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© CSC 2012 1
Getting 3Vs to 3Is to deliver Business Value
Andreas Hufenstuhl
2 © CSC 2012 December 3, 2012 2 © CSC 2012 December 3, 2012
Agenda
Transforming Organizations and Industries
Client Success Today
How to Drive Business Value
© CSC 2012 3 December 3, 2012
Transforming Organizations and Industries
4 © CSC 2012 December 3, 2012
The Data “rEvolution” Is: “Setting New Expectations”
• Credit and risk scoring
• Fraud detection
• Trade analysis
• “Whole earth” modeling
• Climate change
• Alternative energy
• Counter-intelligence
• Situational awareness
• Disease surveillance
• Drug discovery
• Personalized healthcare
• Sentiment
• Consumption
• Promotions
• Speed
• Traffic flow
• Detection
5 © CSC 2012 December 3, 2012
Appropriate Use of Big Data Can Better Inform Your Organization
PAST (Intelligence)
FUTURE (Informed Intuition)
PRESENT (Insight)
What should I do about it?
What is likely to happen?
Why did it happen?
What happened?
Why is it happening?
What is happening?
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Why Now?
Economy/Marketplace Pressures
Data Mining Technology Advances
Falling Costs of Infrastructure
+ +
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Big Data Value is better Intelligence, Insight and more Informed Intuition put into Action for your organization
Big Data is about creating competitive advantage
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What One Piece of Information, If You Had It, Would Change the Way You Do Business?
CIO
Procurement
Supply Chain
Finance
Industry- Specific Marketing
Sales
Customer Service
COO
Human Resources
CEO CFO CMO
Business Directed, IT Enabled
© CSC 2012 9 December 3, 2012
Client Success Today
10 © CSC 2012 December 3, 2012
How Are Organizations Taking Advantage of Big Data?
Retail/CPG
Performance optimization and analytical insights into POS and
regional sales trends
Healthcare
Integrating data from member communities
Wholesale
Maximize profitability
Transportation
Better scheduling
Insurance
Single version of the truth
Travel & Leisure
Customer Intelligence Lifetime Value Model
Government
Reduce Tax Evasion
Commodities Trading
Climate data leveraged for commodities trading
Financial Services
Claims fraud detection
Natural Resources
Real time management of operations and maintenance
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How to Drive Business Value
12 © CSC 2012 December 3, 2012
Where Are You on Your Big Data Journey?
Are You … Not yet Experimenting
Implemented
in Some
Business Units
Implemented
Enterprise-Wide
1 Embracing Big Data strategically?
2 Leveraging unstructured data and social media data to improve business
decision making?
3 Transitioning your organization into predictive analytics?
4 Addressing latency due to complex queries, analytics and reporting against large
data warehouses, or batch processing with database appliances and parallel
processing?
5 Improving performance management and self service with scorecards, dashboards,
heat maps, forecasting, and advanced visualization tools?
6 Consolidating disparate databases into an integrated DB architecture?
7 Implementing MDM, data quality, and data governance programs to meet
operational, regulatory, and customer service requirements?
8 Establishing Hadoop-based architecture environments for mining unstructured
sources, including social media, email, mobility, and other sources?
9 Implementing search intelligence and semantic engines against document
management, content management, and other enterprise sources for analytics?
10 Considering adopting “analytics as a service” transformation models?
13 © CSC 2012 December 3, 2012
Lessons Learned
Start from the business need/opportunity
Imagine the potential from disparate data sources
Present the output in an easily assimilated form
It’s an iterative approach…
Avoid costly mistakes
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What Do I Need to Start Thinking About? Innovate Your Business Based on Complete View of Internal/External Dynamics
• Exceed business intelligence benefits Dynamic analysis of various types of data
• See hidden opportunities Address fundamental business challenges based on stronger analysis methods, drive new ways of thinking
• Technology advances Breaking previous limits on data volume
• Stronger analytics techniques Use advanced programming; statistical, research, text analysis; or data mining techniques
• Internal structured data Enterprise applications
• Internal (semi) structured Email, knowledge repositories, portals, desktop applications
• External (semi) structured Data providers, business partners, Web services
• External unstructured Social media, consumers, mobile
3. Unlock Big Value 2. Apply Modern Methods 1. Leverage Disparate
Data Sources
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Probably the Greatest Challenge Is Assembling the Right Skills
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• Analytics as a Service
• Business Intelligence as a Service
CSC offers clients full life cycle support through industry specific and cross-industry solutions
• CareVeillance
• ClimatEdge™
• Dashboard 360 Management
• Defense Supply Chain Analytics
• EI for Retail as a Service
• Electronic Patient Folder
• Fraud Analytics Management
• Manufacturing PBL Command
• Petroleum Enterprise Intelligence Information Management
• Dashboard 360 Implementation
• EI for Retail Implementation
• Field Tech 260 Implementation
• Fraud Analytics Implementation
• Health Enterprise Content & Collaboration suite
• Insurance Optics
• Petroleum Enterprise Intelligence
• Rail Control System
