Process Mining vs. Business Intelligence

MYB, my new business podcast is back with another episode. I'm joined, as always, by my colleague and friend, Jakob. How are you? Hi, I'm doing fine. Today we are talking about a very interesting topic that has been discussed plenty of times on the internet. What is the difference between a process mining tool and a BI tool? And which one should I be using? And can I get away with using Excel? All of that, and more coming right up, let's do it. Today's episode is going to be about you, people of LinkedIn. Why? Well, because a few months back, I actually posted something interesting, well, I thought it was interesting on LinkedIn, where I was literally thinking and comparing BI tools compared to process mining tools. The LinkedIn post went sort of viral, at least in process mining community and I got tons of feedback there. Patrick Slathing, he doesn't think it was viral, but a few of you actually replied there and I thought it would be super interesting to make an episode out of it. And before I even get into it, I'll probably read the post so that I can actually frame the discussion a little bit and you might know where we are going with it. So here we go. What is the difference between BI and process mining tool? Forget the technical differences such as the data ingestion or visualization capabilities. In my opinion, it's the mindset. With BI tool, you react, report, operate and consume while with process mining tool, you analyze, recognize, initiate, and act. With BI tool, you are a passenger, passively watching your processes do their thing. And with process mining tool, you are the drivers that have power in their hands to steer the entire organization. And I think it's pretty empowering. Patrick, what do you think? Good. I'm questioning where you got the awards react, report, operate, consume, and analyze, recognize, initiate, and act from. Desaurous? Yeah. I mean, I somewhat agree. I think the capabilities of both kind of disciplines, I should call it, are different. You can't deny that. And I think it requires some sort of different way of thinking and come also what you want to achieve with them. I think that's one of the bigger questions, but let's get into it, shall we? Yeah. 100%. When I actually was starting with process mining or actually working in process and what is now almost five years back, I encountered an interesting situation. I think I was, the data scientist who took it the longest before he actually implemented an actual end-to-end process because I was called it lucky or called it unlucky, your choice. I was lucky enough to always work on rather BI focused topics or projects where we were literally implementing a very small piece of the process, a focus report, and basically all the logic behind the report was coming from what you could call a typical BI. So it took me almost two years before I went to implement purchase to pay your accounts payable process. And that's why my framing or my attitude towards BI and process mining is somehow, I would say, impacted by that because I was always thinking, why don't we just look at the whole process, why are we looking at this small piece where we just present certain KPIs when we could literally have the end-to-end process and, you know, analyze it from a perspective of end-to-end. And that got me thinking already back then and well, now I'm just very happy that I have the opportunity to work with actual processes in process mining tools. And very often I'm thinking, why even building focus reports when you can basically filter down to anything you want when you have this, and I would call it almost send box in a process mining tool. Yeah, I think that's also very strange that you'd never, or you took you that long to actually implement a process end-to-end. I would say for me, the history of BI has been more, I wouldn't say Tarners, but definitely marred by just using Excel and in ways that it should never be used ever to build some sort of wacky reports that got sent to management every week. That was an absolute pain, so in talks with BI tool versus process mining tool, Excel just doesn't cut it for the most part, so that completely leaves the discussion. And that's been most of my BI quote-unquote experience, and that was significantly atrocious. So when I made the jump over to process mining, actually, the experience got a lot better because all the pain points and all the suffering I had to do with Excel realized, oh, there is a better way. You know, all the questions that I had, yes, there is a better way, and it's so easy and all the things that I want to do and all the things I want to see in my process are just there. Speaking of Excel, first of all, I think it's the biggest competitor to any BI tool because people love Excel and it's crazy how many organizations are still running on reporting in Excel. You know these memes where you have this little stick basically holding the whole pyramid of the organization and if the stick breaks, which is represented by Excel, your organization just shatters the pieces. And speaking of my previous experience, when I was actually working on these BI reports, which was crazy because I was asked to build an actual BI report in a process mining tool which, you know, you can do there a lot of things, it's not designed to do that, but you can achieve it. The worst thing is that it's probably not priced to be a BI tool in the first place. And then I was literally crying because, you know, seeing the users then working in a process mining tool, consuming the BI report and then exporting the data to Excel to work on the data in Excel was just like a complete reduction of the knowledge to