Courtesy of Software AG's J-M Erlendson, below is a transcript of his speaking session on 'Bimodal process mining for operational agility' to Build a Thriving Enterprise that took place at BTOES Process Mining Live Virtual Conference.
Bimodal process mining for operational agility
Gas is a real treat for all of us, directly from Toronto, Canada. one of my favorite cities in the world, We have J M Arlen Sun, joining us. J M is a Transformation Engineer lead as software AG, working with top companies around the world to build and scale, process driven business solutions. He brings a diverse background and unique perspective to each engagement, drawing upon years of experience in, management consultant, business, and enterprise architecture, project, management, and as a successful entrepreneur.
J M also has a passion for public speaking, and performance, seems frequently at industry conferences and on tour, as an international recording, artists. So you don't know where you're going to get here, may actually get a bit of a show going on. So, J M, real pleasure to have you, have you. Thanks for Taking the time to share your expert expertise and insights with all of us.
So, thank you so much for having me. And thank you so much, everyone, for, for, joining us today. I, today, I'm gonna be sharing a little bit of my thoughts on what's going to, what's been happening in process mining, and particularly helping to explain one of the terms that I really hold dear. When we talk about process mining, which is the ... process, mining, I'll explain that to you today. Go through some of the scenarios. one, might use it for, and ultimately help you understand how it can get value for you and your organization.
So, we see, um, a lot of challenges are running the business right now, running businesses. Particularly data driven businesses, and people being forced to challenge, and challenge to change, based on already industry requirements are being competitive, and being able to keep up with technology as it evolves, but that change can happen without leveraging insights from your running business. And so, as you're trying to change, also trying to figure out what you're doing right now, and that means you're kind of changing the tires as you're driving the car. You're evolving your business as you're running your business, as you're evolving your business.
And that requires an ability to understand how you're doing, where you're struggling, and what you can do to make it better.
And that happens in a couple of different ways. Process mining as a, as a core component is the overarching sort of umbrella that covers this. But, different details will help you get into exactly where value can be found, and understand and split how you're going to get that value based off of what you have available, and the kind of outcomes you're looking to achieve.
Because we understand that, a real process transformation does require a life cycle, A movement of information and effort between different phases you're going to use now, the conventional design implement execute idea of sort of process modeling, has been successful for organizations looking to transform, but it's been based off of a combination of soft skills based decision making. So, not really data driven or strategic initiative based decision making, which is good, but it's focused more on executive alignment, rather than on actual data outcomes.
And now, we're moving to a culture, and trying to shift it to this measure first.
But you see the idea that when you measure first, with things like process mining analytics, you also want to have a life cycle of checking back, and being able to understand what those measurements mean. So checking, conformance, simulating process, change it so you can understand how you might actually achieve those business goals. And then understanding and analyzing the impact of those changes, And that whole life cycle happens in two different ways, which we're going to talk about today in bimodal IT.
Now, for those of you have been following along, we know that executed processes, they leave trails. Those trails are things we can follow that help us better understand what's happening, those traces that we can see, Oh, is it happening in a different ways or a variation? that's occurring. Is this something that we can learn from as an organizational piece of capital or is this a non compliance that we need to find ways to engineer out or train out?
The difference is we want to take that and use that to populate and understand what your process actually is, as models. So, one of the things we think about a lot in process mining is, not just that we want to take a look at the data, but we want to build a knowledge repository out of that data. So, let's start at the idea of Digital twins.
Before we get into truly the ..., my bimodal IT, a process model, we're trying to build a representation of a business reality.
And that knowledge repository has to represent the real-world that's ongoing.
But to see that real-world in conventional ways we've done these sort of time and motion studies and things like that, or business discoveries.
Instead we want to represent and understand how system software sees it. And what sort of system software supports are actually executing proxies in the real world.
And we'll grab event logs from those systems and softwares and be able to get discovery of the processes. understand how proxies match up with our expectations and how we can make things better to really get a true digital twin of reality. Because ultimately, where we want to end up populating this best practice knowledge repository. That's the sort of source of truth, for how you're going to move forward. Process mining is really one step in your journey.
The end up, for which, of course, is improvement.
And to do that, we want to understand how you designed it, how you implemented it, and how it's actually running, and where those don't matchup. You can only really improve what you can measure, and so let's start with getting our digital twin.
And that digital twin comes with a couple of different things. We need to make sure we have first, and foremost is process mining, integrated through this entire idea.
First and foremost, we start off with gathering data and turning it into modeling, and then modeling, turning into dashboarding and dashboarding turning into actions and actions turning into implementation.
And with all those put together, we're able to get a much better picture of what we have, where we are struggling, what we should do in the future.
