Download - Market research project for IRMA placement
IRMA PRM 35
PLAC
EMEN
T OF
FICE IRMA
PRM 35
BY:
GROUP 8SECTION B
Allocation of Project
Qualitative Techniques
Quantitative Techniques
SegmentationPositioning
Utility determination
Suggestions to Placement Office
Objective: To give the submissions to IRMA Placements Office regarding the jobs valued and preferred by participants based on the detailed research conducted among PRM 35 participants
Sampling Plan:• Simple random sampling• 74 sampling size
K means Clustering
Factor Analysis
Conjoint analysis
RO
AD
MA
P
QU
ALI
TAT
IVE
AN
ALY
SIS
ENGINEER ARTSCOMMERCEAGRISCIENCE
Important Parameters
Qualitative Analysis of Interview Major factors/parameters for choosing a company during placements
Expectation from IRMA Placements• Organization pool to be increased with more emphasis on Government
organizations
Feedback/suggestions for IRMA Placement Office• Government organizations to be invited• Conduct resume-building workshops• Maintain Transparency & Neutrality in placements• Students should decide which company will come for placements and in what
order• IRMA placements must occur before other B-schools’ Placements
Job Profile Sector
Salary Career growth
Location Work flexibility
Brand Organizational values
Insights From Interview
Agribusiness15%
CSR22%
Microfinance15%
NGO11%
Livelihood11%
Dairy7%
Govt11%
Social enterprise4%
Others4%
Sectoral Preference
Tier 231%
District38%
Tier 119%
Tier 36%
Village/ Block6%
Location Preference
Market21%
Adhocracy21%
Clan43%
Hierarchy14%
Work-culture Preference
Sales9%
HR9%
Marketing23%
Microfinance27%
Supply Chain18%
Operations5%
Others9%
Specialization Preference< 6 Lakh
9%
6 - 8 Lakh55%
> 8 Lakh36%
Min-package Preference
7 - 9 Lakh86%
> 9 Lakh14%
Average-package Pref-erence
Undecided37%
Higher Studies27%
Career Growth27%
Civil Services9%
Future Goals
SEGMENTATIONQUA
NTI
TATI
VE A
NAL
YSIS
Basis Variables for Segmentation
Standard Deviation of Basis Variables
Std. Deviation
Diverse job profiles from organizations 1.51Branches/Offices 1.44Sponsoring higher education 1.33Entry position in the organization 0.93Compromise on your preferred designation 1.68
Higher preference to other factors in comparison to “preferred sector” 1.50
Join an organization where no IRMA alumni have worked in the past 1.41
Alumni feedback 1.11Pre-Placement Talks 0.97Perks and other benefits 0.85Bond or contract 1.59Job profile 1.04Designation 1.89Attrition rate in the organization 1.10Notice Period 1.56
Basis Variables (selected)
Diverse job profiles from
organizations
Designation
Bond/ Contract
Notice Period
Market trend impacting preferred sector
Descriptive Variables
Package
Location
Language
Work experience
Gender
Age
Educational Background
Verification of chosen basis variablesTotal Variance Explained
Component
Initial Eigenvalues Extraction Sums of Squared Loadings
Total% of
VarianceCumulative
% Total% of
VarianceCumulative
%1 1.611 20.134 20.134 1.611 20.134 20.1342 1.549 19.366 39.500 1.549 19.366 39.5003 1.272 15.899 55.400 1.272 15.899 55.4004 1.005 12.564 67.963 1.005 12.564 67.9635 .880 11.003 78.966 6 .742 9.272 88.238 7 .619 7.744 95.981 8 .321 4.019 100.000
We have taken only those basis variable. Whom standard deviation is greater than 1.40. Eight components are taken in Diverse job profile from organizations, designation, Bond/
contract, Notice period, Market trend impacting the choice of preferred sector, Branches, Higher preference to other factors in comparison to “preferred sector” and Join an organization where no IRMA alumni have worked in the past.
Initial five basis variables are explaining 78.966% of variance. So we taken only those basis variables for clustering.
