Dual-Cycle Task Management Using Process Mining Across Departments
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Solution Overview
Problem
Existing digital deployments in enterprises are fragmented, failing to effectively enable digital empowerment, overlook system processes for achieving enterprise objectives, and neglect data utilization, leading to inefficiencies and resource wastage, with traditional methods requiring significant manpower and time, and lacking holistic data integration.
Innovation Solution
A digital dual-cycle task management system employing process mining algorithms and automated analysis to optimize business processes, visualize sub-goal business processes, and integrate data across departments, utilizing a CATAC cycle model for targeted resource allocation and task assignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional business process sorting methods are used, then manual analysis can be performed, but it requires massive investment of manpower and time, consuming significant enterprise resources
Solution Approach 1:
The patent replaces manual mechanical process sorting with automated process mining technology. The system automatically extracts process information from execution logs, reconstructs business processes, and generates process models without human intervention, thereby eliminating the need for massive manpower and time investment while significantly improving sorting efficiency
Solution Approach 2:
The process mining system performs self-service by automatically analyzing execution logs, identifying process patterns, and generating optimized process models. The system serves itself by extracting insights from data without requiring external manual analysis, reducing resource consumption while maintaining high productivity
2Reliability
If traditional analytical methods are used, then data can be analyzed, but data from different business departments exists independently, lacking integration and sharing
Solution Approach 1:
The patent merges data from different business departments by using process mining to extract and integrate execution logs across the entire enterprise. The system consolidates scattered data into unified process models that show cross-departmental flow, enabling comprehensive analysis that improves reliability while recovering lost data integration
Solution Approach 2:
The process mining platform provides universal functionality by serving multiple business departments simultaneously. It analyzes processes across different departments through a single unified system, enabling shared insights and integrated decision-making that enhances analysis reliability while eliminating data silos
3Adaptability or versatility
If traditional digital deployments are implemented, then digital systems can be deployed, but they are often fragmented, failing to effectively enable digital empowerment
Solution Approach 1:
The patent applies segmentation by dividing the digital transformation into modular components: data collection, process mining, model generation, and optimization. This structured segmentation allows the system to handle complex digital empowerment tasks through manageable segments, reducing overall system complexity while maintaining high adaptability
Solution Approach 2:
The system implements feedback mechanisms that continuously monitor process execution, compare actual performance against optimized models, and automatically adjust processes. This feedback loop enables the system to adapt to changing conditions while maintaining coherence, effectively enabling digital empowerment without increasing fragmentation
4Measurement precision
If comprehensive process sorting is performed, then all aspects can be covered, but it requires massive investment of manpower and time
Solution Approach 1:
The patent replaces time-consuming manual process sorting with automated process mining algorithms that rapidly analyze execution logs and generate comprehensive process models. This substitution achieves high measurement precision across all process aspects while reducing time consumption from months to minutes
Data Source
AI summary
The digital dual-cycle task management system for enterprise operations, comprising a process sorting module, a digital remodeling module, and an empowering operation module. The scheme can establish a dual-cycle task management system, taking the strategic goals of enterprises as the starting point, and combining the status of digital operation management of various enterprises to make targeted resource investments and improvements, thereby achieving optimal resource allocation; the scheme employs process mining algorithms to comprehensively sort and optimize business processes, breaks down corporate strategic goals into different business areas to achieve the visualization of sub-goal business processes, thereby enhancing the operational efficiency of enterprises and reducing costs; the scheme utilizes automated analysis to finely manage data generated by process operations, clarifies the behavioral trajectories, waste, inefficiencies, and problem points in different business departments through data support, thereby enabling targeted training and assisting personnel in enhancing their effectiveness.