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October 26, 2020

Process Mining Live- SPEAKER SPOTLIGHT : Achieve Process Excellence by Combining AI, Process Mining and Task Mining

 

Courtesy of Celonis' Yiannis Broustas, below is a transcript of his speaking session on 'Achieve Process Excellence by Combining AI, Process Mining and Task Mining' to Build a Thriving Enterprise that took place at BTOES Process Mining Live Virtual Conference.

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Session Information:

Achieve Process Excellence by Combining AI, Process Mining and Task Mining

Abstract: 

In their journey towards Process Excellence, business leaders are increasingly extending Process Mining with Task Mining in order to get a 360 degrees process insight, identify their next-best actions, and leverage intelligent automation for driving their desired business outcomes. In this session, discover how to leverage Desktop Data for capturing the granular manual steps involved in your processes and for completing your digital twin.

Key Takeaways:

  • Sense friction points in your manual processes which directly impact your desired business outcomes
  • Determine how to act on these opportunities with automation or other approaches
  • Get a glimpse on the role of Artificial Intelligence in fully understanding how your processes work and in improving them

Session Transcript:

So without further ado, let's welcome our very first speaker today, I'm excited to have with us.

Yun's brewster's, who is a product marketing lead, our global product marketing marketing leader, as Salon, is, yarn, is go ahead and bring up your camera. I will do a brief introduction and let your carry on from here. So, young. This is a process analytics, and task mining, thought leader, in the organization. Also a thought leader in artificial intelligence, digital transformation, and intelligent automation. He has embarked on a global artificial intelligence journey for more than a decade ago, and continuously seek to help stakeholders leveraged their powers towards a more intelligent, yes sustainable future. He has implemented advanced applications of machine learning within pre seed, Seed, Series A, B, C, startups, and Fortune 500 organizations, combining product, marketing, and business development, sales and expertise, Youngest. We're very grateful to have you with us, very much looking forward to your presentation today.

Yeah. I was really good morning, good afternoon and good evening to everybody, depending on where you are in the world. Thank you so much for joining me for this beautiful day. Jose, can you confirm that we can see my screen and the first slide of my presentation?

It's Looking Good eon is yes.

Perfect. So, thank you very much and for the next 30, 35 minutes, I want to take you through, the journey. That salon is, is, is actually towards process excellence.

And we're going to focus on how we can combine different sets of data that come dot com, both from our backend systems and we call this business data, but also from how people really execute the tasks, really get work done. And that's what ... money is actually helping us do. So, with that, within that context, I want to give a very brief introduction on celani's in salons in case as people in the audience don't know exactly what it says. We're a company based in Unique and New York City. We started about 10 years ago and I'll go into a bit of history here in the next couple of slides. And we are the global leader in process mining technology. We are trying to make your business frictionless, and we want to drive your desired business outcomes by AI driven automation and processing for improvement and auctions that go straight into your systems, into your front end data as well.

So, if we look at the history of process excellence, that we started, I would say more than 10, maybe 20 years ago, when we started mapping our processes. It meant that we would use a lot of white boarding, and a lot of us needs to actually design and share with each other, how the process should look like. And then, based on human interviewed 1 to 1 interviews, you could go in and say, OK, what do you think your processes? And how do you compare it with how it should have been. Following that, we move the process of discovery, which was something that I think is the topic of, of this, of this webinar, but, this conference.

Which, which was the question of how to get visibility into your processes, and really impact them, change them, and adjust them, compared to where you wanted them to be. However, the next level, the next iteration, is, how do you have to process excellence in order to drive your outcomes?

Screenshot - 2020-09-07T152543.376

So, not only you can map your processes, not only you can visualize them, but now you can intervene find the next best action, and leverage AI, predominantly to actually see if they improve the KPIs that you're focusing on, and achieve the goals that your organization is really like caring for.

So, a bit of an outline of about ....

I'm going to start with my February Covered Business Review quote, that you should be exploring process mining, as simple as that is a very simple code that encapsulates why process mining has been insights and not an upward trajectory in the last decade or so and salon. Is is named the Market Leader by Gartner in 20 19. And we're expecting something similar from the new report coming out soon.

We have been doubling ourselves here and here and we have, we have had more than 2000 customer deployments. If you look at the small logos in terms of size but these are really massive companies that we're working with. And the analyst's endorsements and the global press coverage is always talking about how processes mining is really changing the way these companies operate and how it helps them achieve the results.

