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Process Mining Party 1

Process Mining Party

So we heard you like process mining, but do you also like to party? Well, if you do, you are in for a treat: Join us for our very first Process Mining Party next week!

When? — on Monday, 8 September 2014, starting at 21:00
Where? — at Hoogste Tijd in Eindhoven, NL

Why? — What, you need a reason to party? Ok, let us elaborate…

Next week, the BPM 2014 Conference will take place at Eindhoven University of Technology. This is the 12th instalment of the premier academic conference of Business Process Management. Originally, the location for the conference was to be in Haifa. However, due to the volatile political situation in Israel, the conference has been relocated to Eindhoven.

The BPM Conference is the most prestigious academic conference in the BPM area. Wil van der Aalst started the conference in 2003 and since then it takes place every year somewhere else. Researchers try to get their best papers into the main conference, which only accepts around 20 articles each year with several hundred submissions. Newer work is presented during one of the themed, parallel workshops at the workshop day.

The BPM conference, and from the workshops especially the BPI workshop, have always been the first choice for process mining researchers to publish and discuss their new work. (You can check out our recap posts from 2012 and 2013 to see how much has been going on.) This year, process mining is stronger than ever at the BPM conference, with process mining-related papers making up more than 50% of the conference program.

Monday, 8 September, is the day of the BPI Workshop and it is the process mining day of the conference this year. Consider this:

When we realized that all these process mining people where coming right to our home town, we decided to throw a process mining party to celebrate, inviting all of you along as well. And that’s what we are doing!

Fluxicon is organizing the party and the music. And the Special Interest Group (SIG) Process Mining of the Dutch industry association Ngi-NGN is sponsoring the first few rounds of drinks.

When: Monday, 8 September, 21:00 – 02:00
Where: Hoogste Tijd, Eindhoven (see map)
Entrance fee: Nope
Free drinks: As long as they last…

Expect a relaxed atmosphere, great music, and nice people.

It’s a special day for process mining and a fantastic opportunity to bring researchers and practitioners together. We hope you can join us, and we are looking forward to seeing you there!

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Disco 1.7.0 5

Software Update

It is our pleasure to announce the immediate release of Disco 1.7.0!

In many ways, this release is the biggest update to Disco since its initial release two years ago. The new features we have introduced in 1.7.0 will enable process analysts to not only work much more efficiently and fluently, but we think that these extensions will also open up many new opportunities and possibilities for applying process mining in your organization.

Disco will automatically download and install this update the next time you run it, if you are connected to the internet. You can of course also download and install the updated installer packages manually from

If you want to make yourself familiar with the changes and new additions in Disco 1.7.0, we have made a video that should give you a nice overview. Please keep reading if you want the full details of what we think is a great summer update to the most popular process mining tool in the world.

Continuous use and bigger data

When we first released Disco in 2012, process mining was still very much something new for most companies we talked to. Consequently, most of its practical applications were proofs-of-concept or pilots, and had a decidedly “project” character to them. A data set was extracted from the company’s IT systems, and a small team would spend some weeks or months analyzing it.

In the years since, the tide has clearly started to turn for process mining. There are now more than enough practical experiences, in a wide range of industries and use cases, that there is less of a need to “start small” for many companies. Furthermore, many of the early adopters are now way ahead in their process mining practice, and have integrated it deeply all across their daily operations. Consequently, the share of our customers that have a large installed base of Disco, and who use it every day in a repeated fashion, is about to become the majority.

At the same time, there has been an unrelenting trend for data sets becoming bigger and bigger. On the one hand, this growth of data volume reflects the increased importance that many organizations place on collecting and analyzing their operations. On the other hand, it is a testament to the success that process mining has experienced. Many companies have extended their use of process mining onto more and more segments of their operations, while more and more of the largest enterprises have embraced this technology as well. When you analyze a larger (part of your) business, you consequently have more data to analyze.

From the outset, we have designed Disco to be the perfect tool for all process mining use cases. It is easy to get started with for beginners, and at the same time the most flexible and powerful tool for experts. This flexibility has always made Disco great for exploratory and one-off projects, and thus very popular with consultants and process excellence groups. At the same time, our relentless focus on performance, and a smart design that rewards continued use, make sure that Disco is also the best companion for continued use on large data sets.

With Disco 1.7.0, we have focused on making Disco an even better tool for continuous use within organizations, and for ever-growing data sets. This release adds a number of features and improvements that not only make using Disco more enjoyable and productive in continuous use settings, but also open up completely new application areas in your organization.

At the same time, Disco 1.7.0 stays true to its nature of being the best tool for every process mining job. All the changes and additions that we have made will make Disco a better solution also for project use and other use cases, and we think that it significantly improves the Disco experience across the board.

There are three major “tentpole” features in Disco 1.7.0, which we will introduce right below: Overdrive, Recipes, and Airlift. Of course, this release is also chock-full of many more features, improvements, and bug fixes, which you can read about further below.



From the very start, we have designed and engineered Disco from the foundation to be as fast as possible, and to be able to deal also with very large data sets. Over the years, we have been able to steadily improve this performance, keeping Disco well ahead of other process mining solutions in terms of speed and scalability.

There are two major use cases where performance really matters in Disco: Loading a data set into Disco, e.g. from a CSV file, and filtering a data set, either to clean up data or to drill down for analysis. First, let us look more closely at what happens in Disco when you load a data set.

Data loading performance breakdown

In the first phase, the actual data is loaded and parsed from your file, organized in a way that enables process mining (e.g., sorted by timestamp and into cases), and stored within Disco for further analysis. This is the part that will typically consume the most time, and there is not much we can do about this, since it depends on the speed of your hard drive, and also on the characteristics of your data set.