So we did clustering on Diverse job profile from organizations, designation, Bond/ contract, Notice period and Market trend impacting the choice of preferred sector.
Number of ClustersOmega Values
Number of Clusters Pooled VRC Omega values
2 87.282 3 109.449 -56.574 75.049 46.925 87.574 -14.036 86.065 -4.037 80.527 16.828 91.805 -35.079 68.014
1 2 3 4 5 6
-80.00
-60.00
-40.00
-20.00
0.00
20.00
40.00
60.00
Omega Graph
Axis
Title
Number of clusters = 3
Scree Plot – Data
Cluster number 2 3 4 5 6 7 8 9
Inter cluster distance 2.94 3.70 3.78 3.86 4.25 4.31 4.52 4.71
Intra cluster distance 3.23 2.87 2.80 2.63 2.42 2.32 2.21 2.15
Ratio (Intra/Inter) 1.10 0.78 0.74 0.68 0.57 0.54 0.49 0.46
1 2 3 4 5 6 7 80
0.2
0.4
0.6
0.8
1
1.2
Scree Plot
Number of clusters = 3
Cluster Membership
1 2 3Cluster
0.0005.000
10.00015.00020.00025.00030.00035.000
Number of Cases in each Cluster
Total number of respondent is 74. Cluster number 1 has maximum number of members 29. Cluster number 2 has 23 members. Cluster number 3 has 22 members.
Inter-Cluster Comparison C 1 C 2 C 3
Package8 to 10 Lakh average
packagehighest # (14/29)
highest # (12/23)
highest # (9/22)
Preferred functional area
1st mkt (10/29) mkt (7/23) mkt (7/22)
least preferred Sales, Op, IT – 1 IT, Sales – 0 Sales – 0
Work experience
# of fresher highest # (15/29)highest # (12/23)
highest # (8/22)
1 to 2 years 4/29 min (3/23) max (5/22)
2 to 3 years max (7/29) min (3/23) 5/22
Home statenot preferring home state
as work locationmin (11/29) max (15/22)
Tier City you like to work
Preferring Tier 2 city highest # (18/29)highest # (12/23)
highest # (14/22)
Individual Cluster Profiling
Cluster 1 Features Package 6 to 8 lakh 8 to10 lakh > 10 Lakh
Functional Area Marketing 2 6 2
Work Ex Fresher 3 9 3
Job Location Tier2 7 8 3
Job Location
Tier1 Tier2 Tier3
Work Ex Fresher 5 10 0
Home Town Job Yes 6 12 0
Alien to Local Language Yes 3 10 0
Functional Area
Marketing Finance HR General Management
Tier2 6 1 3 5
Fresher 5 4 2 3
Cluster 2 Features Package 6 to 8 lakh 8 to10 lakh >10 Lakh
Functional Area Marketing 1 3 3
Work Ex Fresher 3 6 3Job Location Tier2 3 8 1
Job Location Tier1 Tier2 Tier3
Work Ex Fresher 4 8 0
Home Town Job No 6 8 0
Alien to Local
LanguageYes 9 9 0
Functional Area
Marketing Finance General Management
Work Ex Fresher 5 3 1
Job Loc Tier2 5 1 3
Cluster 3 Features Package
6 to 8 lakh 8 to10 lakh > 10 LakhFunctional
Area Marketing 1 3 3Work Ex Fresher 1 3 4
Job Location Tier2 4 8 2
Job Location Tier1 Tier2 Tier3
Work Ex Fresher 4 4 0
Home Town Job No 6 9 0Alien to
Local Language
Yes 3 4 0
Functional area
Marketing Finance OperationsGeneral Manage
ment
Count Count Count CountFresher 4 2 1 1
Tier2 2 2 5 4
Selected Conjoint Attributes For Partitioning
Package Sector Functional Area Job LocationAttribute
0.0005.000
10.00015.00020.00025.00030.00035.00040.00045.000
Importance Value
We got these importance value of attribute through conjoint analysis. We choose package and sector as basis variable for partitioning of data. This will help us to verify number of segments in our data.