So, the industry is that the process mining can work with, and that's one of the, of the beauties of process mining, and, consequently, Epsilon is, is, that, it's a, it's a, it's an industry agnostic. And it's a role agnostic technology that we've worked with manufacturing. We've worked with life sciences, consumer goods, retail, logistics, telecommunications, and with people who are, users, are already in supply chain, financing IT in R&D. Because any organization that goes above a certain size has processes, any process that has data mining, can actually work with it.

So Getting a bit deeper, going deeper into the topic of today.

The objective of off of any problems mining solution out there. And of course of salons, is to provide the 360 degrees processing side in order to drive intelligent action in order to achieve your business outcomes. And in this triad off of pop steps, none of the steps should be discounted or should be considered as a given, because the processing side will drive the action, and the business outcomes are going to drive which actions are the ones to be taken.

So why, Why talk about ... mining today and why combined past landing with process lining?

So for the last decade of growth would be looking at our business data Si P, Salesforce, Oracle, or all our backend systems and the processes that go with the customer journey. Procure to pay, the order to cost and so on and so forth. But the reality is, at the same time, we have people that work in these processes and execute them.

And there is always, there are always steps that's happening.

It's clean, that are closely connected with how people execute these processes, and this is where desktop data comes in. And that includes, you know, how people will look up information on an Excel sheet to too close to move MSRP process step further, or what, how they're browsing the internet to find specific information. Or how they're e-mailing each other in order to achieve the desired desired goal in executing their tasks, and thus mining.

What, what does Planning allows you to do is you complete the 360 degree processing side, because you combine those two types of data, business data and this data, and it allows you, it gives you a perspective on how the manual tasks are executed. So the benefits of that is, first of all, you are able to discover anything since is that live outside of your back end systems. So traditional courses mining definitely is amazing for finding inefficiencies in your back end systems. However, mining takes that one step further and it helps you understand those inefficiencies that are not in your event logs. Same time, that allows you to quantify the value of streamlining your end to end processes.

Btog CTAIt adds to the quantification that you would get some process mining, by being able to quantify the cost, the opportunity, the savings, the actual final outcome. If you can streamline end to end most business data, both sort of business processes and desktop manual activities. At the end, it also optimize workforce productivity.

And I want to add an angle to that. We are all living through the cold in 19 challenges in the last 6, 7 months or so, And our processes have to change without us knowing, self selecting how these changes will happen. So that's my name is a great tool to help you understand how, how your workforce is working from home, how your processes have to change, and how you can really get the best insight on either fixing those processes, changing them, or even helping, helping you understand things like training. How do I train my people now that they are not in the same office, and they all work from home?

The way that works is that it captures this data it runs in the background and it collects clicks sprawls, and user oxidants. Well, and Allow Listed Application app is being used.

That means that only only when your users, or your, your employees are using applications that are selected by you and are closely connected to the process, that's where money is monitoring. And it's actually capturing this data to make sure that the processes are executed in the best possible way.

Then we leveraged OCR in AI in order to have context and to cluster these activities together in order to then match them to the business need. And what, what the magic here is that we, we, we scan the noise. You can scan through the noise in the past mining and that that's the manual tasks to the business step, to the case. Like this ID that you're actually trying to analyze. And the process starts with Windows desktops, that's where the money is, the most efficient came And then in terms of Business Cloud of Salon is, takes over the work of doing that the contextualization and the matching for the business data.

So, the use case I want to talk about, because I know the audience is way more advanced than, than a general audience in process mining, is, to show you, and talk about how, we can extend process mining with tasks finding. The benefits of that is, that, that's what allows you to create a digital twin with your granular manual steps. So it's not only that, you got, you can, you can create between, based on your backend systems. But you can also understand how your company operates. Also, on manual perspective, you can see what mangled steps are involved in all the activities, and it can, as I said, you can act based on the outcome driven. Next, best action recommendations. And with that, I'm going to start with with a demo. And I'm gonna take you in this, in this hypothetical scenario, orphaned accounts payable department.

So this specific accounts payable department has been facing a lot of pressure from other internal teams because of how they were charging them for treating their invoices.

So, the challenge they are facing is how can we actually know what do we do with our AP process, with our accounts payable processes, in order to be able to justify, explain, and come up with a true cost model that can then be used in our discussions with, with our federal partners. So, them, the four KPIs that these ... trying to optimize is standardization. In other words, how do I standardize my process? Handling time, how much time do I actually spent handling those invoices? First time. First time, right rate.

