Notes: COMPENSATION SURVEY OR COMPENSATION ANALYSIS

COMPENSATION - SURVEY 13/12/96

Nirmit / Nagkasahel

Let us discuss after you had opportunity to study enclosed note.

All the "raw-data" required to implement this project is already entered/available in our database. What we need is a Software (a Statistical Analysis Package) to process this data and prepare the graphs for analysis.

Once each graph is printed, anyone can write-down "Observations - Findings"

And in this case, we can genuinely claim our own "Authorship". We will also find a number of "buyers" if done quickly, since Nimit's remarks in Business World (Coming Salary Squeeze) are still fresh in the minds of Corporates.

COMPENSATION - SURVEY

COMPENSATION ANALYSIS

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 infructuous.

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 computerisation of course), plot graphs, Charts, draw conclusions, 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 corporates 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 to 2000 executives. So, for them there is no ensuing benefit (What is there for me?) Why should 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" information about himself to somebody who is a total stranger - especially when he sees NO BENEFIT for himself. He is even afraid of his information leaking 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 executive's 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)

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 same "age"

- of same "Industry"

- of same basic Edu: Quali:

g - Total years of Experience

Across the industries

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. 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 $\approx 2000$

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.

Graph # 1: Y-axis: Salary, X-axis: Year of Graduation
Graph # 2: Y-axis: Salary, X-axis: Age
Graph # 3: Y-axis: Salary, X-axis: Years of Experience
Graph # 4: Y-axis: Salary, X-axis: Designation

(Note: All graphs show a vertical line for salary and a horizontal line for the other variable, with no plotted data points, indicating the axes setup for the analysis.)

(A) Designation Group:

GENERAL MANAGER
Manager
Vice President

For each "designation-group" repeat Graphs # 1 / # 2 / # 3.

(B) Industry Group:

Automotive
Consumer Goods
Power
Telecom.

For each Industry group repeat graphs # 1 / # 2 / # 3 / # 4.

Engineers
Chartered Accountants
Co. Secretaries
Commer Graduates
MBAs

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
" " Age
" " Designation
" " Industry
" " Experience
" " Function

(e.g. Mfg / Mktg / Sales / Finance / Personnel & Adm / R&D etc)

Besides the above-mentioned analysis, one could also analyse 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 than other regions
North have more "allowance %"

Telecom Ind. has more Perks. etc etc

What Companies are offering "loans"?
" " " " "Co-flats"?
What are "tax-free" components?
What are "trends" in Specific allowances

e.g.

Uniform allow / attire allow
Edu "
Lunch / Canteen "
Travel "
Entertainment "
HRA "
CCA "
LTA "
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 grows, accuracy will also improve

13/12/96

Chart 5

Salary Distribution

POPULATION = [Box for Value]

SALARY IN RS. (LAKH)

Graph: Gross Annual Salary (Y-axis) vs. Age (X-axis)

(Data points scattered, with a "LINE OF BEST FIT" drawn diagonally upwards.)

Chi-square method
Regression Analysis

Page 1

Chart 7

SALARY DISTRIBUTION

AGE: 35 Years

Graph: No. of Person (Y-axis) vs. Salary (Rs. Lakhs) (X-axis)

(A line graph showing a frequency distribution curve, heavily skewed to the left/higher frequencies at lower salaries.)

Chart 1

SALARY DISTRIBUTION

AGE: 65 YRS

Graph: SALARY (Y-axis) vs. FREQUENCY (NO. OF PERSON) (X-axis)

(Shows two lines: FREQ_SAL and SALARY_LAK, plotted against frequency. The pink line, SALARY_LAK, decreases as frequency increases.)

Page 1

INFOSEEK 8-11-97

What salaries executives get? (taken from Annual Reports)

Once we build-up a large database (say, 100,000 executives / 1000 companies), several interesting ANALYSIS / PRESENTATIONS are possible:

(1) Scattergram

Graph: Gross Annual Salary (Y-axis) vs. Age (X-axis)

(Shows scattered data points, a "Line of best fit", and a "Salary distribution curve of all execs. aged 35.")