a back to something, you know, a bare boner and that's like building a really, really nice car and then the person you give it to just gets out and starts pushing it. Yeah, that was exactly that. So I had my fair share of the BI implementations not to mention I also had a project where I was actually building reports in a SAP Analytics Cloud, so I was also interesting. And even back then, when I was a working student, I did some BI reporting in Siemens, although you would argue that it wasn't a complete BI because we were more focused on some very specific data regarding buildings and so on. But it was very much very similar because you were building a report with specific APIs and, you know, access that you were looking in time and try to somehow get the right data and so on. But I would say, let's kind of get into the discussion because there were a lot of interesting points that some of the readers made and before we do so, I would probably try to even tell you what process mining and business intelligence is. However, if you are really interested in what process mining is, then first of all, you probably already know that because you're listening to mining your business podcast. And second of all, we've had an episode on this topic. And therefore, you know, process mining, a family of techniques, right, I think the fields of data science and process management, that's a definition from Wikipedia. And business intelligent is intelligent, sorry, comprises the strategies and technologies used by enterprises for the data analysis and management of business information. It's basically in the nutshell what these two terms are. So let's talk about the differences from the way that we view things, right? Yeah. And I think it's important to highlight that this is still our view and we didn't at least I didn't study this. So maybe if there are academics listening to this, I think, okay, man, maybe the syntax or rave the description should be more precise, but just go with it. Yeah, exactly. And if you do have some qualms about the things that we say, come on, let's show them correct. That's where we're all here for it. So differences, how do I see the differences? Well, I think in BI tools, be it whatever BI tool you would like, even going so far as to use Excel, right? I think one part is the general use for it, right? Those many tools are process-related things, right? That's the strength of them analyzing processes from end to end, doing all the KPIs in a process context and all that stuff. BI on the other hand, isn't focused on such a context in normal cases, right? So you could be looking at a dashboard for website traffic. You could be looking at a website for, I don't know, like your imagination. You're really your only limitation for the most part. I mean, it needs to be technically feasible, of course, but for the most part, you can display a lot of things that don't really have a process that are just a KPI. You can argue one way or another that all KPI's are somehow process-related, right? But for a lot of things, instant reporting, most BI tools will be just fine and don't need a process context, right? So the, on the other hand, process mining is, like I said, the process context, value adding to your KPI's, you can really deep dive into what's going on, why certain KPI's look the way and is it a process problem? Do my KPI's look the way that they do because it's a process problem, right? So it's putting that into the context of process in a business process that makes it the process money tool. And I think here is at least my note on this whole BI versus BN topic, you could analyze every single piece of a process in a BI tool. You just, you could just do that. If you're looking at purchasing process, you could look at the purchase requisitions, you could look at how they are being processed, whether they're released in time and so on. You could build a report around that in BI. If you go down the process in issuing of the orders or sending them to the vendors, every single piece can be represented the day in structured data, which means that you can bring it up to a BI tool and think about what do you want to see, whether you want to see some segmentations, whether you want to see some high level KPIs or actually represent some bottlenecks. The thing is that you always are building the report with the goal in mind. You are always addressing the thing that you want to tackle. While in process mining, I think that the huge benefit of it is that you are working somewhat with the similar, exactly the same data, but in a way that it enables you to explore it and look for similarities or look for some correlations when you do this, what happens at this part of the process. That's even why I'm always saying, let's think about the use cases that we want to use process mining for, but let's also spend some time actually analyzing and looking into what we call a process cockpit, where you are exactly playing with these filters, with the consequences, with how the process is executed with the different steps. You are exploring what it means in the context of the whole process, because it's one thing to look at the KPIs that you might have a late payment ratio that's too high and unacceptable for your company, but it's a whole another thing to have this KPI in the context of the process and be able to play with the actual process steps and see what impact and what relationships do different sequences have on this overall KPI? You made a very good point, and I think this goes back to one of the discussions we had earlier about the x-ray capability of process mining, and so if you don't know what your process looks like, then process mining is