• Analytics Transformation
• Business Intelligence Implementation
• Master Data Management Implementation
• Aftermarket Roadmap
• Field Tech 360 Strategy and Architecture
• Insurance Optics Business Intelligence Roadmap
• Payor Optics 360 Roadmap
• Petroleum Enterprise Intelligence Discovery and Design
• Enterprise Intelligence Strategy
• Big Data Strategy
• Information Exploitation Assessment
• Data Strategy and Governance
Shape Manage
Ind
ustr
y S
olu
tio
ns
Cro
ss-I
nd
ustr
y
Optimize Business Value Realize Business Value Strategize Business Value
Transform
17 © CSC 2012 December 3, 2012
Summary
Achieving business value from data requires business and IT transformation
Change is critical to staying competitive
Your current resources may not be able to support such major transformation on their own
Revolutionize your operating model/performance with Big Data
Many organizations are achieving business value today
18 © CSC 2012 December 3, 2012
www.csc.com/bigdata Thank You
Follow us at:
#CSCBigData
19 © CSC 2012 December 3, 2012
© CSC 2012 20 December 3, 2012
Case Study — Financial Services
21 © CSC 2012 December 3, 2012
Case Study — Commodities Trading/CSC Climate Edge from NASA Data
NASA, the most reliable source of climate data
• CSC’s Climate Edge is now distributed via reports through the Bloomberg network. Data will also be available for predictive analytics in phase 2 for insurance, investments, trading, healthcare, and other industries
• Needed access to leverage Big Data accumulated from climate changes, trends, and patterns that could impact crops, farming, food services, health, and catastrophic events
• Improved information for predictive analytics and outcomes management
• Maximize profitability through predictive and decisive responses to projections for commodities trading, insurance, and healthcare
Challenge Solution Results
Client
22 © CSC 2012 December 3, 2012
Case Study — Financial Services MetLife Auto & Home
A leading insurance company
• Analytics
• Insurance Fraud Analytics Solution
• Uses data to detect patterns and behaviors that might be signs of fraud
• Detect fraud as early as the first notice of loss, without disrupting claims process
• Detect potentially fraudulent claims much earlier and with very few false positives
• 16% increase in investigations
• Significant return on investment within 6 months
Challenge Solution Results
Client
23 © CSC 2012 December 3, 2012
Case Study — Investment Banking Major Global Investment Bank
One of the world’s largest investment banks
• Master data management
• Data warehouse
• Business intelligence
• Create single repository for all data deemed useful for multiple applications
• Enable very large information and data flows to be used more effectively
• Significantly improved decision-making ability and exposure monitoring
• More accurate and reliable regulatory reporting
Challenge Solution Results
Client
24 © CSC 2012 December 3, 2012
Case Study — Insurance AG Insurance Company
Large insurance company
• Master data management
• Data warehouse
• Business intelligence
• Iterative, incremental approach to life insurance data warehouse design and implementation
• SAS Enterprise Data Integration and Business Intelligence software
• Change management action plan, before, during, and after the project
• Gain “single version of the truth” from centralized data definitions, data flows automation, data transparency, and traceability
• Generate faster, standardized dynamic reports and dashboards
• Reduce risks in knowledge sharing between business and IT
• More dynamic and responsive reporting
• More time to analyze figures and give advice
• Fewer risks in data traceability and knowledge sharing
Challenge Solution Results
Client
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Case Study — Healthcare
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Case Study — Healthcare BlueCross and BlueShield
One of the world’s largest healthcare organizations • Master data management
• Data warehouse
• Business intelligence
• Designed and developed data warehouse system that integrates data from 40 member companies
• Enhance benchmarking capabilities and enable advanced predictive analytics for world’s largest healthcare informatics data warehouse
• Warehouse can process medical and other claims for 90M – 100M people
• Delivers unmatched detail about trends and best practices
• Provides huge competitive advantage
Challenge Solution Results
Client
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Case Study — Transportation
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Case Study — Transportation Major Global Travel and Leisure Company
A leading global car hire company • Customer intelligence
• Analytics
• Master data management
• Strategic CRM/Customer Intelligence roadmap
• Customer lifetime value model to use for value segmentation
• Analysis, operationalization, and insight
• Increase growth
• Transform from transactional to customer-led, service-driven company
• Better decision making based on customer lifetime value
• 25% increase in more targeted campaigns
• Plan to drive incremental revenue over 3 years
Challenge Solution Results
Client
29 © CSC 2012 December 3, 2012
Case Study — Transportation Swiss Federal Railways (SBB)
Operates most intensively used rail network in Europe • Big Data
• Analytics
• Performance improvement
• System uses hundreds of pieces of data — received per second from train position sensors and other peripheral systems — to calculate journey forecasts and deliver resulting changes to railway dispatchers and customer systems in near real time
• Needed to improve train dispatching
• More trains run on time (up from 92% to 96%)