Even as salary data is being added daily/fortnightly, it should be possible to plot Salary Vs. Age on the fly (on Internet or Extranet).

Thereafter a facility can be provided (to a Surfer) to go along X-axis and click on

any desired "Age" value.

(Of course the scattergram and the line of best fit are already visible to him on the screen).

As soon as he clicks on "Age = 35" the scattergram disappears.

What appears on the screen is:

[Boxed diagram showing a bell curve distribution]:

Y-axis: No. of Exec (Frequency)
X-axis: Annual Salary (Rs. 000)
Title: Executive Salaries at age 35 in 96-97

[Four boxes for key statistics]:

MEAN SALARY
MEDIAN SALARY
STD. DEVIATION
POPULATION SIZE

Of course, over a period of few years, with accumulation of salary-data of thousands of executives year after year, it would be possible to carry-out (and display on screen) many types of TREND ANALYSIS.

Executive Salaries at Age 35

Graph: Y-axis: No. of Exec, X-axis: Salary (Rs. 000)

(Shows three overlaid distribution curves, labeled 96-97, 97-98, and 98-99, illustrating a shift over time.)

"Such trend-analysis" could be repeated for

any given "Age"
" " "Edu. Quali."
" " "Function"
" " "Industry"
" " "Designation-Level"
" " "Company"

Also we could have graphs to show

Salary Vs. Edu. Quali.
" Vs. Function
" Vs. Industry
" Vs. Designation Level
etc. etc

(2) SPECIFIC COMPANY: SALARY ANALYSIS

Any number of executives (especially Personnel Managers) would want to analyse "Salaries of Executives of a Given Company".

Such a "given Company" could be a competitor OR the Industry-Leader (so that you can bench-mark).

e.g. Videocon International Ltd might wish to analyse Salary-details / distribution of:

BPL
Godrej GE
Antirex
Voltas
Philips
etc etc

Personnel Manager of Videocon might like to shoot a query on our database as follows:

Pl. show me Salary-details of

COMPANIES	XYZ
	ABC
	LMN
	PQR

Scan_0021.jpg (Page 5)

For

a) All Executives [box] OR

b) Executives belonging to function

Mfg [box]
Mktg [box]
Production [box]
Sales [box]
Design [box]
R&D [box]
etc

c) Executives with "designation-level" of

CMD [box]
MD [box]
President [box]
V.P. [box]
G.M. [box]
D.G.M. [box]
Mgr [box]
Officer [box]

d) Executives in the age-group of

25-29 [box]
30-34 [box]
35-39 [box]
40-44. [box]

The result could be displayed as a TABULATION OR A GRAPH (without revealing the actual names of the executives).

INFOSEEK 8-11-97

What salaries executives get? (taken from Annual Reports)

Once we build-up a large database (say, 100,000 executives/1000 Companies), several interesting ANALYSIS/PRESENTATIONS are possible:

(1) Scattergram

Graph: Gross Annual Salary (Y-axis) vs. Age (X-axis)

(Shows scattered data points, a "Line of best fit," and a "salary distribution curve of all execs. aged 35.")

Even as salary data is being added daily/continuously, it should be possible to plot Salary Vs. Age on the fly (on Internet or Extranet).

Thereafter a facility can be provided (to a Surfer) to go along X-axis and click on

any desired "Age" value.

(Of course the scattergram and the line of best fit are already visible to him on the screen).

As soon as he clicks on "Age = 35" the scattergram disappears.

What appears on the screen is:

[Boxed diagram showing a bell curve distribution]:

Y-axis: No. of Exec (Frequency)
X-axis: Annual Salary (Rs. 000)
Title: Executive Salaries at age 35 in 96-97

[Four boxes for key statistics]:

MEAN SALARY
MEDIAN SALARY
STD. DEVIATION
POPULATION SIZE

Executive Salaries at Age 35

Graph: Y-axis: No. of Exec, X-axis: Salary (Rs. 000)

(Shows three overlaid distribution curves, labeled 96-97, 97-98, and 98-99, illustrating a shift over time.)

