The core purpose of “Analytics
connect “is to give a brief overview
of Analytics. Data is the
prerequisite for any analytical
activity, and it has to be clean and
accurate. The more accurate is the
information, the better insight
would be. To get the competitive
edge out of the analytical
recommendation, all the
contributing factors responsible
has to be thoroughly studied and
analyzed. Any “miss” has direct
impact on the quality of
recommendation.
Analytics connect
Analytics provides the
business with the cushion time
to meet the actual scenario
with optimum service level.
It’s not only improves your
cash flow, rather it also
provide signal well in advance
so that business take
appropriate measure in
terms of aligning their
strategy with their target, and
making best decision upon
their working capital.
“In God we trust, all others must bring data”
-
W Edwards Deming
“There is a striking correlation between an organization’s analytics sophistication an competitive
performance”
“The biggest obstacle to adopting analytics is lack of knowhow about using it to improve the business”.
- 10 insights: A first look at the new intelligent enterprise
survey on winning with data, MIT Sloan Management review Vol. 52, No1, 2010
What is Analytics and BI
“Science of Analysis.”
“Analytics is the science of examining raw data with the purpose of drawing conclusions from the information.
Analytics is used in many industries and functions to allow companies and organization to make better business
decisions and in the sciences to verify or disprove existing models or theories.”
“The purpose of analytics is to take existing data collected from either a single source or multiple sources and use it
to arrive at the optimal decision. Essentially, analytics can be best defined as a science of analysis.”
“Business intelligence is the ability of organization generate knowledge”
Analytics makes the difference (Company - ABC Inc.)
Business Intelligence: Customer retention (75%)
Business Analytics: Factors that influence customer retention (Why customer retention is only 75%
and how to increase it to say 85%).
Analytics & Companies stake
Gartner Says Worldwide Business Intelligence, Analytics and Performance Management Software Market
Surpassed the $10 Billion Mark in 2010.
Business analytics market grew at 11.2%, and currently at $19.3 billion.
A recent study by Gartner predicted advanced analytics as one of the top 10 strategic technologies for businesses in
2011. IBM has invested over 15 billion dollars in the last 4 years to acquire more than two dozen companies in the
field of business analytics.
Wipro is acquiring Promax Applications Group (PAG), an Australia based analytics company, for 35 million
Australian dollars.
Oracle bought Hyperion for $3.3 billion; SAP acquired Business Objects for $6.8 billion; and Microsoft purchased
Fast Search and Transfer for $1.2 billion.
There have been several other smaller deals too. Even Twitter admitted recently that analytics has become “an
increasingly crucial part of improving our service” and acquired Smallthought Systems, the company behind an
analytics service called Trendly that tracks real-time changes and user trends for website owners.
Why analytics?
Though analytics is not a new field, it has shot up in popularity in the last decade or so.
Businesses have woken up to the power of analytics and more and more enterprises are moving to what is being
termed as ‘fact-based decisioning’.
There are three main reasons behind this phenomenal shift in businesses towards analytics and reliance on data over
intuition.
1. There is a lot more data now than there used to be. 1.2 trillion gigabytes of data was produced in 2010
and it will double in the next 18 months and double again in the eighteen months after, and so on. Wal-Mart,
a retail giant, handles more than 10 million customer transactions every day. The data generated by these
transactions feeds into Wal-mart’s gigantic databases that hold over 2.5 million gigabytes of information
already. Google processes million gigabytes of information every hour.
2. Lot more data is being collected and stored. Storage costs have gone down at an astonishing pace in the last 2
decades. In 1990, the cost of storing 1GB of data was around $9000. In 2010, this has come down to a mere 8 cents.
Costs have gone down by more than 100,000 times in 20 years. This is what has really fuelled the growth in
analytics, allowing businesses to store gigantic amounts of information at a reasonable cost. See this website that has
captured the fall of storage costs since 1956.
3. Analytical tools have become more user-friendly and better at dealing with large data. With faster processing
power and more sophisticated tools, users are able to sift through larger mounds of data and apply complex statistical
techniques to draw insights enabling them to make better decisions on the fly.
More data is being produced. More data is being stored. More data is being analyzed by businesses using better tools
and statistical techniques. All of these factors are leading to better predictions being made. Better predictions mean
better results and hence the growing popularity of analytics in business.
What can analytics do for businesses?
Analytics is enabling a shift in how businesses support operational decisions: from intuition to data-driven. It is
becoming possible to run simulations or create models to provide insights and predict the future, rather than to simply
describe what happened in the past, and to do this in real-time to support each individual business action.
Thus, analytics enables businesses to make better, more informed decisions and compete more successfully.
Marriott International
 A successful revenue management system has helped Marriott to achieve strong financial
performance.
 Marriott’s analytics tries to identify most profitable customer through its rewards program.
 Marriott earned $4 billion through its web analytics
Capitol one
 Capitol One runs over three hundred experiments per business day to target individual
customers
 Increased customer retention to 87% and lowered the cost of acquisition by 83%.
 The value of capitol one’s stock has increased by more than 1000% over 10 year period.
Google Analytics
 Provides analytics as a service to everyone with a website.
 Google analytics helps advertisers to maximize their hit rate!
Analytics in Sports
 A C Milan uses predictive models to prevent injuries to its players
 Oakland athletics use Analytics for Team selection (Won 4 super bowls between 2000 and 2008.)
 Customer Life Time Value is used by many baseballs teams in US to identify profitable customers.
Three pillar of analytics approach
Measurement frame work: How I am I doing, as is process. How is company performing? What are the
current strategic goals and priorities and what metrics to measure success or failure towards those goals? Can
these metrics be aligned with stated priorities, goals and strategies?
Portfolio analysis: what are my business dynamics drivers of business? What are your business dynamics?
How do your products perform in the marketplace? What is the driver of business, and how does it relate to
company strategies and priorities?
Customer analysis: Who are my customers, how do I engage them, how can I communicate my analysis to
customer. What do they want? How do they behave? These are the crucial questions in your customer analysis.
Basic questioning along these lines will create several categories for them.