Now, the question is, how do we get information in, what kinds of things do we need to be successful with process finding? And that's where grouping it into a giant bucket of this is process mining Is simply not sufficient to help you really achieve your goals, because they're they're not just one at a time, or actually a couple of different things.
So what is the bimodal of process mining? Well, that means there are two different things we're going to compare and contrast. And those two modes serve different purposes. They have, they come about as a result of having different sets of information. And, ultimately, they're able to go through this life cycle in different ways.
Mode, one is what I consider Agile, process mining is something that you can think of as taking simple sets of data, or simple, single source sets of data.
And turning that into quick wins, quick insights. Quick sets of data. For instance, taking a CSV file and turning it into a visualization of a process. Now, mode, one process mining is generally something you'll find early on in the evolution of an organization's journey into process mining, where you'll get transaction logs, sort of ETL style, where you'll be able to simply extract them from your major transactional system, sort of one at a time.
And your scope of project and process improvement is going to be restrained sort of to the ability to improve what you're seeing right now in this one place. We see this a lot in single improvement projects, or continuous improvement initiatives, where different teams take the initiative to go after one problem at a time. Scope also tends to be restricted to sub processes, or single single thread processes. It doesn't tend to look at an enterprise and ends because the reason for a particular reason, is a lot of organizations do move through multiple systems. Multiple sources, enterprise, end to end, tend to have longer turnaround times that you're gonna want to analyze.
Hydro process mining is very good, for, particularly for fast, running frequent processes as well. Those things tend to give you really good sets of data that you can respond to quickly, So think about mode, one, Agile.
Mode, two is strategic.
We're looking at disparate, said that sets of data that are usually located or stored are sort of housed inside systems that you'll have to go into, to extract that data from.
And it's a ..., sort of continuous improvement, or ongoing issues, end to end processes. We're looking at much larger sets of data, much longer periods of time, and often much more sources of information. Mode two. And the reason I call it strategic is because those are those kind of changes, aren't the sort of one at a time process improvements, you'll see, that can get you a quick Roy. Those are things that give you a strategic, transformation capability, where process mining can help. You can pivot, major end to end processes, significantly change the way in which you improve your customer relationships, the way you interact with your customers, they can do major transformational initiatives around product delivery. These sorts of things tend to give you massive ROI, and huge, huge, or enterprise capability, but they demand a lot more from you.
I feel like a lot of organizations, and people think of process mining. Is this one big block, or even off, If not, they think of it as a spectrum. But when you think of it in ..., you can understand more quickly a, what you want to get to out of this process of process improvement, and be what you're going to have to provide to get the things you need. In this case, agile process mining requires substantially less to get started, but delivers last, but it delivers its last in context, that allows you to sort of build on quick wins, see that ROI, and use it for smaller transformation, scaling up the larger transformations.
We're trying to answer questions with process mining, and perfect example: is orders are changed to get blocked rejected, how do we maximize touch, this sales orders? So, now we're going to use Process might need to look at a single system maximizing the zero touch orders. And this is sort of our mode. one kind of thing, I'll go into Salesforce or into like a single, like in a real system. one system and grab an ETL, sort of, like I said, I extract of a list of transactions that occurred when they, when they occurred, who did them, and literally just a set of things.
Then, I'm gonna get some immediate insights, not only to how the process went, but how the process changed over time over different possible executions and see all those variants. So this, how do we maximize the zero TH order? The? First, we'll start by looking at the dataset and saying, what are the different ways that it happens? It's sort of, it's sort of a single dataset, the single initiative of analysis.
We're also gonna understand what happened most frequently. So what are people thinking is the standard and how do different variants impact KPIs that we care about in this small dataset?
The next thing we're going to figure out is where those KPIs are exceeding our targets. And so this is part of when you combine the Agile mining with your goals, and your goal, achievement settings, you're trying to figure out with your organization, you say, I'd like to take this initiative to decrease its value by a certain amount. So, let's say, I want to reduce my, my, that touch, the amount of time that I spent in touch sales orders, by 20%. This is a particular one sort of thread thing. I've got a clear mandate, a clear goal, and now I'm gonna go and find things that exceed that number and find those long running processes. Now, this, once again, this sort of mode one. We're still moving pretty quickly. But we're able to now get a set of variants that are no longer acceptable, and try to look into root causes of those variants. And we'll talk about that when we take a look at data.
But, data, sort of the optional extras in the data are going to help us to discreetly identify conditions by which those, those orders are resulting as bad. And, in sort of this mode, one of agile, we can quickly get to a root cause. or at least at the tentative root cause, and start moving towards solutions, one of those solutions, because establishing and maintaining maintaining a happy path.
