Nasscom report on Analytics in India for which they had interviewed various buyers and suppliers in the industry

1. 1

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3. Foreword
India has over 1.2 billion people, over 890 million mobile subscribers, and 213 million internet subscribers. Along with 115 million
Facebook users and 24 million LinkedIn users, India is among the global Top 5 in terms of mobile consumers and social media usage.
India has over 200,000 factories and an estimated public and private sector employment of 29 million. Government of India is estimated
to have spent INR 280 billion on IT in FY2014. There have been over 1 billion eGov transactions and the government aims to achieve
600 million enrollments by 2014 under the Aadhar scheme.
It is therefore not surprising that India is generating loads of data, both structured and unstructured. It is estimated that the digital bits
captured or created each year in India is expected to grow from 127 exabytes to 2.9 zettabytes between 2012 and 2020. This highlights
the scope of applying analytics to this mountain of data and the myriad insights that it could throw up to enable newer and more relevant
services.
However, the level of adoption in India among enterprises is still low. While there are significant precedents, mainly in the telecom,
eCommerce and BFSI sectors, we have but scratched the tip of the iceberg.
Industrialising analytics among enterprises in India - that is integrating it into the organisational fabric - is still a long journey ahead.
There are challenges to be addressed both from the demand and the supply side – lack of awareness of what exactly is the return on
investment, endorsement from top management, cost of investment, data veracity, etc.
Keeping these issues in mind and with the aim of promoting adoption, NASSCOM, in partnership with Blueocean Market Intelligence,
has put together a report ‘Industrialisation of Analytics in India: Big Opportunities, Bigger Outcomes’. This report analyses the global
market size and trends, India’s current scenario, trends in the India market, factors driving adoption, customer expectations,
engagement models and challenges faced by both users and services/product firms.
More importantly, this report showcases global and India examples of how firms implemented analytics and the benefits gained; further,
it sets out a roadmap on what needs to be done by stakeholders involved to industrialise this technology within enterprises in India.
This report is the initial step taken by NASSCOM as part of its Analytics Interest Group (AIG) to create awareness for adoption of
Analytics in Enterprises. We hope you find this report useful.
Please share your feedback at research@nasscom.in.
R Chandrashekhar Ashwin Mittal
President, NASSCOM President, Blueocean Market Intelligence
3

4. Executive summary (1/4)
Overview
Globally, a continuously burgeoning volume of data (40 zettabytes by 2020), data generation from varied channels (Facebook-
800+ million daily users, Twitter-250+ million active users, 9 billion connected devices by 2018) and a corresponding drop in data
storage costs per GB (decline of 99 per cent between 2000 and 2014) has enabled unprecedented access to a variety of data.
This ever increasing data is a key resource that can be “analysed” to generate insights that can help organisations to take
better and faster decisions.
Analytics is a process by which insights are extracted from operational, financial and other forms of electronic data, internal or
external to an organisation. Analytics can be used to create value using different types of data, both structured (high degree of
organisation) and unstructured (lacking pre-defined data model).
Global analytics market
As firms gain access to greater volumes and newer varieties of data, and as they unearth more innovative ways of generating
insights for improved customer engagement, implementing analytics is gaining in importance.
The global analytics market (software products and outsourced services) is growing at over 12 per cent since 2012. The 2014
market size is estimated at USD 96 billion and is projected to reach USD 121 billion by 2016. Outsourced services around
analytics is growing at a faster CAGR of over 14 per cent vis-à-vis analytics software (CAGR ~10 per cent).
This growth is being driven by a host of factors – cloud, in-memory computing; mobile devices, social media; emergence of
different business units across an organisation as consumers of analytics, etc. With analytics being consistently recognised as
the top priority for CXOs, firms are also industrialising analytics within the organisational culture and this in turn, is seeing the
emergence of the Chief Data Officers’ role.
India analytics market
Compared to the global market, the overall India analytics market size is miniscule and currently accounts for only 1 per cent
share. The India market (exports and domestic) is growing at double the rate of global market at 24 per cent CAGR. In FY2014,
the total market was USD 954 million and is expected to reach nearly USD 2.3 billion by FY2016. The ratio of exports:domestic
is likely to remain steady at 85:15 during this period.
4

5. Executive summary (2/4)
5
Currently, this segment has over 600 firms offering analytics-related products and services and it employs about 29,000
people. Of this, India is the primary target market for ~50 per cent of these firms. The fact that India’s Top 100 IT-BPM
(integrated) firms and about 500+ start-up firms are focused on analytics is statement of proof of this technology’s increasing
relevance.
India is rapidly emerging as the analytics hub for the world. It has the complete range of ecosystem players from GICs,
integrated IT-BPM firms, pure-play analytics firms to BPM-KPOs and a vibrant analytics product firms. In terms of geographic
density, Bengaluru has the highest number of analytics firms – 29 per cent, followed by Mumbai and Pune – 24 per cent. Apart
from this, many Tier II/III cities are also emerging hubs - Trivandrum, Kochi, Mysore, Indore, etc.
23%
20%
17%
16%
14%
11%
Better decision-making
Driving sales and
revenues
Cost control,
improve RoI
Process efficiency &
improvement
Greater customer
insights
Targeted marketing
STRATEGIC
Impacting top-
line
OPERATIONAL
Impacting
performance
CUSTOMERS
User
experience
Analytics in the India domestic market
There is also a pull factor from the user side – firms in India are
beginning to realise the value of implementing analytics. Potential
impact can be operational (cost control, process efficiencies), end
customers (user insights, targeted marketing) and strategic (driving
sales, improved decision making).
Firms in the BFSI, telecom and eCommerce verticals have so far
been taking the lead in adopting and applying analytics to a wide
range of business areas – portfolio analytics, risk & compliance
analytics, customer loyalty, subscriber profiling, churn management,
etc. Emerging verticals that are still in the pilot phase of adoption
include retail, manufacturing and media & entertainment. One of the
key verticals that is showing great promise is the Government – SEBI
(fraud detection), NATGRID (anti-terrorism) – and state level
initiatives - Maharashtra Sales Tax Department and Hyderabad’s
intelligent transport system.