Demographics: What are your customer demographics? The relevant demographic metrics will depend
on your specific product/service, i.e. gender may or may not matter, or all of your customers may even
be of the same gender or age group.

Needs: Determine your customers’ needs. Do they have a feature need incremental to
your current product? Do the customers need installation or operating support?

Behaviors: You can look at how your customers behave. Do they pick up your product
at a warehouse or retail outlet? How many are convenience seekers always going for
fastest shipping etc.? Are they mail catalog subscribers?
There should be direct connection between the business and dashboard. Too many dash boards which
basically doesn’t relate to the business objective is irrelevant, so understanding the specific business need is
very important
There are two important aspect of looking at the data from analytics point of view


Metrics: the numbers that measures the characteristics of the past.
Predictive: Way to estimate what will happen in the future.
Metrics are classified into 2 types:1. Process metrics: A metric used to measure the characteristic of the methods, techniques & tools
employed in developing implementing & maintaining the software system.
2. Product metrics: A metric used to measure the characteristic of the documentation & code characteristic.
Metrics is an accurate no., since it is based on the actual data, where as the predictive has a certain
percentage of the accuracy e.g. forecast accuracy of best in class industry is 78.7%.
Analytical approach Hierarchy
1
Standard Report (What Happened? When did it happen?)
2
Ad HOC Reports (How Many? How Often? Where?)
3
Query Drill down (Where exactly is the problem? How do
I find the answer?)
4
Alerts (when should I react? What actions are needed
now?)
5
Statistical Analysis (Why is it happening? What
opportunities am I missing?
6
Forecasting (what if this trend continues? How much is
needed? When it will be needed?)
7
Predictive modeling (what will happen next? How will it
affect my business?)
8
Optimization (how do we do things better? What is the
best decision for complex problem?)
Functional Domain of Analytics