great, because you can explore, you can dig around, see what all the little things that happen in your process and look for inefficiencies. BI does not give you that capability to do so, right? As you said, you can write a KPI for every single part of your process, but the prerequisite is knowing that you know everything about your process, which a lot of businesses don't. Another point I would like to bring up, the difference, I think a lot for a lot of businesses is cost. If you've seen the cost of BI tools versus process mining tools, that's why I mean, that's why Excel is so prevalent in a lot of reporting, just because everyone has it. It's right there, you just open it and make it reporting, you're done. Yeah, I would like to see the yearly fees for using Microsoft for a corporation of 10,000 people. I mean, I'm sure they have special deals and everything. But no, it is a point to consider, specifically if you're a smaller business that doesn't have that many processes well defined or doesn't have even the data or all this stuff, right? Then you just, or maybe you do, but you just don't want to dosh out so much coin for a specialized tool. So we'll probably do fine until you grow to a size where it no longer does. Yeah. And it even brings me back to my initial post where I was saying that with the BI tool, you sort of react and report and consume. And I really think that that's, it's still in my eyes, even after reading all your inputs and all your ideas, it's at the core of this that when you have a report, you are not really prompted to make an action except of, you know, keeping this KPI in green or in red. It does steer you sort of in a way, but it doesn't tell you what to look at to maybe improve something. It might even trigger unwanted detection because you are chasing some numbers without having the context. I mean, yeah, I mean, but again, I think it kind of matters, it depends on what you're looking at. When I was working in, I want to say who, but at a, we were doing transaction credit card transactions and there was a big dashboard on the wall in the network team that basically described how many transactions and what's the failure, right, of those transactions. If it ever got to a certain ratio, it would flash red and everybody will be on full alert. Right? So there is a reaction that you can draw from, from BI, right, and it, it's not really process related. It's just transaction good, transaction bad, right? And then if it's above something, oh, you have a big problem, somewhere in your network, something's not going right and customers are waiting at the tills not being able to swipe their card. A massive problem, right? So as soon as it hits that threshold, then it's go time for somebody. Yeah. Generally, what I find interesting is how you are utilizing process mining to actually build your BI reports. And I think this is what a lot of basically all the process mining vendors understand. And they are going in this direction that, um, which, well, for a passionate analyst of processes is a little shame because I would still argue that spending a lot of time in process exploration is amazing and should be really invested in. But then you have this clarity of this idea, you, you know, put some value on the use case and you want to actually realize the value. And then the moment when you move more into this BI realm, which is the situation where you exactly take this small piece of a process and build what we call a focus report where you define the measuring KPIs, you define the split that you want to see the filters and also some kind of a tracking and potentially monitoring actions that you want to do. And, uh, you know, some vendors are going in, even into the way that they are then either want to automate or help some parts of the processes or, you know, look at how the process is designed and analyze it and benchmark it against the design process. So there is a clear, um, I would say it's very blurry line to even say where process mining ends and process and business intelligence starts and vice versa, which I think is, um, natural. And, uh, when we get to the comments of you, uh, the community around process mining, you will probably even see that some people see it slightly differently, um, but that's what makes it interesting, isn't it? Yeah, for sure. So I think that concept of we have a process mining tool and we have a BI tool, um, I think at some point BI tools will just put things into process context, regardless, right? So, um, so it won't really be a specific process mind tool. I think you'll just be more integrated sucked into the general field of BI and most tools will adopt some sort of process view explorer or whatever you call it, right? I think that's mostly inevitable, um, just from, yeah, I mean, just the hype that process mining is generated would be silly if there wasn't some sort of push for a lot of these vendors to also integrate this sort of report, right? And it's a natural development. I just had this idea when you were talking about it that imagined that 15 or maybe 20 years back, um, you had apps that were designed only to serve you as a texting, uh, application, uh, messaging application. And now you basically have a texting, uh, windows, incorporated and every tool I could text you on the platform where we are recording the podcast and the Zencaster. I could text you in our select channel. I could text you anywhere. Yeah. It wasn't the case 20 years back and what might be happening is that just what you were saying is that these tools, uh, will integrate with one another and then having an overview of your process will be as a natural, um, as, uh, looking at, uh, you know, um, a barcharts