Then, Disco extracts the process metrics from your data set. The metrics are a highly optimized data structure that stores process information about your data in a compressed form that enables fast process mining (e.g., how often activity “A” is followed by activity “B”).

Finally, the Disco miner analyzes the process metrics and builds a graphical process map, based on your detail settings for activities and paths (i.e., the sliders). This final phase is very fast, and happens almost instantly. When you move the sliders in the map view of Disco, this is what happens in the background.

Filtering performance breakdown

When you filter a data set in Disco, the data is first processed by the filters you configured, and the result is then organized and stored in Disco (the “Filtering” phase above). Again, we are basically moving a whole lot of data around here, so there are limits to how fast this phase can be performed.

After filtering, we have to create updated process metrics, since these are based on the now-changed event data, and of course we finally have to create an updated process map.

From the above, you can see that for both our performance-critical tasks in Disco we have three phases. The first phase of both loading and filtering has been thoroughly optimized over the years, and there are inherent physical boundaries to how fast this can get. The last phase has always been close to instant, so we can’t move the needle here as well.

This leaves the creation of the process metrics, and we are proud to announce that with Disco 1.7.0, we have achieved a real break-through in performance here.

Overdrive performance

Both our algorithms and data structures have been thoroughly redesigned and optimized from the ground up for maximum performance. This means that in Disco 1.7.0, generating the metrics will take 70% of the time when compared with Disco 1.6 as a base line.

Today, most computers in use have multiple CPU cores, and their number is growing with every generation. Most software, though, will only use one or at most two cores at a time. The reason for that is that developing for multiple cores adds a high degree of complexity to any software, and is often close to impossible or simply not worth it.

In Disco 1.7.0, the metrics generation phase will now transparently scale across all available CPU cores, using your system capacity to the max. And, as you can see from the chart above, the performance gain you get from each extra core is linear, meaning every time you double your number of cores, your processing time shrinks in half. For example, when you have 8 cores, you are now down to 12% of the processing time before Disco 1.7.0, which can turn a coffee break into the blink of an eye.

Many other performance-critical parts of Disco have been making use of all your CPU cores for quite some time. Bringing the metrics generation phase into the fold has been a real technical challenge, and we are proud to have achieved this linear step up in performance. This is an improvement that all of you will benefit from. But for those of you who use Disco every day, with very large data sets, we hope and expect that it will be a real game changer!



As a Disco user, you know that filtering is a cornerstone of process mining in Disco, and a major factor for its unmatched analysis power and flexibility. Filters allow you to clean up your data set and remove distracting and incorrect data. More importantly, they are a powerful mechanism for drilling down into subsets of your data, and for quickly and decidedly answering any analysis question you may have.

In Disco 1.7.0, we have made filtering faster and more powerful than ever before, for instance by improving the performance of every filter, and the responsiveness and functionality of the filter settings user interface. However, the biggest enhancement to filtering in 1.7.0 are Recipes.

Recipes are a feature in Disco to re-use and share filter settings. This means that you can now export your current filter settings to a Recipe file, and you can also load a Recipe file and apply its settings to another data set, even on another machine.

So far so good, and that’s pretty much the implementation for re-using filter settings that our customers have been asking us for. However, when we add a feature like that in Disco, we don’t stop with the obvious, trivial implementation. We think long and hard about the actual use cases, about when and why someone would re-use filter settings, and only after we have thoroughly understood it all, we carefully design a complete feature and add it to Disco.

Recipes popover

Above, you can see the Recipes popup, which you can trigger from a newly introduced button in the filter settings of Disco. On the lower left, you can open a Recipe file to apply it to your current data set. When you select the “Current” tab on the top right, you can see a summary of your current filter settings, and you can export it to a Recipe file for sharing it.

Next to the “Current” tab, you can see all filter settings in your current project in the “Project” tab. This allows you to quickly transfer filter settings, e.g. from the data set for last month to the updated data you just loaded into Disco.

Disco also remembers all your recently-applied filter settings, which are shown in the “History” tab. This feature acts much like a browser history, and allows you to quickly go back to something you did a few minutes ago and want to restore again.

Especially if you work in a continuous setting, and you have similar analysis questions for similar data sets over and over again, you will probably feel right at home in the “Favorites” tab. For every recipe, you can click the “Favorite” button on the lower right, which will remember this setting and add it to the “Favorites” section. Think of this as your personal “best-of” library of filter settings to clean up your data, or to drill down into specific subsets for further analysis in a snap. You can easily rename Recipes in your Favorites by clicking on their name on top.

Every recipe is shown with a short, human-readable summary of its filter settings. This allows you to quickly establish whether this is what you had been looking for, and to estimate its impact on your data. Moreover, below the recipe name and in the recipe list on the left, we have included a five-star-rating. This rating estimates how well each Recipe fits your current data set. It makes no sense to filter for an attribute that is not even present in your current data, or a timeframe that is long gone. The smart Recipe rating feature captures these problems, and allows you to focus on what’s relevant.

On the very left tab, you can see the “Matches”, which will only display those recipes from all over your Favorites, History, and Project that best match your current data set. This allows you to get a quick start with Recipes, and quickly find what is most relevant for your current context.

We think that Recipes will make working with Filters much more efficient and effortless in Disco. Especially if you are using Disco in a continuous and repetitive use case, Recipes will make your life much easier, boost your productivity, and allow you to focus on what’s really relevant.

Recipes also make it possible to quickly bring a colleague up to speed, by sharing your favorite filter settings with her for a head start. And finally, Recipes now enable consultants to share the “Recipes” of their work with their clients, empowering them to repeat and continue their analysis on updated data, right where the consultant left off.