Supply Chain
Marketing and Sales
Media
Web
Finance and Accounting
Human Resource
Analytics Technique
T
E
C
H
N
I
Q
U
E
S
Analytics Problems
Analytics and Academia
Business has recognized the power of analytics and it is time academia did the same. Today’s business
managers need to learn how analytics can help them make better business decisions that can generate better
business outcomes.
 They need to have an understanding of the statistical concepts that can help analyze and simplify the
flood of data around them.
 They should be able to leverage analytical techniques like decision trees, regression analysis, clustering
and association to improve business processes.
 Finally, it is important for them to have first-hand experience of some of the most widely used software
like SAS, SPSS, COGNOS etc., and exposure to real-life business data.
Analytics programs in India
While India has become the global hub for analytics, there is an enormous shortage of programs offered by Indian
universities to train students for this field. Some of the leading MBA colleges have started to offer courses in
business analytics as part of the MBA curriculum. However, there are still very few specialized degree or certificate
programs available in this field. IIM Calcutta and recently started at IIM-Bangalore a rare exception, offers a 1 year
course in business analytics for professionals with at least 2 years of Work experience. In the US, North Carolina
based Institute for Advanced Analytics also offers a 1 year masters course in advanced analytics.
It is imperative that business education institutes recognize the emergence of business analytics as a powerful field
that is changing the way businesses are run. It is also important to understand the crucial role India is playing as the
global hub for analytic talent.
Education institutes, especially in the field of business administration, need to tailor their curriculum in recognition
of the growing importance of analytics and the shortage of skilled professionals in the field.
Every business is unique in terms of the kind of challenges it faces, the information it possesses and the
decisions it has to make. However, a manager who is aware of the scope of analytic applications for business is
able to leverage the power of data to make better business decisions.
Types of Qualification required in Analytics
Analytics requires high qualification, with a research oriented educational or professional background.
Master or PHD


Operations Research
Marketing sciences
Masters



Business management
Mathematics, Statistics
Econometrics, Finance
Others
Engineering, CPA, CFA
Professional Hierarchy & Career Growth
Manager (7+ Years)
Consultant (5-7 Years)
Senior Analyst( 2-4 Years)
Analyst (0-2 Years)
Masters
Analytics is a high growth field and salaries in analytics have been sky rocketing in the last few years. There is
a strong demand for “data-savvy” professionals in the industry today. As per a recent McKinsey research report,
the US alone faces a shortage of 140000 to 190000 people with “deep analytical skills” as well as a million and
half data-savvy managers and analysts who can deal with big data.
India ranked 3rd in the study – in terms of number of people available with analytical skills – behind the US and
China. Yet India has emerged as the global hub for analytics. This is because India has a steady supply of
English-speaking analytical talent.
Captive & Non-captive Analytics Company
Captive centers are those that are dedicated to a particular company. For example, those working for HSBC
analytics or Dell analytics will work exclusively on the HSBC or Dell business. On the other hand, an analyst
working in an analytics service company such as Manhattan, Symphony, Fractal Analytics, Genpact or
Marketelligent is likely to work across multiple businesses and clients. The latter work tends to be looked upon
as more rewarding since it is more varied in scope. To make up for this, captive centers usually offer slightly
higher salaries than non-captives.
Human Resource Analytics
Entire activity of HR Analytics is governed by the workforce. It offers an accurate estimate of the number of
employees required with matching skill requirements to meet organizational objectives. It is a forward looking
function as human resource estimates are made well in advance.
Analytics in Human resource revolve around different stages of maturity.
Maturity
1. Encourage sufficient
turnover to minimize
layoffs and provide
new openings.
2. Control
compensation costs.
3. Maintain flexibility
and skills of an aging
workforce.
Growth
1. Plan management
succession.
2. Establish formal
compensation structures.
3. Maintain employee
motivation, and morale.
Decline
1. Plan and
implement
workforce
reductions and
reallocations
Implement
2. Tighter cost
control.
3. Implement
retraining and
career
consulting
services.
Introduction
1. Attract best technical and professional talent.
2. Meet
or exceed
Attract
best labor market rates to attract
needed talent.
technical and
3. Define future skill requirements and begin
professional
establishing
career ladders.
talent.
HR Maturity Model
“Workforce Planning is the process that provides strategic direction to talent management activities to
ensure an organization has the right people in the right place at the right time and at the right price to
execute its business strategy“
Why HR Analytics/ Work Force Analytics?
External Challenges: Liberalization, privatization and globalization (LPG era) have created huge
demand for people in software, finance marketing, and manufacturing fields.
Organizational Decisions: Decisions such as expansion, diversification, and relocation leading to
demand for people possessing requisite skills
Workforce Factors: Such as retirement, resignation, and termination etc creating manpower gaps.
Basic Workforce Supply Model
Sources of Inflows