6. To do this, the industry must first address various challenges. The demand side survey conducted indicated that proving the
business value from analytics is the top challenge among users. This was followed by the firms’ ability to share data across
business units and the total cost of ownership. For non-users, the top three challenges were budget constraints, RoI and costs.
Additionally, both users and non-users expressed lack of endorsement from top management as another key challenge.
From the supply-side perspective, the lack of awareness of this technology among potential users and lack of top management
commitment is the primary challenge. This is followed by challenges with regard to data collection, siloed data, and a greater
focus on short-term, output based results rather than on long-term, outcome focus.
The journey to industrialisation involves three broad phases:
• Phase 1: Discovery (firms pilot a few short-term analytics projects)
• Phase 2: Establish (analytics becomes a little more centralised with organisation buy-in and this phase would also see more
standardised tools and processes
• Phase 3: Industrialise (where analytics is a core strategy linked to business outcomes).
Executive summary (3/4)
6
Industrialising analytics in India
Although adoption of analytics is very nascent in India, its
relevance is not lost on end-user industries. A survey of ~600
demand-side firms (both users and non-users of analytics)
indicated that while >60 per cent of user firms recognised the
importance of analytics, the corresponding percentage among
non-users was ~40 per cent. Significantly, only 14 per cent of
non-users indicated that analytics was not important. A further
analysis of user firms showed that 80 per cent had either
uncoordinated or localised initiatives.
Hence, for long term value gain, there is a need to industrialise
use of analytics – that is integrate analytics into the
organisational fabric.
19%
25%
34%
40%
43%
46%
53%
58%
64%
Insufficient in-house expertise
Where do I start?
Poor data quality
Budget constraints
Management support, vision
Analytics tool cost
Vendor costs
Sharing data across BUs, siloes
Proving the RoI, business value
Key challenges for analytics deployment (Users)

7. Executive summary (4/4)
For each of these stages, the supply-side would need to address specific issues:
• Phase 1: Showcase RoI, use cases - value add in learnings from global and Indian peers
• Phase 2: Address entire analytics value chain - integrate multiple data sources, optimise data utilisation, data security, data
maintenance
• Phase 3: Industrialise: Greater demand for functionality across business value chain; after sales services – a key differentiator
Industry stakeholders will need to work on a 6 point agenda which involves:
Six point agenda for Industry stakeholders
1. Raising awareness
2. Creating talent
3. Variabilising cost of offerings
4. Standardising tools and technologies
5. Setting up cross functional analytics teams
6. Getting C-level buy in, to drive industrialisation of analytics in India
7

8. Table of Contents
Acknowledgements 9
Setting the context 11
Global analytics market and trends 13
Indian analytics market and trends 18
Industrialising analytics in India & Way forward 36
8

9. Acknowledgements
This report has been prepared through a collaborative effort by several institutions and individuals.
First, we would like to extend our thanks to NASSCOM member firms who provided us with a detailed
overview of trends and insights in the analytics industry, both global and Indian. Additionally, we would like to
acknowledge the support and guidance of NASSCOM’s Analytics Interest Group.
Second, we are also grateful to the customer side of the business. blueocean conducted a detailed survey of
nearly 600 user firms and conducted in-depth interviews with firms in the advertising, auto, CPG, eCommerce,
healthcare, oil & gas, telecom verticals and a large firm with diversified businesses.
We deeply appreciate the effort put in by Mr. Vinay Kulkarni, the independent research consultant who
conducted the supply and demand side interviews.
Finally and not the least, we would like to thank the team from Blueocean Market Intelligence, particularly Ajith
Sankaran, Ishma Siddiqi and Dhanya Vishwanath, who were instrumental in producing this study.
A special acknowledgement to the NASSCOM research team for their efforts and contribution towards this
report.
9

10. Study methodology
NASSCOM carried out this study in partnership with Blueocean Market Intelligence:
• Online survey among analytics users/non-users: blueocean conducted an online
survey among Indian firms covering both users and non-users of analytics across ~600
firms
• In-depth interviews with users (demand side): blueocean and an independent research
consultant jointly interviewed nearly 15 analytic user firms to get deeper insights about
analytics adoption, drivers and challenges. These firms represented various verticals
including advertising, healthcare, telecom, auto, eCommerce, microfinance, energy &
utilities, CPG, etc.
• In-depth interviews with analytics vendors (supply side): NASSCOM’s internal team
and an independent research consultant conducted in-depth interviews with analytics
vendors (20 firms representing service providers and analytics product firms) to
understand their perspectives on the domestic market potential
• Secondary research: blueocean researchers looked at business, industry, and
technology publications for information
10

11. SETTING THE CONTEXT
11

12. What is analytics?
Gartner defines “Analytics” as a process by which insights are extracted from operational,
financial and other forms of electronic data, internal or external to an organisation.
These insights can be:
• Historical, real-time or predictive and can also be risk-focused (e.g., control effectiveness,
fraud, waste, abuse, policy/regulatory non-compliance)
• Performance-focused (e.g., increased sales, decreased costs, improved profitability, etc.)
• Frequently provide the “how?” and “why?” answers to the initial “what?” questions often
found in the information initially extracted from the data
Analytics can be used to create value using different types of data:
Structured data - Information with a high
degree of organisation, such that inclusion
in a relational database is seamless and
easily searchable
Examples - relational and legacy
databases, spreadsheets, flat files
Unstructured data – Information lacks a
pre-defined data model, is unorganised
and raw and can be textual or non-textual
Examples - social media, blogs, web
pages, multimedia, chat, call centre data
Source: Gartner, blueocean, NASSCOM 12

13. GLOBAL ANALYTICS MARKET AND TRENDS
13

14. Pre-relational
Descriptive
What is
happening?
Diagnostic
Why/How did it
happen?
Predictive
What may
happen?
Prescriptive
What should we
do?
Analytics: Progress from reactive to proactive, real-
time response
Evolution: From static to real-time, dynamic analytics
Examples:
• Sales reports
• Customer
segmentation
Examples:
• Web analytics
• Location intelligence
Examples:
• Propensity modeling
• Sales forecasting
Examples:
• Price optimisation
• Marketing mix
optimisation
Complexity,usageofstatisticalmethods
1990s 2000-2004Pre 1970s
Examples:
• Data generation
• Storage
2005-2010 2011 onwards
Technologies
Relational Databases OLAP tools
Web analytics tools
Data virtualisation
Packaged analytics tools
Mobile BI NoSQL
Hadoop, Hive
Cloud BI
Big data HANA
ETL tools
BI suites
Dashboard tools Data integration platforms
Machine learning
AI
Source: blueocean, NASSCOM 14

