What is Process Mining? How does it work?
in Learning

What is Process Mining?

Process Mining 101 series: Part 1

Have you heard of Process Mining or Process Mining Software before but are not sure what’s the meaning, how it works or if it has any value to you? Or are you completely new to the area of Process Mining and just arrived here by pure chance? Don’t worry. We’ve got you covered. In this five-part series we’ll give you a comprehensive guide to Process Mining. We’ll start with the basics and go into more details regarding application, use cases and possibilities along the way. The series ends with common misconceptions about Process Mining that cause confusion and hold people back from getting started.


Part 1: What is Process Mining

Part 2: Goals and Steps

Part 3: Use Cases

Part 4: Process Mining in Power BI

Part 5: Misconceptions about Process Mining (1)

Part 5: Misconceptions about Process Mining (2)

Comprehensive 51-page guide to Process Mining >> Free Download here

What is Process Mining? How does it work?

We start our workshop with the basics of Process Mining. What do we mean by ‘process’? How does Process Mining work? Where did it come from? What are its advantages? Who can use it? What are the typical application areas? And what do you need to get started?





Who can use it

What you need

Technology of Process Mining

What is a process?

In Process Mining a process is a chain of events made up of process steps with a clear start and end activity. Those process steps are individual actions or events in the process. An easy example of such a process is running a pizza place and baking a pizza. It starts with an order placement for a type of pizza and ends when the pizza is delivered. Those are start and end points. They and all the steps in-between (preheat oven, prepare dough, add toppings etc.) are process steps.

What is the definiton of Process Mining?

The term Process Mining actually describes a mix of technologies and methods that fall into the broader area of process management. The main goal of Process Mining is to analyze how processes actually transpire, how they deviate from the ideal model, what problems occur, what optimization measures should be taken, and then start to improve the process.

You can use the technique on any process as long as the relevant data is stored in an accessible IT system. Nowadays that describes any digitalized process.

Modern Process Mining tools do more than visualize your process. You can use them to:

  • do an in-depth analysis
  • benchmark
  • compare
  • monitor
  • trigger workflows
  • collaborate on process improvements
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How does it work?

Process Mining algorithms use data from so-called event logs. Those are not typical log files but different types of databases and files from enterprise information systems or enterprise resource planning systems.

Examples for typical event log data sources include SAP®, Salesforce, MS Dynamics, Excel sheets and many custom software tools.

PAFnow finds and marks a shortcut
Employees are very effective in creating shortcuts in your process. They can improve your workflow or be serious compliance violations, that’s why it’s so important to find them. Process Mining is the best solution to unveil the invisible net of pirate paths in your company.

The data is visualized in a process flow and shows your process as it actually happens. There are no guessing-games with Process Mining. You get a fact-based view on the events in your organization.

After your data has been visualized, you can start the analysis. There are filter options, root cause analysis for problems, different levels of detail and many other functions with which you can get to the bottom of the driving forces in your process.

There are even AI-supported tools to help you if you have no idea where to start your analysis or what to look for.

History of Process Mining

Before Process Mining

Now, you might say that the idea of analyzing data isn’t new and you are correct. However, the way we collect and analyze data is changing rapidly. Before data was readily available in digital form, people simply went through documents by hand or collected data from interviews to find useful information and deviations from the norm.

Even business processes were analyzed that way. It took a whole bunch of consultants, weeks of time, workshops, interviews and an awful lot of money to get an idea of how things were happening and what could be improved.

There were several problems with this approach because usually people have an idea of how things should happen but lack the greater picture of how things are actually happening. Then, there are also exceptions to the standard procedure. Steps might have to be redone because there was a mistake or something changed (for example, an order was changed), the process itself can evolve and change due to outside factors or process steps need to be adapted to a new situation. No one can be aware of all these exceptions and keep track of all deviations from the norm.

The results from the old approach were thus subjective, incomplete and often outdated by the time they were available.

ideal process image and missing actual process image
Your ideal process and your actual process can look very different. Traditional approaches tend to give a picture very similar to the ideal model but very far from reality.

