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Process Mining vs Process Modeling in '24: 4 Best Practices

Process Mining vs Process Modeling in '24: 4 Best PracticesProcess Mining vs Process Modeling in '24: 4 Best Practices

Businesses use process mining and process modeling to discover, measure and improve their processes. The Google Trend graph above shows how process mining has been replacing process modeling in Google Search since 2008. Business leaders and analysts, on the other hand, may not even be aware of how these two tools differ. As a result, it becomes difficult to decide which tools to chose while analyzing business processes.

In this light, this research compares process mining with process modeling and provides recommendations to help business leaders make data-driven decisions when choosing the right tool that fits their business needs. 

Process Mining vs Process Modeling

Process modeling and process mining are business process management (BPM) forms.  

Process modeling

Process modeling refers to visualizing business processes and workflows by leveraging event logs data to increase process visibility and understanding, and process improvement.

Process mining

Process mining is the discovery and improvement of business processes and workflows by extracting and analyzing the event log data to identify trends, deviations and errors and to generate and compare models with each other.

Feel free to read on process mining architecture, how process mining leverages machine learning and AI-powered algorithms to discover, visualize and manage business processes.

Process MiningProcess Modeling
Does the solution use AI/ ML?
Applies ML algorithms for automatic extraction, analyzing and modeling the process data
Applies ML algorithms for visualizing the process data
What are the end-goals for the tool?
1. Generates process models, 2. Compares idealized workflows and operations against existing models, 3. Modifies existing models, 4. Simulates potential process changes with a DTO
1. Generates process models
What are the benefits the tool offers?
1. End-to-end understanding of workflow, 2. Enables process improvement, 3. Facilitates automation, 4. Helps assess process performance and model accuracy
1. End-to-end understanding of workflow, 2. Enables process improvement, 3. Facilitates automation

Recommendations for choosing process mining or modeling

1. Process mining as automation enabler

If you go through a digital transformation project, process mining is probably the most useful software for you as an automation enabler.

Both process mining and modeling tools bring visibility to your processes and ease the discovery of automation opportunities. However, process mining tools offer more functionalities than process modeling for automation implementation.

For example, some process mining software can generate a digital twin of an organization to run hypothetical models by implementing changes in processes and measuring the expected ROI. They also allow users to track the entire automation project flow and assess the performance of the automated processes, which is not the case for process modeling software.

Discover how process mining facilitates RPA implementation and digital transformation.

2. Process mining for comparison and contrasts

If you have existing models, for the internal rules or general regulations that you want your processes to comply with, you should start reviewing process mining tools.

Process mining conformance check enables users to compare their existing processes against rules, regulations, existing models, and pre-defined process KPIs, to identify deviations and errors in order to modify and standardize them. Recently, some process mining software have included automated root-cause analysis that have enabled users to determine the main factors behind these issues.

See how process mining enables internal audit and compliance for businesses.

However, you could also pair both process mining and modeling to benefit from them: You generate a reference model in process modeling, and then upload it to process mining software, to compare the reference model against the model discovered from the real-life data.

3. Process modeling for an easy process management

If you want to have accurate and objective process models that are also easy to use, process modeling is the business process management form you should choose.

Process models are helpful to transform abstract workflows into images that use standardized symbols, such as arrows and triangles. Therefore, they are mostly easy to interpret and use for every employee without the help from an expert, explaining the models. 

Typically, process mining tools might require some time for employees to adopt and utilize them fully. In such situations, we recommend to get help from consultants during the initial phases of employing process mining or deploy process mining as a service to benefit from expert help along with other benefits.  

4. Combine process mapping for qualitative aspects

If your business want to understand business processes from both qualitative and quantitative aspect, you can combine process mining or modeling with process mapping.

Both process modeling and process mining offer quantitative and objective process illustrations, because both leverage event logs data to discover process trends. Both tools are capable for several use cases mentioned above. Yet, they both fail to capture and analyze qualitative data. 

There are different methods to capture and discover business processes such as internal workshops and interviews. Process mapping visualizes processes by identifying activities, people, resources and systems involved based on such qualitative data.

Further Reading

If you are interested in process improvement and automation tools such as process mining and modeling, feel free to read more on the subjects:

If you want to use process mining and/or modeling tools for your business processes, feel free to check out our data-driven lists for process modeling and process mining .

And if you need guidance to find the right vendor, let us talk to you:

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Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Hazal Şimşek
Hazal is an industry analyst in AIMultiple. She is experienced in market research, quantitative research and data analytics. She received her master’s degree in Social Sciences from the University of Carlos III of Madrid and her bachelor’s degree in International Relations from Bilkent University.

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