15. Analytics: Globally, one of the fastest growing
technology markets…
• Increasing maturity: Firms worldwide expanding
analytics adoption from descriptive and diagnostic
analytics to predictive and prescriptive analytics
• Data and analytics - no longer sole responsibility
of IT: Organisational culture changing from a siloed
ownership of data and insights to cross-enterprise
approach
• Firms driving cloud-based BI: New scenarios such
as collaboration with customers and outside-the-
firewall mobile access also accelerating adoption
35 42 51
42
54
71
2012 2014E 2016P
• Self-service analytics becomes the norm at fast-moving firms: Businesses are beginning to expect
flexibility and usability from their dashboards. Monolithic infrastructure stacks will pass in favor of solutions
that can work with new data sources
• In-memory computing providing an opportunity to rethink information systems: In-memory
computing will have a long-term impact by changing users’ expectations, application design principles,
and vendors strategies
• Emergence of the CDO: While it rolled up under CIO priorities earlier, with analytics pervading across
business units, the role of Chief Data Officer (CDO) is emerging
Software
Services
CAGR 14.3%
CAGR 9.7%
Notes:
E: Estimate; P:Projection
#: Represents only outsourcing services market
Source: Cloudtech, Gartner, IDC
Global analytics market
USD billion
76
96
121
#
15

16. …Driven by data explosion, access to affordable
computing & business imperatives
Volume of data is exploding
10x increase
Zettabyte
16
4
40
2013 2020
10X
2000 2014
Data comes from increasing Variety of sources; with increasing
Velocity: Social media, cloud, IoT, eCommerce, cloud computing
Significant reduction in cost of
acquiring, storing, managing data
Increased need for
analytics: Firms realising
the value of analytics to
compete and operate
efficiently
Data storage cost
USD/GB
800 mn+
daily active
users
6 billion
hours of
video
watched
every month
250 mn+
active users;
100 mn+
tweets every
day
1 Exabyte
data stored in
cloud, growing
rapidly
9 billion
connected
devices in 2018,
up from 2 billion
today
Increased vendor
activity: Analytics is
emerging as one of the
top revenue opportunities
Analytics: A top priority for CXO’s
CIO priority surveys
(2012-2014)
Priority rank for
Analytics & BI
1
C–Suite survey,
2013 1
CIO Conference
Poll, 201 1
State of CIO
survey, 2014 1
99%
Source: cdn.business2community, Gartner, IDC
0.1 – 0.5
10

17. RoI: New revenue streams, cost savings, operational
efficiencies
UPS’ On-Road Integrated Optimisation and Navigation (ORION) system
captures data on 16.3 mn+ packages per day for 8.8 mn customers, with an
average of 39.5 mn tracking requests per day. “Big data” comes from
telematics sensors in 46,000+ trucks (speed, direction, braking, etc.)
Commonwealth Bank of Australia used SAS and Teradata solutions to
migrate siloed information onto one platform to analyse customer
transactions in real-time
Professional society for physician assistants: Quatrro created a big data
platform by analysing over 250 types of data sources, leveraged descriptive
and inferential analytics, database building, data cleansing, and
standardisation by leveraging cloud infrastructure
Central Government client uses analytics to uncover hidden relationships
across 1 billion internal and external data items and to streamline risk and
compliance operations
Analytics engine for a global financial services firm to predict customer
behavior and for trade analytics: Altimetrik leveraged Hadoop, Hive,
Sqoop, and Pig. Cloudera distribution of Hadoop was installed and cluster
was setup. A prototype was built for customer data, cash flow and credit
card history data for reporting and analytics
Deployed IBM’s predictive analytics for understanding customer
behavior and to proactively reach out to customers with a high potential to
churn
• Saving of >8.4 million gallons
of fuel
• 2X level fraud detection
• Fraud alerts for internet
banking increased by 60%
Reduced:
• Membership churn by 42%
• Research and analytics cost by
80%
• Generated £1.4 billion
additional yield to-date
• Client’s Customer Experience
Index up from 20 to 35
• Development cycle down from
9 months to 3 months, reduced
time to market
• Increased customer retention,
subscription revenues
• Average annual RoI - 376%;
annual profit - USD 3.8 mn
Source: blueocean, IBM, Informs, SAS, NASSCOM
Organisation Analytics application areas Benefits
17

18. INDIA ANALYTICS MARKET AND TRENDS
18

19. India market: CAGR of ~25 per cent to cross USD 2
billion by FY2018
92 163 375
521
791
1,900
FY2012 FY2014E FY2018P
Domestic Exports
Indian analytics market
USD million
613
954
2,275
CAGR 24%
CAGR 26%
Notes:
#: Represents only outsourcing services market
*: The break-up given includes over-laps; hence a direct total can't be calculated
**: Top 100 IT-BPM firms who offer analytics services and products
Source: NASSCOM
India: Player landscape*
nos.
• ~USD 1 billion revenue; to grow >2X over 4-5 years
• Domestic market still nascent; to double by FY2018
• Total employees: ~29,000; domestic market: ~5,000
• Number of analytics firms: 600+ nos
• Top 100 IT-BPM firms offering analytics services/products
• >300 analytics firms focusing on India market
• Tier-II analytics hubs: Trivandrum, Kochi, Mysore, Indore, etc.
• Emerging firms : Crayon Data, Germin8, Padma, Gazelle,
Cognowise, Datapub, Clarisnow, etc.
Key trends
FY2014E
Analytics firms
Start-ups
Product firms
Integrated firms**
600+
500+
200+
100+
#
• Indian businesses increasingly seeing transformative
benefits of improving resource management and market
intelligence
• Noticeable shift toward cloud-based solutions
• Domain specific players: Indian product firms developing best-
in-class products, platforms and enabling tools; smaller firms
specialising in analytics for niche domains
• Product firms redefining core offerings and exploring service
differentiators in conventional and emerging business models
19