Early Process Mining

In the late 1990s things started to change. Large amounts of data became available digitally. Professor Wil van der Aalst (the ‘Godfather of Process Mining’) and his dedicated team found a way to use that data in combination with analytics and visualization software.

Early Process Mining was born.

Things sped up further when the economic potential of Process Mining became apparent. First generation Process Mining tools entered the market. They focused on the visualization of as-is processes and allowed for analyses, but they lacked the BI elements we can find in 2nd generation tools.

Process Mining 2.0

The latest wave of Process Mining tools is much more advanced. It is a combination of data analytics, data mining, process analytics and Business Intelligence (BI). That means, on top of visualization and analysis (which also got improved) you now can benchmark, compare and monitor processes and KPIs (Key Performance Indicators), start workflow-triggers directly from your Process Mining software and collaborate in your organization’s IT infrastructure to communicate and solve problems.

What are the benefits of Process Mining?

Process Mining comes with serious advantages both over traditional approaches to data analysis or process management and in terms of competitiveness in the market.

Compared to old approaches

Real processes are much more complex than the ideal model. Understanding how you’re currently doing things is crucial to come up with an improvement strategy. Process Mining has a lot of benefits compared to the traditional approach and is able to resolve the weaknesses and problems that arise during old-fashioned data gathering and analysis.


Process Mining is much faster than the old approach to process optimization. Instead of conducting interviews and holding workshops that then need to be analyzed, the results appear at the push of a button.


The process flow gives you a completely objective view on your real process. There is no specific lens that was applied to the view. You see your process as it is not as anyone perceives it.

ideal process image and real process image
Ideal process vs actual process: Process Mining shows you the actual as-is process based on facts. There are no more guessing games!

The entire picture

You get the complete picture. Where individual people know what they are doing, there usually is no-one who has an idea of the entire process. With Process Mining, you see the entire process from start to finish including every individual step. This makes it much easier to communicate problems and find optimization potential.

Changing processes & exceptions

The process flow shows you all the paths from start to end activity in your process. This includes all exceptions, deviations from the norm, skipped steps, reworks, etc.

You can react to changing processes and find out if your target model is actually what your process should look like or if there are better ways.

Since the results are available faster, you can also react better to natural changes in the process.


With most processes happening digitally, it can be very hard to see how and where work is done. In the old days of huge piles of paper that moved from one desk to the other for different steps, things were easier. Process Mining makes visible what is hidden. It shows the movement of those ‘virtual stacks of paper’.

Process Mining turns a hit-or-miss guessing game into a fast, fact-based and on point picture of your actual process and allows you to utilize this picture in many ways.


Aside from the advantages over typical optimization procedures, Process Mining also boosts your competitiveness and puts you at the front of the digital transformation race.

Fact-based approach

Process Mining is based on facts, not gut-feeling. The main advantage of applying Process Mining tools in your business is the ability to depict what is actually happening and to pinpoint exactly what needs to be improved and what has the highest priority.

Continuous optimization

Because it’s fast and easy to receive results from Process Mining, it is also much easier to react to changes in the business world. It is also much easier to assign priorities and develop a comprehensive, pro-active and sustainable but also adaptable optimization strategy.

Complete transparency & maximum visibility

You get the entire picture of your process. You may find that one of the exceptions in your as-is process is actually better than your ideal process model. You may also find that you need to deploy changes to the whole process or just too very specific stages. Whatever you find out, you gain the insights you need to develop the best optimization strategy.

Continuous monitoring

This is not a one-time solution. You can monitor KPIs, see how your optimization measures are impacting your process performance, adapt your strategy to outside changes and stay on track while optimizing your business.

Empower your employees

Successful companies are the sum of excellent processes – and the people who work in them. With their commitment and experience, they contribute to growth and innovation every day. With Process Mining, you can use this valuable wealth of expertise to make processes better where they are happening.

You stay informed about your actual process performance, can react to problems and changes before they become huge obstacles, maintain sustainable and successful optimization strategies, and base your decision on facts. Everyone can understand and contribute to optimization measures as a process expert to ensure the strategy is working out in the long run.