"Such trend-analysis" could be repeated for

any given "Age"
" " "Edu. Quali."
" " "Function"
" " "Industry"
" " "Designation-Level"
" " "Company"

Also we could have graphs to show

Salary Vs. Edu. Quali.
" Vs. Function
" Vs. Industry
" Vs. Designation Level
etc etc

(2) SPECIFIC COMPANY: SALARY ANALYSIS

Any number of executives (especially Personnel Managers) would want to analyse "Salaries of Executives of a Given Company".

Such a "given Company" could be a competitor OR the Industry-Leader (so that you can bench-mark).

e.g. Videocon International Ltd might wish to analyse Salary-details / distribution of:

BPL
Godrej GE
Amtrex
Voltas
Philips
etc etc

Personnel Manager of Videocon might like to shoot a query on our database as follows:

Pl. show me Salary-details of

COMPANIES	XYZ
	ABC
	LMN
	PQR

A minimum of 3 companies must be mentioned.

(This page is an almost identical duplicate of Scan_0021.jpg.)

for

a) All Executives [box] OR

b) Executives belonging to function

Mfg [box]
Mktg [box]
Production [box]
Sales [box]
Design [box]
R&D [box]
etc

c) Executives with "designation-level" of

CMD [box]
MD [box]
President [box]
V.P. [box]
G.M. [box]
D.G.M. [box]
Mgr [box]
Officer [box]

d) Executives in the age-group of

25-29 [box]
30-34 [box]
35-39 [box]
40-44. [box]

The result could be displayed as a TABULATION OR A GRAPH (Without revealing the actual names of the executives).

CYRIL 18-4-99

Compensation Analysis

Here is an opportunity for 3P to earn big bucks!

And, If we can earn big-bucks, then you too can earn, at least, small bucks!!

Potential is very much there. Question is "how FAST can we exploit this potential?"

This question is very pertinent, since all databases are "PERISHABLE Commodities".

I am talking about Gross Annual Compensation earned by Corporate Executives during 1997-1998.

After many months of struggling to get Annual Reports - and then an equally long struggle to create a database (thru data-entry), we finally have a database of

approx 31,000 executives
from 902 Companies

The database "fields" are:

Name of Company:
Name of Industry: (mostly blank but can be quickly derived from KOMPASS $\Delta$ database already created)
Name of Executive:
Designation:
Function: Totally blank for all records
Co's Products: Totally blank for all records
Annual Salary: (Rs. L/yr.)
Edu. Quals:
Experience (yrs):
Age (yrs):
Commencement of Employment (date):
Last Employer: } Occasionally filled-in
Last Designation: }

I have $\checkmark$ those which can be used by us in our ANALYSIS.

The IDEAL analysis would be graphical - although in some cases (typical example: EDU. QUALIFICATIONS), it is simply not possible to draw a graph on the small screen of a computer, when X Axis has 50 intervals!

I feel anything more than 10 intervals may be difficult to draw - and impossible to "read".

In which case, we may have no choice but to present the analysis in a "TABULAR" form.

In the enclosed sheets, I have shown how graphs & tables may appear on the screen.

Although Sajida has started preparing some tabulations, after looking at

the number of "Population"
no. of variables in each "population"
and therefore
the no. of "permutations/combinations" possible,

I have come to the conclusion that it is IMPOSSIBLE to prepare hundreds of thousands of tabulations manually - leave alone drawing "graphs" for each of these tabulations!

So, presenting our findings in the form of thousands of static HTML pages is out of question.

What we need is a SOFTWARE that would "dynamically" generate each of these tabulation/graph depending upon the QUERY, and display the same.

NOW,

I am NOT talking of having this Software/functionality on our WEBSITE.

Then we don't make any money!

I am proposing to put all of these (Database + Software) on a CD (of course, securely encrypted), and selling each CD to Corporate Clients for - Say Rs. 30,000/- each.

If we can find just 100 buyers, [a line is cut off] business of RS. 30 LAKHS!

To market this product, we would need to

Advertise heavily in newspapers/magazines
Send out $10,000+$ mailers
follow-up over phone
give "demonstration" seminars to Personnel Managers/CEOs in 5 star hotels (followed by drinks/dinner)

But if we come-out with a good product - and come out QUICK - then there is a good chance of success. Of course, we would need to RISK a few lakhs of rupees on "promotion" but then RISK is an integral part of any "PIONEERING" product.