One of the most remarkable benefits of process mining is that it makes analyzing business processes so easy and fluid that even more non-technical business users can start improving their processes right away. This sets process mining apart from more technically involved analysis methods, both from the classical statistics and the big data space. However, since the actual analysis part is so approachable and efficient, it highlights even more the challenge of getting event log data to analyze, and also the hurdles associated with getting that data into your process mining tool in the correct format.

Disco can read your log data from files in a number of formats. While the XES and MXML standards are more popular in the academic space, most business users prefer importing from CSV files, which can be easily exported from almost all process support system and data base servers. Many people have complimented us on our very user-friendly CSV import user interface in Disco, which intelligently aids users in configuration, and makes sure that you don’t have to do unnecessary work here.

However, the fact remains that configuring your CSV data for import, that means mapping columns in your data to case ID, activity names, and timestamps, is arguably the most complex task for most Disco users. Even worse, every user has to master this step before he can even start with the much more enjoyable and productive phase of actually analyzing their process.

Airlift distribution

With Disco 1.7.0, we are introducing Airlift, which addresses this problem. Airlift is an interface which provides a direct and seamless integration between Disco and the system where your event log data is stored. When you request log data over Airlift, technical details like case IDs, activities, and timestamps are already configured on the server side, so that business users can directly dive into analysis tasks.

Another benefit of Airlift is that it directly connects any number of Disco users with a single, canonical data source. You no longer have to maintain a shared space where the regularly exported CSV dumps are stored. Every user has direct access to up-to-date data, which she can request right at the point in time where she needs them.

As an interface, Airlift is located at the perfect position between the business side and the IT side of process operations. The IT staff can concentrate on configuring and maintaining the data source, while business users can focus on analysis only, without concerning themselves with technical details. And when you need an updated data set, there is no longer the need to involve the IT staff with your request, since you can directly download your data over Airlift.

Connecting to Airlift server

In Disco, you can access your Airlift server simply over the toolbar. The “Open file” button can now be switched to a “Connect to server” option, which brings up a login screen. As a Disco user, you need to provide the URL of your Airlift server, as well as your login and password details only once. After that, Disco will remember your settings and provide direct and fast access to your server every time, as simple as accessing the local file system.

Airlift Browser

When you are connected to your Airlift server, Disco provides you with a view where you can browse all data sets available on your Airlift server. For every data set, you can see some meta-data, like the number of cases and events, and the timeframe covered by the data set. Before you download, you can also specify which timeframe of data you are interested in, and whether you are only interested in completed cases.

Once you download a data set, only the data that you have requested is transferred from your Airlift server. Combined with a transfer format that is optimized for speed and throughput, an import from Airlift is much faster than importing that data from CSV. The time required for downloading log data is basically only limited by the speed of your network connection, and by the performance of your Airlift server.

Airlift is the perfect solution when you want to apply process mining in a continuous use case, and when you have multiple business users analyzing the same data sets in your organization. It provides the following main benefits over a file-based input.

Of course, Airlift support in Disco is only one part of the solution. You also need an Airlift server, capable of serving your data sets to Disco. Some of our customers already have an infrastructure of data warehouses and legacy systems, where their event log data is stored. If that is your situation, we can help you connecting your data source systems to your Disco clients with an Airlift server through our professional services.

Airlift Official Partners

Even more exciting, we are also introducing Airlift Official Partners. Theses are select vendors who have built the Airlift API right into their products. When you are using a system from an official partner, you get Airlift functionality out of the box. Just connect Disco to an official partner system, and you can start analyzing the processes supported or recorded by these systems right away, without any configuration or setup work.

We are especially excited about our three launching partners.

Alfresco Alfresco Activiti provides a highly-scalable, Java based, workflow and Business Process Management (BPM) platform targeted at business people, developers and administrators. Alfresco provides an out-of-the-box Airlift integration to Disco for any process that is deployed with their Activiti Enterprise BPM system. Since the Activiti system makes it easy to modify and update business processes, you can directly close the loop from running your process, analyzing it with Disco, and going back to implement the required changes in Activiti.

TransWare Profiling for SAP is a software and service solution from Transware, based on latest SAP technology standards like SAP Solution Manager. Transware enables a direct integration of your SAP system for process mining with Disco via Airlift. Transware’s Airlift-enabled solution is especially interesting if you want to continuously analyze your SAP processes with access to live data, while also limiting the impact on your SAP system’s setup and performance.

UXsuite UXsuite are specialized in data collection and analysis for measuring, controlling, and improving the customer experience of your users. Their SaaS service can collect data both from embedded systems in the field, and from websites and web apps that your customers interact with. Via UXsuite’s built-in Airlift integration, you can now analyze your customer journeys directly with process mining in Disco, with minimal setup and without installing any software.

We are really excited about our three launching partners, because we think that they provide exceptionally strong solutions in areas that are particularly relevant for process mining. For those of you that are using either of their solutions, process mining with Disco just got a whole lot easier and more powerful!

We are going to publish more in-depth articles about these particular Airlift integrations, and about Airlift in general, in the following weeks on this blog, so stay tuned! You can also get in touch if you want more information about these solutions right away.

One of our goals here at Fluxicon is to make process mining as easy, powerful, and accessible as possible for everyone, and we are very happy about our great set of launching partners. Going forward, there are already a number of further official partners hard at work on finishing their Airlift API implementations as we speak. If you have a product that you would like to offer Airlift integration for your customers, or if you would like the vendor of your process-supporting system to support Airlift, please get in touch with us at, and we will help you get the ball rolling!

Secondary Metrics

In Disco’s map view, you can project a number of frequency- and performance-related process perspectives onto the process map, which will both be visualized in terms of the color and shading of activities and paths, and also explicitly given in their respective text labels.

When we designed Disco, we have chosen for this view to show one metric at a time, for a number of reasons. For one, this makes the interaction with Disco much easier and more fluent, since when we only show one thing, we can show a larger part of the process map at the same time. This is one main reason why Disco is so successful in displaying very large and complex behavior with its compact map layout.