• Passengers are happy
• Switzerland is now the leader in international punctuality statistics
Challenge Solution Results
Client
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Case Study — Government
31 © CSC 2012 December 3, 2012
Case Study — Government
Large government institution responsible for tax collection
• Data warehouse
• Six business-oriented projects
• Data warehouse (combined traditional reporting, data analysis, advanced data mining)
• Predictive model for bankruptcy
• Need to be more efficient
• Pressure on government budgets and regulations (e.g., privacy)
• Manual information management processes (errors, time consuming)
• Low business intelligence maturity
• Increased profitability of tax recovery process (reduce tax evasion) — prioritize risks, new trend analysis to identify emerging threats
• Reduced litigations
• Single source of data: Increased cross-organization information management, improved access, business-intuitive format
Challenge Solution Results
Client
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Case Study — CENR
33 © CSC 2012 December 3, 2012
Case Study — Natural Resources Major Global Mining Company
A leading global resources company
• Big Data
• Analytics, machine-to-machine and predictive
• Performance improvement
• Enterprise Intelligence Strategic Roadmap Project (in process)
• Discovery – Operations Readiness
• Future state design
• Roadmap
• Big Data volume and velocity of machine-to-machine sensor data from 12 borers and other mining assets operating 24x7x365
• How to gain real-time insights to efficiently operate the 21st century mine
• Future expected benefits
• Real-time management of drilling operations
• Predictive equipment maintenance
Challenge Solution Results
Client
34 © CSC 2012 December 3, 2012
Case Study — Wholesale Large Diamond Company
One of the world’s largest diamond companies
• A simple and intuitive business intelligence and document management solution that delivers a competitive edge in performance
• Provide access to accurate, timely, and up-to-date business intelligence on customer demand, current stocks of rough diamonds, competitive activity, and market trends
• Improved information management
• Can maximize profitability through fast and decisive responses to even very small events and developments in national markets
Challenge Solution Results
Client
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Case Study — Retail
36 © CSC 2012 December 3, 2012
One of the nation’s largest discount clothing retailers
• 4,800 stores and 28,000 employees
• More than 1 million POS transactions and 2 million historical transactions processed daily
Case Study — Retail/CPG Major Retailer
• Leverage database appliance (Netezza) and BI tools (MicroStrategy) for dashboards and analytics. Create an enterprise data mart for analytics and dashboards
• Lots of data. Latency in getting reports to users. Reliance on electronic spreadsheets. Long batch cycles. Manually intensive. Limited visibility into profitability and opportunities to optimize
• 957 million rows of data processed in 20 seconds. Eliminated electronic spreadsheets from operational reports
• Improved accuracy, profitability; eliminated manually intensive reconciliation
• Allowed costs to be managed at SKU/location level, and merchants/ finance to have visibility into financial results
• Real-time availability of dashboards and reports for stores and operations
Challenge Solution Results
Client
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Case Study — Other
38 © CSC 2012 December 3, 2012
Technology services company that provides mission- critical network services and communication infrastructure
• Serves most of the major telecommunications operators, public sector agencies, and large-scale enterprises across the UK, Ireland, and Germany
Case Study — Technology Services
• Delivered strategy and direction by profiling and assessment of the business aspirations
• Targeted initial core business challenges (SCM, Finance)
• Created full suite of reports and dashboards
• Manual, ad hoc, and bespoke/customized spreadsheet based reporting
• No accurate control of budgetary spend and no ability to forecast or predict events
• Business information flawed, decreasing reliability of information
• No single view of truth to drive business growth
• Clear and accurate reporting to the board, executive community
• User self-service report generation
• Centralized reporting solution including single view of truth
• Tighter controls on budgetary expense and predicting spend
• Business expense savings
Challenge Solution Results
Client
39 © CSC 2012 December 3, 2012
Wireline and wireless telecommunications provider transitioning into professional services, digital content sales and delivery, and cloud services
• Corporate performance management
Case Study — Telecommunications
• Defined and designed critical corporate KPI dashboards
• Built technical designs for interim enterprise date warehouse housing all finance summary data
• Combined 16 manual reporting processes for wireless and wireline BUs
• CFO recognized business need for consolidated/aggregate reporting made available directly from source systems, with drill-down capability and availability via mobile devices
• Corporate Performance Management system provides dashboard and analysis reporting for executives across all divisions. Key users include Sales, Finance, and FP&A
• First release: Summarized analysis supporting leadership financials
• Second release: Key finance and business metrics as well as drill-down for monthly financials and operational data
Challenge Solution Results
Client
