Process Mining Ambiguity Resolution via Participant Feedback
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Solution Overview
Problem
Process mining tools often fail to capture all elements of a process, leading to low-fidelity process visualizations that can affect the accuracy of results generated by these tools.
Innovation Solution
A computer-implemented method that captures an active process using event log files, identifies ambiguities, and utilizes participant feedback from relevant subject matter experts to transform the process and generate a new workflow, thereby enhancing and accelerating process times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If process mining tools automatically discover processes from event logs, then automation is improved, but measurement precision deteriorates due to missed process elements
Solution Approach 1:
The system sends polls to relevant participants to resolve ambiguities in the event log, creating a feedback loop where human expertise corrects automated discoveries. Participants provide feedback on ambiguous process elements, which is then used to refine the process model and improve visualization fidelity while maintaining automation.
Solution Approach 2:
Relevant participants act as intermediaries between the automated process mining tool and the actual process reality. They resolve ambiguities that the automated tool cannot detect, bridging the gap between automated discovery and accurate process representation.
2Productivity
If process mining tools use automated discovery from event logs, then productivity is improved, but reliability deteriorates due to missing process elements
Solution Approach 1:
The system implements a feedback mechanism where participants review and correct ambiguous process elements discovered by the automated tool. This feedback ensures that the final process model is both efficient (from automated discovery) and reliable (from human verification).
Solution Approach 2:
The system performs preliminary automated process discovery to identify ambiguities, then proactively engages participants to resolve these ambiguities before finalizing the process model. This preliminary action maintains productivity while ensuring reliability through advance human review.
3Measurement precision
If process mining tools capture all process elements with high fidelity, then measurement precision is improved, but device complexity increases
Solution Approach 1:
Instead of making the automated tool overly complex to detect all ambiguities, the system introduces participants as external intermediaries who provide the missing contextual knowledge. This maintains system simplicity while achieving high measurement precision through human expertise.
4Reliability
If process mining tools monitor all process deviations, then reliability is improved, but loss of time increases due to comprehensive monitoring
Solution Approach 1:
The system uses feedback from participants to selectively focus monitoring efforts on ambiguous or critical process elements rather than uniformly monitoring all deviations. This reduces the time required for comprehensive monitoring while maintaining high reliability through targeted human expertise.
Data Source
AI summary
Described is a method for transforming an active process utilizing participant feedback and generating a new workflow for an enhanced and accelerated process includes capturing an active process with a plurality of components based on a plurality of event log files and a plurality of relevant participants of the active process. The method also includes identifying, based on the plurality of event log files, ambiguity associated with at least one component of the active process. The method also includes sending a poll to at least a portion of relevant participants from the plurality of relevant participants, where the poll identifies the ambiguity and includes a request to resolve the ambiguity. The method also includes receiving feedback from the portion of relevant participants and generating a new process by transforming the active process based on the feedback from the portion of relevant participants.