Which means, how can I just have going to have more bachelor's invoices without having to intervene manually.

And then, second time, what's the cycle time that, that I will actually need to manage this process.

So, the first thing that you get with that money is an application, and this is, interestingly, interestingly, interesting to see, because you get the full view of how your backend and your front end systems are used. So, in this case, because it's accounts payable, so there's a lot of invoices, people go on and off S&P, So you see a very high S A P percentage of out of mining. However, if you go to other processes, you will see the number dropping significantly. However, you can see that people are also collaborating with Teams. They're sending e-mails. They're looking, they're using Word, PowerPoint, and Excel, at a certain extent, They're browsing and, in general, you can see what programs and what's up with applications They're using to execute the tasks in this specific process.

21one of the most powerful thing about process mining and past mining, is that you can combine your process mining steps and your ... steps.

In one, in one process explorer, in this case, in blue, you can see your app, back end system, sub steps, and then, in red, you can see that the steps that were captured by, that's fine. And, as you add more and more steps, you can immediately see that.

All your processes are then inter-connected, and people do, jump on and off their desktop. They do have manual tasks that they're working with in order to actually achieve or actually complete their tasks. So, if we go to standardization, you can immediately have a view on which applications are used. What are, what are the hops? So if you've seen this in this specific view, you can see what, how people hop to hop between application. And, and obviously, in this case, sap logo on is that one of these use the most, what are, what are the drill down and what's the average handling time by different by the different materials.

When it comes to handling time, you can see that actually handling time has been improving recently. But I want to focus more on the first time, right rates for for the purpose of today. And you see that rate is 70%, which is definitely not ideal.

Good, accounts payable first time, right?

So, that's less invoice rate, would be above, probably, like 90%, which means that that should be the target, or let us say 80%, 80 to 90% would be a good enough target.

But, this 70% means that we are doing a lot of manual steps and a lot of rework in order to manage, to treat these invoices. So, if we start drilling down on what this, what's causing this?

We see that actually seems quantity is something that happens pretty often, So it is something that happens pretty often at the same time if it's something that shouldn't happen because an invoice should have the correct quantities.

So, if we filter down in this change quantity step, we realize that every invoice that goes through that has like a significantly increased number of works, steps, which is there, There are hot, they're up by more than 50%. And what we need to do here, we understand here, is we need to focus on how to improve this KPI. So by immediately taking action, we're moving to what we call, in Salon. is an actual engine, which is a personal inbox. So in this case, I'm wearing the hat off and account the Accounting department. I'm Janice and I, I received this does not notifications from salamis on things. I could intervene in order to improve my, my KPI in order to improve the way that I actually do my work. So by, by selecting, but by actually filtering on the one that has the higher impact. In terms of gross amount, I click on it, and I immediately salamis, tells me.

That is 89% of the relevant cases.

Accounting Clerks check specifically specific Excel sheet called ... OS vendors. So, not only, I get that insight and I'm able to understand why, What is causing the problem with how people are solving it. But so long as allows me to immediately take action and check the specific Excel saved from within salon is in order to do my work Much faster, much easier for the specific invoice.

By implementing some of these automations and I'm not gonna take your time for talking much more about it today.

I am immediately able to realize that my first time rate rate has been fly me over the last 3 or 4 months from 70% that it was, it's now up to 82%.

And if we continue on the trajectory, we're going to soon be above 85, close to 90% in due time.

So, with that in mind, I wanted to do, just, and, the, the, the, the presentation part of off today by, sharing with you the fact, that, extending process, mining mining allows you to get an even fuller picture than what you have before. So, we talked about *** elements and how it can be. it seems, we talked about how mining can be combined with us money. We saw a demo, an example of our accounts payable department could actually intervene, and resolve, or improve their KPIs. And now, what I invite you is to, First of, all, I wanna thank you for attending today. And I would like to open the floor with a bit longer of a discussion for Q&A. Since, I think it's A topic which is very, very interesting. And it's, it's, it takes process mining to the two step. Or a few steps further. So we thought we thought in mind, please, thank you very much. And I'm looking forward to having an open dialog.

Very good Yarn is very good. So I'm going to ask you to stop sharing your presentation so that the audience can see you. And the, As we go through that, I'm keeping an eye here on the questions that the audience has.

