Feb 18 , 2013
Google calls it PageRank – to decide the importance of a web page – then use this number to decide the rank ( position ) of that page within the search results
Let us follow Google ( very safe ! )
And call our “ Ranking Mechanism “ of any given resume , a “ Pa-Rank “
Then arrange all arriving resumes ( in the mailbox of a Recruiter or on our web site ), in the descending order of their Pa-Rank
Highest ranked at the top
So , the Recruiter need to open / read only the top 5 - 7 ! No more !
In much the same manner that 95% of the searchers never go beyond the first 3 pages of any search-result despite millions of pages
Just imagine how much time it will save the recruiters to zero-in on the best candidates from amongst hundreds applying for any given job
This has the potential to revolutionize the On-line recruitment industry !
How can we determine a candidate’s Pa-Rank ?
Just like PageRank , which takes into account,
# No of Incoming links to a given page
# Importance of each incoming link ( based on its own incoming links )
No doubt , Google’s actual algorithm must be very complex – and continues to evolve
Thru our mobile app , “ Resume Blaster “ ( and someday , thru app “ My Jobs “ as well ), we pick-up the “ Contact List “ ( of mobile nos ) of say, Ajay ( a user registered on our site )
These are his “ Primary Incoming Links “ – say , 40
Out of these 40 , say , 10 have also registered on our site AND , are also using our mobile app “ Resume Blaster “
In turn , these 10 have , between them , 600 contacts ( “ Secondary Incoming Links “ )
So , for Ajay , total Incoming links = 40+600 = 640
Now , if Ajay thinks he has figured out how our software computes Pa-Rank then he will somehow find out the mobile number of Mukesh Ambani , and add into his “ Contacts “ – assuming that at one stroke ,he can add ONE MILLION incoming links to himself !
But , we know that such high-flying executives are unlikely to have registered on our site – much less , to be using our app , “ Resume Blaster “ !
Hence we treat this as a “ Dead Incoming Link “
On top of that , we can further refine our Pa-Rank based on,
# The frequency with which Ajay keeps calling each of those 10 persons ( who have registered on our site AND are also using our app “ Resume Blaster “ )
# The duration of each call ( or even text message ? )
We can multiply / sum-up / find average , etc of such “ exchanges of messages – both ways “ and arrive at some “ FACTOR “
Then multiply the “ Total No of Live Incoming Links “ with this “ FACTOR “ , to compute PaRank
Looks crude , no doubt !
But Google has proved that it works !
What PageRank is for all the web pages in the World , someday , PaRank will be to all the resumes ( which too , like any web page , are documents ) , in India
We must do it !
On internet , “ Ideas are dime-a-dozen “
But elegant executions are rare !
8 years earlier ( on 21 Dec 2005 ) , I had sent the following proposal to the Shri Ashish Kashyap ( the then Country Manager - Google India ) :
It was only this week that Google launched “ Google Job Search “ ( for USA jobs )
23 June 2017
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