the State of Analytics within the Enterprise and how to adopt Analytics.. a Perspective being shared

1. Growth and Approach towards Analytics

2. Analytics growing as a business mandate.
Data is Growing Performance Gap Widens Capability Gap Exists..
4.4x
2.7x
2.4x
2.4x
2x
Investment in Data and
Analytics
Top Performer Bottom Performer
Sources: IBM Breakaway Now with Business
Analytics and Optimization
17%
42%
28%
10%
USE OF DATA BY BUSINESS*
75% or more 50-74%
25-49% 0-24%
++ There is a skill gap
60% executives say they “have more
information than we can effectively
use”** [IBM Report] .
McKinsey Report on Big Data estimates
50-60% gap in the supply of deep
analytical talent; equaling 140,000 to
190,000 unfilled positions.
40% growth in global data
annually
Globally 2.5 quintillion bytes of
data per day
90 % of the data in the world
today has been created in the last
two years alone.
Customer Transactions
Customer records through device
ubiquity and better data mgmt..
1
Customer Interactions
Social Unstructure, semantics..
20B events / Day – Facebook
2
Machine Interactions
Logs sensors intelligence on all
equipment
3
IBM Report  Global Business Analytics
market size is pegged around $105 billion
and growing at CAGR 8%.
Shifting Priorities for
Management in Analytics..

3. Major themes for Analytics
Customer Insight
Business Risk
Operations /
Service Warranty
Service /
Warranty
 Customer micro Segments – Delivering personalization
 Customer propensities for action, Cross sell, preferences,
Next Best Action
 Digital Marketing, Below the line & Discovery
 Pricing Models / Sensitivity
Especially in BFSI where financial Risk coverage for
regulation and internal business
Portfolio Management & Ops Risk management
Worldwide financial services OpRisk and GRC technology
market will grow to $2 billion by 2013 [ @ CAGR 6.5% ]
 Inventory, Parts Supply,  Service Management
 Geo-Loc coordination for Logistics, Users, & producers
 Predicting failure of service and business components,
 Customer contact, sentiment and intent
 Resource Allocation and Triaging
 New Product Design  Pharma, Automobile, Hi Tech
 Smart Pricing  utilites and Energy
 Claims And Litigation  Insurance

4. Analytics Value to Business
Business
outcome
Operations
Transformation
Insights Data
•Strategic themes
•Customer Insight
•Digital Marketing
•Pricing / Risk
•Product Design
•Service / Operations
•BI / Dashboards
•Manual Operations
•Embedded Analytics
•CEP / Rules Engines
•RT Integration
•Analysis / Methods
•Prediction / Data Mining
•Machine Learning
•Sample vs Large Data
•Parameterized and NON
•Volume, Variety, Velocity
•Data Sources { External,
Unstructured }
•Data Integration {ETL}
•Data Lineage {Metadata}
•Data Preparation {Index,
Search}
•Customer Segmentation,
Behavior based models in
all industry
•Price Sensitivity analysis
•NPD / Molecule research
in Pharma
•Risk in BFSI
•Driving Digital Initiatives
like Mobile
•Triaging / Routing in
Contact centers
•Running a Analytics KPO
that provides insights for
Operations
•Methods like
Segmentation, Regression
based scoring,
• Sensitivity Scenarios ,
What-if
•Text and media mining
capabilities [ PCA ]
•Semantic Search
•70% of the effort is spelt
out in Data
•External sources, public
and paid..
•Text, media processing /
Index