Who can use Process Mining?

Process Mining is applied in different areas by different people for different purposes. The tools of the 2nd generation can work with millions of data points so as long as the basic event log requirements are met, there is no limit to the process you can explore. However, there are still common application areas and user types, as well as typical industries that already leverage Process Mining.

Business Areas

Depending on the area you’re workin in, Process Mining can be used from your employees in-house and from outside service-providers.


  • Process Managers
  • Process Improvement Teams
  • IT Departments
  • Data Science Teams


  • Auditors
  • Consultants

User Types

With modern Process Mining software, you don’t have to be a tech-wizard to achieve results. Although there are a lot of tech-related user types, even end users with no coding experience can easily use the tools. In general, the people interacting with Process Mining applications are:


View, work and interact with existing analysis. They work on the report and visuals levels

Process Analysts

Create and configure their own analysis. They work on the report and visuals levels.

Data Scientists

Model, create and integrate data. They work on data levels, making sure the data is available in the right form, and processed and imported correctly.


Care for administration and infrastrucutre. They manage the IT infrastrucure in which Process Mining tools are embedded.

Application areas

The following list includes just some examples of industry sectors where Process Mining is already used:

  • Manufacturing
  • Services
  • Governmental institutions
  • Healthcare
  • Consumer Goods
  • Telecommunications
  • Audit & Banking
  • Financial
  • Educational/Research

What do you need for Process Mining?


You need Process Mining software to start. We have our own free version. It is very user-friendly because it does a lot of the data-preprocessing, loading, and transformation for you. ;)

Data/Event Log

You need data to analyze. Usually, this is stored in your IT system and you shouldn’t have to worry about it.

Process Mining uses data in a so-called event log. This means databases that store the following information: CaseID, Timestamp, Activity name.

Let’s go back to our example of the pizza delivery service. A typical process would look like this:

Receive order → preheat oven → prepare dough → spread sauce on dough → add toppings → bake pizza → put pizza into box → deliver


A case is one completed route through your process. So, for example, one completed pizza delivery. In our example every order is a new case and needs a new CaseID so that the individual process steps can be linked to a specific case.
For example Customer A orders a pepperoni pizza – that’s one case. Customer B orders a cheese pizza, a pepperoni pizza and a pizza with cheese and pineapple – that’s also one case but it has way more steps because you have to make a total of three pizzas.


When did a process step happen? A timestamp either tells you when a process started, when it ended, or you have two timestamps and include start and end time. The version with two timestamps is obviously the most precise.

When did you put the pizza in the oven? That’s the start timestamp for ‘Bake pizza’. When did you take it out of the oven? That’s your end timestamp. When you don’t have an end timestamp you wouldn’t know how much time was wasted between taking the pizza out of the oven and putting it in a box. The process step ‘bake pizza’ would last until the beginning of the process step ‘put pizza in box’.


What was done? This is the descriptor of your process steps. Activity names are usually short and on point. Examples are ‘Create PO’, ‘Send Invoice’, etc.

In our example of the pizza place activity names would be ‘preheat oven’, ‘prepare dough’, ‘add toppings’ etc.

You can add more information to your Event Log to get a more detailed analysis. For example, if you have various people baking pizza for you, you could add them to the event log. Or if you have more than one pizza place, that could also be a category. The more categories you add, the more detailed you can go with your analysis. Just keep in mind, that CaseID, Timestamp and Activity Name are mandatory while everything else is optional. Otherwise you have complete freedom in the process you want to analyze.

We’re getting into more detail about the goals and steps of Process Mining in part two of this series.

If you have any questions or want to learn more about Process Mining, try out our demo version, contact us, get the free visual, or just contact us. We are happy to help you, answer your questions and tell you more about the mission of the Process Analytics Factory (PAF).

E-Book Process Mining 101

This e-book is a comprehensive guide to Process Mining in Power BI. Suited for newbies and veterans alike.

PAFnow Process Mining E-Book