What is Process Mining?
What is process mining? And how can it help you gain valuable insights into your processes?
Definition:
Process mining is a data-based technique that is used to analyse and improve business processes. Data is extracted from the event logs, the digital traces of actions and interactions within your process.
Process mining uses special software and algorithms to collect and analyse data about the sequence of activities, decisions and interactions between people and systems within a process. These analyses help to identify inefficiencies, bottlenecks and other areas for improvement in a process. They also provide information about the effectiveness of process changes and interventions.
What are the advantages?
1. Increased visibility:
The visual representation of the process flow makes it easier for everyone involved to better understand the process flows and also helps to identify the need for optimisation.
2. Improved compliance:
By uncovering non-compliant activities and areas for improvement, process mining can help ensure that processes comply with regulatory requirements and internal policies.
3. Increased process efficiency:
Process mining helps to make processes more efficient, for example by recognising bottlenecks and inefficiencies. Identifying areas in business processes that can be optimised not only improves workflows, but ultimately also reduces costs.
4. Better decision-making:
By using process mining, all parties involved gain insights into the actual execution of processes. This creates a new basis for more informed decisions about optimising business processes.
5. Increased agility:
Process mining helps companies to react quickly to changes in their processes or market conditions. This not only increases competitiveness, but also helps to utilise new opportunities more quickly.
These benefits make process mining a valuable tool for companies to gain better insights into their business processes - leading to a better understanding and greater adaptability.
What types of process mining are there?
Discovery :
This type of process mining is used to analyse the actual process flow. Event logs or other data sources are analysed for this purpose.
Conformance:
In this type of process mining, the actual process flow is compared with the intended or ideal process flow in order to identify deviations or violations.
Enhancement:
This type focuses on optimising the process flow. Enhancement process mining identifies areas for process improvement by analysing the actual process flow and highlighting bottlenecks, inefficiencies and other potential for improvement.
Success factors for the use of process mining
We have compiled some proven methods for the use of process mining for you here.
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1. Start with clear goals:
Define specific goals for your process mining initiative. Whether it's to improve efficiency, reduce costs or ensure compliance, clear objectives guide analysis and focus efforts on actionable insights.
2. use high quality data:
Ensure that the data used for process mining is accurate, complete and up-to-date. Poor data quality can lead to misleading results and impair the effectiveness of the analysis.
3. Involve stakeholders at an early stage:
Involve key stakeholders, including process owners, IT and business departments, from the outset. Their input is crucial for understanding the context of the processes and ensures that the results are relevant and realisable.
4. Focus on end-to-end processes:
Analyse entire processes instead of isolated parts to gain a holistic view. This approach helps to identify bottlenecks, inefficiencies and potential for improvement throughout the entire workflow.
5. Iterate and refine:
Process mining is an iterative process. Start with a broad analysis and refine the focus step by step. Monitor and evaluate your processes continuously. This ensures that the processes can be quickly adapted to changing business needs.
6. Use visualisations:
Use visual representations of processes to make complex data more accessible and understandable. Visualisations help to communicate results to stakeholders and promote data-driven decisions.
7. Continuous improvement as a strategy
Integrate process mining into a broader continuous improvement strategy. Use the insights gained to implement changes, monitor their impact and continuously optimise processes.
Follow these simple tips to gain comprehensive insights into your business processes with process mining - and develop a data-supported strategy for the continuous improvement of your processes on this basis.
Glossary terms used
Log of events and activities that take place within a process. Used as a data source for process mining.
Making changes to a process to optimise its performance, efficiency and effectiveness.
Describes the process of analysing the actual flow of a process on the basis of event logs or other data sources.
Analysing and understanding a process flow and the associated data in order to identify opportunities for improvement.
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