20. Mobile and internet growth, technology base, growing
economy sets the base for analytics growth in India
Increasing internet, mobile
penetration driving data growth
internet users
29
382
2012 2016
Smartphone users
in India# (mn)
Organised retail growing rapidly,
driving need for analytics
2012 2015E
40.5
88.3
Increased awareness at C-suite
level
Regulatory compliance
social media
users
• Big data & analytics - No. 2
(after cloud) in key areas for
investment for CIOs
• RBI’s Automated Data Flow
initiative (ADF)
• International Financial
Reporting Standards (IFRS)
• eXtensible Business Reporting
Language [XBRL]
To further push firms to invest in
analytics and BI
243 mn
168.7 mn
Organised retail*
USD million
Retail eCommerce
is exploding (no of
online shoppers)
20mn
2013
40mn
2016
Rapid technology adoption by
Indian industry
• Limited legacy IT challenges,
enable rapid technology
adoption
• Huge potential for analytics as
large number of Indian firms get
increasingly IT enabled
Growing economy,
competition, globalisation
• India: One of the fastest
growing economies
• Stabilising economy,
globalization, increased on-
data, fact-based decision-
making tools
Source: Accelpartners, Avendus, blueocean, CIOandleader, Gartner, IBEF, IBM 20

21. Mumbai16%
Bengaluru29% Chennai 8%
Pune8%
Delhi11%
Hyderabad11%
Gurgaon7% Noida 7%
Kolkata
4%
India: Vibrant analytics vendor ecosystem
• 1.5X: Growth in number of analytics firms in India in last two years
• ~3.6X: Increase in average employees of analytics firms in India from 76 in 2012 to 270 in 2013
…Geographic spread in India
per cent
Analytics vendor landscape in India…
Global in-house
centres
50+
Pure-play
analytics service
providers
80+
BPMs & KPOs
80+
Integrated
firms
100+
Analytics
software /
product firms
200+
Source: Analytics India magazine, blueocean, NASSCOM 21

22. Key drivers: Data driven decision making, customer
insights, improved performance and efficiencies
Base 286; multiple responses allowed, value indicates number
of respondents ranking these in top 3
Primary factors driving Indian firms to deploy analytics
No. of responses
• Implementing analytics – being explored by both
large firms and SMEs; many still in pilot phase
• Analytics – enabling competitive advantage
• eCommerce firms and MNCs, esp. in BFSI and
telecom, leading the charge
• Firms in India looking to analytics to formulate
business-driven strategies and derive value…
• …And better manage costs, optimise
operational processes, earn higher returns
• Unlike globally, firms in India currently not using
analytics for fraud prevention, pricing strategies
• Distinct vertical trends:
o Banks-fraud detection
o eCommerce-web analytics
o Manufacturing, retail - supply chain
optimisation
23%
20%
17%
16%
14%
11%
Better decision-making
Driving sales and
revenues
Cost control,
improve RoI
Process efficiency &
improvement
Greater customer
insights
Targeted marketing
STRATEGIC
Impacting
top-line
OPERATIONAL
Impacting
performance
CUSTOMERS
User
experience
Source: blueocean, NASSCOM 22

23. Telecom, BFSI, eCommerce – trendsetters in analytics
adoption
Source: blueocean, NASSCOM
Verticals Adoption rate Analytics services areas
Telecom High
Network monitoring & optimisation, capacity planning analytics, forecasting,
customer scoring, customer acquisition, churn analysis, real-time analytics,
pricing models, campaign management, churn prevention, fraud prevention
BFSI High
Customer analytics, marketing analytics, portfolio, credit risk, fraud & risk
analytics, pricing models, demand forecasting, cross- and up-sell models, churn
modelling, loyalty & claims analytics
eCommerce High
Web analytics, customer & data analytics, logistics and distribution analytics,
inventory management, real time analytics
Retail Medium
Merchandising analytics, customer analytics, churn analytics, inventory
management, supply chain optimisation, sales performance analysis, market mix
modeling, CRM analytics, fraud detection and prevention
Manufacturing Medium
Supply chain, logistics and inventory management, demand forecasting and
SKU rationalisation, process and quality analysis, engineering analytics,
predictive maintenance
Media &
advertising
Medium
Demand signaling, sentiment analysis, targeted advertising analytics, customer
acquisition
Healthcare Low
Portfolio performance analysis, treatment flow analytics, clinical analytics, supply
chain analytics
Education Low Learning analytics, relationship mining, predictive analytics
23

24. Government of India: Ripe ground for analytics
• NATGRID, India’s national intelligence network invested USD 16 million to use real-time analytics in anti-
terrorism efforts
• SEBI implemented a comprehensive SAS Business Analytics Platform including an enterprise data
warehouse for fraud detection
• Karnataka Vocational Training and Skill Development Corporation is using IBM’s employability analytics
to understand demand and supply trends
• Aarogyasri Health Care Trust partnered with SAS to leverage predictive analytics to optimise performance
and reduce operating expenses. SAS analytics solution provides real-time access to AHCT and aids in
understanding the lead time between pre-authorisation approval and surgeries, forecasting funds
requirement, preventing fraud, spotting disease trends, and taking preventive health measures
• Maharashtra Sales Tax Department is using SAS Business Intelligence and SAS Analytics with the help of
Capgemini to tackle fraud and improper payments
• Hyderabad implemented an intelligent transport system provided by CMC. Data gathered from GPS in
public buses is being used to track the frequency and delay of buses in each route, allowing city officials to
plan deployment of more buses
Source: blueocean, Economic Times, futuregov, IBM, Informatics, SAS 24

25. eCommerce: Leading in analytics adoption
Faced a pressing need to improve inventory utilisation. Using a
solution from QlikView , Flipkart was able to integrate complex
data from disparate sources and deliver analytical data to the
staff in various departments
Wanted to ensure that the top stores got the pick of merchandise
due to their size, catchment and customer profile. However,
owing to overstocking at some stores, merchandise allocation to
smaller stores was less than optimal. Usage of BI stack helped
overcome this problem
Using IBM’s ExperienceOne and SPSS Predictive Analytics
solutions, the firm was able to identify customers and target
them with individual campaigns. It also provided access to
clients’ real time data and analysed it - helped in innovative
marketing efforts
•Inventory utilisation up by
5 per cent
•Optimise stock levels
•Lower costs
•Optimise merchandise
allocation more accurately,
based on actual sales
throughput
• Helped utilise subscriber
data better to discover
perfect match credentials
• Deliver integrated
marketing messages to
target potential partners
Source: Secondary sources
Organisation Analytics application areas Benefits
25