So not only are we saying, Here's how we respond to challenges, but we're also starting to create organizational collateral.
So, mode one, you've started to get these process models that are now your golden standard. We have decided, based on the information we have and the KPI outcomes, that this process flow is what we want to have for this particular process. I can publish that. I can make it available to a larger number of consumers, and I can give them the resources they need to implement that over and over again, not just in a single location, but across the organization, because now I've established best practices. And now I can use that as a mechanism of encouraging change and other projects elsewhere to increase the value that I get from this single mode. one exercise, so, what, well, mode, one, once again, is a smaller scope. It does have the capacity to scale, particularly when you're looking at taking best practices and pushing them out to a larger consumer.
Now, the mode two is something like a perfect example, how can we harmonize our sales process globally?
What are the differences to today?
So, that's why we'd look at actual execution across a variety of systems, all the possible executions in those different spaces. I would look at it across geographies or between different data sources. And this is where I'm not looking at getting a CSV file as an extract to sort of put into my process finding cool. When I'm looking into hooking into actual process mining, process mining into real systems, that's when we're taking a look at things like, you know, taking web queries that come out, or are going and hitting its data tables for true integration into those systems. Because, not only am I talking about this from a once, sort of looking at it as a snapshot, but I'm also going to want to go and do this over a long period of time.
Harmonizing in standardizing the sales order process could take us a very long time. It could be a transformation that would go on, go over or go on over a series of months or even years to sort of harmonize this. And we want to keep a steady track of what's going on over time. And then once we've started to reach a steady state, we can continue to use process finding as a strategic tool to monitor how the execution is going and keep compliance back against those different business units to adhere to the standards that we've decided.
And that's when we talk about conformance, checking anomaly detections, that's where process mining, and in mode two, this sort of, strategic view, ends up being, sort of like, the BI tool. And in some capacity, it's not real time, That's not what process finding is intended to be, but it's relatively real-time, It's or, it's, it's as real as you needed to be. And let me explain that. The velocity of the change in the velocity of execution, if you're doing an order, and your orders are happening, Let's say you have a lead time on an order of, let's say, 72 hours.
You don't need information to be updated every second. And you have a live, real-time dashboard. If it was updated every minute, or every 10 minutes, or every hour, or even every every finding a four hours, that would be relatively real-time, because it's close enough.
But changes within your process aren't happening fast enough to make the next best action have to happen sooner than the latest refresh of data.
And so, this is where we take this and take a mining, exercise and improvement exercise and turn it into an ongoing support and improvement exercise. So conformance checks go back and look to see, Are people executing the processes? As, you know, in different locations? As per the decided standards we put out for ourselves? And so that's where we take a process model, and we compare it to the process execution discovery. So, we say, hey, are you doing steps in the wrong order? Are you missing? Is that, are you adding a step we didn't expect? And we can see that in dashboards and different sorts of an analytics that help you to emerge out A, what you have to do, B, Where it's working, and not working, and see how you can get better at this. And so that's sort of the ongoing exercise of learning and development that's gonna go out to your different teams. It could be an exercise of geographical, specificity and re-engineering for different areas, this could be an idea of, of, of enterprise transformation architecture, transformation.
Perhaps you look through the mining and one of your systems that's providing data, you can see that this is one of the sources of challenge for your organization.
Not perhaps you should be looking at finding ways of either changing your business logic and rules in that system, or going through a transformation in a system landscape upgrade to help meet your business needs.
And then the next question is, how does that happen?
Well, when we talk about mode one, this is something that's a little bit simpler mode one is, once again, getting sets of data, that are just, you know, literally flat exports, usually, that give us really fast insights. And so, we talk about activity, tables as a core piece of the puzzle and, whatever system you're using for transactions, whatever automation system, or whatever business rules engine you have, I guarantee you have some form of activity table that you can pull out where, it covers where, thing, what, the case IDs are, so isn't focusing on. These, are the process executions that happen and we're sort of labeling them.
This is an order X or Y or zed, Then things that happen so activity names are really important for us to understand the steps that occurred and all these systems will be able to produce something like that. Then time-stamps note that I did put only that the start time-stamp as a mandatory thing, because in mode one and even sort of Agile process mining, one of the things we can't be as we can't be choosers because we're trying our best to move quickly, and get whatever data we have. So a lot of systems, you know, we can try and ask for more information than we know. Then we need, and slow down our agile process transformation in mode one. So activity start is really all you need. You can sort of Interpol eight what happened. You can look throughput time, rather than single activity time. There's lots of ways we can get around having to have both activities start and end. Although, that, of course, is ideal. Having both means I can get a look at individual step time plus interstitials time, which is a useful tool to say how much are we waiting for people to be available for the next step to occur? But if you don't have that, that's totally fine.