in your BI tool. Yeah. I, I think that would be the, the natural progression for this to go. Um, so I think, um, one of the things you wrote down is PM, just, as, uh, process mining just to hype. Um, you could argue one way or the other. I think the, um, the push for it certainly has been great. And I mean, the interest in it, especially here in, in Europe has been phenomenal, right? And so the, yeah, the, I know your favorite phrase, make business process management great again. Uh, that, you know, kind of revived that whole thing, uh, no, of course, not only 10,000 times or so. Um, so there is some hype, of course, but I think it's, it's relevant. I think it's justified, right? Um, because all of a sudden this process X ray that you all of a sudden have is giving, um, you know, businesses that view that they've never had before, right? And I'm something that B.I. couldn't give them before, right? Otherwise, it wouldn't exist if it weren't useful. Yeah. And looking into what other community members say, uh, there are some very interesting opinions, uh, also some that sort of disagree with us, which again, I love, um, first of, first, first, uh, reply I got was from didrick, uh, jibben, who actually was also on our podcast a few episodes back, so make sure to listen to that one, um, who actually says that process mining enables the conversation with the process, uh, it allows to jump back to the root cause and leading indicators and also jump forward to the area of impact, which I would say very much aligns with what I was saying, where you have this platform, which you can interact with and, um, you know, subtract insights from, yeah, I mean, that's, uh, absolutely true. I mean, allowing the, or just giving the ability to go backwards and potentially forwards in a process in this object that you're tracking, like, what is it going to do next? Will this object in my business go the way that I think or, um, can I look back at what cost it to be stuck in this place in the first place, right? So, um, having that forwards and backwards view is, is, um, something that process mining enables, yeah. That's a really good point. We will, for sure, see also a lot of developments in this regard, especially in automation and prediction models. Again, you can refer to a few episodes of ours, uh, either with, uh, Marlon Duma or Marcel Larissa, who we're talking about these topics, who even said that, uh, process mining is like 20% of capacity where it's going to go and, yeah, that's at the, ultimately, that's one of the reasons why I believe that, uh, while the mergers will occur and process mining might get integrated into BI tools, uh, who are, uh, objectively usually larger and have been on the market for longer, have bigger market share and everything. Um, there's still a lot to cover, uh, and, uh, therefore, I don't think it's going to go anywhere. Um, and it's here to stay and it's actually, um, an area worth of exploring and, um, worth of, um, keeping an eye is open for, and, uh, Deidre, even, uh, one more, uh, interesting things what he wrote and, uh, beautiful analogy related to sports. He literally says that the BI shows you the statistics of the match, ball context, successful passes, goals, et cetera, while process mining connects performance to the training effort and exercises. And, um, I think that also sounds very lovely. Yeah. Yeah, for sure. Um, I think that's, uh, that's a nice context. Yeah. And, uh, moving on to Christian J. Peterson, who wrote, BI, BI is like a scale. You are on it one to two times every week and get your weight, BMI, et cetera. The scale helps you report and track over time. Process mining is like a Fitbit. You are checking the app for sleep patterns, steps, HR, activity, et cetera. Fitbit allows you to be proactive during the day and make adjustments. You will tell you when to go to sleep or go walk based on patterns and insights. Yeah. Thank you, Christian, for this post. Um, again, I think it relates very much to, to Dietrich already said and, uh, to my view of the problematics where you literally have these continuous insights and you can react to each of it in almost a close to real time. Um, obviously there are some cavities to that, uh, you know, having everything in real time and so on. But the point is it's, uh, pretty much doable and, um, this Fitbit analogy serves the purpose pretty well. Yeah. I would say so I mean, you can measure a whole lot of things, um, in BI as well. So I mean, it's just a smaller version, um, but you know, the, the, the steps and the, you being the object in this case and the things you did beforehand and the things you could possibly do in future is that, is that process mining benefit? Mm-hmm. Um, I, I heard a very, uh, interesting thought actually and it's, uh, that the process mining so far is deployed mostly in processes that are super important, um, for the organization, but not vital because if you think about it, like if you have, um, organization that's, uh, you know, every organization is, the point is to make money and the processes, the big four processes that you usually implement are not truly the money making processes. You have money hidden in there, but you, your process is not to process invoices, right? Or your, your business model is not to process invoices. It's like a byproduct of doing the business, um, not saying that it's not important, but there are also processes which are much more important for your customer satisfaction or even customer interaction, such as, um, if you are in a bank, that's the, uh, that the moment where you're actually facing the client when they come and you know, they are deciding, uh, what product to take. And, um, again, going