5. Changing Landscape .. Analytic Techniques ..
MIT SMR – IBM Study – The New path to Value 2012

6. Thanks to Teradata

7. Thanks to Teradata

8. Analytics Services Maturity Model
ALIGNED INTEGRATED OPTIMIZINGFRAGMENTED
DATAANALYTICSVISUALIZATIONPROCESS[ACTIONS]
SCALE / STRUCTURE
SOURCE / RETRIEVE
CONFIG - CONTROL
INTERACTION
ALGORITHM
MODELING
DESIGN
EXECUTE
MANAGE
PRESENTATION
STRUCTURE
Simple 2-Dimensional Graphs and
reports including Types of Visuals
supported?
Static simple play out
Simple structure, numeric [ cardinal]
and non-numeric- [ Ordinal]
Internal Local Files, federated
Ad-hoc Customer opportunity
Operational Changes >
Basic Functions and statistics
User Configuration, Data Security
Structured Data with metadata
support,
Integrated data sets through DB-
DWH, SQL based retrieve
Single Iteration playout
Computational Flows
Process Maps, Kpi- Metrics
Breakdowns,
Manual Process Change / Actions
Tactical Changes – re-structure to
Business operations, processes..
Linear Functions, Regression,
Statistics,
Strategy Changes - New services
models, synthesis of business value
Integrated Partner Actions,
Automation into systems,
scenario analysis, what -if analysis,
Complex Statistics [econometrics] ,
Numerical Method, Clustering
Analysis,
System Generation-Automation ,
visual re-formation,
Compliance and traceability effort in
adding new data sources
external connectors – API,
Composite Visuals, infographics
Unstructured text, Data Scale – Size
and time
Value Chain Analysis , Benchmark
Data
New Revenue Models
Sense and response mechanisms,
Simulation, optimization,
Text & Analytics, Neural Networks,
fractals,
Actions integration - external
systems.
Storyboards, Virtual Reality
late binding – auto discovery of
structure
Access to non standard data, late
structure binding
Real time search
Data as Media like Voice, Image and
Video Bigdata Management
pivot based interaction – User self
service
Maps, Multi-dimensional Graphs,

9. How are Businesses acquiring Analytics
Inhouse /
Captive
Solution
Utilities
Services /
Resources
Platforms /
Products
1. A Typical Bank would have a 1Bn USD budget
2. 80% spend inhouse and in Captive
3. 1200 Person = 600Mn $ Value / 100 Mn $ Cost
4. Slow, lethargy, internal Constraints, IPR
1. Small Boutique companies getting seeded
2. Focusing on either large platforms [ splunk ] or a
very specific Business use Case [ Mydrive ]
3. Scale issues, pricing,
1. Large resource houses, with 80% $ from staff Aug
2. Fragmented delivery, water fall, change is a
challenge , Utilisation is key , security & leakage
3. Can Scale, some can partner,
1. Best complement to Inhouse / Captive
2. Developing the foundations for the next gen,
3. Focused more on tech rather than business
4. Partner to all above entities,

10. Delivering Analytics Value to Business
Business
outcome
Operations
Transformation
Insights Data
SolutionsservicesToolsPlatforms
300 400 7000
wipro
Other players  CTS, TCS, Big 4, musigma
TeraData
Pivotal
Opera
Cloudera
Tableau
Clikview
RevoR
Mydrive InfoChimp
70 1200 500Bank captive

11. Typical Analytics Practice
Strategic Eco-system Alliances
1051
Analytics [ 140 – 60 USD ]
BI [ 100 - 40 USD ]
Data / Integration [ 100 – 30 USD]
1. 80% of the business is still Staff
Augmentation
2. 80% of the business in BI / MI and
low end data services..
3. Large players like Wipro / TCS /
MuSigma in the range of 5000-
10000 resources
4. Lot of SME consulting Smaller
players
5. Clients are slower than the vendor..
1. Staff Augmentation in various Skill Areas
2. Partnering and COE development for clients
3. Project based Delivery – Agile Waterfall
4. Embedded Analytics in Operations and other initiatives
like Digital, mobile etc..
5. Service Transformational Analytics – CTS
6. Very weak in industry / Business domain
For Every Analytics
Resource.

12. Analytics Shifting Trends
Rapid Outsourcing
Growth
Bringing Data
together
Capabilities, Scale, =
purchase
Management End
User
Multiple Delivery
focused on Captive
Data Driven Business
Partnership, Eco-
system, Speed
Business End User
• Past helped ISV Grow Business [+30%
CAGR ]
• Analytics == IPR  Captives
• Talent and Skills still a big shortage
• From structured to unstructured
• IOT / sensors, new external data
• Unstructured Data Media = Big Data
• Large Data – Lakes, Metadata
• Shift from Model to Compute
• Show & Tell + 0 consulting + Action
• Partnerships, COE, Investments, Utilities =
Value Add
• Utilities and Plug-n-Play
• Generating Business Use Cases Keeping
managers charmed = BI Sophistication +
Cool Tools
• Integrate Analytics within Digital
Initiatives
• Management  Ops  Customer
• Privacy + Security
Past 5 years Next 5 Years