The next piece, recommend the act and time-stamp we talked about. And we also recommend additional activity data. And this example I've got executed by. one of the things we talk about sometimes in process mining is something we call interaction analysis.
And so interaction analysis means which people interacted with which process steps to achieve this goal, and that that helps us to break down. For instance, down from like organizations, what you can score and gamify how an organization is doing based off of the people in their allocation to roles and ultimately organizational units. Or if you want to get very Big Brother, Interaction analysis does allow us to go execute or buy execute, or, you know, who is performing, well, who is performing slowly, in their in their daily tasks.
A lot of folks don't want to have that conversation. I understand it, but just to say that that kind of information and decomposition can exist if you have a recommended set of data like the additional activity data.
The other part of mode one is is if we can be both beggars and choosers, we can enhance our tables with more information.
And this is where you grab whatever is available to establish.
two things we call them measures and dimensions.
So a dimension is something by which we can categorize the process that you were seeing in front of us. Perfect example is the purchase organization, The product category, the vendor country, these are additional dimensions which we can actually set as you know, different filters to see how things are performing or their root causes. We can analyze and get out associated with one of these dimensions. And if so, we can we can hone in on that and say, oh, we're seeing that the KPI here, we're not meeting our SLA and the dimension we're finding that happening mostly on as a certain product category. Like office supplies. We aren't able to ship our office supplies as quickly as we want. What's going on with this? Let's delve into that, let's let's use this sort of Agile analysis to immediately get a quick hint as to where we can look next. So once again, mode one.
So you're sort of, at this point in time, you're getting small sets of data. You're getting whatever you can from whoever whatever is available and you're turning it together into something that can move quickly.
Mode two is a little different mode to we're pulling from this variety of application systems and getting it as a set of data. So we're pulling these, the single events single instance is that occurred and we're aligning them. So the first piece of puzzle is we're collecting all this information. And you're going to end the in the in mode two. It's a lot less transparent to the ..., So if you're, for instance, if you're doing a process finding activities and somebody who's a prep process professional, you're not going to see as much that mode two is happening because it's a lot of direct integration. So you're not like loading Excel files into a tool. But they're going to pull a series of steps. And then this is perhaps the most important one. We're going to have to keep all those steps to those process instances or those case IDs I talked about earlier. But that keying maybe harder, because you've got different systems. So one of the things we needed, particularly in Mode two, is we need a master key between system the system.
So the air waybill number in this system is key to our shipping number in that system.
And that sort of teeing file allows us to take those and actually align these process instances too, their groups. And then then we can take that Time time-stamp Information, and sort it, like we talked about before in Mode one. But, but that keep that, that second step is something that takes us a little bit more time in mode two. Which is why I say mode two is more of a strategic view. It's not that sort of agile movement of information. But the benefit and the value of mode two can be substantially higher. It's just it takes more investment. And it takes more of a strategic and sort of our executive will to achieve.
So we're correlating end to end process steps across sources and making mode to happen in the end. Both those give us really good outcomes. We're able to move quickly and make small improvements. Are we able to see overall views that let us get to We'll strategic transformation.
And the different use cases, we want to recognize apply to different types of, types of views. So, we want to take a look at a process, discovery view. So, we said, as I said this at the beginning. And it's important to recognize that one of our outcomes for, for these modes is both modes actually used to end up with some mechanism, a process discovery. We want to build these into a model that we can do something with. Um, I always tell that story, that the process mining without business process modeling is like buying a car with only two tires. You're only going to get halfway there, and sure, you can probably drive and screech it along as you get to where you wanna go, but the truth is, you're missing half the puzzle, which is executing on that improvement.
If you want to get across to Discover, you want to build it into models.
The next is, you want to check those models back. So, for instance, in the case of mode two, you want to check back against how you expected things to go. So, if you have a process modeling tool in place, you're all set. If you don't, what we do is we do a discovery. And we do a transformation that we do a rediscovery and talk the talk about that in a strategic capacity.
The third is enhancement. You want to get those three different things out of process mining, if you can't get all three, then you're missing something. There's enhancement relies on KPIs and thresholds, and business goals. And both mode, one and mode two have enhancement capacity mode. one is very target oriented. And mode two is something that's more of a strategic transformation oriented, so you're seeing where your strategic weaknesses are. And then you can check back. Through the same sort of processes conformance, did I achieve my strategic targets? And in the process enhancements, that's where we talk about Profit Group data life cycle. We're looking to do so.