Secondly, picking a single process metrics for display provides instant context, which can then become subconscious. For every label you read on the map, you don’t have to think every time “What does that number say, again?”. You pick it once, and then you know it and move on to analysis. Focusing on a single metrics for map visualization thus provides also mental focus and improved productivity, which is why we have been very happy with this choice.

However, there are also some situations where you would really like to see two metrics on the map, at the same time. For example, the “Total Duration” performance perspective is great for visually highlighting the bottlenecks with the greatest impact on your process performance. When you want to learn more about these bottlenecks, though, you need to switch perspectives.

You will want to know how frequent that bottleneck occurs (i.e., its total or case frequency), to see whether you are dealing with an outlier. At the same time, you also want to know the specific extent of the delay (i.e., median, mean, or maximum duration), to properly estimate your improvement potential. In situations like this, showing two perspectives at the same time would actually improve your productivity, outweighing the detrimental effects introduced thusly.

Secondary Metrics in Map View

In Disco 1.7.0, you now have the option to add a secondary metrics to your process map visualization, by clicking on the “Add secondary” button below the perspective legend on the bottom right. The primary metrics will still take center stage, and will determine the visualization (colors, shades) of your map to ensure focus. But now, the labels of both activities and paths will now also feature a label detailing the secondary perspective.

Beside the specific situations where this is beneficial, like the one outlined above, this feature is also useful if you want to export more information-rich process maps (e.g. as a PDF) to share with other stakeholders of your analysis. We believe that, for the overwhelming majority of use cases, you should stick to a single perspective at a time. However, for those situations when one metrics is not enough, you now have a choice.

Filter Summary

While you are analyzing your data in the Map, Statistics, or Cases view, you often want a quick reminder of what you are looking at exactly. Disco has always had two small pie-chart indicators for displaying the filtered percentage of cases and events, but often you also want to get a quick overview of the filter settings you have applied to this data set.

Quick Filter Summary popover.

In Disco 1.7.0, you can now click on these pie-chart indicators to open a condensed filter summary. This summary is human-readable and to the point, like the filter settings display in the Recipes popup, allowing you to get a quick overview without entering the filter dialog every time.


We have designed Disco to be the perfect tool for process mining, and as such it includes all functionality that you need to analyze your business processes in depth. Focusing on process mining, however, also means that there are a lot of things that Disco does not do, because there are other tools better for these jobs.

To make sure that you can move seamlessly between Disco and other data analysis tools, like MS Excel, Disco allows you to export almost any result for further analysis in other software. In Disco 1.7.0, we introduce two additional export options that can help you to perform even deeper analysis in third-party tools like MS Excel.

When you export a process map in Disco, you typically want to export a graphical representation to a PDF document, or to a PNG or JPG image. With Disco 1.5.0, we have introduced an XML export for process maps, including all process metrics.

Process Metrics CSV Export

Starting from Disco 1.7.0, you can now also export the full set of process metrics to a set of CSV files packaged in a ZIP archive. This is the raw data that the Disco miner uses to construct the process map from, and is independent from the activity and paths slider settings. While this data is very low-level, it is the perfect starting point when you want to analyze your process metrics very in-depth, in a tool like Excel, Minitab, or SPSS.

As you may know, you can also export the full list of variants from Disco to CSV by right-clicking on the variants table in the Statistics view. This CSV file includes all meta-information about the variants, like the number of cases they cover, their number of events, and mean and median duration of cases. Starting from Disco 1.7.0, the exported CSV file now also includes the activity steps for each variant. This makes it easier for you to map each variant’s meta-data to their exact sequence of steps for further analysis or documentation.

Improved bug reports from within Disco

We could not plan the roadmap from Disco without the great amount of high-quality feedback we get from all our customers. For us, this feedback is essential for understanding how people are applying process mining, what problems they are trying to solve, and what challenges and problems they encounter with Disco today. Your feedback ensures that our roadmap tackles the relevant problems and challenges.

It is also challenging to develop process mining software bug-free out of the gate. Our customers use Disco for very different use cases, and the data sets they are analyzing differ widely in their characteristics. In order to make sure that bugs get fixed as quickly as possible in Disco, we have added in-app feedback from the beginning. By clicking on the speech-bubble icon in the toolbar, you can directly send us your feedback about bugs and problems you encounter, and you can also let us know your suggestions and ideas for improvement.

With Disco 1.7.0, we have improved our feedback system even more, to fix bugs and problems even faster, and to make it easier for you to help us make Disco better.

Report problems with diagnostics information from error dialogs.

When something goes wrong in Disco, you will see an error or warning dialog. With Disco 1.7.0, we have added a button to each error dialog that lets you directly provide feedback on this problem, right when it occurs. After you have sent your feedback, Disco will bring you right where you left off, so your flow of work will not be interrupted.

For every feedback option, from an error dialog or from the toolbar popup, we have also added the option to transmit diagnostic information to us. This is a set of information that allows us to see the precise context and state of Disco at the time of feedback. Especially when you report a bug or problem, diagnostic information allows us to get a better idea of what may have caused this problem, and enables us to fix it faster and in a better way.

Please note that this diagnostic information contains no personal data, and it also contains no information about your data sets. Its purpose is strictly to let us better understand the internal state of Disco, and to pinpoint the conditions that may have led to the problem you experienced. This information will help us to fix bugs and problems better and faster, with less of a need for you to provide more information or run tests for us. If you prefer not to send diagnostic information, you can always disable this option while still sending feedback.

Your continued feedback is a major reason why Disco is the best, and the most stable, process mining solution out there. By making it easier to send feedback right from error dialogs, and by including diagnostics information, providing feedback is now both easier and even more productive than before. Please keep sending us your feedback, and help us make Disco even better!