26. AdNear: Air traveller behavioural insights for targeted
marketing campaigns
Analyse air traveller behavior in India for targeted
marketing campaigns
Client & business challenge
• AdNear used Apache Spark and Hadoop
frameworks, data structure server Redis, and Python
• Locational analytics, customer segment analysis and
cluster analytics were used
• AdNear tracked 650,000 travellers - all mobile users
- across six airports in India: Mumbai, Delhi,
Chennai, Bengaluru, Kolkata and Hyderabad
Analytics solution deployed & methodology
• Customer segmentation and behavioral insights
• Improved campaign planning for maximum impact
and sales conversion
Benefits to customer
26

27. Airtel’s churn management initiative
Airtel wanted to identify pointers that would help reduce customer churnClient & business challenge
Analytics solution deployed & methodology
• Enabled Airtel to develop an automated tool to mine customer call texts and calculates aggregate probability
for churn
• Whenever the probability crosses a certain threshold point, Airtel takes up special tele-calling to these
customers to ensure quicker resolution of their issues and save the churn
• Helped reduce churn significantly over last one month
Benefits to customer
How to use customer care
calls’ data in churn reduction:
• Step 1: To quantify the
importance of customer care
in a customer’s life cycle
journey
• Step 2: To do text mining
and figure out early churn
and therefore save the
customer
• Airtel looked through multiple customer touch points and figured out that
Customer care plays one of the most impactful role in case of trouble shooting
• Used analytical tools to figure out the specific texts used by customer or call
agents which might indicate possible churn
• Also checked calls of customers who have not churned for the same texts and
identify differences in the usage of same text between churn vs non-churn
groups
• Ran a stochastic modelling to attach a probability to each of these texts which
indicates probability of churn
OBJECTIVE METHODOLOGY
27

28. BRIDGEi2i: For an Indian conglomerate, measure
effectiveness of promotions on trade revenue
Large Indian firm with major CPG focus wanted to measure effectiveness of various trade and consumer promotions on trade
revenue while segregating impact of promotion from impact of price change, competitive actions, SKU cannibalisation and halo
effects
Client & business challenge
• Outlet segmentation based on
similar responsiveness and
product assortment
• Creation of price indices,
promo calendar, competition
and cross-category interaction
indices
• Data treatment trend,
seasonality, outlier etc.
• (Mixed Effect) Regression
modeling of volume sold
against price, promotion,
competition, interaction indices
• Decomposition of volume
realised into base volume,
cannibalisation, promotion net
impact, competition impact etc.
• Analyse RoI of
promotion spends
based on incremental
value
• Identify optimal
promotion and price for
each channel and
segment
DATA APPROACH
SEGMENT DATA, CREATE
INDICES
MODELLING DECOMPOSITION
OF IMPACT
SCENARIO ANALYSISSegment level data for
outlets
Historical sales by
volume and value
Historical price and
promotion data
Channel and competition
data
Model results
and scenario
analysis
• Improved promotion strategy and RoI of promotion spend across segments
Benefits to
customer 28

29. Essar Oil: ‘EOL Dashboards’ for operational excellence
At Essar Oil, after setting up a 20 MMTPA refinery, the focus is on maximising returns from the newly and substantially
enhanced capacity of the high-complexity refinery in next 3-4 years
Client & business challenge
Objective: Set up Operational Intelligence tool (EOL
Dashboard) to measure, monitor, improve KPIs across
business value-chain (crude to product):
• Enable sharing of information across the firm, quickly,
easily and appropriately
• Allow users to consume large amounts of information
in a simple, graphical view
• Enable management to monitor organisation-wide
KPIs in real-time with complete drill-down facility
• Align users to a single version of the truth
Analytics solution deployed & methodology
Solution: EOL implemented the Oil & Gas specific
analytics tool of Siemens XHQ across four key business
transaction systems:
•SAP ERP
•AspenTech’s Manufacturing Execution System
•Commodity trading platform of ‘The Bulldog’ and
•A set of custom-made Microsoft technology-enabled
solutions
The data generated from these systems is
approximately to the tune of 1.5 Terabytes
Benefits to customer
• Covered all KPIs of firm’s Balanced Scorecard and those monitored by functional heads and their line managers
• Operations visibility through functional & cross-functional overview, KPIs, analysis and opportunity cost optimisation
through pushed exceptions, drill-downs to lowest detail, on demand
• Enabling business users take quicker decisions and reduce dependency on people
• Helped gain important insights in the refinery operations and also in responding quicker to any challenges faced
• Unlocked automation opportunities in some business processes
• Has been extended to users with access to tablets making it easy for them to track KPIs in real-time
29

30. 2014 Lok Sabha election analysis in real time by
Gramener (A Data Visualisation firm)
Client & business challenge
• Gramener -CNN-IBN-Microsoft partnership for historic & real-time update
of 2014 Lok Sabha election
• 300 parties, 8,000 candidates, ~800 million voters, ~21,000 votes/sec on
live counting day – A Big Data Problem in every sense
Analytics solution deployed & methodology
• Client received data from Nielsen
• Gramener installed it’s Counting day ETL scripts (Python script) which
pulled data every 10 seconds from SQL server and converted it into 2
JSON files: one storing the candidates and another storing their
status/votes
• These files were copied via rsync every 10 seconds to ibn.gramener.com,
which is an Azure VM in Singapore – a 4 core 7GB RAM Ubuntu system
• The server had a copy of the Gramener visualisation server installed
which had built-in analytics and visualisation capabilities
• Results rendered in real-time using a visualisation template
Benefits to customer
• The system was able to analyse over 10 million pages worth of election
results in real-time, enabling CNN-IBN to stay ahead of other channels or
websites
30

