Intelligent Presence Server Expert Availability
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Solution Overview
Problem
Existing systems lack an efficient method to determine the real-time availability of subject matter experts for timely communication in business applications, relying on human reasoning which is ineffective when integrated with automated workflows.
Innovation Solution
An intelligent presence system that computes availability probabilities for subject matter experts based on historical communication patterns and real-time presence data, identifying the most accessible expert for communication requests through a communication pattern analysis module and processing engine.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If human reasoning is used to determine expert availability, then flexibility in decision-making is maintained, but effectiveness is insufficient when integrated with automated workflows
Solution Approach 1:
The patent replaces manual human reasoning with an automated computer-based system that uses algorithms to determine expert availability. The system processes presence state data and historical communication patterns automatically to select experts, eliminating the need for human intervention while maintaining effectiveness in automated workflows.
Solution Approach 2:
The system enables self-service by automatically determining expert availability and selecting appropriate experts without requiring manual input. The automated workflow independently processes availability data and makes selections, allowing the system to serve itself rather than requiring continuous human oversight.
2Loss of time
If subject matter experts are contacted without availability assessment, then communication requests are issued promptly, but response time increases due to expert unavailability
Solution Approach 1:
The system performs preliminary assessment of expert availability before issuing communication requests. By evaluating presence state data and historical patterns in advance, the system identifies the most likely available experts beforehand, ensuring that when communication requests are issued, the experts are actually available to respond promptly.
Solution Approach 2:
The system incorporates feedback from historical communication patterns and actual expert responses into its availability assessment algorithm. This feedback loop continuously refines the availability predictions, improving the accuracy of expert selection over time and ensuring higher reliability of responses.
3Quantity of substance
If broadcast communication requests are issued to all experts, then all experts are notified of the request, but time is wasted contacting unavailable experts
Solution Approach 1:
Instead of treating all experts uniformly, the system applies local quality by assessing and treating each expert's availability individually. The system evaluates each expert's presence state and historical patterns to determine their specific availability, then tailors communication strategies accordingly, contacting only those likely to be available.
Solution Approach 2:
The system segments the expert population into distinct categories based on availability status. By dividing experts into available and unavailable groups based on their presence state data and historical patterns, the system can selectively contact only the relevant segment (available experts) rather than broadcasting to everyone.
Data Source
AI summary
A method for directing inquiries to available subject matter experts includes storing an expert database in memory and defining presence states to describe present attributes of each subject matter expert with respect to a number of resource elements. Inquiries are directed to the experts, and response histograms are populated based on whether a response was obtained in a given presence state. The response histograms describe or define a response probability for each subject matter expert, as a function of the corresponding present attributes for each of the resource elements.