And I will prioritize those questions. So keep providing your questions, we have an eye on those yannis you go into the goto Webinar panel and there is under Sharing. There is a button to stop sharing. So if you click on that, Stop Sharing button.

Yeah, there you go. You gotta, man. You got it.

Well done, so let's see what we're going to have here.

We have, first question that has come up, jaan's, is that, loss of commentary about great insights. You got into an overview, and then you got into some details on how process, mining, and text mining can, can work together. Back up a little bit.

Screenshot (4)And when you go work with a new client that has not done anything before, maybe their IT infrastructure. You know, doesn't even know what private process mining really is. Guide us for this steps that you think are the optimal steps. For someone who's starting in that journey of process mining. From what type of IT, infrastructure, and manpower they should have, to support this effectively, to some of the steps that you will carry on with them, on implementing, process mining with the golf scaling over time.

That's a great question because, and it's a question that we tend to answer every single time process mining for, for good or bad reasons, is not something that people have top of mind. It's not that you have executives waking up and saying, oh, I need to do personal mining tomorrow. So, there is always a certain level of education that we all have to go through and obviously, most companies that are going, or I would say all companies that go through their digital transformation journey. They have heard about, you, know, big data and silences and noise. And how do you actually sold from?

Solve these problems versus mining. And especially the way salon is approaches, it has really moved the needle away from that issue. We start by by a very simple but very powerful point, which is the event and events are captured in any event log of any system that you, you actually use and you actually have in your organization.

And based on that, we can really separate from the noise. The other types of data would have. By building the bi weekly integrating and salon is has more than 80 connectors to any system or most of the systems that companies have today. And we also have collaborations with, with customers who have home-grown systems, you are able to weekly, very quickly, in, like, we actually are, our promise to our customers is that they're up and running in a matter of a couple of weeks. So, actually, they realize value in 30 days. That's actually are synonymous promise, because very quickly, by connecting with the systems, you're able to capture the data that you need in order to paint the picture. Of how the process actually operate. If we add the task mining aspect of it by, By, using thus, mining on, on, on, on the desktop, You immediately get data.

Yeah.

On the same day. So, building your past mining side of, of your, of your data, or your data model is as fast, even faster than how you're building your processes running.

So I would, I would actually turn that question back to anyone, and say, tell us what your outcome is, What are you trying to see? What is keeping you up at night when it comes to your KPIs? Let us understand, let us let us take the journey together into which processes you're using for that specific KPI, and then then our technology will do the work of understanding them, and helping you take the next next, next next.

Very good. Very good youngest. And the other questions, I have surface here, and, again, audience, keep asking the questions. I'm going to capture as many of these as possible during the time that we have here.

The other question has to do about typical implementation timelines. And, let's, let's kind of put some barriers around constraints around that. Let's say, for example, in the example that you share with us related to maybe reducing cycle times on the accounts payable process. What does it mean? Of course, different sizes of organizations and complexity levels will play a role in this. But, typically, if you take, you should get a bit of the average case. What does it look like in terms of implementation timelines? How much time is on the upfront investigation, if you will, And then that the discovery process?

OK, Can you hear me now?

Yeah, your video has stopped there momentarily.

Is your audio is still on?

Are you able to hear us?

Can you hear me?

Yeah, I can hear your audio is frozen, which is OK, but I can hear you if you're able to just use I'm sorry Your videos frozen. If you're able to hear us, we can carry on that way.

Screenshot - 2020-09-07T152543.376Yeah, sorry, sorry for, I don't know what's going on with my connection. I can hear you very well, and I think the video will come back.

Yeah, no problem. And honestly, if you need to turn off the video so that you know, that doesn't hogg your bandwidth, that's totally fine as well. The question that Yeah, that's good. The question that we had was, if you get a bit of a typical case and Accounts payable process cycle, Time Reduction Effort, like the one you just share with us, Guide us on what a typical implementation timeline may look like. How much time on each one of the main stages on doing that type of work.

Yeah, so that's what I what I was referring to earlier. That's actually our, Our salon is promised space that you're gonna get up and running in 30 days.

So you can not only, not not only the great, but actually start achieving your goals within that timeframe. So, we, we get, we get connected to your systems with, with our, with our connectors. We are able to start building up, building up the necessary necessary necessary data models out of that. And immediately, you get views that you can use in order to drive your actions. So obviously I don't want us don't want to jump into telling you that everybody's going to get actions in 10 days but within a matter of weeks not months. We're able to achieve that for an organization of any size. one of the biggest advantages, especially of salon. is is that the enterprise readiness so far. All four of our platform, that allows any size, any type of organization, to join the journey. And we, and you can see that by the type of organization that we are already working with.