13. How to Buy $$ Analytics
Business
outcomes
Partnering
Vendor
Total Cost of
Operation
Future
Proofing
• Deep integration with a Business outcome [ MyDrive]
• Charging and Collection Model [RDC]
• Time to deploy and transform [ Splunk ]
• Agile Delivery Models
• Show and Tell / Productized services
• Ability to Partner / Co-innovate
• Non-Linear Scale in the Business Model
• Easy to Consume, Utility, Pricing
• Eco System Partnerships
• Application potential across the Economy [ MyDrive]
• Keeping it simple.

14. Solution Capability Development
Business Value Modeling.
Analytics Program Model..
Business Value and thereby Performance Hotspots drive solutions and messages
Sales &
Marketing
Member
Mgmt & UW
Provider
Mgmt
Claims
Mgmt
Customer
Service
Medical
Mgmt
Revenue - GTM
Business Case
Account Intel
Pitch /
Proposal
Partnership /
POC
Events / ABM
Engagements
Quote
Generation
Broker
Mgmt
Campaig
n Mgmt
Market
Research
Member
Retention
1. Brand Perception / Perf
Ratio
2. Influence Ratio
3. Number of leads
4. Cost per lead
5. Medium Conversion Rate
6. Avg Premium Val
7. Days visit to purchase
8. Task Completion Rate SOLUTION
CATALOG
KEY
OUTCOMES
Key
Resources
Partnership Algorithm
Training Research LAB/ COE
Understand Business Landscape:
What value is business after? Key pain
points in decision making / operations
Leverage Internal Capability:
No duplication of work already done /
capability already in existence
In Sight of the Customer:
Develop capability through the
customer, interface, POC / Pilots
Develop Ecosystem for delivery:
Relationships with established &
emergent OEM who will drive the
market
Time Bound:
Ensure outcomes with time frame. 3
months to customer and 6 months to
pilot
Develop Systemic Solutions:
Consulting to understand customer,
quick entry, low change and capital….
1
2
3
4
5
6Data
Process
Actions
Analytics
Visualization
Capability Framework
1
2
3
Key principles
Program Status

15. Business Themes and Analytics COE
Marketing RoI & Growth analytics
Customer acquisition analytics
Customer retention analytics
Social media driven analytics
Customer/Employee fraud & risk
Competitive intelligence analytics
Supply chain analytics
MFG process quality & compliance
Early warning analytics
Asset Perf. Maint. & warranty
Network analytics
Service Problem Analysis
Service Logistic & Resource Alloc.
Governance, Risk & compliance
Integrated financial perf. - EPM
Store operations Analytics
Merchandising & Pricing analytics
Claims analytics
Pre-Trade Post Trade Analytics
Drug discovery analytics
Post market analytics (Pharma)
Care & Safety analytics
Care analytics
Member Retention Analytics
Smart meter analytics
Technology
Business Automation Modeling
Data
Analysis
Visuals
Process
People
Methods
Tools
Vertical
Themes
Customer
Lifecycle
Service &
Warranty
GRC
EPM/WIPM
• Product Mgrs [10]
• Clustered  Solution
Themes + verticals
• Teams for Verticals
program mgmt
• Modelers & Technologist
report in.
• Business Consulting
• Innovation &
Transformation Client Pitch
/ Engagement
• Analytics Program
Management
• Long term  look at
business Automation
solutions
• Modelers
• Cluster  Solution Themes
• Exploring Analysis Tools
• Develop Models/Methods
• # Of experiments
• Play with data
• Information Technologist
• Cluster  1
• All Data Gather & Aggregation
technologies
• Solution Warranty / Scale
• Speed, Variety – API
• # Of experiments
• Manage COEEnv.

16. Vishwanath Ramdas
Head Analytics FCC Compliance , Large MNC Bank
8 years in the industry with 17 Y experience in Business Transformation.