back to earlier episodes, you there, there are already initiatives on capturing those processes as well, those more rooted into what, uh, is the core business of the organization and, um, you could probably see a lot of potential there as well. Yeah. Um, I kind of get it. I mean, so if you're looking at production, the thing that makes you money is what you produce and then sell, but then exactly there goes, again, one of the popular ones ordered to cash, right? So there you go. How do you get the thing that you make into the customer hands and get paid for it, right? Or, um, for example, you are hiring or you're looking at a recruitment process or anything like that, right? Um, you need people to do the work that makes you money. And, you know, so it all kind of interconnects at some point to your money maker, right? Indirectly or very directly in terms of production planning, they all relate back to the, the money maker, right? With your bread and butter. I would say production planning for sure would be this, this very much core process. Um, the order to cash, interesting, interesting to think about it because at the end of the day, you are expected to be paid, obviously, it's there to get paid, yeah, it would be good to get paid. So if you're like, think, okay, I saw something I get the money, uh, who cares about the rest of the process. Um, but yeah, obviously it makes a total difference because you still want your organization to be efficient. Yeah. Uh, for sure. I mean, the, the core processes, if you can optimize those, again, they'll make your other processes faster, right? If something goes wrong in production, you have to promise the customer a new delivery date and all these things that might, you know, hurt the client reputation with you and can therefore lead to less cash, but that isn't an ordered cash problem. That is a production problem because we have a production, right? Right. I get it. All right. Um, the next one we have here is Janice Snacke, who we also actually had on the podcast from NRV. Who says that, um, process mining is a natural development or evolution of, of a B.I. Um, which I do agree with. Um, I think you could look at it from this technical point of view and seeing, uh, process mining to even be a sub category of, of, uh, of B.I. Um, yeah, that makes, uh, quite, quite logic for me. And, um, he also says that when doing process mining, you are the navigator giving hints and advice, uh, to your organization. And he also emphasis the importance of execution. And, um, I, I think that we talked about it pretty, pretty, uh, often, uh, with our previous guests, uh, that, you know, process mining and insights are awesome, but without the action, you know, it's just insights that you, uh, what you could do or should have done. So one. So the, the execution part is definitely important, um, interestingly, or I will be very excited to see how it evolves in the future because so far, uh, while there are initiatives and there are, uh, organizations that are pushing towards these automation, uh, topics, um, I wonder how is it going to evolve because still I would say most of the, um, work that's being done is still looking retrospective and only slowly these organizations are getting into this continuous improvement cycle when they're, uh, you know, improving their processes and actually even creating these, these improvement, um, cycles automated that they would improve sort of themselves. And there are a lot of research on these topics on how you could insert AI to make more educated predictions and, uh, you know, prescriptions based on the past behavior. Yeah. That's, uh, that's a good point. I think I'm going to be a bit criteria, uh, contrarian, um, in terms of Janice's point about it's the evolution of BI. I think it's more of an evolution of business process modeling, right? Because, you know, you can model a process, right? You think, okay, now we're going to do this and then it flows into this path and then it does this and then it's at this person's desk and then it flows back. And then the obvious next conclusion or the question that you need to ask, okay, well, how well are we doing that? You know, does, does what we just modeled actually happen in reality, right? And that's exactly what process mining actually answers, right? Um, have you, Patrick, ever worked in Google Analytics, uh, like analyzing the web traffic and so, uh, no, uh, because there is a very, uh, I love this graph. It's, um, a path of a visitor of your website and how they flow through the, it's like a flow chart and it shows, uh, what page did the user enter to your web? And then you see, like in percentage, it's, uh, it's, you know, it's captured in the width of the arrow, uh, to what page does it go next eventually when it leaves? And you see, like, the more steps do the longer it stays on the website and you see these outflows going out of your website, right? And thinking about it, it could also, you could almost say that this was the, uh, the, the predecessor of process mining because you are literally looking at the process of a traffic on your website. I mean, the predecessor to process mining was just, you know, the modeling of process steps like, uh, petri nuts, right? So I mean, that was really just, hey, here's the state. Where does it go from here? And if I activate the state, where does it go next, right? So that's the, that's the precursor, which is, you know, you know, graphing and all, grap theory and all this stuff, yeah, which is, you know, um, just nodes, nodes and edges at the end of the day. Yeah. And by the way, you mentioned, uh, contrarian view, uh, speaking of contrarians, we also got to reply from Roland