PROCESS MINING: Everything you need to know

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First things first

Process mining is a technique to analyze and monitor processes. In traditional business process management, it is done with process workshops and interviews, which results in an idealized picture of a process. Process mining, however, uses existing data available in corporate information systems and automatically displays the real process.

As a novel technology for business process management (BPM), process mining complements Business Intelligence tools. It allows businesses to get the greatest advantage out of the data they already have and yields fast identification of process deviations and improvements on all levels.

Read more about business value of process mining here.



Make the most of the back-end data

Process mining platforms combine technologies from data analytics, data mining, process analytics and Business Intelligence (BI), resulting in holistic and deep insights into processes. These insights can then be used by data analysts to optimize processes.

The next step is to make these insights available to business users, resulting in a much higher impact on their business. They enable everyone to continuously use the process insights that process mining offers: from high-level managers and executives, to everyone involved in the process.

Process mining provides a full picture of internal and external processes, with the opportunity to further delve into minuscule details.

Empowered by advanced data technology, process mining users identify actual process bottlenecks and risks, discover potential improvements on operational efficiency and costs and even monitors data to optimize and predict future events.




Technology development

As mentioned earlier, process mining is a BPM technique of gathering existing data and transforming it into a visually structured, comprehensive process graph, showcasing the actual process compared to the assumed one.

But this was not always the case. In quite recent times, traditional BPM techniques were still applicable – the process model was drawn by hand and there was no precise data to fill it with. Process creation was really time consuming; a lot of effort was required by business analysts and managers to organize workshops and write down desired processes. Until someone at the Eindhoven University of Technology (TU/e) had a brilliant idea.

As a big fan and professional of data science, professor Wil van der Aalst came up with the idea of combining data analytics and visualization. “What if instead of doing this all by hand, we automatically do it using the existing data?” – thought Wil. Together with his colleagues he focused on process analysis using event data in research – and it worked!

For a long time it stayed unknown in the business world, until it was taken out of academic frames, therefore earning recognition and business value.

Further developing such topics as process intelligence, workflow management and others, Van der Aalst – one of the world’s most-cited data scientists – made a big impact on developing the process mining industry.

As a result, Wil has got many followers – smart minds of Data and Computer Science, who then turned the scientific technology into useful solutions and boosted market growth.

At first there were only tools for technical data analysts that used process mining to do a time-consuming deep process analysis. But the technology grew, hardware got better, and more data was gathered by companies – now the technology has found its demand and appreciation among enterprises.

Companies now get access to the information that other BPM techniques couldn’t provide in the past. There is no longer a need to draw idealistic business processes that skip hundreds of different scenarios. Process mining gives insights into every scenario, every event. Optimizing workflows in a large organization with dozens of processes, activities, duties and timings has never been easier.

Process mining is rapidly crossing the chasm to businesses, being used in a much more practical and continuous fashion, making it virtually effortless for business users to continuously stay on top of their processes. This way process insights are made available to business professionals at an ever-increasing rate.

Process mining today

Process mining software vendors are striving to move the technology forward by constantly suggesting innovative approaches on analytics, data management and process visualization. As a result of such initiatives, the new patent-pending TRACY algorithm was developed by a TUe former student – Robin Mennens during his research project at ProcessGold.

The new layout engine shows processes in such a way that they are easier to understand and allow you to draw conclusions faster.


It’s all about event logs

In order to do process mining, a minimal initial data set is needed – the event log. This event log should contain every step that is performed (the Activity) during the process and stores the moment at which the event happened (the Timestamp), and for which instance of the process (the Case ID).

Using this event log, process mining algorithms generate a process model that shows the process as it really is, not as it is perceived. Other data science methods can then be applied to further enhance this model. The result is then used for process discovery, conformance checking and process enhancement.

Process mining platforms take this process model to the next level, allowing users to dynamically interact with the process and combine these insights with related data. This makes it easy to derive new insights about the process.


Process improvement consists of several parts: identifying the issues and opportunities, modifying the process, and monitoring changes for further optimization. While process mining is an excellent technology for problems identification, Robotic Process Automation is gaining momentum by actually changing processes that are currently being performed manually.

RPA enables bots to take over activities that have high chances to boost process efficiency if automated. Among such activities are repeated, simple, often transactional tasks. Virtual workforce bots have certain advantages: 24/7 availability, precision, high-speed and fewer errors than humans. Besides, they free the human employee’s time up for more complex, creative and strategic tasks.

The union of process mining and RPA has given a start to a new technology trend – Hyperautomation. The combination of various process optimization and automation tools makes it easier for an organization to take full advantage of corporate data and become a self-evolving enterprise.

Want to learn more about RPA? Read on! 

Reinforcing RPA with process mining

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Process mining and RPA forming hyperautomation

Explore hyperautomation


Currently, process mining tools are capable of processing large sets of data, with millions of events. Because process mining is a very generic technique, it can be used on almost any process. The only requirement is that the process data that needs to be tracked, is stored in corporate IT systems, which is usually the case for any digitalized process. Data can be taken from large ERP systems like SAP, MS Dynamics, or Salesforce, but it is also possible to do this with small custom software tools or even your Excel sheets.

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Process Mining is mostly used in, but not limited to, the following industries:


Governmental institutions

Educational and Healthcare


Audit and Banking


Fast-Moving Consumer Goods

and more!



Obviously, by implementing process mining, a company gets several competitive advantages, which allow it to scale-up faster:

  • Fact-based approach. A strong point and the whole sense of starting to think of process mining is its ability to showcase real business processes and allow transparency.
  • Continuous improvement. In a world of constant change, one needs a structural method to improve business processes and keep optimizing them to fit the current situation.
  • Holistic vision. A holistic end-to-end view of your entire process allows for broad strategic changes instead of local optimizations.
  • Continuous monitoring. Keep improving and optimizing your process, steadily transforming your business.
  • Empower everyone. Realize a paradigm shift towards process-oriented thinking. Everyone within the process is involved in optimizing their processes to maximize the impact.

With the technology, process owners are able to react faster and develop plans according to actual data in an earlier stage. Thus, it leads to faster decision-making, based on one single truth – the data. Long discussions and gut feeling estimates are history.

Instead of focusing solely on KPIs, one can question whether they’ve been set correctly and get a clear vision on business performance. As a result of treating the data as a valuable asset, a self-evolving company can take the lead in its independent development.

Less errors – more transparency. Less quessing – more fact-based decisions.

Want to know how Process Mining can help your organization? Talk to us!