does its thinking, then it can be a force for bad as much as it is a force for good. I think certainly on the process intelligence journey that we're going on and some of the other things is the ability to teach it how we have set up our process intelligence. We have used it to teach it how our configuration is all set up, which means that if I want to change that configuration or really take the next steps on that journey, I can do so much quicker and much more easily because it can do some of that critical work for me. And I can start to use it as a true assistant in getting the most out of process intelligence. I think in other areas of CI in general, we have been limited. Like I said, we've got Copilot now, but that's a relatively recent addition to the business. Before that, obviously, we are very conscious of what data we put out into the world. So we try not to use the external GPT models to do activity for us where we have to give it data because obviously we don't want to put our data beyond our firewalls. So we're still learning in this space. I know process intelligence has some AI capability. I've had mixed results with. I think certainly for most of the work that I do, I use some of the external tools. It's in its infancy. I think we don't harness it enough. I'm still looking for that big bang moment where we go, actually, that's what it's going to be amazing for on the CI world, and we go use it. But I don't think we're quite there yet.

SPEAKER_00 25:53

I think that's a lot of people I'm speaking with in this space or in a similar space where there's potential for, but it's not quite being realized yet. Dash had something interesting earlier today. I was looking at converting some old SOPs I had from internal documents. I was trying to get them into a process model, but do that using clawed code to try to rip it from this Word document, put it into an XML file, and then import it. It worked great for one. And then I realized I burnt all of my tokens until Friday. Not sure it's a scalable solution, but heyho. I did have a big bang earlier moment as well, I should say. I don't know if you've seen this yet. There's uh a new AI uh website over. Uh it's called Guinness Index. Not yet. So, what it's done is someone set up 11 labs, run a survey of every single pub in Ireland, how much is a pint of Guinness, and they've got this fantastic view of where you're gonna get ripped off and where you can get an absolute bargain of a pint.

SPEAKER_02 26:42

I think the use cases are out there, and I think we'll start to identify them at a pace as we go forward. I mean, I've played in a personal capacity with the board a lot. I'm trying to replicate that, like I said, with Copilot and like the project work where you can use the generic information, but I can also focus it down on a finite data set to really hammer home the issue and train it as to how I want responses. So I do a lot of that, and like I said, it's been hugely helpful. But yes, outside of work, I have travel planners set up with all the places that I have been, all the places that I want to go, the kind of holidays that I like to go on, so that it can help me identify and plan my next trip.

SPEAKER_00 27:17

So, final question for someone who's maybe earlier in their career and they want to get into the CI, the BPM, the process intelligence space. What's the advice that we want to give to them?

SPEAKER_02 27:29

There's a few different elements here. I mean, the first is be curious. I think that's the thing that has stood me in the best stead. I mean, especially as I've moved into the process intelligence world, is I want to know how stuff works. I want to get a feel and an understanding rather than just blindly use a tool. And I find that gives me the knowledge and the base to make better decisions with. Don't be afraid to make mistakes as you go forward. And then really talk to your SMEs, your subject matter experts within your processes. As a CI person or whether you're working into the process intelligence world, you cannot know and really understand the nuts and bolts of every process. You need to be working with the subject matter experts in the business, taking their advice, their understanding. Process intelligence makes certain assumptions, same with process insights, that might not necessarily be true. So, for example, it might tell you that something is being done manually when it's not. Um, maybe you've instigated a customized way of loading data in and it sees the person that pushes a button as somebody has created a manually a hundred items. It takes 10 minutes to create an order, you've just created a hundred orders, therefore it's a hundred times ten minutes. Where in reality it didn't. It took you 10 seconds to press a button. So always be prepared to challenge the numbers. If something looks too good to be true, it just might be. So always be ready and willing to kick the tires. Embrace AI, but challenge it at the same time. Really make sure that you don't take everything you see at face value. When you get a report, when you get a piece of data that tells you something is fundamentally wrong, understand the problem and make sure it's genuine because sometimes you will get false positives, and that's part of the course. Always be curious, always go looking, and always be open to change because our industry is always going to be one change after another.

SPEAKER_00 29:04

Fantastic. Oh, Paul, really interesting here about CI and PI and how it all plays together. Thank you so much for your time. That was a fantastic conversation. It's been a pleasure. Thank you very much. Happy to be here.