Person-Oriented Workflow Allocation from Central Task Pools
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Solution Overview
Problem
Existing workflow management systems are task/queue oriented, leading to inefficiencies in task distribution, prioritization, and completion, which can result in missed customer commitments and deadlines.
Innovation Solution
A person-oriented workflow management system that holds all tasks in a central work pool and distributes them based on user profiles and task definitions, allowing workers to request tasks that match their skills and availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If tasks are distributed manually based on manager's memory and judgment, then task allocation can be flexible, but the system becomes inefficient and time-consuming
Solution Approach 1:
The system enables workers to autonomously request tasks from the work pool based on their own availability and skills, eliminating the need for manual task assignment by managers. Workers self-manage their workload by requesting tasks when they are ready to work, which automates the task distribution process and frees managers from time-consuming manual allocation.
Solution Approach 2:
The system pre-establishes a centralized work pool containing all tasks before they are assigned to workers. Tasks are prepared and organized in advance with defined characteristics, and workers can request from this pre-prepared pool, eliminating the need for real-time manual task creation and distribution decisions.
2Reliability
If reactive monitoring systems alert managers when tasks sit in queues too long, then task completion can be monitored, but customer commitments and deadlines may still be missed
Solution Approach 1:
The system proactively prevents task delays by having workers request tasks before they are needed, rather than waiting for reactive alerts. Tasks are distributed in advance based on worker availability and task characteristics, ensuring that work is already assigned and in progress before deadlines approach, eliminating the need for reactive monitoring and redistribution.
Solution Approach 2:
The system continuously monitors worker availability and task status, providing real-time feedback that enables dynamic task redistribution. When workers complete tasks or become available, the system automatically identifies and assigns new tasks from the work pool, ensuring continuous workflow optimization without manual intervention.
3Productivity
If tasks are reassigned to workers with immediate availability, then task completion speed increases, but the newly assigned worker's own queue may be delayed
Solution Approach 1:
The system dynamically adjusts task assignments based on real-time worker availability and workload status. When a worker becomes available, the system evaluates the entire work pool and worker queue states, making intelligent decisions about task redistribution that balance immediate completion needs with overall workflow optimization, preventing queue delays for other workers.
Solution Approach 2:
The system changes task assignment parameters dynamically, considering worker skills, availability, current workload, and task characteristics. Rather than simple round-robin or first-come-first-served allocation, the system adjusts assignment criteria based on multiple variables to optimize both immediate task completion and overall system efficiency.
Data Source
AI summary
A system includes a data storage medium to store a plurality of user profiles and at least one work project, each of the work project including at least one task that is characterized by a task definition, and a processor to receive a request for work from a user, the processor including a task management engine to allocate the at least one task to the user based on the user profile and the task definition in response to the request for work.