Getting all those pieces in place is really important, Because ultimately, we're trying to support business transformation. We're trying to provide transparency, which is a, which is crucial, to helping your transformation come to life, and keeping all your stakeholders informed. Keeping them involved in the process. We're trying to help with shaping to build documentation, structured documentation that helps to inform, and educate, and enable your team, and ultimately, to engage with the business, to engage with your customers. To engage with the, with the transformation that you're trying to achieve. And that helps to give your process mining, real sticking value in the organization, And that's where you take something like a mode, one success, where you're able to go get some agile processes. To show some quick wins in process mining, and turn that into the onus for executive support for mode two, approach.
Because ultimately, we're trying to help you, and process mining is trying to help you, depending on who you are, who you report to. It's giving you the resources you need to achieve strategic targets. So how do we do that?
Well, let's say you're part of the operational excellence team.
Your CEO, you're part of the BP 18 are part of the compliance team. Our challenge is, we want to provide transparency for reliable decision. So, we want to, under, identified these underperforming processes, want to figure out why and be able to improve those processes.
Our compliance, we were trying to figure out why are people not doing what they said they would do? There's, there are some legal and front end, and we are regulatory risks, but they're introducing as a result of that. But also, just in general, if you're non compliant to a Golden Standard, there's a reason why people put that golden standard out. And it's because they thought that we would be a better way of doing things. We want to provide that insight to you. So what do we do?
We give you visibility, and we allow you to adapt your processes as a blueprint for execution. Because this this bimodal mining is going to give you the visibility what you need to do. The information, you need to be able to use it, the models, you need to be able to transform, and the ability to implement those models in the organization's systems. And then ultimately, check back to make sure that that's a achieved, and so whether or not you're you roll up under the CEO, whether or not you roll up under compliance, those are going to help you achieve those goals can help you meet your challenges and exceed there are things that are put against you.
Conversely, let's say, you're trying to actually get money, and it's a chief savings, we are to KPI targets, maybe you're part of the c.f.o.'s office.
Let's say we have, yeah, outstanding invoice. We have cash, it's stuck an outstanding invoice, three days, unbuild, outstanding, those sorts of things, that's going to be a target That's levied against you. You want to get that money out of those outstanding invoices getting free up that cash flow. Or let's say you're the CEO, and you're trying to roll out best practices, you know that there's there's money to be saved in this, but you need to be able to convince people to make changes. Well. Let's give you a dashboard, Let's give you ways of communicating in the fashion that people can understand and accept. And that means that you're able to take that information and share it with people.
And you'll be able to build in this kind of proof to your various business units to overcome, resistance to change and take process mining outputs and turn them into real transformation capabilities. So you want to, you know, we're going to show you this and be able to show you where you're minimizing overdue Balance is calculating those those that block cache give you visibility back and allow you to take action on it or identify the standards and push them out and be able to see those.
the, those outliers come up with this best practice and then prove to your various business units that best practices, what you need, to put me in front of people.
And so, once again, both these modes are really giving you the individual process execution and achievement, or a strategic transformation, that you need to be able to do this.
And we've done this for a long time. Software G has been a big part of helping people transform it with, with process mining, and get insights into their business.
And that's with our, our, well, I've done, have been doing for a long time, with Eris, which has been a process finding tool out since, I believe, the year 2000. So, it's been a, it's been a long time of being able to see these, these successes. and what I've seen at organizations, and the use cases that I've seen them achieved, really sticks to me why this is important. Perfect example. And I'm not gonna name client names today. We're not going to go through, sort of all the success case, but let's talk about. But let's talk about, just in general, what, what this is. A global IT services corporation that I, that I saw really succeed with with mode one process mining.
So they had, they were looking to deliver services. And they had a lot of highly paid workers doing, essentially, low value tasks. This, is a perfect example of a case for RPA, where you're trying to implement that, but the question is, well, where can we really get the most value Out of it? Where should we leverage tools like RPA? And they took a mode, one look at this.
There was an Agile project, I mean, it's the IT services corporations, let's say, because all the resources were very highly paid for them to do an internal project, was also very expensive.
And, you know, a quick sense of proposition if you were looking to do this long strategic transformation, so, know, they couldn't convince their executives. And we certainly couldn't convince them to take a lot of people off the bench, and put them into this internal improvement process. But, if we offered, and we offered an agile solution, something that was quick and easy, take datasets, give them quick wins that they could use to automate, and understand where they were to improve.
