One can Survey the Companies
Or
One can survey the candidates.
(A) Surveying Companies :
-
Requires preparation of elaborate questionnaires
-
Establish "equivalence" (across a group of companies_ of
. Grades
.
Scales
.
Levels / designations etc
Without which, comparisons become difficult or infectious.
-
Convincing lot of companies to participate & give - out information in questionnaires
and across the table.
- Having
convinced, getting them to do that
- Setting
aside one / two persons (who can command respect) to go and meet dozens of
personnel Managers across the country over 2/3 months of time.
- Then
tabulate / analyse the data (thru computerization, of course), Plot graphs/
charts, draw conclusion write report, print and send - out copies to all
participating companies.
All of above is
. Tedious
. Time -
consuming
. Pain -
staking
.
Expensive
. Not
much remunerative ?
If found remunerative, we may still do this
sometime in future when
- Time/
money resources permit
- We have
acquired a "standing" for corporate to respond.
(B) Surveying Candidates
This is even more difficult because
- A much
larger SAMPLE - SIZE is required. Hence greater effort.
- We
cannot promise a copy of report of 2000 executives so, for them, there is no
ensuring benefit (what is there for me?) why should be they take the trouble to
fill in a questionnaire, spending 2 hours of his precious - time?
- An
executive is reluctant to part with this "CONFIDENTIAL" to somebody
who is a total stranger - specially when he sees NO BENEFIT for himself. He is
even afraid of this information leading to wrong parties.
All in all this is not a viable proposition.
However,
as far as we are concerned there is a THIRD &
SIMPLE alternative which is also
-
Accurate
-
Reliable
- Fast
-
Provides greater statistical analysis
In our EDS (Executive Data Sheet) we get detailed
(break - up) data on an executives
COMPENSATION PACKAGE.
For that executive, we also know (from EDS),
a - Name/
PEN
b - City
of Posting (Regional Pattern of Compensation)
c - Edu.
Quali - & year of Passing
(-
Education - wise compensation pattern - year of Passing - wise analysis)
d - Birth
- Date
(Age
- wise analysis)
e - Current
Employer - Company
(Company wise analysis if there are 20 executives from same company)
Or
at
least
- Industry
- wise analysis (the industry to which a company belongs)
f - Post
Qualifications (MBA etc)
Do these
guys get a better package as compared to others ?
. Of
come "age"
. Of
same "Industry"
. Of
same basic "Edu. Quali"
g - Total years of Experience
Across the Industries
Or
Within a given industry,
How do salaries "Progress" with exp?
h - Designation
What
are the salary - patterns within each "designation - groups"
(hierarchy - levels) ? For same "designation - group", what are the
differences / spreads based on
.
Industry
. Edu
. Exp. etc.
Since May 1996, we have started receiving duly -
filled in EDS
Till end Nov. 96, We have received ........... 2717
Of these, we have already entered in computer
= 2000
Of course, there may be some EDS Where, the
COMPENSATION - PACKAGE data
. is
totally missing
. is
incomplete
. is
confusing/ erroneous
We would have to ignore such EDS.
But
The balance do provide a good enough
"population / sample" to carry - out several statistical analysis
We could thereafter use this analysis for
-
Incorporating "Highlight of Findings" or "overall Trends in
compensation" in our quarterly MAILER to 1000 top companies.
-
"Selling" detailed report to those companies who are interested.
The enclosed pages show what type of analysis can
be carried out.
(A)
Designation Group : GENERAL MANAGER
Designation
Group : Manager
Designation
Group : Vice President
For each "designation - group" repeat
Graphs #1/ #2/ #3.
(B) Industry Group : Automotive
. Consumer Goods
. Power
. Telecom
For
each Industry group, repeated graphs #1/ #2/ #3/ #4
(C) Edu - Qualification - Groups
. Engineers
.
Charted Accountants
. Co.
Seevetaries
.
Commerce Graduates
. MBAs
etc etc
Repeat Graph #1 / #2 / #3/ #4 for each of the Edu.
Quali. Groups
(D) REGION (North/ East/ West/ South. Central) /
ALL INDIA
Repeat all graphs "Posting - location" wise to bring - out
"Regional Disparities/ Differences" for
-
Same Edu. group
-
Same Age group
-
Same Designation group
-
Same Industry group
-
Same Experience group
-
Same Function group
(e.g. Mfg/ Mktg/ Sales/ Finances/ Personnel & Adm / R & D etc)
Besides the above mentioned analysis, one could
also analysis different "Sub groups" within the total compensation - package. These are
. Basic
.
Allowances
. Perks
. Reimbursements
.
Annual Payments
.
Retirement benefits
. Other
Benefits
After calculating the "Percentage" (%) of
each to the TOTAL package, one could compare these "Sub - Groups"
across
.
Industries
.
Regions
.
Designations
To determine the influence of these (Industry -
Region - Designation) on the various CONSTITUENTS (i.e. the sub - groups)
Does this analysis e.g. show that
. Higher
the designation higher the perks/ reimbursements
. Western Region
has better Reimbursements
. North
have more "allowance" %
Or
. Telecom
Ind. has more Perks etc etc.
. What
companies are offering "Loans" ?
. What
Companies are offering "Co - flats"?
. what
are "tax - free" components?
. What
are "trends" in specific allowances.
eg.
. Uniform
allow / attire allow
. Edu.
allow / attire allow
. Lunch/
Canteen allow / attire allow
. Travel
allow / attire allow
. Entertainment
allow / attire allow
. HRA
allow / attire allow
. CCA
allow / attire allow
. ITA
allow / attire allow
.
Medical Reimbursement
If we wish to "market" compensation Analysis
as a "By - Product", we could even consider modifying our EDS and
devote one entire page to compensation package
Of course as the SAMPLE - SIZE groups, accuracy
will also improve.
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