Other changes

The 1.7.0 update also includes a number of other features and bug fixes, which improve the functionality, reliability, and performance of Disco. Please find a list of the most important further changes below.

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Process Mining News – July / August 2014

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Every 1-2 months, we create this list of collected process mining web links and events in the process mining news (now also on the blog, with extra material in the e-mail edition).

Fluxicon Articles

Here are some blog articles that you may have missed:

Last month was all about Process Mining Camp, which took place on 18 June in Eindhoven, the Netherlands. You can find some photos and a summary of the day here.

Prior to camp, we held fire-side chat interviews with most of the speakers about different process mining topics: 

Interview with Frank van Geffen, Rabobank. Frank gave a practice talk and a workshop on 'How to get management buy-in for process mining'. He also participated in the panel.

Interview with Johan Lammers, Statistics Netherlands. Johan shared his experience from using process mining at CBS in a practice talk.

Interview with Shaun Moran, CDAnalytics. Shaun gave a workshop on 'Process mining and customer experience' at Process Mining camp.

Interview with Antonio Valle, G2. Antonio gave a workshop on 'Process Mining and Lean'.

Interview with Nicholas Hartman, CKM Advisors. Nick gave a practice talk and held a workshop on 'Data science tools that complement process mining'. Nick also participated in the panel.

Interview with John Müller, ING. John shared his experience on applying process mining to customer journey processes in a practice talk.

Interview with Erik Davelaar, KPMG. Erik told us about three different process mining projects from an auditing perspective.

A special issue on process mining was produced by the Dutch magazine 'Informatie'. You can read more about this special issue and download the PDF from our article in the magazine here.

Furthermore, an article about process mining in IT Service Management processes was published in the current issue of the itSMF magazine (in German). You can download the PDF version of the article here.

Process Mining on the Web

Here are some pointers to new process mining discussions and articles on the web, in no particular order:

Non-English language:

Event Calendar

To make sure you are not missing anything, here is a list of the upcoming process mining events we are aware of. 

Training Calendar

Do you want to get a head start in your own process mining initiatives by learning from the experts? Sign up for one of our monthly process mining trainings in Eindhoven

You will get a solid introduction into the general process mining concepts, combined with practical considerations like getting the right data, typical analysis questions, how to structure a process mining project, and hands-on exercises with our process mining software Disco. 

These are the training dates for the rest of the year:  

We have a very limited number of seats available, since we want to keep the training groups small, intimate, and productive. Sign up now, and reserve your spot!

Would you like to share a process mining-related pointer to an article, event, or discussion? Let us know about it!

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Recap of Process Mining Camp 2014 2

Full House at Process Mining Camp

We had a great day at Process Mining Camp three weeks ago! Half of the campers came from the Netherlands. The other half came from 15 different countries, some from places as far away as Brazil, the USA, and South Korea.

Because camp tickets were sold out very quickly, and the waiting list grew larger and larger, we were even running a livestream this year.

Camping Online

Anne Rozinat — Fluxicon, Netherlands

The program was started off by our keynote, where we shared our view on how we can advance process mining adoption. At the end of the keynote, we gave a sneak preview of what is coming very soon with Disco 1.7. The campers we spoke with were very excited about the new functionalities. Stay tuned!

Fluxicon Keynote at Process Mining Camp 2014

John Müller — ING, Netherlands

Then, John Müller showed us how ING Direct Australia had used process mining to improve the customer journey across website and callcenter channels. It was a great example of how business users are empowered by process mining, because they can analyze their own process directly, in an interactive and explorative way — rather than having to wait six months for their new report from BI.

John Müller from ING at Process Mining Camp 2014

Oliver Wildenstein — MLP, Germany

Oliver Wildenstein from MLP gave a new perspective on using process mining to monitor outsourcing providers. Many companies have outsourced processes, but are these processes really meeting the performance criteria that are in the contract? Without process mining, one has to believe the self-reports from the provider. With process mining, the customer gets a controlling mechanism for the outsourced process — but often has to pay to get access to the data.

Oliver Wildenstein at Process Mining Camp

Nicholas Hartman — CKM Advisors, USA

Nicholas Hartman from CKM Advisors showed us based on two IT Service Management examples how process mining helps to derive actionable insight for process improvement projects. Typical management reporting is not actionable, because it is heavily averaged and the granularity is limited by pre-determined categories. Process mining can be used to find the actual problem areas, such as bottlenecks. Furthermore, it can help to find out where cases could have been prevented in the first place — because the most efficient process is one that doesn’t happen at all!

Talk at Process Mining Camp by Nick Hartman

Johan Lammers — CBS, Netherlands

After the lunch break, Johan Lammers from Statistics Netherlands took us on a journey how official statistics are made. One way to study dynamics in statistics is to take snapshots of data over time. A special way is the panel survey, where a group of cases is followed over time. To produce statistics of good quality, and as cost-efficiently as possible, process improvement and process mining can be used. Johan showed concrete results from analyzing the labor force survey process — and how process mining could test certain hypotheses much faster compared to statistical tools like SPSS.

Johan Lammers at Process Mining Camp


Then, five parallel workshops provided an opportunity to share knowledge in smaller groups, with a deep-dive on specific topics. The workshop topics were “How to get management buy-in”, “Managing complexity in process mining”,
“Data science tools that complement process mining”, “Process mining and customer experience”, and “Process mining and lean”.

Workshop on getting management buy-in at Process Mining Camp 2014

Erik Davelaar — KPMG, Netherlands

After the workshops, Erik Davelaar from KPMG presented three case studies, where they used process mining at their clients. In one project, the processes were different for every country, and process mining helped to understand and audit these differences. In another project, the access rights were not strictly enforced on the system level, but with process mining segregation of duty violations could be assessed objectively. And in the third project deviations from the expected process were found. Process mining provides clear benefits — both for auditors and auditees.

