Congratulations,
Pawan Goyal
( Chief Business
Officer – Naukri.com )
Context :
India
Inc's hiring activity up 57% in September, according to Naukri's JobSpeak /
Eco Times / 09 Oct
Naukri JobSpeak, a
monthly hiring activity index based on job listings on Naukri.com, grew for the
third consecutive month in September to hit a record high of 2,753, growing 21%
over September 2019 levels and 57% year on year.
"India is witnessing a never-seen-before
activity in hiring," said Pawan Goyal, chief business officer of Naukri.com.
My Take :
Ø For looking up JOB STATISTICS for any particular month, look up :
https://www.naukri.com/blog/naukri-jobspeak-report/
Ø Here is a place where you can find / read all the JOB STATISTICS ,
in an elaborate manner :
https://drive.google.com/file/d/1vLayE2rkidR6VGVjTrDXuExPO1fvrzfL/view
Obviously, the job-statistics presented are
based on the actual “ Job Listings “ found on Naukri , month after month ( jobs
posted by 76,000 employers registered on Naukri website )
But that is an incomplete picture , since
there are hundreds of other Job Portals , which may carry , many more
job-postings
If ,
Ø Job Data from all the job-portals were to be available , on an
on-going basis
And,
Ø If these data was subjected to BIG DATA ANALYTICS / PREDICTIVE AI
Software,
- - then , what insights can we have
?
Ø Here is a glimpse :
ANNUAL
EMPLOYMENT SURVEY ? ………..[ 26 Oct 2015 ]
Extract :
Ø Who
( which Companies ) are advertizing and when ?
Ø What
jobs / vacancies / positions are being advertized ?
Ø What
is the frequency with which a particular job gets advertized ? By entire
industry ? By a given Company ?
Ø Which
regions / cities have max / min no of new jobs ?
Ø What
are regional disparities due to ?
Ø Which
Industries are advertising most – creating most jobs ?
Ø What
Edu Qualifications are in max demand ?
Ø What
kind of jobs demand what kind of Edu Qualifications ?
Ø What
is the level of co-relation between , Position and the years of Experience
demanded ?
Ø For
identical positions being advertized , how much do “ Job Descriptions / Desired
Profiles “ differ, from company to company ?
Ø Are
there significant differences in the “ No of years of Experience “ being
demanded , for identical positions ?
Ø What
is the probability of finding the “ Keywords “ in “ Job Description / Desired
Profile “ ?
Ø What
is the extent of duplication ( redundancy ? ) between , “ Job Description “ and
“ Desired Profile “ ?
Ø What
percentage of Advts fail to make any mention of , Compensation Offered ?
Ø When
a company posts an advt for same / identical position , at different points of
time , are there any differences in values ( fields ) ?
Ø From
an analysis of all the advts posted by a given Company ( over past 7 years ) ,
can any conclusion be reached as to the changing nature of that company’s
business (by co-relating the “ Skills related Keywords “)?
Ø Can
the algorithm predict what job a company will advertize next – and when ?
Ø Is
there any correlation between , “ Designation / Position “ and the “ Keywords “
?
Ø From
analyzing this huge data , can software auto-generate , a complete / editable
job advt , as soon as a Recruiter simply types the “ Designation / Position “ ?
I believe , so far , no
one has undertaken such a Data mining project
If carried out diligently , I am sure , the
outcome would be of immense benefit to :
Ø HR
Managers
for Manpower Planning / Compensation Planning
Ø Recruiting
Managers
for framing Man Specifications / Job Description Manuals
Ø Educationists
for deciding what Edu Quali are in demand and tailor the Courses
Ø Students
to figure out what “ Skills “ are in demand by Industry and prepare
Ø Planning
Commission ( NITI Aayog )
for allocating Resources to States / Regions , based on imbalances
Ø HRD
Ministry
For long term Macro-Planning in respect of Education
Ø National
Skills Development Commission
for chalking out Skills Development Programs in collaboration with
Companies / Industries
What can / will such a project yield
?
Without exaggerating , it would be
safe to assume that , this vast database of job advts would contain :
Ø 50
million phrases / sentences
Ø 500
million words
Obviously , each word / phrase /
sentence , is nothing more than a
“ Database of Intentions “
of the Employer Companies
( to borrow from John Battelle’s
well-researched book about Google )
Our goal shall be to make this ( Data
mining Algorithm ) a dynamic / continuous “ Process “ , so that , we can
measure the changing nature of these “ Intentions “ , over a long , long period
And we must enable a “ Researching
Visitor ( of web site ) “, to benefit from these trends / patterns
Even though 5 million job advts may contain 500
million “ words “ , these are not Unique
Most of these are used again and again , hundreds
or thousands of times
Thru data mining , it is not difficult to compute
their “ Frequency of Usage “
And then , these frequencies can be graphically
plotted against any particular time-period
Such Graphical Representations can be further
broken up by ,
Ø City Names
Ø Company Names
Ø Industry Names
Ø Function Names
Ø Designations ( Vacancy Names ).. etc
And such graphical analysis can be done , not only
for “ Keywords “ but even for “ Key Phrases “ and “ Sentences “ !
===================================================
With regards,
Hemen parekh / hcp@RecruitGuru.com /
17 Oct 2021