Low-Code Process Mining in Practice

Process mining uses data mining techniques to analyse event logs to identify trends and patterns to improve the understanding of business processes, optimize and make them more efficient.

Organizations are becoming more aware of the value of their data, which makes process mining very useful for detecting and diagnosing any irregularities in their processes.

Organizations can use process mining to discover new automations and detect deviations in their running processes, but low-code tools are needed to make the necessary adjustments with the agility and efficiency required in today’s business environment.


Process mining facilitates the acquisition of control over data, and its use to draw conclusions that allow us to make decisions based on occurrences rather than intuition.

Companies need to look at their past and analyse their mistakes to improve results. It is not possible to improve the overall performance of a business when the deficiencies and missed opportunities are not analysed nor is it possible to make predictions about the future without looking at the trends and patterns reflected in the historical records.

Process mining can help organizations to:

  • Detect problems in their workflow
  • Improve operations.
  • Discover bottlenecks.
  • Reduce time in the execution of processes, prioritizing the most profitable actions.
  • Discover new processes.
  • Increase customer satisfaction.
  • Define the automation of our processes.

Processes play an essential role in a company’s path to success. As the company grows, new elements come into play that may slip out of control. For this reason, it is very important that our data always provides a real view of the organization’s state.


Most organizations believe that they have good control over the execution of their processes, and that everyone always knows what to do. In fact, this is not always the case. Generally, there are deviations between the ideal process drawn up by management and the way processes are actually executed.

It is true that, automating a process with a low-code BPM tool can help to standardize the execution of process activities, but true control can only be obtained by analyzing the data.

The information alone is not enough! It must be used to measure the efficiency of the changes.

Many companies use different technologies to record their activities (ERP, CRM, BPM, …). And each one of them generates large amounts of data, but unfortunately on many occasions this information is isolated. This makes it necessary to have a tool that has connectors that make it possible to carry out the integrations in a simple way, and thus we can access a consistent depiction of events.

The use of data mining is only effective if we have access to information from all applications in our system and can perform our processes to identify possible improvements and bottlenecks.

The days of visceral decisions are over, and nowadays it is not possible to make important decisions, or to drive organizational change, without having data to support the actions.


Process mining focuses on collecting data from event records by identifying what happened at a given time and provides a workflow for analysing and detecting process loops, inefficiencies, bottlenecks, and possible improvements.

The value of process mining is its ability to cut through the noise.

However, if we are not able to implement it quickly and effectively the information is of no value. In order to do this, the best option is a low-code tool that allows us to implement new solutions in a minimal amount of time, guaranteeing the integration of all system components, data control and process monitoring.

Low code is the tool that allows us to implement the strategies that data mining discovers, and to reach its objectives, ensuring end-to-end process.

Tomás Martí