Now, I was a lot of any of an easier sell, and an easier, actual resolution, So, once, again, we take a look at it, you know, a couple million dollars of savings. And that, they estimated, based off of what they were able to achieve. That seems like A, It's a good savings. But, you know, you've, you've seen transformations that save 50, $100 million, that's fine. Those are major transformations, We're not looking at looking at smaller wins. If these guys are able to prove out, and, in fact, they don't think they ever got to mode two, they stayed in mode when they say Agile, because they knew that they could get all the value. they needed. A half off of just getting quick data wins, quick datasets, and then doing an improvement, implementing a new process. And that's been fantastic. And so, this, this is an example of, you know, service organizations, leveraging their processes, and IT investments better using data driven insights in mode, one.
Conversely, I take a look at, let's say, top three international logistics company says, either. you. Once again, we're not using client reference aims, but that, but you think you can figure this out. The point is that they use strategic and an end to end transformation to talk about moving through the various parts of their supply chain and then the logistics. And this was a very challenging one because this was a, they had a very heavy SLA requirements that were lodged against them by their various B2B customers. And they were looking to improve supply chain that went through a bunch of different systems. There was a lot of legacy technologies that they were leveraging.
Plus, they were trying to use Cloud technologies to to sort of speed up some of their office, back office processes, and ultimately all that sort of that that spider web and that spaghetti of interconnectivity made it very difficult for them to see into their systems. So what we, what we did is, we took all that data, and we got that, once again, that, that really important keying. So that's one thing they were very good at. They did have a very good keying system to go between their different. There are different systems. So even in the legacy system, they had like, you know, a listing of this particular case ID Equals this a airway bill number.
And they underwent a pretty major end to end transformation, and talking about reducing cargo delivery time by nearly 50%. And that was through a bunch of things, whether or not it was, they did. They did some, some major process overhauls at a strategic level. So they eliminated certain systems. They took our business rules and processes. They had to do. They had a lot of transparency that sort of reveal to them where they were doing legacy processes and using legacy, thinking to try and solve tomorrow's problems. That was certainly not working. They also did things like, I, channel management. So they are able to see, based off of which systems were hit, at, which time, in, which geographies, they were able to meet better route shipments and use different cross border efficiencies to get through parts. So this is a global delivery service.
Organizations are, watching, you know, this this particular time-stamp, between Country A and country B, we see a lot, a higher number here. So if we do a movement of goods to this channel, instead, we can see an overall improvement, and they did, the massive cost savings, were an outcome that was undeniable. And so, these are the kinds of sort of and this was a long project, well, I'll be honest like this, this, I think this was.
So, I think it was 12 to 18 months before they really saw the full value of what was coming through. But, once again, if you have an executive level support, and they knew that, they weren't can be able to continue to keep up if they were using these old thinking processes, using their old, the old way of approaching challenges. So, they use process mining mode to process mining to make a serious, and lasting change the organization. And they've been able to keep up and Excel as a result partially of the work that they did in this particular project.
And so, spending 12, 18 months, and a lot of resource time, they manage the receipt achieve, substantial, operational, and cost savings.
That's what we're trying to help get with process mining. And it's, that's why it's so important to differentiate between mode one and mode, to know what you're going for and get out there and do it. Don't stop yourself if you don't have all the data. Think about it, an Agile capacity, think about it, it's mode one. But understand that you have so much more potential to move up to a mode to, to get out, get and integrate disparate systems, or recognized early on that the Agile transformation, you're trying to undergo spans, A bunch of systems spans, a bunch of business units and involves a huge amount of data that's from disparate sources.
You're not going to be able to achieve that in a mode one. You're going to have to get executive level of support. You're going to have to look at longer timelines, but you're gonna be able to achieve larger savings. So, now, you can start to build a better business case. Because, once again, ultimately, we're trying to build this transparency, or trying to help you shape your business and enable your people, and enable your customers. To be more successful. Happier and move through this. This. This whole business execution with ease and without the barriers that come up as a result of operational inefficiencies and operational operational barriers that come up and get revealed through process mining, both mode one and an Agile capacity and mode two as a strategic transformation enabler.
And, that's what we want you to do, And software has been doing this for a long time. We've been very successful, and very happy, and lots of great customers with it, And we think that we think that this sort of looking at this in a bimodal capacity helps maybe you be successful in that same capacity.
Thanks so much for listening to my talk, and it says, this is a great opportunity to speak to everyone. If you have questions, I would like to open the floor and just say thank you for having me in this. I'd like to open it back up and stop presenting, Go to my screen only, so we can maybe talk about how all this is working at and how we can see things coming to bear.
That's terrific. Terrific, J M: lot of real masterclass on, on process mining, for value creation, We really appreciate that. That was, that was very, very good. Well done. Well communicated.
Yeah, Lots of questions that have come up here. I always start with, kind of the obvious question, which is that, that came during that, your presentation.
