If there was a line depicting spends on job boards on an axis of time, there is only one direction it would head - UP. With ~30mn graduations every year - but an ever increasing skills gap, the jobs market in India is fundamentally lopsided. If you add to that, the churn that happened in FY-22 (The Great Resignation, Startup layoffs galore, 90mn job changes) - Job Boards seem to be quiet benefactors of this situation. And this reflects in their pricing strategy.
Recruiting the right candidate was hard - but it’s just become ever more expensive. The truth is that this cannot be eliminated away - but it sure can be managed.
A lot of companies miss out on making their own data sweat more. Every recruitment company / agent / freelancer - over years and years of sourcing - accumulates a sufficiently large pool of candidate data. Given that data collected a few years ago might not be “fresh” (current candidate willingness to switch) they are often not organised digitally. These profiles are deigned to exist within the realms of Google documents, or Outlook e-mails or excel sheets. Ergo a continuing reliance on Job Boards unabated - and with a plethora of “almost there” candidates - this reliance is not easy to navigate past. There are ATSs (Applicant Tracking System) of course - but they were fundamentally designed to track the application process and not to enable data search and outreach efficiently.
Also, searching for the RIGHT profile from the stack of resumes is akin to searching for a needle in a haystack. Because ATSs are fundamentally workflow automation systems - most of the searches that are done today are string match searches. Search for a “front end developer” and ideally that term needs to be there in the underlying resume for a match to surface. There is no “context” within the search.
Resumes are extremely personal artifacts - they are an expression of purpose that each individual words as intimately as possible. That is the reason why resumes are not standard documents - precisely because they are unique - quite like a fingerprint of the individual. This expression of purpose thus needs to be deciphered and best matched to the context of what is wanted by the hiring manager.
But picking up context is hard. Resume parsers have been around for years now but still matching based on inferred skillsets is hard. Inferring if the profile is a great match for “front end developer” if they have “Worked on React” is, hem, tricky. Context is harder still when it comes to frontline workforce - because there are no standardized job roles. A Sales rep is also known as a demand executive, business development executive, a customer executive or in plain terms, a salesperson. All of these refer to someone who has the skill set of being able to make customer contact, inspire trust, communicate the product proposition - be able to “sell” in short.
The frontier is being pushed on this though - Deep learning models and NLP engines are now adept at understanding the underlying skillset that is being described. Context will become the gamechanger not just for matching - but slowly to predict whether a profile has the potential to do what is needed for the requirement at hand.
Back to the task at hand - once a recruiter is able to pull out the relevant profiles from their own database - the challenge is to check whether the job / demand at hand is interesting enough for the candidate to make a switch. This is the 2nd part of the problem - to ascertain interest. This is where unfortunately recruitment begins to resemble telecalling operations. This is where the FIRST candidate that broadly fits takes precedence over the RIGHT candidate that contextually matches.That is where enables 1) a central lead database of all interactions 2) a contextual match and 3) multi-channel outreach to all matches in real time. The relevant shortlist is first made aware of the job and is then engaged about its prospects. This enables a reduction in TAT at a fraction of the total cost of hire. Since all data is centrally visible across the organization - recruiters search internally before venturing out. Forward looking TA organisations are engaging with us on how to make their recruitment process efficient - and make their data sweat. Data is the new oil or so they say - but you ought to let your data fuel your business better. And that would manage the spend on the job boards with time.