Very good. Tell us a little bit more about the task, mining aspects of the, of the activities, here. What type of, I mean, you're sending a client to, you know, some sort of utility application to the to the, to the operator, if you will, to this, to the individual, who's installing that on their desktop laptop? And there's leveraging their cameras, and microphones, and things like that. What type of capabilities do you have with Dan and LP AI? Well, what are the things running behind that? So discuss a little bit more about the sensor portion, and the data process that takes place.

Yep. So, that's when it gets installed on, on the organization's desktops, or at least the users that are important for the specific process. And, it works in the background in the same way that you have a Dropbox opt for example, that that.

Only gets activated when a pre-selected application is being used. So, if the system administrator says, I only want you to monitor how people slack each other, how my, my, my, my age, and slack each other for the specific process, that's mining, will only capture the data from that specific process.

That means that the full freedom and the food security lies with the organization that is using the technology. So that the units this is not any theta is able to take that and leverage it to their, to their benefit.

Now, as of that point, there are different technologies that we leverage those.

There is a screenshot capturing capability, where you you, you enable OCR or you leverage OCR to capture some contextual information from those screenshots. There are other technologies that we are able to create a new event log out of. Out of, out of the tasks that people doing the desktops, for example, with Windows, they have used time-stamps, clicks, Scrawls, so, you're able to create this, the whole data lake or data set, that data event log from, how they really execute the tasks only, again, for the applications that they are using or that they are unmistakable has selected as as allow listed. I want to also bring up the security point here, because you talked about cameras, and microphones.

We don't use any of that. We don't get into anybody's cameras microphones. We not only that, but we also obscure any personal data or any e-mail, passwords. Any of that gets it gets everything, is that it doesn't come to us. Everything stays with the user. And we have really taken, extreme measures to make sure that this is the most secure solution, while, at the same time, giving the freedom to that customer organization to select which parts of the processes they want to actually capture data from.

Very good. Very good.

21And, uh, we didn't Fuller has a question here related to the typical attributes of the individuals who analyze the mine data. So, you do this exploration. You collect the data, if you will, and now you're doing some analyzes there. What type of backgrounds, those individuals, have, maybe technical backgrounds, continuous improvement, and innovation backgrounds? Just curious about what you see in terms of education experience, kind of qualifications that people have for analyzing the this mind data to decide on improvements and innovations.

So, we don't use any humans to analyze these data. All these data is analyzed by, by the ABC, the Intelligent Business Cloud. So, old data, we have both business data and Desktop data.

They're all uploaded into our Intelligent Business Cloud, which is our Solange Cloud infrastructure, and, And it's all done by the cloud. There's no human intervention into actually analyzing the data. So I'm not sure if I can answer the question, because I Actually It doesn't cover the mining. So. I. I hope. I addressed I addressed it as best as I can. Well, that's, that's a really interesting point. Because, I think that there is a perception that, that once you put your mind, the data, if you will, in your, And you'll have that, then, new insights that. There is that, that, I think, for most people, is, a bit surprising. that there's no human intervention, that the system is deciding the improvements. And, implementing those improvements in real time there is no, like, oh, let's look at this, and try to understand what's going on here, Because some of this could be system could, some of, this could be human behavior, So, I'm curious about is that fully automated?

It's fully automated, and that's why the title of today's session is, Artificial Intelligence, with process mining and mining. That's exactly where AI comes into play. So, we leverage AI not only to capture the data, and give it context, but we use AI to combine these data.

The action, so that's why we're talking about AI driven, next, best action, So, absolutely, no human intervention into analyzing these data. It all happens from our technology.

And that's why we are able to have the scale or the enterprise level readiness that we have, because imagine, like, just, let us take an example, like, if we're capturing screenshots and you use an application, that is why these allow listed for 10 minutes, and we capture one screen shot per second for 10 minutes. That means that we are talking about 600 screenshots, like there is no, I think that's one user for only one application for 10 minutes. There is no, it's not it's humanly impossible to be able to sit down and analyze those, those screenshots by yourself or if, if, if we are capturing the, the, the time-stamps of a specific activity that happened in the desktop. And those activities are clicks or their scrawls imagining that the number of data that that model would have to go through.

