The Indian Business Process
Outsourcing Industry:
An Evaluation of Firm-Level
Performance
Arti Grover
Delhi School ofEconomics
Agenda
◈ Background
◈ Theoretical Models
◈ Data
◈ Preliminary Analysis
◈ Econometric Model
◈ Empirical Results
Introduction
◈
Motivation:
• No theory of BPO Firm: Pre-cursor to build a theory of BPO firm
• Outline the factors that impact the performance of a typical service provider
firm
◈ Importance:
Macro perspective
• Key to the expansion of the global offshoring industry:
• BPO industry makes a crucial contribution to the host economy through trade.
Micro perspective
• Buyer: If the factors determining the performance of the supplier are known,
then an increase in the vendor’s efficiency is an additional source of productivity
for the client.
• Supplier: For optimal resource allocation, it is crucial to know how a change in
one variable filters through the organization to affect the bottom-line
performance.
Introduction
◈ Theoretical Framework:
Aghion et al (1999):
• Firms in BPO industry provide differentiated services and thus fit in the
Monopolistic Competitive set up
• BPO firm leverage technologies to provide services
• Needs to update technology to improve service quality
• Factors: VC funded firms, Fixed Cost of Operations, High variable /Labor
Costs, Seat Utilization, No. of Clients
Arora and Asundi (1999)
• Impact of Investment in Quality (ISO Certification)
• Quality Effect and Signaling Effect
• Other Factors with similar effect: Number of plants/locations (Additional
signaling effect of BCP), Information Security Certifications, Quality measure:
Degree of Specialization – Voice based services (Wipro, Technovate)
Introduction
◈ Theoretical Framework:
Antràs (2005)
• Which organizational form (captive or TPV) has higher productivity
◈ Data:
Firm Level:
• CMIE, CRIS INFAC, DqIndia, Voicendata, NASSCOM
Aggregate Data:
• NASSCOM
Preliminary Analysis: Partial Correlations
Preliminary Analysis: Partial Correlations
Empirical Specification
◈
Productivity Measure: Revenue per employee - Arora and Asundi (1999) ,
Aron, Yeaple (2003), Idson, and Oi, (1999), Bernard and Jensen, (1999) and
Bernard, Jensen, and Schott, (2003)
◈
Based on Aghion et al (1999), Arora and Asundi (1999)
    1VC   2Operational Cost Variables   3 y
  4 SignalingVariables   5 Experience factor  
◈
To ensure that results are invariant to estimation procedure:
Number of Clients determined endogenously with revenue per employee
y     1 SignalingVariables   2   
Empirical Results
◈
Ordinary Least Squares: BPO Firm Performance
Empirical Results
◈
Testing for Normality
8
Series: Residuals
Sample 1 22
Observations 22
6
Mean
Median
Maximum
Minimum
Std. Dev.
Skewness
Kurtosis
4
2
Jarque-Bera
Probability
0
-4
◈
-3
-2
-1
0
1
2
Testing for Heteroskedasticity
3
4
5
0.006820
0.141564
4.922343
-3.619899
1.989774
0.074041
3.420573
0.182242
0.912907
Empirical Results
◈
Ordinary Least Squares: Number of Clients
Firm Models – Resembling BPO Firms
Aghion et al (1999) – Endogenous growth model
Intermediate Good Supplier
Profit Maximizing
• Self
◈
Funded BPO
Non-Profit Maximizing
• VC funded or outside source of finance
Similarity with Input suppliers of Aghion et al
- Firms in BPO industry provide differentiated services and thus MC model
is fit
- BPO firm leverage technologies to provide services: BPM combines
management and implementation technologies like BPMS
- Needs to update technology to improve service quality
Aghion et al (1999)
◈
Examples from BPO:
•
•
Initial VC funded firms – Infowavz and Tracmail
Fixed Cost of Operations/Technology Acquisition: Lowers T –
Example from
BPO – Voice Based Processes (Wipro Spectramind made a concious
decision to lower from 84% to 60% in 1.5 yrs)
•
•
•
High variable /Labor Costs: Lowers T -- expected profit from
adoption and the cost of adoption rises – Evidence from BPO –
High Attrition rates (Voice versus Non Voice, 50-55% versus 30-35%
eg. GE, Wipro)
Suggestion: Increase Shift Utilization – Lowers operational Costs
Sell to more number of clients – Example - IBM Daksh
Model
Attracting Clients – Arora and Asundi (1999)
   p z    w  N z  
◈
Profit Function:
◈
Impact of investment in quality:
N z  
  p z   

 N z     p z    w 
z
z
z

 



 
Quality Effect
◈
-
Signaling Effect
Other variables which have similar effect:
Number of plants/locations (Additional signaling effect of BCP)
Information Security Certifications
Quality measure: Degree of Specialization – Voice based services (Wipro,
Technovate, Trinity Focus), change demand induced
Organizational Structure – Antràs (2005)
◈
Demand Function:
y  p
1
1
 x 
y   h 
 1 z 
1 z
 xl

 z



z
◈
Production Function:
◈


Difference between Captive and TPV:      1     
◈
Final good Producer maximizes:     p. y   w N x h
◈
Profit Maximizing Price:
◈
w  w 

N 1z
p
S z
  1z (1   )z
Technology adoption, Spillovers higher for high-tech industries: Denny,
Bernstein, Fuss, Nakamura & Waverman (1992)
Organizational Structure – Antràs (2005)
Captives have higher productivity:
Large Size – Amass larger capital for Investments
Attract better talent – brand name
Captives of International BPO Players: Convergys, Accenture, Sitel
BPO arms of IT Outsourcing firms/Indian Business Houses: Progeon,
Zenta, Epicenter
Export Revenue by Organizational Mode
5000
Export Revenue ($m)
◈
◈
◈
◈
◈
Third Party
Captives
4000
3000
2000
1000
0
2000-01
2001-02
2002-03
2003-04
2004-05
2005-06 Year
Empirical Specification
◈
Importance of the Study: All firms
◈
Importance of the Study: Domestic TPV