31. GrayMatter: Consolidation of information across
enterprise for GMR Group
• One of the largest infrastructure players in India, GMR wanted to integrate data across multiple airport
locations and have a corporate level single view dashboard of airport business
Client & business challenge
• Management gets a quick snapshot of entire airport business at the corporate level on live data
• Online current receivables and payables status improved finance decision making abilities
• Commercial department can easily identify and eliminate leakages in revenue on the retail side
• Advise airlines on optimising their flight frequencies at the airport, thereby increasing traffic
Benefits to customer
• GrayMatter’s pre-built stack on SAP BO BI
platform used to quickly customise solutions
around customer’s unique requirements
• Key data elements identified from all data sources
relevant to the pre-built and customised metrics
• Created single version of truth with a centralised
data repository
• Implemented GrayMatter’s unique user interface
and dashboards
• High reaction time due to lag in consolidation of
information across enterprise
• Manual intensive consolidation process
consumed critical resource time and effort
• Integration of data across multiple airport
locations
• Corporate level single view dashboard of airport
business, a critical need
• Exorbitantly high cost of alternate solutions
• Data correctness across disparate data sources
Key challenges
Analytics solution deployed & methodology
Solution
31

32. Persistent: Social media and digital analytics for
Chennai Express, a Bollywood movie
• Digital team wanted to use social media as the focus of their marketing strategy
• Objectives: maximising customer reach, build campaigns to translate social media traffic
into increased audience in theatres
• Persistent and eMee evaluated online presence
and implemented “Actionable Insights”, a
recommendation system that uses analytics, big
data tools and calibrated metrics to gauge what
people like and their engagement levels
• Big data analytics, using a variety of in-house
and off-the shelf tools and their unique approach
based on 4A model of engagement
• Cross-pollination of social networks - Twitter,
YouTube, Facebook, etc.
• 1 billion cumulative impressions, 750K+ tweets over 90-day period
• Made Twitter history in India as the first film to be listed in the top
trends for more than 10 consecutive days
• Became first Indian film in twitter history to trend at worldwide No. 1
with two separate hashtags #ChennaiExpress,
#ChennaiExpressWeekend
• Box office collections mirroring social media buzz
Client & business
challenge
Analytics solution deployed &
methodology
Benefits to customer
32

33. Serco: Product affinity analysis for a leading retail
chain in India
• Improve inventory management through cross-selling by identifying basket of products or brands which
are most likely to sell together
• Identify key profitable product categories and impact of promotions on the product sales
Client & business challenge
Analytics solution deployed & methodology
• 3 per cent overall promotional revenue
impact
• Identified key profitable product categories
to optimise profits
• Helped in crafting successful cross-sell
Benefits to customer
• Data Mining – Data
was cleaned and
necessary data
transformation
techniques used for
getting the derived
variables for data
mining
• Product Affinity
Analysis was done
and association
strength of various
products and brands
was derived
• Price sensitivity
Analysis - Price
elasticity of each
product was derived
pre-promo and post-
promo and price
sensitivity analysis
was carried out
• Customer unaware about basket
of products or brands most likely
to be bought together
• No clarity on key profitable
product categories on which to
focus their marketing efforts
• Unable to identify impact of
promotions on sales of product
Before Analytics Scenario
• Client rolled out the cross-sell strategy with the help of
insights received from Product affinity analysis
• Marketing efforts were focused on Key profitable
categories in order to maximize the profits
• Suggested more effective promotional offers by deriving
impact of promotion on sales of product through price
sensitivity analysis
After Analytics Scenario
33

34. Tata Motors: Applying analytics to track direct
material costs
• Manage direct material costs
• Trace millions of cost reduction/cost increases in price amendments back to product variant level
• Monitor on a monthly basis changes in cost of product variant and also of critical aggregates, components
Client & business challenge
Analytics solution
deployed & methodology
• Operational Impact: 80% of cost is at design
stage so it gives visibility to the designers on
the cost, thus help design lower cost variants
• Strategic Impact: Visibility on how movements
of cost would make pricing more responsive
to market needs
• Customer Impact: Ability to price more
competitively and be more responsive to
changes in commodity price fluctuations
Benefits to customer• Material cost contributes 65% of
total cost
• Biggest problem was to link cost
reduction/increases to changes in
cost of product variants
• Tata Motors implemented SAP
Business Objects/BW to help
analyse nearly 480 lakh data points
a year
• Manual compilation of data over 3-
4 weeks
• Reporting done once in six months
and confined to a department/BU
• Impact of price rise across the
BUs/firm could not be ascertained
• Decision making was largely
reactive (post impact)
Before Analytics Scenario
• Direct Material Cost tracking solution rolled
out to all business planning agencies across
manufacturing locations, material price panel,
designers, new product introduction teams
• Monthly analysis/reporting enabled across
the firm giving critical insight to materials,
business planning & R&D
• Data reported is factual enabling pro-active
decision making and monitoring price
increase/cost reduction at item level
After Analytics Scenario
34

35. WNS: Customer segmentation for an Indian apparel
retailer
• One of the top three Indian apparel
retailers wanted to customise
marketing messages based on
customer preferences, needs and
habits
• Had large loyalty card base but no
understanding of purchase patterns
Client & business challenge
• Holistic customer segmentation proposed based on customer value,
discount hunting behavior, lifestyle preferences, life stage
• Transaction and demographic data analysed and fed into segmentation
algorithms
• Large volumes of data > 45 GB churned for analysis
• Decision trees and clustering algorithms generated customer segments -
five segments with distinct profiles were unearthed
• Segments profiled extensively on transaction frequency, monetary value,
typical products purchased, etc. to create a holistic picture
Analytics solution deployed & methodology
• Complete segmentation solution for
all loyalty card customers
• Customer file creation and
maintenance to track segment
behavior
• Segmentation implemented at
client site in CRM system
• working with client to use
segmentation to customise various
direct marketing campaigns
Benefits to customer
35

36. INDUSTRIALISING ANALYTICS IN INDIA &
WAY FORWARD
36

37. How can IT-BPM firms differentiate their solutions?
76%
69%
60%
54%
46%
31%
30%
Base 286; multiple responses allowed, value indicate number of
respondents rating these as top 2 on a 5 point scale
Important criteria while selecting analytics solutions & services
No. of responses
Return on investment
Proven cases,
references
Assistance in setting up
analytics system
Cost, discounts
Vendor brand/reputation
Product functionality
Responsive after sales
service
Source: blueocean, NASSCOM
Clear need for showcasing business value:
• Demand side seeing value add in learnings
from global and Indian peers
Phase 1:
Discover
Phase 2:
Establish
Phase 3:
Industrialise
Hand-hold across the analytics value chain:
• Integrate multiple data sources, optimise
data utilisation, data security, maintenance
• Lower total cost of ownership
As analytics gets further embedded into firms’
business culture:
• Greater demand for functionality across
business value chain
• After sales services – to emerge as a key
differentiator
37