So, absolutely done with AI, Obstinately bandwidth are within our intelligent business Cloud. And that's what allows us to actually drive these actions, because we're able to do weekly, understand where the inefficiencies lie and what the next action would actually make the, why the next action would actually make them go away.

Very good. Yeah, I need one more, one more on that. There is another follow up related to that. And the question, again, goes back to the human interaction. What is the systemic issues that you're observing are driven by human mistakes, and human error, and people just entering data wrong, people using a field incorrectly? How do you capture that?

Yeah, that's an awesome question.

So that's one of the powers of fast binding.

So for example, there are a few ways to answer that. So I'm gonna give you two examples and then we can let, you can tell me if you if we can go deeper into the into the top. So for example, let's assume that you are an organization and you're very interested in in some compliance regulations. So let's assume that there is a specific way that you need to manage the documents. And there is a specific, specific list of things that you need to do while you're taking the mining allows.

The organization didn't know exactly how each single document was checked, how many, how much time will spend the next field, and how, what were the steps, the process that we followed throughout the process?

So, the data that you capture allows you to identify extremes. For example, if somebody said says or each task planning gives you the insight, that specific user went through the form. Check the form and the form is two pages and he did it in one second.

That immediately triggers an auction of double checking that form so you've got to what the action is from Salon is is that it takes like first of all it floods that this does. That sounds irregularity is with it is below the threshold of swapped. The normal taking time is, and then the second step is to send that same document to a second per second Approval second checker in order to arrive to that point.

So, about 1, 1 gets the other case that you could actually find mistakes, is by cohort the, Let's, let's use the term of cohort behaviors.

So you can, with ..., combined with Process Planning, you can identify behavioral patterns, You can understand what's the best way to execute the specific tasks, and when, when you build your process map, you can drill down, and we call these the spaghetti process explorer. You can drill down even to the individual variance of Y, one particular case, or some particular cases, compared to 10000 total work done differently, and whether this is a mistake or not. So the power of automating all all this data, capturing and visualizing it with a Process Explorer, which combines mining and mining, is that you're able to identify those inefficiencies, even to the visual. And I hope that answers the question, but I'm happy to lobby. one final wrap on that, then. So how does the feedback get back to that individual who may be unaware that he or she is making that mistake, maybe they need a little bit more training on something, how do you close the loop with that individual?

Yep. I'm going to refer back to that to the demo that I'll just show you, This is what we call ... so that individual would receive a signal that you know, we identified that you've done this, this process step in a way that is not the recommended one. Can you please correct it now and maybe get training on how it should be done? So so you can drive actions directly from the system that can be executed with with the click of a button. So, yes.

It's a great question.

It's all automated and that's one of the big benefits and powersoft of salons, very powerful stuff, very powerful stuff. Let me scan here for, there are lots of questions. So let me scan here for the next one, this one comes from, and that Martinez and, and that is saying, first of all, great presentation. Your product really helps organizations improve their processes. Do you see some departments question the data once it's live, or the data accuracy, based on what you demonstrate. I think I know what you're going to say, but I want to hear directly from you. Do you have issues? When your mind, the data you do, the AI is making its decisions on the background, but, but, the organizations may still question that?

Um, we think it ties back to one question that you asked me earlier. We don't do any, any, any transformation, The data, we base that data on your organization's event logs, right? So, if your event log tells you that this is an event, like obviously we can have a discussion, at the end of the day, there is no human intervention, neither into the analysis more into the action that needs to be taken.

So, at the end of the day, you're right, we can sit down and have a look, But I'll give you a dust landing examples is, we are talking about just before, you have the screenshot. You can just pull up on the screen shots and have a look and say, do you agree that this is a screenshot of how the specific documents should have been treated? And you can actually go and check. And I, I, I think, Anna, for the question, because it's a, it's one of the salon's question. It's a process, by any question. I understand why organizations. We were asked to invest in processing, mining, and quite given recommendations that, could be, could be in the millions, right? You give a recommendation, and the impact of the intervention, could say that the organization millions. I absolutely understand, why, the organization would want to be sure that this is actually accurate data, we.

Screenshot (4)I'm going to talk from, from the salon's experience. I don't want to talk on behalf of the ... Solutions.

