Digital Twin Workflow Allocation for Adaptive Intelligence Matching
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Solution Overview
Problem
Organizations face challenges in aligning their workforce strategy with business priorities, improving productivity and process optimization, retaining valuable employees, and enhancing employee experiences, exacerbated by rapid market changes and remote/hybrid work models, with existing solutions lacking integration and real-time responsiveness.
Innovation Solution
A processor determines an intelligent workflow with digital twin simulation to allocate specific intelligences to workflow steps, iteratively optimizing the workflow based on resource performance in a physical environment, using digital twin simulation and real-world monitoring to enhance alignment and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional business management approaches are used, then organizational structure and processes remain stable, but they cannot keep pace with rapid market changes and disruptions
Solution Approach 1:
The patent implements dynamic workflow management where workflows are not static but can be continuously adjusted and optimized in real-time based on performance data. The system allows for dynamic reconfiguration of workflow steps, resource allocation, and process parameters to adapt to changing market conditions while maintaining manageable complexity through automated control.
Solution Approach 2:
The system incorporates continuous feedback loops that monitor workflow performance, resource utilization, and outcome metrics. This feedback is used to automatically adjust and optimize workflows, enabling the organization to adapt to market changes systematically rather than through complex manual restructuring.
2Productivity
If standalone HR software and periodic skills assessments are implemented, then some HR functions are addressed, but integration and real-time responsiveness are lacking
Solution Approach 1:
The patent merges previously separate HR functions (skills assessment, workflow management, resource allocation) into an integrated intelligent workflow system. This consolidation improves productivity by enabling real-time data sharing and coordination across functions while actually reducing overall system complexity through unified management compared to multiple standalone systems.
Solution Approach 2:
The intelligent workflow system serves multiple functions simultaneously: it performs skills assessment, manages workflow execution, allocates resources, and optimizes processes. This multi-functionality improves productivity by eliminating silos between HR functions while managing complexity through a single versatile platform.
3Adaptability or versatility
If digital transformation is implemented comprehensively, then talent and business process management capabilities are enhanced, but implementation complexity and resource requirements increase
Solution Approach 1:
The system incorporates self-service capabilities where workflows automatically adjust and optimize themselves based on embedded rules and algorithms. This reduces implementation complexity by eliminating the need for complex manual configuration and ongoing manual management, while still achieving real-time responsiveness through automated decision-making.
Solution Approach 2:
The patent implements digital transformation by changing key parameters from static to dynamic, enabling real-time adjustment of workflow parameters, resource allocation, and performance metrics. This approach achieves real-time responsiveness through parameter optimization rather than through complex structural changes, simplifying implementation.
4Productivity
If workflows are optimized for specific skills and competencies, then employee strengths are utilized better, but flexibility to adapt to changing business priorities is reduced
Solution Approach 1:
The system dynamically adjusts workflow assignments based on real-time assessment of employee skills, current workload, and changing business priorities. This dynamic approach maintains workflow flexibility while optimizing for employee strengths, as the system can rapidly reconfigure assignments without rigid structural constraints.
Data Source
AI summary
According to a technique of designing an intelligent workflow, a processor determines an intelligent workflow including a plurality of workflow steps to be performed. The processor performs digital twin simulation of performance of the intelligent workflow in a physical production environment. The processor determines, based on the digital twin simulation, at least one type of intelligence among a plurality of types of intelligences to be allocated to each of multiple of the plurality of workflow steps. The processor determines multiple types of intelligences for the plurality of workflow steps. The processor allocates and deploys, in the physical production environment, production resources possessing the determined types of intelligences. The processor thereafter iteratively optimizes the intelligent workflow based on observation of execution of the intelligent workflow by the deployed performance resources in the physical production environment.