"Towards Data-Driven Process Modeling" is a series of blog posts with the aim of looking into data-driven approaches in the process modeling space that are transforming the practice. This post is the second in the series, building upon the initial piece on the process modeling lifecycle, which also covers the explanation of various data types that can be leveraged for modeling.
In today's digital age, data is serving as the cornerstone for informed decision-making across industries. Process management is not an exception and leveraging data can unveil invaluable insights into the organizational workflows, shedding light on optimization opportunities. Process modeling stands as one of the core phases of every BPM initiative, and leveraging data whenever possible is key to expediting this process. This approach enables process professionals such as owners, modelers, and analysts to focus more on the details and fine-tuning, rather than starting the modeling process from scratch. With the advent of process mining data, organizations now have access to a wealth of information that can revolutionize their approach to process modeling.
For many years, different algorithms have been designed to mine BPMN models, yet they often come with challenges such as accuracy, completeness, and speed. Split Miner is a groundbreaking algorithm designed to discover process models from event logs in process mining with elevated accuracy and efficiency. with SAP Signavio Process Intelligence incorporating Split Miner (check the release communication), organizations can harness the potential of their process mining data for modeling like never before.
Why discover BPMN models with Split Miner?
Split Miner represents a paradigm shift in process model discovery methodology. Unlike previous algorithms, such as various iterations of the inductive miner, Split Miner excels in accuracy, completeness, and speed. Its innovative approach to filter the directly-follows graph induced by event logs and identify split gateways ensures unparalleled accuracy in process discovery. By striking a balance between fitness, precision, and generalization, Split Miner produces simple process models that accurately capture concurrency and causal relations.
Moreover, Split Miner's efficiency streamlines the process of deriving BPMN models from process mining data, significantly reducing time-to-insight. By automating the discovery of split gateways and concurrency relations, Split Miner empowers organizations to focus their efforts on analysis and optimization, rather than laborious manual model construction.
Three key benefits of this updated algorithm in SAP Signavio Process Intelligence are:
- Enhanced Accuracy: Split Miner employs a novel approach to filter the directly-follows graph induced by an event log, ensuring unparalleled accuracy in process discovery.
- Increased Efficiency: With Split Miner, organizations can expedite the process of deriving BPMN models from their process mining data, significantly reducing time-to-insight. By automating the discovery of split gateways and concurrency relations, Split Miner streamlines the process discovery phase, empowering process professionals to focus their efforts on analysis and optimization.
- Improved Collaboration: Split Miner's accuracy and speed enhance collaboration across departments, like IT and business domains. By generating accurate, easy-to-understand business process models, Split Miner enables focus on collaboration over early-stage model fixing.
How to generate BPMN models in SAP Signavio Process Intelligence?
In SAP Signavio Process Intelligence, leveraging Split Miner to extract BPMN models from variant explorer is a straightforward process. Follow these steps to export variants as a BPMN model: Select Variants: Begin by selecting one or more variants from the panel on the right within the variant explorer.
- Select Variants: Begin by selecting one or more variants from the panel on the right within the variant explorer component.
- Generate BPMN: Once your desired variants are selected, choose "Generate BPMN" to create a BPMN 2.0-compliant model.
- Edit in Process Manager: The SAP Signavio Process Manager editor will automatically open, displaying the generated process model of the selected variant(s).
- Customize: Here, you have the flexibility to customize the process model as needed. You can name the process model, make adjustments, and refine details to ensure accuracy and alignment with organizational requirements.
- Save Changes: Once satisfied with the modifications, simply save the process model within the Process Manager editor.
By following these simple steps, users can seamlessly harness the power of process model discovery by means of mining BPMN models within SAP Signavio Process Intelligence as well as its integration with SAP Signavio Process Manager editor in order to export variants as BPMN models, fine-tune, and store them in the process repository of SAP Signavio.
Example BPMN model generated in SAP Signavio Process Intelligence
Summary and Outlook:
In conclusion, the introduction of Split Miner within SAP Signavio Process Intelligence signifies a transformative leap in process model discovery methodology. By integrating data-driven modeling, SAP Signavio Process Intelligence empowers organizations to unlock the full potential of their process mining data, revolutionizing the way they approach process modeling (also look at how modeling and mining complement each other). One of the core use cases is what SAP Signavio provides under the umbrella of the Plug and Gain approach with which you can quickly analyze your SAP processes and generate a BPMN model out of the desired variants for further investigations such as comparison with reference models or leveraging it for further analysis with process simulation.
As we continue to delve deeper into the realm of data-driven modeling, the possibilities for process optimization and business excellence are endless. By leveraging insights from process mining data, organizations can gain a competitive edge, drive innovation, and achieve operational excellence. Stay tuned for further insights and innovations as we continue this exciting journey towards data-driven process modeling.
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