Partitioning based on Conjoint Attribute
Cluster No. Pooled VRC Omega
2 244.786
3 396.471 -416.899
4 131.257 325.930
5 191.973 -49.993
6 202.696 -50.634
7 162.786 78.400
8 201.275 10.147
9 249.912
1 2 3 4 5 6 7
-500
-400
-300
-200
-100
0
100
200
300
400
Basis Variable
Package
Preferred Functional Area
POSITIONING
ITC
RGAVP
AKRSP
YES BANK
SBI
DHARMA LIFE
ESCORTS
GCMMF
PWC
S. No.
Sector Organizations
1Co-Operatives & Associated Organizations
GCMMF
2Government Development Agencies
RGAVP
3Non- Government Development Organization
AKRSP
4 Agri-finance & Microfinance Yes Bank, SBI
5 Social Enterprise Dharma Life
6 Technology & Consultancy PWC
7Agribusiness & Rural Marketing & CSR
Escorts
ITC
Attributes
Brand Reputation
Job Profile
Package
Career Growth
Job Stability
Job Satisfaction
Selection Procedure
Work Location
Work Culture
Selected Organizations & Attributes
Cluster 1:- Total Variance ExplainedTotal Variance Explained
Component
Initial EigenvaluesExtraction Sums of Squared
LoadingsRotation Sums of Squared
Loadings
Total% of
VarianceCumulativ
e % Total% of
VarianceCumulativ
e % Total% of
VarianceCumulativ
e %1 4.445 55.568 55.568 4.445 55.568 55.568 2.835 35.435 35.4352 .942 11.774 67.342 .942 11.774 67.342 2.553 31.907 67.3423 .713 8.912 76.253 4 .619 7.741 83.995 5 .548 6.846 90.841 6 .310 3.878 94.719 7 .221 2.766 97.485 8 .201 2.515 100.000
As 2 factors are explaining 67.342% of variance. So we taken only two components for making of perceptual map.
Rotated Component Matrix
Rotated Component Matrixa
Component
1 2Brand Reputation
.121 .894
Job Profile .362 .732
Package .378 .701Job Stability .364 .621
Job Satisfaction .757 .388
Selection Procedure
.681 .254
Work Location .809 .243
Work Culture .850 .257
Brand reputation, Job profile, Package and Job stability are forming one component of perceptual map.
Job satisfaction, Selection procedure, Work location and Work culture are forming second component of matrix.
Good Brand Reputation
Good Work Culture
Sector Company Brand Reputation Work Culture
Agribusiness & Rural Marketing & CSR ITC High Mild
Agri-finance & Microfinance Yes Bank High Mild
Non- Government Development Organization AKRSP Low Mild
PERCEPT
UA
L MA
P
Cluster 2:- Total Variance ExplainedTotal Variance Explained
Component
Initial EigenvaluesExtraction Sums of Squared
LoadingsRotation Sums of Squared
Loadings
Total% of
VarianceCumulativ
e % Total% of
VarianceCumulativ
e % Total% of
VarianceCumulativ
e %1 3.018 60.358 60.358 3.018 60.358 60.358 2.176 43.528 43.528
2 .826 16.528 76.886 .826 16.528 76.886 1.668 33.359 76.886
3 .517 10.331 87.218
4 .433 8.663 95.881
5 .206 4.119 100.000
As 2 factors are explaining 76.886% of variance. So we taken only two components for making of perceptual map.
Rotated Component Matrix
Rotated Component Matrixa
Component
1 2Brand reputation .918 .126
Job Profile .873 .311
Job Stability .207 .833
Job Satisfaction .247 .813
Work Culture .684 .447
Brand reputation, Job profile, and work culture are forming one component of perceptual map.