Volt, um, another, another guest on our podcast, uh, who's, um, also running his own podcast, um, what's your baseline? And, um, you could have heard to run in our episode that the process mining is a hipster child of a business process management, which would probably align with what you just said, Patrick, about, uh, that, um, process mining is the ancestor, uh, sorry, the other way around pre-disney process management is the ancestor of process mining, uh, and he even predicts that process mining as a own category will go away in three to five years. Do you agree? Or what would you say about this, uh, this old prediction? Um, I do agree, um, just for the sole reason that I think, um, this has legs. And I think it's putting it into a lot of context. And I believe, um, Marlon Dumas, when he says, yeah, we're only scratching like 20% of what we really could do. And I don't think, um, this will really go away by itself or we'll just naturally evolve without there being like a focused, um, attention and just, okay, it's just another BI thing, whatever, but no, there's, uh, this can be described as its own discipline that requires its, uh, centers of excellence and all these things that really focus on this specific part of, okay, if it is in a BI tool or not, but there will be one specific part that will, that will have so much depth, um, to it that you can, you know, it's not just a KPI. You can invest a lot of time and effort in order to optimize your processes. Yeah, not to mention that we wouldn't like to lose our jobs, right? Um, um, that's not what I was thinking at all, um, but ultimately, um, it could happen that it's, uh, we, that the process planning in three to five years is not the process mining we know today. Um, what could happen is that it's, uh, it branches out so much that it just, uh, starts to, again, have this blurry distinction between where we are doing business process management and where we are doing actually process mining and when we are actually building BI. So what could happen is that, uh, actually this whole business process management evolves so much that when you are saying you're doing process mining, you are very much also, uh, the architect of the business processes and you are so much into this topic that you work with a very specific data, um, it's not like analyzing or doing statistics on some, uh, geographical, uh, data or some, um, sociological data, right? It's a bit different. It's looking into process, which I think, um, distinguish this business discipline, uh, this business process discipline so much from any other, um, mathematical or statistics areas where you are looking and trying to calculate some, some, some, um, different, uh, data. Uh, so I could see that these mergers, uh, that he also mentions, uh, are continuing happening. We've seen a lot of smaller, uh, or mid-size process mining companies being purchased by, uh, bigger players on the market and, um, who knows, maybe it's not the end of it, um, but I can also, I would still argue and I, I think I'm on the same page with you Patrick here on this one that, um, I don't see it going away completely exactly for those reasons that there is still so much more potential to be uncovered. And, um, this potential also means a lot of upsides for the, for the focused vendors, uh, because there's still a lot of money in this. And, um, not to down, not to downgrade any big, big companies, but once you are part of the huge corporation and process mining is not your, uh, focus area or your domain anymore, um, these companies tend to be slower when it comes to coming up with new technologies. Yeah. Uh, I think I would agree. I think the, um, yeah, how do I best put this, the, I think it's all a lot of definition, right? How do you define process mining? Well, with, if you ask one person, they say it covers this realm of my, um, of my business intelligence or, like, quote unquote data analytics, um, and other personal disagreements as it encapsulates also the simulation part and the digital twin and all this other stuff, whereas, um, you know, five years ago, process mining meant something completely different, right? So I think a lot of it is just a thing about definition. If you can't agree on what process mining is, then you will disagree about, um, what it's best use for and how it fits into your organization or, you know, if you just talk with other people about process mining, which I'm sure you dear listeners do all the time. Um, you know, you need to have some sort of common definition of what that means, right? Yeah. Coming back to this instant messaging, uh, it's not longer only instant messaging. You can send pictures, you can send music. You can create, uh, huddles and have a calls with one another. You can share gifts and have a lot of loves there. So there's so much more into this and it's just starts layering up and you can just do a lot. And the same will happen and is already happening with process mining. Are you telling me you're going to send me event logs on Slack? Uh, I hope not. Actually, I might have, I might have done that before. Oh, my board for your, for your, uh, yeah, for your, whatever. For you to inspect. Uh, moving on, we also have your comment from, uh, Dr. Aziz Yaramade, uh, who says that from his perspective, it's more the context and the business value that defines which of these tools are more relevant. Additionally, the action plan built on top all in all data analytics is a vast scope and different terms describing it overlapped with each other at the end, only a great vision and structure way of working can choose the right analytics tool. Oh, that's, it's good. That's good. I'm very much agree. I mean, you can try and