Mode, one mode. two, very important distinction you made there. I think that there's a lot of confusion in the marketplace, and people kind of do hybrids of that. But there's also there is this tendency that Bazel the commentary. People share that, you know, there's the standards to think that Agile is always better. Write all that jazz. So, must be better, I'm quick and nimble. And, in working with lots of seals across many industries, I often hear CEOs talking about technology in not so fun ways. And they are one of the quotes the realistic with means, that one of them used to say all the time, that that knowledge can make stupid happen at the speed of light, and And That's summarized this kind of, that agile approach that is sub optimizing and.
So, the big question is, there is value in both clearly, but when you see organizations that are doing well, well, how do they balance the mode one versus mode to, do they start with mode one and move into mode to do they do a mode to strategic view? And then they do the mode, one, Agile opportunities. There's clearly, there's an X in the marketplace. What do you see as best practices?
That's a great question. So, the real truth is that we see a lot of organizations, they're, the ones that are smart or smart about this, are trying to see quick wins and grow based off of organizational capital. That they develop organizational knowledge. The ones that I see struggle or people who jump both feet in and try to get too much too fast. Where they don't have internal resources capable of delivering on the promises that they're trying to put out there. And the truth is that that mode to process my name is very hard, it's not, like you can just get away with no tossing mode to out there and say, oh yeah, we're we're all good on this. No, it is. It is something that requires executive level commitment.
Which is hard to achieve. It requires resources internally that have the skills to understand what data is necessary, how to connect that data, and what the insights are getting it mean. And it requires teams that are able to implement the suggestions, the ideas that come out of the insights you get.
Without all three of those. You're just showing dashboards to executives that really mean nothing and don't do anything, but boy, you spent a bunch of cash on a product. Congrats. So organizations really need to take a look internally first. What do we have the organizational capacity to do? Let's be realistic about that.
The second piece in this, this, this is why organizations that that start small and grow from there, are much more successful, is what data do we have? What insights can we, can we get? What information can we get from our systems? And so I go, I go to a lot of organizations that think, oh, We're going to walk into the strategic transformation. And I say, OK. So tell me a little bit more about your systems. What can I, what information? Can I extract them? They said, Well, you know, really, we're looking for you to do that discovery for us?
I said, Well, what do you What do you mean by that? He said, Well, our systems don't really tell us anything about it.
OK, so I said, well, then the first conversation you're having, isn't a conversation about process mining. It's really a conversation about robotic process discovery. You're going to want to put like desktop agents, or you're gonna want to install sniffers out there in your systems first to get good data. So, we're not even going to have this conversation until you can start doing that, And that information comes in really one source at a time. So now we're going to be forced to look at more than mode one.
No matter what. And so, their goals need to align with the data that they can get out. That's number two. And, number three, is that you need to think about what your organization's goals are as a transformation. Are you thinking an organ? Is? Are you an organization that is willing and open to do major overhauls on end to end processes that are enshrined in multiple business units? Do you have the political capital, will, and, really, enterprise level, strategic transformation goal, that that's going to align with that?
Because that's hard, and that's also not necessarily what organizations want. A lot of times, when they're thinking about Agile, they're thinking about moving fast. What they're thinking about is exactly the quick wins, and they might think they want to grow and see this multi multi business unit, multi geo execution really, you know, show a big number against their improvement.
But that's not what they really want. What they really want, and what their what their organization is telling them they want is to see those small wins, and they see those particular KPIs levied against business unit owners. And so, don't, don't make mistake to think that mode. one can be, is actually small. It's small per execution, but you can implement a program that it's agile, and spread across the sea overall, consolidated, major, transformations, and savings. But they need to be specific specific. You need to have scope for each one of those.
And so, need to know your organization, know your data, and know your goals. And if you have all those three things, normally organizations start with a conversation about mode one, first.
There are certain, certain cases, And I've come across a couple, where they had, they did jump straight into strategic conversation, and that's, I mean, frankly, a lot of organizations in manufacturing have a much more tight control, much more tight control, over it. But when they talk about the logistics company had a really, really good set of data, And they had a pretty serious history of data science.
And so their first conversation was mode two, but they were ready for it For the rest of them. I generally think of mode one is where we start, but knowing that you can scale up to mode two, is a really good piece of the puzzle. And also, don't invest in single serving technology, even if you're thinking agile, because you want that technology to scale. Once again, mode one might be a little projects, but you add them all up, and you've got a huge savings. But only if your technology is able to scale, at an enterprise level, even if you're thinking mode wants to start with.
