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California-based Tech Company
Optimizes Hiring with JD Matching API
User Details
- A well-established technology company with over 1,500 employees, based in San Francisco, California.
- With a human resource department, consisting of 10+ dedicated professionals, from interns, and assistants to managerial level, the company is known for its dynamic work culture and collaborative environment.
Problem Statement
The company’s internal work environment is highly dynamic, with consistent hiring and onboarding of both permanent and contractual employees. This renders the HR department crucial, and they face multiple challenges during the recruitment process:
High Volume of Job Applications
The HR dept. received an average of 5,000 applications per month for various job postings, overwhelming the HR team and leading to obvious delays in processing.
Time-Consuming JD Matching
With the best talent acquisition experts in hand too, manually matching job descriptions with resumes took an average of 15 minutes per resume, resulting in over 1,250 hours of manual work each month.
Inconsistent Resume Parsing
Diverse resume formats caused hurdles in extracting key information (Name, work profile, experience, education, skills, and 15 more parameters), leading to errors and missed opportunities to identify suitable candidates.
Integration Issues
The existing Human Resource Management System, HRMS (Workday) was not effectively integrated with hiring platforms like Monster and Naukri, causing a lag in data synchronization across the system and increased administrative workload.
Looping In “HireLakeAI”
One of the company’s acquisition interns discovered a significant boost in processing speed and accuracy after trying HireLakeAI’s free trial. Based on this success, the company opted for the premium plan, which includes enhanced features like advanced analytics for resume parsing and JD matching.
AI-Based JD Matching
With HireLakeAI’s advanced AI algorithms, the time to match each resume went from 15 minutes to under 60 seconds. The tool automatically screened and shortlisted candidates based on the specific criteria outlined in the job descriptions.
AI Resume Parsing
HireLakeAI’s resume parsing feature accurately extracted relevant information from various resume formats in seconds. This ensured consistency and completeness for further processing. With not just “keyword-based parsing”, HireLakeAI scanned the entire resume to extract valuable insights for a complete understanding of each candidate.
Seamless Integration
Embedded HireLakeAI’s API with Workday, facilitating real-time data flow between the HRMS and hiring platforms like Monster and Naukri. This integration scrapped the manual data entry part, reduced errors, and ensured up-to-date candidate information across all platforms.
User Impact
The HR team saved over approx. 1,000 hours per month, translating to a cost saving of approximately $21,000 per month in HR operational costs.
The accuracy of matching candidates to job descriptions improved significantly, reducing mismatches by 39% and enhancing the quality of hires.
The HR team’s productivity increased, allowing them to focus on strategic initiatives such as talent development and employee engagement.
By reducing the need for temporary hiring staff and improving processing efficiency, the company saved an estimated $80,000 annually.
The response time to applicants was halved, from an average of 10 days to just 4-5 days, significantly enhancing the candidate experience and employer brand.
All-in-all, by integrating HireLakeAI into their Workday HR system, they dramatically sped up hiring, reduced manual errors, and saved money.
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