Erik Davelaar at Process Mining Camp

Frank van Geffen — Rabobank, Netherlands

The last practice speaker was Frank van Geffen from the Rabobank, who shared their impressive journey of adopting process mining worldwide. In one of the projects, an IT service desk process could be improved such that after 6 months the team had reduced waiting time in aggregate by 72,000 hours, and prevented 2,000 incidents from being raised. In another project business expense claim turnaround time has been reduced from 11 days to 1.2 days. Frank ended his presentation with concrete recommendations for how you can make process mining a success in your own organization.

Frank Frank van Geffen at Process Mining Camp

Wil van der Aalst — TU Eindhoven, Netherlands

In his closing keynote, Wil van der Aalst from TU Eindhoven, the “godfather of process mining”, talked about how process mining fits in the wider data science spectrum and which research programs will be coming up at the new Data Science Center Eindhoven (DSC/e). At the DSC/e, process mining will be combined with other data science techniques such as data mining and statistics, the internet of things, but also look at human and social aspects.

Wil van der Aalst at Process Mining Camp

Panel Discussion

This year, Process Mining Camp was closed by a panel discussion, where we brought together different process mining perspectives.

Next to the previous speakers Wil van der Aalst (representing academia), Frank van Geffen (representing industry), and Nicholas Hartman (representing consultancies), we were joined by our very own Christian Günther and two industry analysts, Marc Kerremans from Gartner and Neil Ward-Dutton from MWD Advisors in the UK.

Panel discussion at this year's Process Mining Camp

The discussion was very lively and followed up on a number of themes that were brought up earlier throughout the day.

One of the themes was around adoption. While Marc Kerremans said that process mining was quickly climbing the Gartner hype cycle, Neil Ward-Dutton disagreed and insisted that we are much earlier in the adoption curve than that.

This was also discussed in the context of maturity: 90% of the business uses pen, paper, Powerpoint, and Visio for process improvement. Process mining can provide huge benefits here also without combining it with other tools like data mining.

Wil van der Aalst suggested that today’s business analysts need to become more nerdy to use new technologies. Furthermore, Frank van Geffen made the point that organizations need to create the space for innovation. They need to allow people to experiment with new techniques like process mining to be able to eventually roll them out broadly and productively as done at the Rabobank.

Finally, it was also discussed that once one is using data-driven analysis techniques like process mining, one needs to ensure that data and analysis results are used responsively and in accordance with the rules and ethics of the society and the company.

The audience really liked the practice talks and keynotes, workshops, and the panel discussion, and we would like to thank all speakers and panelists again for their contributions!

See you next year!

Because our campers were happy the hosts were very happy at the end of the day, too.

Anne and Christian at Process Mining Camp 2014

Would you like to look at some of the presentations (again), or share them with your colleagues? All speakers were so kind to provide a public PDF version of their slides. You can download them here:

The five workshop hosts have also provided their slides and materials for you to download (contact them directly if you have questions about the materials):

We recorded the practice talks, the keynotes, and the panel discussion, but making them available will take some more time.

If you want to be notified about new videos and next year’s Process Mining Camp, you can sign up on our Process Mining Camp mailing list here.

See you all next year!

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Process Mining in IT Service Management (in German) 1

Process Mining IT Service Management

IT Service processes are a very interesting application area for process mining, because delivering great IT support for the business is crucial for any company, and because the data are usually very easy to get. ITSM systems keep records of all activities related to a ticket number, which can be used as a case ID in process mining.

The June edition of the itSM Magazin now features an article that we wrote with Dierk Söllner on the use cases of process mining in IT Service Management (in German).

The whole issue is only accessible for itSMF members, but you can download our ‘Process Mining in IT Service Management’ article here.

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Special Issue on Process Mining in Dutch IT Professionals Magazine ‘Informatie’

Dutch magazine 'Informatie' this month as a special issue over process mining!

One of the challenges we process mining enthusiasts are facing is to make more people aware of the fact that process mining even exists. That is why we speak at conferences, write articles, organize special interest groups, events — and special issues.

Special issues have a special magic — A whole volume about just process mining gives all of us the chance to look at this topic from new, and different, angles. It allows to not remain at the surface by just introducing and positioning the matter, but to go in-depth and explore multiple perspectives.

After the Novática monograph on process mining, there is now a special issue of the Dutch magazine Informatie (nr. 5 – 2014), edited by Wil van der Aalst and Frank van Geffen.

This special issue showcases a broad array of different applications of process mining, and Christian and myself are very proud that we could contribute to the issue as well. You can download the PDF of our article ‘Toegevoegde waarde van process mining’ here. This article is in Dutch, but if you don’t speak the language you can read an English version at BPTrends here.

The complete special issue is only available for members of the Dutch IT professionals association Ngi-NGN (if you become a member now, you will still get one). But Ngi-NGN was so kind to sponsor 100 issues for the attendees of Process Mining Camp last week. And because half the campers came from outside the Netherlands, we have a few magazines left. So, if you want one of these rare keepsakes you can send an email to and we will mail it to you.

[Update: All remaining magazines have been given away.]

This special issue of ‘Informatie’ is a great success of the new Special Interest Group (SIG) Process Mining in the Ngi-NGN, which initiated this edition. At the SIG1 we also organize events around process mining and support members who want to share their knowledge and experience.

If you don’t have a special interest group on process mining in your region yet, why don’t you start one? Get in touch with us, and we will help you get started!

  1. where Fluxicon is also a board member 
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Livestream at Process Mining Camp!

