Dynamic Peer Group Selection for Process Benchmarking
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Solution Overview
Problem
Traditional process mining methods provide descriptive analysis of business processes but lack insight into how to improve them, and benchmarking against other processes is hindered by the difficulty in selecting relevant peer groups.
Innovation Solution
A software system that generates custom process diagrams using document data and enables external benchmarking by comparing a target process against a reference process diagram constructed from best-in-class processes, along with a filtering system to select relevant peer groups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If process mining algorithms execute on log data to generate process graphs, then descriptive analysis of business processes is provided, but insight into how to improve processes and comparison with industry peers is lacking
Solution Approach 1:
The patent introduces a peer group selection module as an intermediary component that bridges the gap between process mining analysis and industry benchmarking. This module selects relevant peer organizations and facilitates comparison between target and reference processes, thereby providing improvement insights without requiring complete system redesign.
Solution Approach 2:
The system segments the benchmarking function into separate modules: peer group selection, process diagram generation, and comparison analysis. This segmentation allows the process mining system to maintain its core descriptive analysis capabilities while adding benchmarking functionality through independent, manageable components.
2Loss of information
If peer group selection is enabled for external benchmarking, then actionable insights for process improvement are provided, but difficulty in selecting relevant peers increases system complexity
Solution Approach 1:
The system performs preliminary actions by pre-defining relevant peer selection criteria and pre-processing organizational data to identify potential peers. This preliminary preparation reduces the complexity of real-time peer selection and provides users with guided filtering options rather than requiring them to manually navigate complex selection processes.
Solution Approach 2:
The peer group selection mechanism enables organizations to self-service their own benchmarking needs by allowing them to define their own peer selection criteria and filter organizational data. This self-service approach reduces the need for complex manual intervention and system configuration.
3Loss of information
If process graphs are provided to explain business processes, then understanding of process flow is achieved, but insight into performance relative to industry standards is insufficient
Solution Approach 1:
The system applies local quality by providing detailed process diagrams and analysis for specific target processes while comparing them against selectively chosen peer processes. Rather than attempting to analyze all organizational data uniformly, the system focuses computational resources on the specific process areas most relevant to the user's benchmarking objectives.
Data Source
AI summary
Provided is a system and method for filtering data records via user interaction on a user interface. During the filtering process, the user interface can provide insights into the next filtering step by displaying additional insight on the user interface. In one example, the method may include displaying a user interface comprising interactive controls, receiving a selection of a filtering condition based on input on the user interface, in response to the selection, filtering a plurality of data records based on the selected filtering condition to identify a subset of data records that satisfy the filtering condition from among the plurality of data records, identifying a subset of filtering conditions from among the plurality of filtering conditions that are available for the subset of data records, and displaying an identifier of the subset of data records and identifiers of the subset of filtering conditions on the user interface.