The Firm
Transfers
Current Staffing
Level
 Promotions

New Recruits

Recalls
Projected Outflows
Employees Out
Employees In

Promotions

Quits

Terminations

Retirements

Deaths

Current
staffing
level
–
Projected
ou tflows
this year
+
Projected
inf lows
this year
=
Layoffs
Firm’s internal
supply for this
time next year
Work Force Planning Process flow
Predictive Analytics as an emerging trend
Workforce Predictive Analysis
Workforce predictive analysis Step 1: Scan the External Job Market
Start developing a workforce strategy by looking outside of your company at what’s going on in work and
employment in your community. There are key pieces of workforce data you can gather:
External Factors Affecting Labor Supply




Unemployment rate
Graduation rates
Demographic makeup of local market
Knowledge of direct competitors
When reviewing these areas of the job market, you are looking for opportunities and threats. Is there an
especially large number of college grads coming into the job market in your geographic area who can fill entry
level office positions cheaply? Or, more specific to our current economic situation, is the job market saturated
with highly-skilled employees looking for work who you could be snapping up before the economy improves?
Workforce predictive analysis Step 2: Take an Internal Scan
Once you’ve taken a look at the workforce available to you, now is your chance to analyze the jobs that need to
be done in your organization and the skills of your current employees available to do them.
It’s important to take a look at the whole business and get a sense for all of your human resources needs. Here’s
a way to organize your research. Start with:
Jobs and Skills Required by the Organization




Jobs that exist now
Number of employees doing each job
Importance of each job
Characteristics of anticipated jobs
Once you’ve summarized your company’s human resource needs, take a look at the actual employees you have
available to you to fill those needs. Review your:
Organizational Capabilities


Detailed information about current employees and their capabilities (knowledge, skills and abilities)
Information about special expertise, mobility restrictions and specialized job qualifications
Workforce predictive analysis Step 3: Predicting Workforce Demand
Now that you know what you have available to you both inside and outside of your organization, it’s time to
take a guess at what human resources you’ll need down the line. And, before you head into this next step, keep
in mind that workforce planning and forecasting is an art, not a science. Your best approach is to be as informed
as possible and include others in the workforce planning process.
You will start by gathering some basic supply and demand information. First, gather information about the
possible demand for replacement of positions.
Possible Causes of Employee Replacement



Retirement trends
Turnover rate
Internal fill rates
Once you’ve gained a sense of which employees might be moving on or up in your organization over the
coming years, you should then gather information about the possible demand for new or evolved positions. To
research potential causes of new workforce demands in your company, go straight to the top. Meet with your
leaders and let them know that your goal is to understand the business and understand the business’s objectives.
This information will help you know what sort of new positions may be needed in the coming years.
Workforce predictive analysis Step 4: Predicting Workforce Supply
At this point, you have a good idea of what resources are available to you and what needs may come up. Now
you can drill down to the details of a plan for hiring for the coming years. Remember that workforce forecasting
should be done for the short term, intermediate and long term. Here are the practical steps:
Set a Realistic Timetable That Includes



Fill time for open positions.
Economic conditions and availability of labor.
Needed ramp time.
Take an Assessment of Internal Workforce Supply



Who’s in line to step up?
What are the training needs?
Are there succession plans in place?
Adjusting to Unexpected Changes in Workforce Supply and Demand
Once you have completed the steps above for forecasting your workforce supply and demand, you cannot sit
back and just hope that everything goes smoothly in the roll out of the plan. You next need to know how to deal
with unexpected changes to your workforce plans and how to keep consistent, company-wide interest in
following through with this HR plan.
In our future post, I will discuss dealing effectively with HR surplus, how to maintain support for your HR
workforce plan and give you a list of things to keep in mind so that you achieve success with forecasting
workforce supply and demand no matter what changes come.
Classification of Predictive analysis:
Trend Analysis – a quantitative approach to forecast future personnel needs based on extrapolating
information from historical changes.

Delphi Technique –forecasts and judgments of a group of experts are solicited and summarized to
determine the future of employment.

Impact Analysis –trends are analyzed by a panel of experts who then predict the probability of future
events.