Process Mining Camp 2014

Were you among the disappointed who did not get a ticket for Process Mining Camp this year, because it sold out so quickly? Or would you have loved to come but simply can’t make the trip to the Netherlands?

We have something for you!

For the first time, we will try to live-stream the Process Mining Camp. This means that you can follow the event live in the Internet while it takes place. There are some technical questions that remain open, so we are not yet 100% sure it will work, but let’s have a try and see how it goes!

So, how can you join?

  1. Take a look at the program to decide which talks you would like to see (use this timezone converter to check your local times for the camp schedule)
  2. At the time of the event, simply visit the regular Process Mining Camp website. We will embed the livestream at the top of the page, where you can then watch the program right in your browser.

Again, please don’t be disappointed if it does not work and expect the quality not to be great. But we will do our best and are excited that we can invite you all in.

See you at camp!

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Process Mining Camp 2014 — Fireside Chat with Erik Davelaar

Process Mining Camp Tickets are sold out this year but why don’t you sign up for the Process Mining Camp email list? You will receive the links to the slides from the speakers and to the video recordings of the talks as soon as they become available. And you will be the first to know when the registration opens for next year.

As a warm-up for camp, we have asked some of the speakers for an up-front interview. Previously, we have already spoken with Frank van Geffen from the Rabobank, with Johan Lammers from the Centraal Bureau voor de Statistiek, with Shaun Moran from Customer Dimension Analytics, Antonio Valle from G2, Nicholas Hartman from CKM Advisors, and John Müller from ING.

Erik Davelaar

Today, you can read the last interview with Erik Davelaar.

Erik is IT auditor at KPMG and at camp he will share his experience about how process mining fits into the auditing and compliance practice.

Interview with Erik

Anne: Hi Erik, thank you for sharing your experiences at camp! You are specializing on process mining in the IT audit area. How well-known is process mining among auditors today?

Erik: Hello Anne, thank you for having me. The past year I have been trying to convince our audit colleagues of the added value of process mining. After a number of pilots in the leasing sector and one at a mortgage provider we have convinced our audit colleagues at our financial sector clients of the added value.

This year we will use process mining at almost all our relevant financial sector clients. However we also have a large client base in the corporate clients sector. In this sector we have not yet used process mining. At the moment we are exploring the possibilities to use process mining at these clients. So the auditors in the financial sector are well aware of the possibilities of process mining, but we need to convince a lot more colleagues in other sectors.

Anne: Right! From your experience in all these projects in the financial sector, who is benefitting more from process mining and why: the auditor or the auditee?

Erik: That is kind of hard to say, it depends a bit on the client and the case.

For the auditor one of the biggest benefits is that they get a higher degree of assurance during the audit. Instead of using just a sample of 25 of the cases, all cases of the year are analyzed.

The biggest benefit for the auditee is that the audit is more efficient and fewer resources of the organization are needed during the audit.

There are more benefits for both the auditor and the auditee, but I will discuss these more in-depth during my presentation at the camp.

Anne: Excellent, thank you. We are looking forward to your talk and see you tomorrow at camp!

Come to Process Mining Camp!

Process Mining Camp takes place on 18 June in Eindhoven! Tickets are sold out for this year’s camp but why don’t you sign up for the camp email list? You will receive the links to the video recordings of the talks, and you will be the first to know when the registration opens for next year…

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Process Mining Camp 2014 — Fireside Chat with John Müller 1

Process Mining Camp Tickets are sold out this year but why don’t you sign up for the Process Mining Camp email list? You will receive the links to the slides from the speakers and to the video recordings of the talks as soon as they become available. And you will be the first to know when the registration opens for next year.

As a warm-up for camp, we have asked some of the speakers for an up-front interview. Previously, we have already spoken with Frank van Geffen from the Rabobank, with Johan Lammers from the Centraal Bureau voor de Statistiek, with Shaun Moran from Customer Dimension Analytics, Antonio Valle from G2, and Nicholas Hartman from CKM Advisors.

John Müller

Today, you can read the interview with John Müller.

John is a data scientist at ING bank and will give a practice talk about how he helped to improve the customer experience at ING Australia with process mining.

Interview with John

Anne: Hi John, you came across a use case for process mining that will be very interesting for many people at camp: The analysis of the customer journey path on a website before the customer calls the help desk. Can you tell us a bit about that moment when you realized that process mining was a solution for the problem you were facing and why?

John: First of all thank you for the invite. I’m honored to be invited. I came across the idea to use process mining already some months into my analysis. I was struggling with giving back the right kind of visualization of my analysis to the business user, I had tried the more traditional ways of plotting some things in R or some graphs in Excel but none of those options came close to my dream of giving something back to the business user where I could empower him to find his own answers to his questions.

We discussed how best to approach this when it hit me that this entire analysis could be seen as a customer journey or process if you will. Just because a website has no specific order in which people have to click didn’t mean it wasn’t fit to use process mining.

There was a clear start; the login, a clear middle, the switch to the call center and a clear end; hopefully a satisfied customer hanging up. The Disco tool by Fluxicon gave me the chance to give the preprocessed logs back to the business user and let him explore his own process and find his own answers, thus using his domain knowledge to the fullest.

Anne: That is so good to hear, because this is exactly what we are trying to do: Making process mining accessible for the people who have the domain knowledge about the process! Do you have an example of where they could find something in their process that you had completely missed when you looked at the same data yourself before?

John: I would actually put it the other way around, being able to visualize the data in such a powerful way opened up my eyes to how many things I had not seen when exploring the data by myself.

I had noticed a few recurring patterns of parts of the website that seemed to be causes of calls, but there would have been simply no way of finding all the relevant parts without a significant time investment in getting to know the domain.