38. Acquirer Target Year
Value
(USD million)
Strategic advantages
Facebook Little Eye Labs 2014 10-15
Performance analysis capabilities and acquire monitoring tools for mobile
app developers
Tech Mahindra FixStream 2014 10
Access to data integration and analytics platforms for datacentre and cloud
management
Pegasystems MeshLabs 2014 NA
Adds social listening, text analytics and natural language processing to
enhance customer service & marketing
IbiboGroup YourBus 2014 NA
YourBus.in has a GPS-based bus tracking & analytics platform that provides
real-time data to travelers and bus operators
MphasiS Digital Risk 2012 175
Mphasis added highly specialised risk, compliance and transaction
management solutions for mortgage industry
Crisil
Coalition
Development
2012 49
Strengthened positioning in high end research and analytics space for
leading investment banks globally
Wipro
Promax App
Group
2012 33
Strengthened positioning and capability in management, analytics &
optimisation of trade promotions
Equifax NettPositive 2012 NA Deepen Equifax’s footprint in the Indian market
Moody Amba Services 2012 NA
Grow expertise in investment research and quantitative analytics for
financial institutions
IMS Health PharmARC 2012 NA
Acquisition strengthened IMS’s BPM capabilities, services delivery platform,
and suite of proprietary technology and apps
Cognizant CoreLogic 2011 50
Provide end-to-end business processes and sophisticated analytics
solutions across the mortgage industry
Genpact
EmPower
Research
2011 NA
Acquisition added social media monitoring and measurement, event impact
research, brand tracking, and data management
M&As: ~USD 500 million - quicker access to markets,
customers, capabilities
Not exhaustive
Source: Avendus, Saviance, blueocean, NASSCOM 38

39. Analytics firms’ attracting significant investor interest
- ~USD 400 million funding since 2011
Funded to Funded by Year
Deal value
USD million
Capillary Technologies Amex Ventures 2014 4
Sapience Seed Ventures 2014 0.758
Mu Sigma MasterCard 2013 45
Opera Solutions Wipro 2013 30
Fractal TA Associates 2013 25
Qubole Lightspeed, Charles River 2013 7
UNBXD IDG Ventures India, Inventus Capital Partners 2013 2
AbsolutData Fidelity Growth Partners India 2012 20
Manthan Systems Norwest Venture 2012 15
iCreate Sequoia Capital 2012 9
IQR Consulting Seed Ventures 2012 0.525
Mu Sigma General Atlantic 2011 108
Opera Solutions Silver Lake Sumeru 2011 84
Mu Sigma Sequoia 2011 25
• Outbound: Wipro invested in Opera Solutions (USA), Zodius Capital invested in Antuit (Singapore)
• PE funds investing in smaller analytics services providers: Demonstrating confidence in their ability to provide strong
growth and higher returns
• Analytics firms proactively looking for funding to expand portfolio offerings through addition of new verticals and building
technology and platforms
Not exhaustive
Source: Avendus, Saviance, blueocean, NASSCOM 39

40. Engagement models: Largely hybrid of dedicated
internal teams and vendor engagement
• In the Indian domestic market, large part of analytical engagements continue to be driven by internal
teams. When Indian firms look at outsourcing analytics, large firms prefer annuity/FTE models. Smaller
firms opting for ad-hoc engagements to pilot analytics based projects, analyse the RoI, and then make
larger investments
• In many cases, Indian firms work with analytics software vendors for tools and systems and
implementation services, and then have their own internal teams run and manage the analytics services
• IT-BPM firms offering analytics as part of the packaged deal; independent pure analytics outsourcing
projects yet to gain sufficient traction
Internal
teams
One-off/Project
based
engagement
Annuity/FTE
engagement
Outcome based
models
Adoption by Indian
analytics users
High Moderate Low Negligible
Source: blueocean, NASSCOM 40

41. Supply-side challenges: Proving business case, data
veracity
• CXO level commitment lacking - Analytics remains a priority to select teams/individuals
• In many Indian organisations, there is a lack of understanding of analytics and its potential benefits
• Customers focus on short term results vis-à-vis long term growth goals – more “output” focused than
“outcome” focused
• Data collection capabilities are not robust or standardised in many Indian firms; siloed data available,
and these don’t talk to each other; no consolidated view
• Reluctance to change existing internal IT structure or some of the existing organisational systems
• Difficulty in finding resources with knowledge of statistics and analytical tools plus domain knowledge,
business analysis skills and program management skills
• Internal analytics teams of customers not exposed to business side – leading to lack in
understanding of requirements at both ends
Challenges mapped to
analytics value chain
Source: blueocean, NASSCOM 41

42. Demand-side challenges: RoI and costs, leading
concerns for users, non-users
Base: 286-analytics users and 312-non-users of analytics
(multiple responses allowed, value indicate number respondents ranking these in top 3)
Key challenges for analytics deployment
• Proving RoI and TCO – among the top
concerns for users/non-users
• Both groups highlight need for top
management endorsement
Source: blueocean, NASSCOM
31%
39%
42%
50%
57%
72%
77%
86%
Lack of in-house expertise
Where do I start?
Lack of domain skills
(vendors)
Data collection issues
Lack of management
support
Cost of solutions and
services
Unsure of benefits
Budget constraints
19%
25%
34%
40%
43%
46%
53%
58%
64%
Insufficient in-house expertise
Where do I start?
Poor data quality
Budget constraints
Management support, vision
Analytics tool cost
Vendor costs
Sharing data across BUs, siloes
Proving the RoI, business value
Users Non-users
• Budget constraints – the top challenge for
non-users
• Need for domain understanding among
service providers/product firms
42

