Measuring Service Delivery18 – 19 February 2013

Uncovering the hidden wealth in your data for enhanced decision making 

Dheeraj Chowdhury

Principal Consultant – Business Platforms

Infosys Australia & New Zealand

(Former Group Leader Digital Media – NSW DEC)

Agenda

•Data for deeper insights and informed decision making process

•Tools and techniques•Best practice lessons

In GOD we trust. Everyone else,

bring DATA

Service Delivery

Australian Government (DPMC) – Service Delivery

Source: http://www.dpmc.gov.au/publications/aga_reform/aga_reform_blueprint/part4.1.cfm

Australian Government (DPMC) – Service Delivery

Source: http://www.dpmc.gov.au/publications/aga_reform/aga_reform_blueprint/part4.1.cfm

Australian Government (DPMC) – Service Delivery

Source: http://www.finance.gov.au/publications/delivering-australian-government-services-access-and-distribution-strategy/principles.html

Data and Productivity: Potential

Source: http://www.mckinsey.com/insights/mgi/research/technology_and_innovation/big_data_the_next_frontier_for_innovation

Data

Which DATA

Source: Infosys

Why and What DATA

Source: Infosys

Understanding the data

Sources of data

Source: Infosys

Source: http://www.go-gulf.com/blog/60-seconds

Quantity

Source: Infosys

Source: http://www.web-strategist.com/blog/category/social-media-measurement/

Data types

Do’s and Don'ts

Ride the elephant

Source: Infosys - http://www.infosys.com/art-and-science/pages/index.aspx

Source: http://www.go-gulf.com/blog/60-seconds

STOP

Tools and Techniques

v vv

v

v

v vv

v

Measuring and Reporting

Data vs Reporting

It happens again and again. And again. And…again! It goes like this:

• Someone asks for some data in a report• Someone else pulls the data• The data raises some additional questions, so the first person asks for more data.• The analyst pulls more data• The initial requestor finds this data useful, so he/she requests that the same data be pulled on a recurring

schedule• The analyst starts pulling and compiling the data on a regular schedule• The requestor starts sharing the report with colleagues. The colleagues see that the report certainly should be

useful, but they’re not quite sure that it’s telling them anything they can act on. They assume that it’s because there is not enough data, so they ask the analyst to add in yet more data to the report

• The report begins to grow.• The recipients now have a very large report to flip through, and, frankly, they don’t have time month in and month

out to go through it. They assume their colleagues are, though, so they keep their mouths shut so as to not advertise that the report isn’t actually helping them make decisions. Occasionally, they leaf through it until they see something that spikes or dips, and they casually comment on it. It shows that they’re reading the report!

• No one tells the analyst that the report has grown too cumbersome, because they all assume that the report must be driving action somewhere. After all, it takes two weeks of every month to produce, and no one else is speaking up that it is too much to manage or act on!

• The analyst (now a team of analysts) and the recipients gradually move on to other jobs at other companies. At this point, they’re conditioned that part of their job is to produce or receive cumbersome piles of data on a regular basis. Over time, it actually seems odd to not be receiving a large report. So, if someone steps up and asks the naked emperor question: “How are you using this report to actually make decisions and drive the business?”…well…that’s a threatening question indeed!

Source: http://www.gilliganondata.com/index.php/2012/02/22/the-three-legged-stool-of-effective-analytics-plan-measure-analyze/

Source: http://www.web-strategist.com/blog/category/social-media-measurement/

Source: http://www.web-strategist.com/blog/category/social-media-measurement/

Source: http://www.web-strategist.com/blog/category/social-media-measurement/

Source: http://www.web-strategist.com/blog/category/social-media-measurement/

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Infosys Approach

Agg

rega

te

Pro

cess

Visualize

Analyze

Pre-built transformers for data transformation and cleansing

Graphical easy to use User Interface with drag and drop features for configuring data pipelines

One-Click Cloud Deployment - Seamless Analytical Cluster Setup, Configuration

Metadata driven Data Ingestion Framework with Pre-built Adapters

Industry leading Visualization techniques for deep insights

Integration with wide variety of industry solutions

Comprehensive & easy to use Analytical & Machine Learning algorithms support

Full Featured Hub Management

Pre-built components for Stream Processing & Real Time Analytics

Best Practice - Approach

Case studies

Service Delivery – Data = UK Public Sector

Source: http://www.policyexchange.org.uk

Estimated Savings £16 – £33 billion

Service Delivery – Data = Value proposition

Source: http://www.policyexchange.org.uk

Service Delivery – Data = Value proposition

Source: http://www.policyexchange.org.uk

Business operations transformation

ChallengeInability to determine the  “total” liability of  the borrower

Solution

BusinessValue

Establish risk exposure connections using ‘Record Linkage’ algorithm

Pre-built information sources to both internal systems and external sources significantly improved the accuracy of risk exposure calculations.

Agility for insights and actions: 4 weeks vs. 4 months.

Real-time discovery: Uncovered hidden exposures for 43% of accounts

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Risk exposure ‘hidden’ and spread across various disconnected levels.

Borrower risk exposure analysis Industry

Financial Services

Revenue

$8+ Billion

Employees

25,000+

Service Delivery – Data = Value proposition

Source: http://www.mckinsey.com/insights/mgi/research/technology_and_innovation/big_data_the_next_frontier_for_innovation

Big Data - Launch event

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Doug CuttingChief Architect,Cloudera

S. D. ShibulalCEO and Managing Director, Infosys

Vishnu BhatVP and Global Head – Cloud & Big data, Infosys

Featured Speakers

Global Live Streaming (simulcast) of the launch event will be available

Event highlights

50 clients and prospects from Global 2000

The future of big dataDoug Cutting, Chief Architect, Cloud era

Executive keynoteS. D. Shibulal, CEO and Managing Director, Infosys

ModeratorVishnu Bhat, VP and Global Head – Cloud and Big Data, Infosys

PanelistsDoug Cutting, Chief Architect, Cloudera

Robert Stackowiak, Vice President, Big Data & Analytics Architecture, Oracle

2 Clients/Prospects

Unlocking the business value of big dataPanel discussion

REGISTER NOW for the simulcast

References

• Embracing the Elephant in the Room • Big Data Spectrum • The Big Data Opportunity

• Infosys – Art and Science

• Big data: The next frontier for innovation, competition, and productivity

THANK YOU

www.infosys.com

Dheeraj Chowdhury

Principal Consultant – Business Platforms

Infosys Australia & New Zealand

m: 0412107479

e: dheeraj_chowdhury@infosys.com

twitter: dheerajc .