Machine Intelligence for Predicted Employee Targeting
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Solution Overview
Problem
Recruiters face challenges in finding candidates that match job descriptions and are interested in changing jobs in a timely manner, as existing methods are slow and inefficient, often resulting in unsuitable candidate selection.
Innovation Solution
A computer system employing machine intelligence to parse employee data against job change interest models, calculating a job change interest score to identify predicted employees and deliver targeted job messaging, thereby improving the efficiency of recruiting message delivery to interested candidates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If recruiters use traditional methods (calling employees from websites or company directories), then they can find candidates matching job descriptions, but the process is slow and inefficient
Solution Approach 1:
The system performs preliminary actions by pre-identifying and storing potential candidate profiles in a predicted employee cache before actual recruiting needs arise. Machine intelligence applications continuously analyze employee data to predict job change interest and prepare matched profiles in advance, so when a job opening occurs, recruiters immediately have pre-sorted candidate lists ready for contact
Solution Approach 2:
The patent replaces the manual mechanical recruiting process (recruiters manually searching websites, attending conferences, and calling candidates) with an automated machine intelligence system that uses algorithms to parse employee data, calculate job change interest scores, and automatically deliver targeted job messages to predicted employees, eliminating time-consuming manual efforts
2Reliability
If recruiters contact potential candidates from files, then they can fill positions, but many candidates are not interested in job changes or are not good fits
Solution Approach 1:
The system introduces a new parameter - job change interest score - calculated by machine intelligence applications that analyze multiple data points about each employee. This parameter transformation allows the system to filter and rank candidates not just by skill matching but by predicted interest in job changes, delivering targeted messages only to those with high interest scores, thereby improving both suitability and efficiency
Solution Approach 2:
The system implements feedback mechanisms where machine intelligence applications continuously monitor and update predicted employee profiles based on new data, refining job change interest predictions over time. This feedback loop ensures that the candidate matching becomes increasingly accurate, improving reliability of candidate suitability while maintaining high recruiting speed
Data Source
AI summary
A method, computer system, and computer program product for on-demand job messaging to predicted employees. A machine intelligence application compares data for an employee to a job change interest model. Responsive to comparing the data for the employee to the job change interest model, the machine intelligence application determines whether the employee is a predicted employee. The predicted employee enables improved targeting of job messaging by a job messaging application in a computer system.