43. Over 60 per cent of users recognise relevance of
analytics
No
opinion
4% Not
important
5%
Somewhat
important
30%
Important
38%
Very
important
23%
Importance of analytics
Indian firms
42%
37%
18%
3%
Central analytical group that closely
coordinates analytical activity across
the enterprise
Central analytical group; some
coordination over analytical activity
across the enterprise
Localised analytical capabilities that are
beginning to share tools, data & people
Uncoordinated pockets of analytical
activity
Current state of analytics in Indian firms
Users
Base: 598; 286 analytics users, 312 non users Base: 286 analytics users
Source: blueocean, NASSCOM
No
opinion
9%
Not
important
14%
Somewhat
important
38%
Important
26%
Very
important
13%
Users Non-users
Focus area for IT-BPM industry
in immediate future
43

44. Need to “industrialise” analytics for sustained long
term value
• Few firms currently have been able to integrate analytics into organisational fabric and generate sustained
long term value. This is largely due to disconnect between business priorities and analytics initiatives, often
resulting from:
a) Analytical teams that focus most of the resources on theoretical pursuits or the “art” of analytics
b) Organisational siloes and lack of investment from the ultimate “users” of analytics
• In order to address this challenge, what organisations should aim for is “Industrialisation of Analytics”
• This implies analytics programs that are tightly tied to business outcomes, delivered via engagement models
that disaggregate analytics process chain, hive out repeatable and standard processes to centralised process
teams, and use standardised tools & approaches
Businessvalue
Phase 1: Discover
• Data discovery
• More of “art”
• Analytics pilots
Phase 2: Establish
• Deliver initial pilots/models
• Organisational buy-in
• Standardise tools, processes
Phase 3: Industrialise
• Link analytics business priorities
• Disaggregate analytics, move “heavy
lifting” processes to shared services
teams/outsource
• Standardise tools, processes
Source: blueocean, NASSCOM
Mid term Long termShort term 44

45. • >60 per cent of analytics workforce in India has
work experience of 3-10 years
• Analytics jobs being created at a faster pace as
compared to other geographies
India advantage: A hub for analytics with mature
ecosystem
Strong vendor
ecosystem
• 600+ analytics firms
in India; of which
~200 are product
firms; ~500 are start-
ups, and ~100
integrated firms
• 300+ analytics
players focusing on
the Indian domestic
market; of which
100+ firms are
analytics product
vendors
• Tier-II cities like
Trivandrum, Cochin,
Mysore, Indore, etc.
emerging as
analytics hubs
Scalability and
leadership
• Mature global
delivery market
• Best-in-class
governance
frameworks
• Excellent CSAT
across IT services
Talent pool
Strong analytics
capabilities
• Best practices hub
• Centres of
Excellence
• A primary hub for
providing analytics
services to global
clients
18%
14%
10%
9%
8%
8%
7%
6%
4%
3%
3%
3%
3%
2%
2%
Risk Analytics
BI/Reporting
Others
Marketing Analytics
Retail Analytics
Digital Analytics
Financial Analytics
Research
Big Data
Healthcare Analytics
Supply chain Analytics
HR Analytics
Consulting
Customer Insight
Strategy Analytics
Analytics job postings based on functions
2013
Source: Accenture, blueocean, NASSCOM 45

46. Stakeholders collaborating to develop a sustainable
analytics talent pool
Specialised analytics
training institutes
Service providers introducing
cross-training to existing talent
Launched an open data
science and big data analytics
training and certification
program in 2012
Provides training to its analysts
via its MuSigma University
programme for core analytical
skills
Launched Infosys Big Data
Certification Programme to
validate and build knowledge of
big data amongst its employees
IMT, Ghaziabad signed an MoU
with Genpact to develop and
implement analytics elective for
a 2-year PGDM program
Taken analytics orientation and
trainings to academic institutes
incl. IIM Bangalore, IIITB, Great
Lakes Institute etc.
Certificate Programme in
Business Analytics
Certificate Programme in
Business Analytics – IIML
Business Analytics and
Intelligence (BAI) – IIMB
Executive Program in
Business Analytics – IIMC
Advanced Certificate
Program in Business
Analytics – IITB
Business Analytics and
Data Mining – ISI, Pune
Academia is making efforts to
build talent for analytics
Significant improvements in analytics training programs enabling India to produce analytics professionals
with relevant skills and domain expertise
Hyderabad
IIM, Lucknow
IIM, Bangalore
IIM, Calcutta
ISI, Pune
IIT, Bombay
Source: Analytics India magazine, NASSCOM 46
Not exhaustive

47. Way forward: 6-point agenda to industralise analytics
in India (1/2)
Awareness Vendors:
- Showcase case studies and highlight customer benefits (global, Indian)
NASSCOM:
- Leverage Analytics Interest Group, annual summit to showcase case studies, thought leadership
- Roadshows across cities; regional events between demand and supply side for exchange of ideas
Talent Vendors:
- Look beyond existing education system to foster talent
- Develop business consultancy/domain expertise skills in addition to core analytical skills
NASSCOM:
- Partner with academia to define right training, skills needs; provide guidance via Curriculum Advisory Team
- Conduct regional and country level hackathons/codefests
Academia and government:
- Promote domain expertise through vertical specific analytics courses, teach business skills
- Collaborate with industry for exposure to real business situations, specialised analytics training programs
- Special government initiatives to integrate academicians with analytics technology
Cost Vendors:
- India specific billing rates/bundled offerings/packaged solutions across value chain
Users:
- Make necessary investments and focus on long term benefits
- Shift from ‘output’ to ‘outcome’ focus and from ‘tools’ to ‘business solution’ focus
Short term Mid term Long term
Source: blueocean, NASSCOM 47

48. Organisational
focus
Users:
- CXO level commitment essential for department level adoption
- Analytics as core strategy, not driven by individual departments/IT
Standardise and
leverage
processes, tools
and technology
Vendors:
- Analytics firms should try and build analytics systems on top of existing systems
- Standardise and leverage common tools and technology
Users:
- Disaggregate analytics processes
- Move standard processes to scalable delivery teams
- Standardise and leverage common tools & technology
- Integrate analytics with legacy systems and tools
Analytics as a
cross-functional
unit
Vendors:
- Partner with clients right through various stages of analytics value chain
- Help with data collection/audits, data organisation, data engineering
Users:
- Set up analytics teams which are cross-functional rather than pure play analytics
Way forward: 6-point agenda to industralise analytics
in India (2/2)
Source: blueocean, NASSCOM
Short term Mid term Long term
48

49. 49