Keeping the theme of features to help you in this candidate tight market as we ride the wave of the great resignation and record high employment rates - We’re looking at 2 of our features that utilise SAP Machine learning with the goal of saving you time in the recruitment process and helping you find the best quality. The two features are Resume Ranking and Find Best Matching Candidates.
Resume Ranking – uses machine learning to analyse job posting details with job seekers resume to provide a ranking of resumes’ submitted.
Find Best Matching Candidates – uses machine learning to analyse a reference resume – and find other’s which are the closest match based on skills, job title, industry, education and years of experience
Potential Candidates (which you’ll recall was the last edition and is in the trail below)– uses sql search of the application to highlight workers ending soon, job seekers etc who share common traits of the job posting – such as job code, currency, distribution list, within the past 40 days
Resume Ranking
What does it do: Resume Ranking parses through the resumes attached to each Job Seeker submitted towards a specific Job Posting and the algorithm assigns a resume score based on closeness to keywords provided in the Job Posting Description, ranking the available candidates in order of out output of the algorithm.
Why should it be of interest:
Effort to implement –easy, service request to enable the change to company config, then addition to user role permission
Effort to test – super easy
Benefits to business – improve quality of external worker hired, automate (assist) processes to reduce cycle time, reduce possible unconscious bias as part of resume reviewing process
When enabled, below we can see in the job seekers tab of job posting, what the seeker's resume ranking is as aligned to the job description
Click here to download Resume Ranking feature document
Find Best Matching Candidates
What does it do: Find best matching candidates enables buyers to search their existing contingent workers, workforce, and job seekers that are similar to a referenced record. So for example – if the hiring manager or program office know that they previously had an amazing Project Manager that would be perfect for a current job posting but not currently available – by using this feature you direct Fieldglass to search existing workers, workforce and job seekers to find who’s the closest match to that reference Project Managers’ resume. So where Resume Ranking uses machine learning to match resume’s to job posting analysis, Find Best Matching Candidates uses machine learning to match a known job seeker’s resume, with current workers, workforce or job seekers.
Why should it be of interest:
Effort to implement –easy, service request to enable the change to company config,
Effort to test – super easy
Benefits to business – Potentially saving you both time and money
When viewing the job seekers tab on a job posting, you have option to open the matching tool
Once opened, you select from drop down your reference worker, and FG will then find the profiles that most closely match that worker
what other Fieldglass features has your program taken advantage of to gain the competitive advantage in the war for talent?
Resume Ranking – uses machine learning to analyse job posting details with job seekers resume to provide a ranking of resumes’ submitted.
Find Best Matching Candidates – uses machine learning to analyse a reference resume – and find other’s which are the closest match based on skills, job title, industry, education and years of experience
Potential Candidates (which you’ll recall was the last edition and is in the trail below)– uses sql search of the application to highlight workers ending soon, job seekers etc who share common traits of the job posting – such as job code, currency, distribution list, within the past 40 days
Resume Ranking
What does it do: Resume Ranking parses through the resumes attached to each Job Seeker submitted towards a specific Job Posting and the algorithm assigns a resume score based on closeness to keywords provided in the Job Posting Description, ranking the available candidates in order of out output of the algorithm.
Why should it be of interest:
- Whilst not a replacement for manual resume review, it’s provides a suggestion to the recruiter of which resumes may be worth while reviewing first – which particularly in a high volume roles and where the market is moving quickly – speed to identify top candidates is key.
- Objective scoring which isn’t influenced by any un-conscious biased that may occur on seeing individual particulars in a resume
Effort to implement –easy, service request to enable the change to company config, then addition to user role permission
Effort to test – super easy
Benefits to business – improve quality of external worker hired, automate (assist) processes to reduce cycle time, reduce possible unconscious bias as part of resume reviewing process
When enabled, below we can see in the job seekers tab of job posting, what the seeker's resume ranking is as aligned to the job description
Click here to download Resume Ranking feature document
Find Best Matching Candidates
What does it do: Find best matching candidates enables buyers to search their existing contingent workers, workforce, and job seekers that are similar to a referenced record. So for example – if the hiring manager or program office know that they previously had an amazing Project Manager that would be perfect for a current job posting but not currently available – by using this feature you direct Fieldglass to search existing workers, workforce and job seekers to find who’s the closest match to that reference Project Managers’ resume. So where Resume Ranking uses machine learning to match resume’s to job posting analysis, Find Best Matching Candidates uses machine learning to match a known job seeker’s resume, with current workers, workforce or job seekers.
Why should it be of interest:
- Reduce time to hire by identifying existing workers or job seekers – so negating the potential need to go to market
- Improve worker quality by extending the internal search feature available concurrently with an external search strategy.
Effort to implement –easy, service request to enable the change to company config,
Effort to test – super easy
Benefits to business – Potentially saving you both time and money
When viewing the job seekers tab on a job posting, you have option to open the matching tool
Once opened, you select from drop down your reference worker, and FG will then find the profiles that most closely match that worker
what other Fieldglass features has your program taken advantage of to gain the competitive advantage in the war for talent?
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