- October 4, 2021
- Posted by: Editorial Team
- Category: Blogs
Search and list qualified candidates, mimicking the recruiter’s process.
Reading time: 9-10 minutes
Key Points: Bots can ease the recruiter’s stress in creating a long list of suitable candidates based on a client’s brief. An iterative process, similar to what a recruiter follows to identify potential candidates, can be programmed in a Bot. What’s more, the most complex Boolean expressions including nested and composite structures can be included! Such a Bot will help the recruiter first create a well-defined dataset and then identify & process candidates into stack ranked list within minutes.
Setting the Context: Every recruiter’s challenge: “generate a long list of qualified candidates that match the client’s brief, from multiple sources and huge datasets”. All modern ATS (Applicant Tracking Systems) integrate with a parser that pulls select information from the Resumes, and ranks the candidates based on desired criteria. However, the more challenging task for the recruiter is to source the right datasets. The quality of dataset depends completely on the quality of source map that is developed. Else, it will be GIGO (Garbage in and Garbage Out), even if you were to deploy a top-notch ATS, as the ATS can process Resumes only from within the dataset provided to it. For this, recruiters create their own collection of queries and draw on their individual Intellectual Property developed over time. Boolean expressions and queries repository of the recruiter is a function of their own experiences and interactions with peers over social media forums.
Net Result: Repeat the non-standard process day-in-day-out of inadequate or improper query formulation, refinement, and evaluation —–> Unable to meet the assigned deadlines or adequate number of candidates at the top of the funnel —–> Poor quality of service to clients.
So, what is the use case for a BOT in recruitment? Especially at the start of the recruitment process? Can a BOT really make the recruiter’s life easy? Are companies using these? To what purpose and with what effect? Perhaps, these are some of the questions that you should think through before deploying a BOT or 4 more to help your talent acquisition team. Again, the moot point would be reduce costs with deploying these BOTs or increase efficiencies of your team by paring them off with intelligent automation.
An interesting use case: Use a BOT to source quality datasets and list best matched candidates!
There is no ideal job board! Each of them deploy their own search algorithms based on the filters you apply & keywords you use. Time & motion study of a recruiter shows that it takes about 3 hours to complete a thorough search activity; this typically involves about 5 queries, with each query taking around 5 minutes to formulate. After each round of search, depending on the results found and a quick scan of the Resumes for suitability, the next query is formulated. This suggests that recruitment follows an iterative process, consisting of successive phases of candidate search followed by other activities such as candidate evaluation for long-listing or short-listing. The task completion time is substantially longer than typical web search tasks for information.
The usual statements that we hear from recruiters are “Boolean logic is important to formulate effective queries”, “Weighting is important to formulate effective queries (e.g. Relevance ranking)”, and “I need to consider synonyms, abbreviations, free-text keyed differently by candidates (e.g. company names) and related terms to formulate effective queries”, “duplicate CVs need to cleaned-up due for refining the query and running the new search criteria on the same dataset” and “finally formulate the restriction criteria to narrow down the results”. Many of these requirements can easily be met by a Bot that is developed based on the iterative process being done by the recruiter.
Imagine a Bot that can look into your ATS and Job Board, using your recruiter’s access to create a long listing of suitable candidates that meet your hiring criteria. Wouldn’t it make your recruiter’s life much easier? And leave them enough to engage with candidates, position the opening, evaluate for fitment and shortlist them for further processing?
If you are interested in knowing more about how TBL can help you hire such a BOT in your recruitment team, do drop in a line to: firstname.lastname@example.org