But, from Ceylon is, we never had an issue with data inaccuracy when it comes to cloud processes mining, visualization, Understanding interventions and driving the action, And that's why, you know, our customers speak speak on our behalf. Because at the end of the day, we base, as you said, as you, as I said before, there's no manual intervention. We base everything on AI and actual data of the organization.

Very good. Another question here, this one coming from Joseph Lackey and Joseph says, The working in the oil and gas industry. There were problems with S A P connectivity with vendors supply chains. This created a communication problem in getting on time deliveries because sometimes the vendors never had the latest software updates from S A P to facilitate the communication. Does ... Platform help resolve this kind of supply side problems with enterprise systems like sap?

Yeah.

So I'm not I'm going to try and answer the question. I'm not exactly sure what the problem was.

No, I'm going to shoot in the dark a bit, because I don't I'm not sure exactly what what it entails this, real quick, jaan. Yes, I agree. Because when I first read, I wasn't quite clear what he said. Because I think he's talking about the fact that the, that part of it is Deficiency is on the data set itself that, let's say, your work of an oil and gas company you're connecting to their safety system. But the problem there SAP's System has a certain reality, if you will, but But there are connecting they need to connect with vendor systems that may not be on on some of their on time deliveries, for example. And now all of a sudden, you're mining that information, so I guess part of the question is that, would you process mining, identified that issue, some sort of node on communication with suppliers that that information may not be accurate? Is that something that process mining can get you?

Yeah, and I would like to talk about another salon, each feature that we're really proud of, called, the multi event Log. And that, multiple log is, is, is, a unique salon is offering we've, we've announced citizenry listed a few months ago, and it allows you to, not only go through S, S one single process and analyze that one. But it allows you to combine different processes into one event, log and understand, cross processing, efficiencies, and cross plus interventions. So again, I don't want to jump the gun here and really tell you, this is the answer to this specific problem. But the multi event log, for example, is, is, is widely used by by purchase to pay in order to cast processors combine, because your order to cast when you have to deliver to your customers is closely dependent width.

Are dependent with your purchase to pay? If you don't have the right product in your warehouses, or you don't have the raw material to produce the right product in your, your warehouses, your on time delivery drops. When you can combine the two processes, and understanding the efficiencies, the system can, actually, Exelon is the knowledge, the kind of flag. You can flag those inefficiencies and say, listen, the supplier has been underperforming.

Or, or, their accuracy of their information is, is really sub optimal in the last two, once in the last three months. So, we recommend you to change, potentially, evaluate these other suppliers, or we recommend you to actually place an order 10 days earlier than what you normally do. And when you do that, it goes down, downstream your order to cast. And, it allows you to really improve your own warehousing, your optimize, your payment terms, and then, optimize the delivery to your customers. So I think if I capture the problem correctly, absolutely, this is something that process mining, in general, and surrounding this particular is capable of doing.

Very good. Very good yann's excellent answer. Our time is up so I want to make sure I'll thank you. Very good reveal. We went from very strategic, high level overview to very much in the weeds, tactical stuff, which is where we solve real problems, and very good coverage. We appreciate your sharing your expertise with our global audience today.

Thank you, Jose, and thank you to the audience. It was a great pleasure to be among you today.

Thank you very much. All right, ladies and gentlemen, this concludes this first segment of process: mining live today. We're going to close the session, and we're going to open back up at the top of the hour with Janice minutes, and Janice is going to talk to us about The Applications of Process Management in a covert 19 world. So, that's gonna be a different type of session where we have an industry leader in the global change leader sharing with us. How covert 19 has has impacted us, specifically how you apply some of this process management approaches to this new world in which we're living in. So, thank you for your participation. I'll see you back in a few minutes, at the top of the hour.

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About the Author

more (12)-1Yiannis Broustas,
Product Marketing,
Celonis.

Yiannis is a Global Product Marketing Manager at Celonis with a focus on Process Analytics and Task Mining as well as a thought leader in Artificial Intelligence, Digital Transformation, and Intelligent Automation. 
 
Yiannis embarked on the global Artificial Intelligence journey more than a decade ago and continuously seeks to help stakeholders leverage its power towards a more intelligent, yet sustainable, future. He has implemented advanced applications of Machine Learning within pre-Seed, Seed, Series A/B/C startups, and Fortune500 organizations, combining Product, Marketing, and BusDev/Sales expertise.

Whatever free time is left, he dedicates it to grooming and supporting early-stage entrepreneurs either as an Adj. Professor of Technology Entrepreneurship at New York University or as an Angel investor. 

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