Process Mining vs Process Modeling in ‘23: 4 Best Practices for Your Business
You likely have heard about process mining and process modeling as increasingly popular ways to optimize business processes. But what exactly are these techniques, and when should you use process mining versus process modeling to improve workflows in your organization this year?
In this comprehensive guide, I‘ll explain the key differences between process mining and modeling, provide real-world examples, and share four best practices to help you determine the right approach to meet your specific business needs in 2024.
Making Sense of Process Mining and Modeling
Process mining and process modeling are two methods for discovering, analyzing, and improving business processes as part of an overall business process management (BPM) strategy.
Process modeling involves mapping out ideal workflows and processes that your business aims to adopt. It is a manual technique often conducted through process mapping workshops and interviews. The goal is to document optimized “to-be” processes.
Process mining takes a more data-driven approach. It uses algorithms, artificial intelligence (AI), and machine learning to analyze event log data that traces actual processes. Process mining software can compare “as-is” versus idealized processes to identify compliance issues and bottlenecks.
According to McKinsey, adoption of process mining grew at nearly 40% per year over the past decade. However, 77% of organizations using process mining also utilize process modeling techniques. The two approaches are often used together.
Key Differences and Benefits
Below I summarize some of the main differences between process modeling and mining:
| Process Modeling | Process Mining |
|---|---|
| Maps future, ideal state processes | Discovers current “as-is” processes |
| Manual technique using workshops, interviews etc. | Automated analysis of event logs using AI/ML |
| Visual models easy for all to understand | Provides objective data-driven process analytics |
As this comparison shows, process modeling and mining each have their own strengths and benefits for process improvement.
Process modeling lets you clearly visualize intended processes in a way that makes it easy for employees to understand workflows. It is ideal when you need to design new processes from scratch.
Process mining provides data-driven intelligence about the processes that are actually happening based on event logs. It enables you to identify unseen bottlenecks and continuously monitor processes.
Common Use Cases
Based on their respective strengths, process mining and modeling each excel in certain business use cases.
Process Modeling Use Cases
- Documenting processes in a new department or for a new product line
- Diagramming future state processes during process reengineering initiatives
- Visualizing processes to train new employees
- Creating simple overview models for executives
Process Mining Use Cases
- Discovering automation opportunities during digital transformation projects
- Comparing actual processes against internal compliance rules or ISO quality standards
- Pinpointing root causes of known process bottlenecks
- Enabling continuous process monitoring and improvement
As you can see, process modeling tends to be useful in scenarios where ideal process flows need to be defined. Process mining is superior for analysis of actual as-is processes based on data.
4 Best Practices for Your Business
When should your business utilize process modeling or process mining this year? Here are four best practices:
1. Use process mining to enable automation during digital transformation
Process mining provides the detailed visibility into actual processes needed to identify and implement automation opportunities via RPA, workflow automation, or other technologies.
2. Leverage process modeling to map future state processes or document current workflows
If you are redesigning processes or need simple visual models for training, documentation, or executive communication, process modeling is often the better fit.
3. Consider combining process modeling and mining
Start with process modeling to design an ideal workflow, then apply process mining to see where the real process deviates and improve it.
4. Incorporate process mapping workshops to add qualitative data
Supplement process mining or modeling with traditional process mapping techniques to capture insights from employees.
Getting Started Tips
Interested in getting started with process mining or modeling? Here are a few tips:
- Start small – Focus your initial efforts on 1-2 key processes to demonstrate value before expanding.
- Choose the right software – Select tools like Celonis or Signavio for process mining and tools like Bizagi or Tibco for process modeling.
- Involve process experts – Seek input from personnel familiar with the processes you want to improve.
- Obtain leadership buy-in – Gain upfront support from executives and managers to drive adoption.
The Bottom Line
Both process mining and modeling provide visualization and intelligence to help you optimize workflows. Evaluate your specific goals, data environment, and resources to determine the right approach for your needs this year. With the proper application of these techniques, you can gain valuable insights to streamline processes and support strategic objectives in 2024.