Since the database pertains to 97-98, it is already ONE year old! 98-99 Annual Reports would start coming out in another $2/3$ months. Thereafter, "Customers" might lose interest in such old data. Hence we must come out with this product within $2/3$ weeks!

Perhaps it may not even be necessary to write a "custom" software. Could we possibly integrate some standard statistical software package such as:

SPSS
STATSOFT
etc ?

I believe these packages cost between $\$ 500 - 1000$.

Will we need an API? And solid ENCRYPTION is a MUST, although we must provide facility whereby a Personnel Manager/CEO can take a hardcopy "PRINT-OUT" of any particular Graph/Tabulation & be able to circulate amongst his colleagues for comments/discussion.

Of course no one would have time/energy to print-out thousands of combinations.

I would like to discuss this with you URGENTLY.

Regards, 18/4/99

POPULATION following FREQUENCY-DISTRIBUTION

Industry	∇
Auto	$\odot$
$\vdots$	$\vdots$
(50)	---

Graph

Population selected by you: AUTO INDUSTRY
Y-axis: Ave. Salary (Rs. L/yr)
X-axis: Designation

Designation	∇
Chairman	$\odot$
CMD	$\odot$
MD
President
(75)
Supervisor

Population selected by you: AUTO INDUSTRY
Y-axis: Ave. Salary (Rs. L/yr)
X-axis: Age

Age - Interval	∇
22 yrs	$\odot$
23 yrs
24 yrs	$\odot$
25 yrs
(43)
65 yrs.

Population selected by you: AUTO INDUSTRY
Y-axis: Ave. Salary (Rs. L/yr)
X-axis: Experience

Experience (yrs)	∇
1 yr
2 yrs
3 yrs
$\vdots$	$\vdots$
(40)
40 yrs

Population selected by you: AUTO INDUSTRY
Y-axis: Ave. Salary (Rs. L/yr)
X-axis: Edu. Quali.

Edu. Quali	∇
1 DME	$\odot$
2 DEE
3 DCE
4 BE(M)	$\odot$
5 BE(E)
6 BA
7 B.Sc
8 B.Com
MBBS
Ph.D.

Designation

Population selected by you: CHAIRMAN
Y-axis: Ave. Sal. (Rs. L/yr)
X-axis: Industry
Population selected by you: CHAIRMAN
Y-axis: Ave. Salary (Rs. L/yr)
X-axis: Age
Population selected by you: CHAIRMAN
Y-axis: Ave. Salary (Rs. L/yr)
X-axis: Experience
Population selected by you: CHAIRMAN
Y-axis: Ave. Salary (Rs. L/yr)

Age.

Population selected by you is Age = 35 yrs
Y-axis: Salary
X-axis: Industry
Population selected by you is Age = 35 yrs
Y-axis: Salary
X-axis: Designation
Population selected by you is Age = 35 yrs
Y-axis: Salary
X-axis: Exp.
Population selected by you is Age = 35 yrs

TABULATIONS

(Population Selected = INDUSTRY = Automobile)

Frequency-Distr: Selected	Salary Vs. Designation

TABLE FOR GENERATION OF GRAPH.

Designation	No. of Executive Records	Highest Salary	Lowest Salary	Average Salary
Chairman
CMD
MD/Dy MD
President/CEO

Frequency-Distr: Selected	Salary Vs. Age

Age	No. of Exec. Records	Highest Salary	Lowest Salary	Average Salary
22
23
24
$\vdots$
(60)

Frequency Distribution Selected	Salary Vs. Exp

Exp (yrs)	No. of Exec. Records	Highest Salary	Lowest Salary	Average Salary

DISPLAY FREQUENCY DISTRIBUTION.