Excellent answer. Very, very open and honest about what it takes to make this journey successful and the Jam. Tell me a little bit about, you know, we have you off course. I understand very well, the capabilities that the software provider can can, can deliver it to a client. But tell me a little bit on the client side. When you see successful projects, what type of it, Regardless of, you know, probably there is a difference between mode one and mode two. But if you could summarize a bit what type of capabilities clients should have in place? The clients that do well have in place or developed as part of this journey? I assume it's a mix of technical and business know-how. But I'd like to hear directly from you, what do you see on the client side that they have a team that has this cross functional, maybe a set of capabilities, and what do those capabilities may look like?
Yeah, it's a good question. I mean, I think there are some common terms that I find when I see this is the lead. So people with backgrounds and things like six Sigma, people who have a data driven business analysis, and I feel like that's a weird hybrid combination. That has to be explained because you are looking at the business, ultimately, you're trying to appeal to your customers. You're trying to be able to, you know, support the operations of your company. But people who have a background in engineering and science that recognize the technical requirements to achieve that, but also have the soft skills to push their their mandates through agenda. An agenda is through executive management and the hard skills to interface. With technical teams, that's that. That's the best capability to have developed.
And so that's why we find it a lot in internal consulting teams, We find that a lot in, or in process excellence teams, people who have that sort of focus. If those are the ones who are, who, have those, though, that background and skills. Deep background in, business modeling and business process automation, is very, very handy. When you start to bridge into process mining, because there's a better understand what they see on the page. And be able to say, Oh, this is why they'll be able to do root cause analysis more easily, but when you have that sort of background on, those are teams that are far more successful.
But, the, the number-one success in, particularly in scaling this, that I see, is, I see it at the level of the CIO or CTO where they have a technical background, particularly around process excellence, where that, that really senior level executive goes, Oh, yeah, we need to become a process driven company. And, to do that, I need data. And to do that, I need to get insights from my systems. I understand that, I accept that. I'm willing to put my my stamp behind it. Really, executive level commitment is very, very handy to see that really scaled success.
You can, you can stay in mode one for awhile, is like an individual team. But the real, like, the biggest numbers and the biggest successes I've seen are when that executive level support has a technical background, Has a process, process engineering background, and they're able to really take it and go with it.
OK, good, ladies and gentlemen. I have to say, you're working with more than 100 across industrial organizations with accelerating excellence and innovation, and with more than 30,000 axons to innovation leaders that I have worked with directly. I will say to you that what Jam has just talked about and his whole session on Master on Mode one and Mode two, is that true masterclass on what is what and create a lot of that in the, in the business. I do not say this lightly, J M so really well done in delivering that. There are questions about is there a way that people can learn more about this mode, 1 mode 2 concept, because it triggered. A lot of people assume these proprietary, I wonder if there's anything available on your website, or any other sources that you could point people to. I mean, obviously, I would reach out to software AG dot com. That's, that's my, the company's website that I worked for and I'm Julia Berlin's then, you can reach me. I'm based in North America.
So there's a lot of, a lot of, but JM, like J M dot ... at software AG dot com. Feel free to reach out to me. I can direct your system to some resources, But this is, this is, you know, from my perspective, this is some emerging thought in the industry, so we're not going to, you don't see a lot of white papers written about it, but it is very much part of what we do and how we present ourselves, so I'd be happy to have a follow on conversation with you. Or if you reject a software EG dot com, there's a lot of my cut my technical colleagues who can really support that.
This is what it's all about. Cross industry and thought leadership on a global basis. Jam. You're doing it. Thank you very much. Terrific session. I appreciate your sharing your wisdom with us.
Have a great day, And thank you so much, everyone, for listening in and enjoying what we have to have to present. So there's lots of fun.
Thank you, Jam. Ladies and gentlemen, terrific. Session of Jam, and we're going to wrap up this segment now. And at the top of the hour, we're going to have another tremendous practitioner sharing with us her journey of organizational excellence and innovation. Christina Pumphrey, who's the director of Processing Engineering Process Engineering, is going to be with us, and she's going to talk about leveraging process mining to design for success, strategic facility, and capacity planning. So this is a real industry leader, re-organization, implementing these tools and techniques in their environment to create value. So, I hope to see you at the top of the hour. Again, pleasure to have you with us. And we'll see you back soon.
Senior Systems Engineer, Intelligent Business Solutions,
J-M Erlendson is a Business Process Architect, Methodology Specialist and Transformation Engineering Leader with over 15 years of experience in Business Process Management, Enterprise Architecture, Supply Chain Management and Project Management, helping clients develop and implement business process framework strategies and execute process improvement and architecture modernization projects. He has consulted for a variety of clients in Canada and the United States, particularly in public sector, retail, utilities, manufacturing, lottery and gaming, telecom and oil and gas. J-M has helped grow and sustain the Software AG ARIS and Alfabet practices across North America for more than a decade.
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