Job satisfaction and job stability are forming second component of matrix
High Job Satisfaction
High Brand Reputation
Sector Company Brand Reputation Job Satisfaction
Agribusiness & Rural Marketing & CSR ITC High Mild
Agri-finance & Microfinance Yes Bank High Low
Non- Government Development Organization AKRSP Low Mild
PERCEPT
UA
L MA
P
Cluster 3:- Total Variance Explained
Total Variance Explained
Component
Initial EigenvaluesExtraction Sums of Squared
LoadingsRotation Sums of Squared
Loadings
Total% of
VarianceCumulati
ve % Total% of
VarianceCumulati
ve % Total% of
VarianceCumulati
ve %1 3.625 51.779 51.779 3.625 51.779 51.779 2.571 36.726 36.726
2 .892 12.742 64.521 .892 12.742 64.521 1.946 27.795 64.521
3 .723 10.327 74.848
4 .638 9.118 83.966
As 2 factors are explaining 64.521% of variance. So we taken only two components for making of perceptual map.
Rotated Component MatrixRotated Component Matrixa
Component
1 2Brand reputation .894 -.031
Job Profile .605 .391Job Stability .654 .305
Job Satisfaction .451 .734
Selection Procedure
.073 .886
Work Location .567 .485Work Culture .669 .374
Brand reputation, Job profile, job stability, work location and work culture are forming one component of perceptual map.
Job satisfaction and selection procedure are forming second component of matrix
Brand Reputation
Transparent Selection Procedure
Sector Company Brand Reputation Selection Procedure
Agribusiness & Rural Marketing & CSR ITC High Less Transparent
Agri-finance & Microfinance Yes Bank High Moderately Transparent
Non- Government Development Organization AKRSP Low Transparent
PERCEPT
UA
L MA
P
CONJOINT ANALYSIS
Attribute Levels
PackageLess than 7 Lakhs
7 to 10 lakhs
More than 10 lakhs
Sector
Agribusiness & Rural Marketing
Development
Microfinance
Others
Functional Area
Finance
Marketing
Other
Job LocationHome State
Other
Total 4 attributes were taken. Total number of levels are 12.
Total number of possible card: 3*4*3*2=72
Used orthogonal design to generate cards.
16 experimental card, 2 hold out cards were generated.
Conjoint Design
Generated Cards
Card ID Package Sector Functional Area Job Location Rate
1 More than 10 lakh Agribusiness & Rural Marketing Finance Home State
2 Less Than 7 Lakh Development Finance Home State
3 More than 10 lakh Microfinance Other Other
4 Less Than 7 Lakh Microfinance Finance Home State
5 7 to 10 Lakh Others Finance Other
6 7 to 10 Lakh Agribusiness & Rural Marketing Finance Other
7 Less Than 7 Lakh Development Finance Other
8 Less Than 7 Lakh Microfinance Finance Other
9 More than 10 lakh Others Finance Home State
10 7 to 10 Lakh Development Other Home State
11 Less Than 7 Lakh Agribusiness & Rural Marketing Marketing Home State
12 7 to 10 Lakh Microfinance Marketing Home State
13 Less Than 7 Lakh Others Other Home State
14 Less Than 7 Lakh Others Marketing Other
15 More than 10 lakh Development Marketing Other
16 Less Than 7 Lakh Agribusiness & Rural Marketing Other Other
17 7 to 10 Lakh Microfinance Finance Other
18 Less Than 7 Lakh Development Other Other
Utility Score for Cluster 1
Utilities
Utility Estimate
Package
Less Than 7 Lakh -0.857 to 10 Lakh 0.152
More than 10 lakh 0.695
Sector
Microfinance -0.14
Agribusiness & Rural Marketing 0.235Development 0.183
Others -0.28
Functional Area
Finance -0.15Marketing 0.241
Other -0.1Job Location
Home State 0.17
Other -0.17(Constant) 4.695
More than 10 lakhs is most preferred level in package. Agribusiness is most preferred sector. Marketing is most preferred functional area. Home state is preferred job location.
Utility Analysis for Cluster 1
Package Sector Functional Area
Job Location0.000
5.000
10.000
15.000
20.000
25.000
30.000
35.000
40.000
35.328
25.125
29.672
9.875
Average Importance of Cluster 1
Attribute Levels Max Utility Score Levels Min Utility Score
Package > 10 lakhs 0.695 <7 Lakhs -0.85
Sector Agribusiness and RM 0.235 Other -0.28
Functional Area Marketing 0.241 Finance -0.15
Job Location Home State 0.170 Other -0.17
Constant 4.695 4.3695
Total Utility 6.036 2.9195
7 to 10 Lakh p.a. 0.152
Agri-business & Rural marketing
0.235
Marketing 0.241
Home state 0.17
Constant 4.695
Total utility 5.493
Simulation Cases
Correlation
Correlations
Value Sig.Pearson's R .970 .000
Kendall's tau .906 .000
Kendall's tau for Holdouts 1.000
As we can see here high correlation is observed between estimated and observed preferences.