This	Vs.	For given This
Salary	Age	Edu.-level (Say B.E.-M.)
	Total Exp	(Say 200 different Edu. Qualifications)
	Designation	(Mean?)
	$\text{Function}$ (Crossed out)	(Mean?)
	Industry
Salary	Edu.	Age (Say 35 yrs)
	Total Exp	(Say 22 yrs $\to$ 65 yrs)
	Designation	(43 intervals)
	$\text{Function}$ (Crossed out)
	Industry
Salary	Edu. level	Total Exp (Say 15 yrs)
	Designation	(Say 40 intervals)
	$\text{Function}$ (Crossed out)	(1 yr $\to$ 40 yrs.)
	Industry
		$\checkmark$ Industry (Say 50 Ind.)
		$\checkmark$ Designation (Say 15 levels)

SALARY ANALYSIS

Parameters

$\checkmark$ Edu. Quali (or level.)
$\checkmark$ Age (derived from birth-date)
$\checkmark$ Total Exp.
$\checkmark$ Designation
$\bullet$ $\text{Function}$ (Crossed out) Not avail in Annual Reports
$\checkmark$ Industry

Frequency Distribution - Graphs

What	VS.	What
$\checkmark$ Age		Age
$\checkmark$ Exp		Exp
$\checkmark$ Edu. Quali		Edu. Quali
$\checkmark$ Designation		Designation
$\text{Function}$ (Crossed out)		$\text{Function}$ (Crossed out)
Industry		Industry

13-12-96

Module # 4 DATA-MINING

COMPENSATION - SURVEY

COMPENSATION ANALYSIS

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 infructuous.

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 computerisation, 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 corporates 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 to 2000 executives. So, for them there is no ensuing benefit (What is there for me?) Why should 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" information about himself to somebody who is a total stranger - especially when he sees NO BENEFIT for himself. He is even afraid of this information leaking 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 executive's 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 ($\checkmark$ Age-wise analysis)

e - Current Employer - Company

(Company-wise analysis if there are 20 executives from same company)

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 same "age"
of same "industry"
of same basic Edu: Quali:

g - Total years of Experience

Across the industries

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 etc.

Since May $1996$, we have started receiving duly-filled in EDS

Till end NOV.$'96$, we have received $\approx 2717$

Of these, we have already entered in Computer $\approx 2000$

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.

| Graph # 1 | Salary vs. Year of Graduation | However $\longrightarrow$ $\text{Annual Report "Year of Graduation" data does not give, so this graph cannot be plotted}$ $\text{Resumes recd. by us on Web (Form) & Floppies do give "Year of Graduation", so for this population, we can plot this graph.}$

| :---: | :---: |

| Graph # 2 | Salary vs. Age |

| Graph # 3 | Salary vs. Years of Experience |

| Graph # 4 | Salary vs. Designation |

(A) Designation Group: GENERAL MANAGER, Manager, Vice President

For each "designation-group" repeat Graphs # 1 / # 2 / # 3.

(B) Industry Group: Automotive, Consumer Goods, Power, Telecom., $\vdots$

For each Industry group, repeat graphs # 1 / # 2 / # 3 / # 4.

(C) Edu. Qualification - Groups:

Engineers
Chartered Accountants
Co. Secretaries
Commer 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.

$\text{This data not available in Annual Reports}$ $\longrightarrow$ $\text{Vs}$ $\text{Vs}$

Repeat all graphs "posting-location" wise to bring-out "Regional Disparities (Differences)" for

same Edu. group
" " Age
" " Designation
" " Industry
" " Experience
" " Function (e.g. Mfg / Mktg / Sales / Finance / Personnel & Adm / R&D etc)

Besides the above-mentioned analysis, one could also analyse different "sub-groups" within the total Compensation-Package. These are

$\left.\begin{array}{l}\text{Annual Report} \\ \text{Data gives} \\ \text{only "TOTAL"} \end{array}\right\}$

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 than other regions
North have more "allowance %"

Telecom Ind. has more Perks. etc etc

What Companies are offering "loans"?
" " " " "Co-flats"?
What are "tax-free" components?
What are "trends" in Specific allowances

e.g.

Uniform allow / attire allow
Edu "
Lunch / Canteen "
Travel "
Entertainment "
HRA "
CCA "
LTA "
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 grows, accuracy will also improve.

13/12/96

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Friday, 13 December 1996

COMPENSATION SURVEY OR COMPENSATION ANALYSIS

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