squeeze your process mining tool or your BI tool into whatever situation, but at the end of the day, it needs to make sense what you really want to achieve and is it the right tool for that goal, right? And without the proper structure, way of achieving the things you want to do about the insights that you gain, it doesn't matter what you use, right? If you don't have all that set up and you don't do it well, regardless of what you use, you're not going to get very far. I'm sure if you are capable and you have a talented organization and a team, you can drive, you know, you could drive improvement even from Excel. Yeah, like I said, for a lot of these things, Excel do just fine. It's a pain, right? But it's right there. Anyone can use it really if they spend a little bit of time and they can probably figure something out, right? So it's a very good point. And I actually, if I go back to my initial post when I was saying that, like, forget about the data ingestion or visualization capabilities where you could argue that they are at the end of the day overlapping a lot, I just say it's again about the mindset. And while you can have the mindset of improvement with any BI tool with Excel and so on, I would say that process mining sorts of pushes you in the direction of asking the appropriate questions, which BI tool might not initiate as easily. And therefore, again, it's about how you utilize it. Yeah, I think that's a good point. I mean, it goes back to what I was saying beforehand that BI then requires you to know the question to ask, but process mining just gives you such a great tool to explore your process that you can start asking questions that you didn't even know you should ask of your process, right? That whole talking to that Dietrich was talking about before that whole conversation within your process, you can discover all the things and start asking more specific why questions that you would not really get to see with that normal BI tool. Yeah. Well, and finally, we actually have here also a comment from Wolfgang Kratch who is going to be a guest in the near future. So I'm staying close, spoiler alert, spoiler alert. He is also a researcher. So you will not be surprised that his answer is rather technical. And who argues that typically BI is based on aggregated data over different dimensions. It's just day, week, month, etc. This mining, however, goes back to unaggregated event data. Therefore, with process mining, you might be able to find the needle in the haystack. Yeah. I mean, that's true. Now it's just a question of how much value does finding that one needle give you, right? At the end of the day, you need to find out how often does this needle in my haystack happen in general? And what impact does it have in general, right? If it happens, what impact does it have, how often does it happen? How many cases does it happen and boom, you're aggregating again, right? Yeah. Patrick, to sort of rep up the episode, we've had a lot of interesting insights going different ways, different approaches and different tackle different ways of tackling the question about what is the difference between BI and process mining. If you would sum it up and we love these elevator pitches, don't we? Oh, go on. I don't want to challenge you. Okay. No elevator pitch. Forget the elevator pitch. What do you make out of it? I think it's a lot of people, like when we're at the office and some people say that it's way too cold, some people say it's way too warm. No one really agrees on what the right temperature should be. I think this is somewhat related that, you know, process mining means a lot of different things for everybody and their view on what it should be and what it can be also varies. And therefore, the decision on when to use it can also vary, right? So there's no clear definition of, you have this use case, this tool is perfect, right? You cannot really make that, of course, there's externalities that you cannot control, like cost, time to implement and all this things, right? But just based on solely if you had all the time and money in the world, right? You could argue any which way what you should be using, right? So I think it's a lot of definition. I think a lot of it, I mean, process mining is not that that young of a discipline anymore, but I think with the push to enable simulation digital twin and all these things, I think it's making its foothold in the BI space. And now it's just a question of how much space will it really occupy in the data analytics as a whole? Yeah, you just said that process mining is not as young anymore and I just realized I'm there for five years already. It's crazy. Oh, man, however, I would still be interesting and curious to hear from all of you, dear listeners, in how do you see the difference between BI and process mining and whether whatever we have just said made even sense to you. So don't hesitate and reach out to us. We are very active on LinkedIn or you can comment under our post. But you can also reach out via email at [email protected]. As usual, we are very excited and curious to hear back from you what you think and if you have any ideas for any of the future episodes and your recommendations and so on. Well, as usual, we are happy to have you with us on this journey. Our podcast is growing and it's really, really fun to see that. Very happy about that. I see Patrick smiling. So he's very happy about it as well. I saw the analytics, I'm happy about it. And we will be looking forward to talking to you in two weeks time with the next episode of Mining Your Business Podcast. So thank you very much for being with us, for listening to our show. We are hope you're having fun. Bye-bye. [BLANK_AUDIO]