Scenario Planning –creating future scenarios that differ radically from those created by extrapolation
of present trends
Commonly used workforce forecasting methods can generally be classified into two categories based
on the utilization of past data. Methods that do not rely on past data include employer’s survey
international comparisons and labor market signal analysis.
Work Force planning data analysis methods
Work Force Surplus/Deficit


Internal workforce supply exceeds the organization’s requirement or demand for personnel
Demand exceeds the current resources available in the organization's workforce
Determine NET HR Requirements
External supply requirements =
replacement + change supply components
Change supply =
hiring to increase (or decrease) the overall staffing level
Replacement supply =
hiring to replace all normal losses
External supply =
current workforce # x (replacement % per year + change % per year
Example: Surplus =
1000 x (4 % per year (0.04) + 2 % per year (0.02)
40 + 20 = 60
Need for 60 employees
Deficit =
1000 x (4% per year (0.04) + -7% per year (-0.03)
40 + -70 = -30
Need to reduce by 30 employees
Trend Analysis
Historical relationship between a business index (e.g., sales, contracts, units sold etc.) and the number
of employees required to achieve that index (labour demand)
Main idea of the method: a forecast is calculated by inserting a time value into the regression equation. The
regression equation is determined from the time-serieas data using the “least squares method”
The general equation for a trend line : F=a+bt
Where:
•
F = forecast, t –= time value, a = y intercept, b = slope of the line.
Regression Analysis
Y = dependent variable (HR demand)
A = constant (Y intercept)
B = slope of linear relationship between X and Y
X = independent variable (e.g. level of sales)
Regression Prediction
Y = A + BX
Y = dependent variable (HR demand)
A = constant (Y intercept)
B = slope of linear relationship between X and Y
X = independent variable (e.g. level of sales)
Example data:
X
Sales ($ Millions)
2.0
3.5
4.5
6.0
7.0
Y
# of Marketing Personnel
20
32
42
55
66
Calculate XY, X2, average X and average Y
X
Y
XY
Sales
($
Millions)
# of
Employees
X2
2
25
50
4
2.5
28
70
6.25
3.5
30
105
12.25
5
6.5
38
54
190
25
351
42.25
766
89.75
19.5
175
Average X = 19.5/5 = 3.9
Average Y = 175/5 = 35 N = 5
𝑋𝑌 − 𝑁 𝑋 (𝑌)
𝐵=
(𝑋2 ) − 𝑁(𝑋)2
Calculate the value of B (slope of the linear relationship between X and Y)
XY
X2
50
4
70
6.25
105
12.25
190
25
351
42.25
766
89.75
N = 5, Average X = 3.9, Average Y = 35
𝐵=
766−5 3.9 35
766−683
89.75−5 3.9
89.75−76.05
, 𝐵=
2
, 𝐵 = 6.09
Calculate A (constant or intercept)
Average X = 3.9, Average Y = 35 B = 6.09
IF Y = A + BX
, Then A=Y ̅- BX ̅, AND A = 35 – (6.09) (3.9) A = 11.23
Determine the regression prediction equation
Y = A + BX, A = 11.23, B = 6.09, Y = 11.23 + (6.09) (X)
Calculate predicted HR demand (Y) by inserting values for X
Predict the HR demand for personnel at $8 million and $10 million.
Y = A + BX
A = 11.23
B = 6.09
X = Sales ($M)
Y= 11.23 + (6.09) (X)
$8 million
$10 million
Y = A + BX
Y = A + BX
A = 11.23
B = 6.09
X=8
A = 11.23
B = 6.09
X = 10
Y = 11.23 + (6.09)(8)
Y = 11.23 + (6.09) (10)
Y = 59.99
60 Staff required
Y = 72.18
72/73 Staff required
Steps for Delphi Technique
•
Define and refine the issue or question
•
Identify the experts, terms, and time horizon
•
Orient the experts
•
Issue the first-round questionnaire
•
Issue the first-round summary and second-round questionnaire
•
Continue issuing questionnaire
Steps for the Nominal Group Technique
•
Define and Refine the Issue or Question and the Relevant Time Horizon
•
Select the Experts
•
Issue the HR Demand Statement to the Experts
•
Apply Expert Knowledge, State Assumptions, and Prepare an Estimate
•
Meet Face-to-Face
•
Discuss the Demand Estimates and Assumptions
•
Vote Secretly to Determine the Expert Demand Assessment
Scenario Planning
Provides a framework to consider what the future holds
•
