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

Now as I approach my 90th birthday ( 27 June 2023 ) , I invite you to visit my Digital Avatar ( www.hemenparekh.ai ) – and continue chatting with me , even when I am no more here physically

Saturday 2 September 2017

Aadhar - for HR ?



Aadhar  Aggregate   Anonymous  Data  Harvesting  about  Recruitment




Even as debate on Data Privacy is raging and B N Srikrishna Committee is debating the PROS and CONS of Privacy vs Publicity ( of data ) , there is a general consensus that aggregating anonymized data for the purpose of GREATER GOOD of the Society , should be permitted


I want to go one step further and say :


Such gathering and using of Anonymized data should be Encouraged / Solicited / Mandated , for policy and strategy formulation


Here is a glimpse of what I have in my mind


I worked in a large engineering company for over 30 years .


So did many of my colleagues , all of us starting as JUNIOR supervisors and retiring as GENERAL MANAGERS, after serving for 20 / 30 / 40 years


This was between 1950s and 1990s


How did we fare when it came to the “ Salary Increments “ that we received ,


·          to compensate us for neutralizing the rising “ Cost of Living “ ?


·          to improve our “ Standard of Living “ ?



Look at the following (  ANONYMIZED  ) data about Salary Growth ( Rs per month )  :



Name  /  Start  / End  /  Diff  /  Years of Service / Growth/month( ave ) / Joining Year


A   /   Rs  2500   /  Rs  19,250   /  Rs 16,750  /  24  /  Rs 698  /  1972

=======================================================
B   /    350     /    17,700     /     17,350    /    39     /   445    /    1956


C    /   3,000    /   13, 270    /   10,270    /   18   /       570     /    1977



D    /   1,600    /    16,900    /   15,300    /   23    /     665    /     1971



E    /    2,700    /   10,300    /   7,600    /   21    /     362    /       1971



F     /    135    /    7,700     /   7,565     /    43    /      176    /     1948


G    /    625    /   9,985    /    9,360   /     31     /      302     /     1959


H     /    2,500    /  6,000   /   3,500   /    17     /      206    /      1972



J     /   1,400    /  7,500   /   6,100    /    23     /       265    /      1965




Do you see the “ limitations “ of the above “ analysis “ ?


It pertained to just one COMPANY / one INDUSTRY / one CITY / one EDU LEVEL / one DESIGNATION LEVEL / nine EMPLOYEES



Can you guess what “ Insights “ such “ Data Analytics “ could yield if it was for :


·         A million  Companies , operating in

·         100  different  Industries , and located in

·         5,000  Cities , covering

·         100 million  Employees , having

·         500  different  Edu Qualifications , and having

·         1000  different  Titles / Designations



Also remember that the above-tabulated analysis was carried out by :


·         one retired employee ( possessing limited natural intelligence ) ,

·         after a lapse of  30 years  and ,

·         taking a  few hours  of data-digging / tabulating ?

·          

Can you guess if such analysis were to be carried out ,

·         INSTANTANEOUSLY

·         DYNAMICALLY

·         AUTOMATICALLY ( without human intervention ) , and by

·         ARTIFICIAL  INTELLIGENCE  ( AI ) ,


Then what kind of  POLICY INPUTS  that could provide  ?



To know ,


·         Aadhar ( Aggregate   Anonymous  Data  Harvesting  about  Recruitment )


·         How it can be implemented ,


Read :


From  BAD to  MAD  [  01  June  2016  ]





I hope the new Minister of Labour ( about to be sworn in ) will find time to read this




03  Sept  2017





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