#UnEmployment #JobsData #EPFO #DigitalIndia

Jobs  Data : How to automate Compilation

Economic Times ( 06 May 2018 ) carries following article :

“ The Job Begins on Jobs Data 

https://economictimes.indiatimes.com/jobs/the-sharp-debate-on-jobs-data-shows-govt-may-arrive-at-a-process-for-understanding-indias-labour-market/articleshow/64045032.cms

Summary :

*  CMIE’s ESTIMATE of JOBS

   2016-17…………………….406.7  million

   2017-18…………………… 406     million

*  GHOSH & GHOSH  STUDY

    FY  17……………………….. 45.4 lakh additions to payroll across 190 industries

    FY  18……………………… ..36.8 lakh

*  EPFO  Data

    Dec-Feb ( FY 18 ) ……………. 9.7 lakh

    Apr-Feb……………………………   46.5 lakh additions to payroll

    Sep-Feb  (  FY  18  )…………  31.1 lakh jobs created of which 18-25 age group category

                                             has 22 lakh

This divergence is not surprising !

It is much like having 5 wall clocks in your drawing room, each needing occasional winding

You may rest assured that , quite likely , all will show a different  “ time “ – even if slightly different from the others

And just because you have 5 clocks to depend upon, you become careless in timely winding !  You feel , you can always count on at least one to be working and showing correct time

Except that you don’t know which one !

So , expect this controversy ( as to which Job Data is correct ) to continue , even after 5 years

Now , the Chinese are very obsessed about “ Skilling / Re-Skilling “ their manpower

So , they are unlikely to be satisfied with just data about their “ Unemployment Rate “

They would want unassailable data about :

#   Total number of employees ( category / region / industry )

#   Employment Density ( Industry wise / Region wise / Skill wise etc )

#   Net Employment Growth Rate ( weekly - monthly / Industry-wise )

#   Co-relation with no of persons graduating at various levels

#   Data about those Unemployed ( " Graduating " less " Employed " )

#   Overtime Statistics ( Use / Abuse )

#   Work-hour Analysis ( Ave hours / week - month )

#   Wage / Salary Rates ( Yuan per hour ) - Industry wise / Region wise

#   Compliance with labour laws / tax laws / Apprentice Act etc

#   Job Market Forecasts through BIG DATA ANALYTIC ( region / industry )

#   Demographic  Profiles of employees  ( Rural to Urban migration )

#   Per Capita Income Growth for persons  ( MOM / YOY )

#   Changing composition between Blue Collar and White Collar employees

So , expect them to implement , in the next 6 months :

From  BAD  to  MAD  [  01  June  2016   ]

https://myblogepage.blogspot.in/2016/06/from-bad-to-mad.html

Even as our EXPERTS continue to spar on TV channels in 2022  !

08  May  2018

www.hemenparekh.in / blogs