To put it differently, the use of such a powerful tool for exploration allowed me and the business user to explore the data without having to think of specific questions to ask up front. No longer was the question something like “How many customers called about account opening that also visited the how to open an account page”, but it had turned into “It looks like a large percentage of clients had visited the interest page before calling, let’s do a deep dive there”.

Anne: Right! So it changed the way questions were asked? Because they did not need to know all the questions upfront?

John: Exactly! We could now go in with a blank slate, letting the data show us where to look next. We could start off by just looking at all the different ways the website was used before any sort of call and then base our next step off of the interesting-looking patterns.

Obviously not everything that we could see at first glance was shocking and new. For example, quite unsurprisingly a lot of customers logged in and clicked on the contact us page right before calling, but by combining the domain knowledge of the business user with process mining we were able to quickly spot unexpected patterns as well as confirm his suspicions about failing parts of the website. The latter part might not sound very exciting but this was the first time that these kind of suspicions were backed up by numbers at short notice, providing them with solid facts to convince other parts of the bank to act.

Anne: Fantastic, it will be great to hear more about this in your talk. Thanks a lot for making the time for this chat and see you at camp on Wednesday!

Come to Process Mining Camp!

Process Mining Camp takes place on 18 June in Eindhoven! Tickets are sold out for this year’s camp but why don’t you sign up for the camp email list? You will receive the links to the video recordings of the talks, and you will be the first to know when the registration opens for next year…

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Process Mining Camp 2014 — Fireside Chat with Nicholas Hartman

As a warm-up for Process Mining Camp, we have asked some of the speakers for an up-front interview. Previously, we have already spoken with Frank van Geffen from the Rabobank, with Johan Lammers from the Centraal Bureau voor de Statistiek, with Shaun Moran from Customer Dimension Analytics, and Antonio Valle from G2.

Nicholas Hartman

Today, you can read the interview with Nicholas Hartman.

Nick is director of CKM Advisors and will give a practice talk and a workshop about process mining in the context of other data science tools at camp.

Interview with Nick

Anne: Hi Nick, thank you for coming over from New York for Process Mining Camp! I can see from your twitter feed that CKM are putting lots of efforts into recruiting data scientists. What do you think is it that makes the job of a data scientist attractive for students?

Nick: Hi Anne. I’m really looking forward to the trip and meeting others within the process mining community.

It’s increasingly common for graduates to move into, and be very successful in, fields that were not directly related to their college or graduate studies. The students we encounter are keen to ensure that that their first steps into the ‘real world’ open even more doors for career options down the line.

A decade ago, management consultancy was often viewed as the main path for getting rapid exposure across sectors before settling down in a particular area. Today for many top candidates, and particularly for those from a science or math background, data science offers a better opportunity to both get that breadth of exposure to business challenges but also utilize and expand upon the technical skill-sets that interest these individuals. As a rapidly expanding field there are certainly a lot of opportunities to continue longer term advancing through data science. However, even those that end up moving horizontally after a few years will still possess the base of skills required to succeed in the data-driven economy of the future.

We also see a lot of top candidates that want to make sure they don’t want to end up as the ‘smartest person in the room.’ Rather, they want to feel like they’re a part of a team of people where everyone can contribute to the problem being solved while also constantly learning new skills from each other. That sort of communal collaborative atmosphere is really at the core of the data science community, and it’s certainly something that today’s graduates find attractive.

Anne: Yes, I can also recognize the mix of business and technical challenges as something that attracts people to process mining. As a field, it lies somewhere between information systems and computer science. So, interesting algorithms can be applied to very relevant problems in today’s companies. This is really exciting.

And you are absolutely right, community is very important. The process mining community is still quite small but an enthusiastic one. Do you think it has a place in the wider data science community now? Should it have a place there? How do you see the relationship?

Nick: Absolutely, process mining is a core component of data science. In fact, for most of the business applications of data science that we’re seeing some element of process mining is a major contributor.

One of the great things about the processing mining movement is that it’s focused directly on applying data to solve relevant issues that matter to stakeholders–the process owners. The broader data science, or dare I say “big data,” movement is often guilty of focusing too too much on tools and too little on developing actionable output with those tools. A focus on process mining as part of an organization’s data science initiative helps ensure that the data science team and its technical assets are focused on delivering output that will have a measurable impact for stakeholders.

In return, the broader data science community can help process miners in conducting analytics on increasingly large and unwieldy datasets, and connecting process data to other information that can help tell a more complete story. Basic process mining can be performed on a single system audit-log file, but increasingly we’re seeing stakeholders asking for things like text analytics to be layered on top of the process mining. These sorts of challenges require close collaboration between a diverse set of data scientists that can bring together these complementary skill sets.

Anne: Right! Next to your practice talk, where you will present two case studies, you will also give a workshop about data science tools that are commonly used together with process mining. What can participants expect from this workshop at camp?

Nick: I’ll start by presenting an overview of the the main steps we typically follow–from data ingestion and storage through to presentation–when completing a project and will highlight popular tools that are used by data scientists to facilitate those processes. In each of these areas I’ll pull from examples of our project work to describe things to consider with different tools, languages and services. There are currently no end-to-end data science solutions available, which means that skilled data scientists will need to integrate an appropriate collection of tools to deliver a successful analytics implementation.

The later half of the workshop will focus on going deeper into a few use cases of such tools, including text mining and automated ingestion of data into an analytics environment for process monitoring.

I’ll conclude with some suggestions on places to get started both in terms of experimenting with tools and getting access to useful test data. It’s certainly a lot to cover, but I hope there will be something new for everyone in the session. I’m also looking forward to learning through the discussions we have amongst the group.

Anne: Thanks, Nick! We look forward to having you at camp next week!

Come to Process Mining Camp!

Process Mining Camp takes place on 18 June in Eindhoven! Tickets are sold out right but you can still sign up and be notified if more ticket should become available…

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