Frontend Process Mining for UI Bottleneck Detection
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Solution Overview
Problem
Existing process mining technologies are limited in identifying issues within user interface (UI) interactions and interrelationships between UIs, as they primarily operate on server-side data and do not effectively analyze frontend user interactions, leading to inefficiencies and resource wastage.
Innovation Solution
Frontend process mining systems that capture and analyze user interaction data from client devices, including mouse clicks and keystrokes, to identify bottlenecks and interrelationships between UIs, generating reports on data re-entry rates and UI performance, thereby improving business process analysis and reducing computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If process mining operates only on server-side data, then data processing is simplified, but UI interaction analysis capability is lost
Solution Approach 1:
The patent segments the data collection process into client-side components (JavaScript code that captures mouse clicks, keystrokes, and UI interactions) and server-side components (process mining analysis). This segmentation allows precise UI interaction capture at the source while keeping server processing focused on analyzing the captured event data, resolving the contradiction between analysis capability and processing complexity.
2Loss of information
If user interactions are tracked in isolation, then data collection is simple, but process interrelationship analysis is limited
Solution Approach 1:
The patent merges isolated user interaction events with process instance data by correlating UI events with backend process logs through process instance identifiers. This combination enables analysis of interrelationships between UI interactions and business processes while maintaining efficient data collection through automated event capturing and systematic data structure organization.
3Measurement precision
If frontend process mining is implemented, then UI problem identification is enhanced, but data collection overhead increases
Solution Approach 1:
The patent implements preliminary action by pre-instrumenting the UI with JavaScript code that automatically captures interaction events. This preliminary setup enables precise UI problem identification through continuous event monitoring without adding significant overhead during actual user interactions, as the tracking infrastructure is already in place and operates passively.
Data Source
AI summary
An application server provides an application or set of applications to one or more client devices. One or more users of the client devices interact with the applications to perform a business process. Data is stored on one or more of the client devices that tracks user interactions with the application. The data is transmitted from the client devices to the application server for analysis. Data from multiple client devices is correlated to enable analysis of a complex business process. As a result of the analysis, bottlenecks may be identified based on a particular process step taking a long time to complete or receiving repeated re-entry of data. The solution is automated and scalable, allowing for analysis of an entire business process landscape.