Identifies new risks and challenges in the future - helps to prepare for the unexpected
•
Enables you to expand your vision and think of alternative futures
•
Most useful when there is limited clarity on the future
•
Helps to balance intuition, judgment and fact
•
Recognizes that forecasting is notoriously difficult
Where has it been used?
Private sector companies, eg, Shell, Body Shop,
•
NHS (National Health Service)
How do you do it?
•
There is no set approach - depends on organization, situation etc…
One approach to Scenario Planning
•
Identify issues and forces that will shape the service and/or care pathway over a defined period of time
•
Identify those that will have most impact
•
Identify those that give the most uncertainty
•
Identify 2 issues that cause most worry from this list and map against each other, taking a positive and
negative view of each one
•
Consider if there may be any wild cards coming into play
•
Then consider what it will look like in each of the scenarios you have created
–
Identify what this will mean for the service design
–
Identify what this will mean for the workforce
–
Identify what this will mean for service users
–
Identify what this mean for partners along the delivery chain
•
Are any common issues identified?
•
What are the risk factors that you need to mitigate against?
MARKOV ANALYSIS-1
•
Produces a series of matrices that detail the various patterns of movement to and from the various jobs
in the organization.
•
Determines the likelihood that an individual will display movement behaviors.
TO: 
A TRANSITION MATRIX
FROM:
TOP
MID
TOP
.80
.02
MID
.10
.76
.04
.06
.78
.01
.15
.01
.84
.15
LOW
LOW
ASSY
EXIT
.18
SKILL
ASSY
SKILLED
.10
.05
.88
.07
------------------------------------------
MARKOV ANALYSIS – 2
(Captures effects of internal transfers)
(Start = 3500)
FROM/ TO: 
TOP
100
MID
200
LOW
600
SKILL
600
TOP
.80
.10
A TRANSITION MATRIX
MID
LOW SKILLED
.02
ASSY
EXIT
.18
.76
.04
.10
.06
.78
.01
.15
.01
.84
.15
ASSY
2000
.05
.88
.07
--------------------------------------------------------END YR WITH:
NEED RECRUITS ?
NEED LAYOFFS ?
100
0
KEEP STABLE 100
190
482
10
118
610
240*
(10)*
200
600
1760
600
[358 left]
368 tot
(10) tot
2000 = 3500 Tot
MARKOV ANALYSIS – 3
(Anticipates Changes in Employment Levels)
Employment needs are changing. We need a 10% increase in skilled workers
(660), and a 15% decrease in assembly workers (1700) by year’s end.
------------------------------------------------------(Start = 3500)
A TRANSITION MATRIX
FROM/ TO: 
TOP MID
LOW SKILLED ASSY
EXIT
TOP
100
.80
.02
.18
MID
200
.10
.76
.04
.10
LOW
600
.06
.78
.01
.15
SKILL 600
.01
.84
.15
ASSY 2000
.05
.88
.07
--------------------------------------------------------END YR WITH:
100
NEED RECRUITS ?
NEED LAYOFFS ?
0
NEW LEVELS 100
190
482
610
10
118
50*
1760
[358 left]
(60)*
200
600
600
1700 = 3260 tot
TARGET STORES STAFFING FORECAST
MODEL
Y = 8 + .0011(X1) + .00004(X2) + .02(X3)
Y = Number of employees needed to staff the store
X1 = Square feet of sales space
X2 = Population of metropolitan area
X3 = Projected annual disposable income in millions of dollars
Y = 8 + .0011(50,000sq ft) + .00004(150,000popul) + .00000002($850 million)
Y = 8 + 55 + 6 + 17
Y = 86 employees needed at this store
VACANCY ANALYSIS
Historic departures used to project turnover
LEVEL
# EMPL
TURN %
Expected Vacancies
TOP MGMT
100
20 %
20
80
MID MGMT
200
24 %
48
152
LOW MGMT
600
22 %
132
468
SKILLED W
600
16%
96
504
ASSY WKRS
2000
12 %
240
1760
TOTALS
3500
536
2964
AVERAGE TURNOVER PERCENTAGE = 536 / 3500 =
Expected to Remain
.1531
References
http://www.gartner.com/hc/images/215650_0001.gif
IIM Bangalore programme “Business Analytics and Intelligence Course”:
Prof. Dinesh Kumar
http://www.analytics-magazine.org/
http://sloanreview.mit.edu/the-magazine/2010-fall/52115/10-insights-a-firstlook-at-the-new-intelligent-enterprise-survey/
www.senga.ca
http://www.payscale.com/hr/resources/hr-planningwebinars01?src=blog
Email: ramesh@samjna.com