Utility Score for Cluster 2
More than 10 lakhs is most preferred level in package. Agribusiness is most preferred sector. Finance is most preferred functional area. Home state is preferred job location.
Utilities
Utility EstimatePackage Less Than 7 Lakh -.891
7 to 10 Lakh .043More than 10 lakh .848
Sector Microfinance -.103Agribusiness & Rural Marketing .201
Development -.049Others -.049
Functional Area Finance .014Marketing .009
Other -.024Job Location Home State .027
Other -.027(Constant) 4.572
Utility Analysis for Cluster 2
Package Sector Functional Area
Location0.000
10.000
20.000
30.000
40.000
50.000
60.000
50.000
13.043
26.087
10.870
Average Importance for Cluster 2
Attribute Levels Max Utility Score Level Min Utility Score
Package >10 lakhs 0.848 <7 Lakhs -0.891
Sector Agribusiness and RM 0.201 Others or Development
-0.049
Functional Area Finance 0.14 Other -0.24
Job Location Home State 0.27 Other -0.27
Constant 4.572 4.572
Total Utility 6.031 3.672
7 to 10 Lakh p.a. 0.043
Development -0.049
Marketing 0.009
Other -0.027
Constant 4.572
Total Utility 4.548
Simulation Cases
Correlation
Correlations Value Sig.
Pearson's R .978 .000Kendall's tau .814 .000
Kendall's tau for Holdouts 1.000
As we can see here high correlation is observed between estimated and observed preferences.
Utility Score for Cluster 3 More than 10 lakhs is most preferred level in package.
Agribusiness is most preferred sector. Marketing is most preferred functional area. Home state is preferred job location.
Utilities Utility Estimate
Package Less Than 7 Lakh -.8907 to 10 Lakh .184
More than 10 lakh .706Sector Microfinance -.219
Agribusiness & Rural Marketing .361Development .111
Others -.253Functional Area Finance -.299
Marketing .422Other -.123
Job Location Home State .071Other -.071
(Constant) 4.516
Utility Analysis for Cluster 3
Package Sector Functional area
Location0.000
5.000
10.000
15.000
20.000
25.000
30.000
35.000
40.000
45.000
39.019
27.18024.001
9.800
Average Importance for Cluster 3
Attribute Levels Max Utility Score Levels Min Utility ScorePackage >10 lakhs 0.706 <7Lakhs -0.89
Sector Agribusiness and RM
0.361 Other -0.253
Functional Area
Marketing 0.422 Finance -0.299
Job Location Home State 0.071 Other -0.071Constant 4.516 4.516
Highest Utility 6.121 3.003
7 to 10 Lakh p.a. 0.184
Microfinance -0.219
Marketing 0.422
Other -0.071
Constant 4.516
Total Utility 4.832
Simulation Cases
Correlation
CorrelationsValue Sig.
Pearson's R 0.988 0Kendall's tau 0.862 0
Kendall's tau for Holdouts 1 .
As we can see here high correlation is observed between estimated and observed preferences.
Package Sector Functional are Job location
35.328
25.125
29.672
9.875
40.971
26.126
23.759
9.144
39.019
27.180
24.001
9.800
Importance Values Cluster 1 Cluster 2 Cluster 3
Inter-Cluster Comparison
Suggestions to Placements OfficeOur Findings:
• Most preferred sector across all 3 clusters: Agri-business companies
• Most preferred functional area across all 3 clusters: Marketing, Finance and General
Management
• Most preferred work location across all 3 clusters: Tier 2
• Package preference across all 3 sectors range from Rs.8 L to Rs.10 L
THANK YOU