Hi Friends,

Even as I launch this today ( my 80th Birthday ), I realize that there is yet so much to say and do.

There is just no time to look back, no time to wonder,"Will anyone read these pages?"

With regards,
Hemen Parekh
27 June 2013

Thursday, 22 June 2017

How to Rank Resumes ?



In an email to Prof Rahul Deshmukh ( IIT – Mumbai ) , I had suggested following approach :




Feb 18 , 2013



Dear Team


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 )


I am sure someone in Google will read this blog – then implement it to change the rules of Online Recruitment Industry !





23  June  2017







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