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Unleash the Power of Big Data with theSAP HANA PlatformBig Data, Big Challenges, and Big Opportunities
Greg Wong, Director AnalyticsCentre of Excellence, SAP Greater China
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Technology Priority for CIO in 2016
Rank Investment Priority1 BI/analytics2 Cloud3 Mobile4 Digitalization/digital marketing5 Infrastructure Data Centre6 ERP7 Security8 Industry-specific applications9 CRM
10 Networking, voice and data comms
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The 5 Most Important Technologies to Insurance CEOs
Top 10 BI Trends in 2016 %
1. Data & analytics 79%
2. CRM 76%
3. Social media communications and engagement 58%
4. Personal data security 50%
5. Web-enabled collaboration tools 49%http://www.insurancenetworking.com/ (2016-Feb-26)
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Six Business Intelligence Predictions For 2016
¡ Prediction 1: The big bang you hear is the explosion of innovation.
¡ Prediction 2: We must adapt or die.
¡ Prediction 3: Whose BI will you buy?
¡ Prediction 4: Enough about data – where’s the information?
¡ Prediction 5: Death by desktop
¡ Prediction 6: We’ll see just as many CDO’s hired as fired!
http://www.forbes.com/sites/groupthink/2015/12/17/six-business-intelligence-predictions-for-2016/#489140ec4f83
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Business Value of an Integrated and Fully Evolved BI Solution
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Business Value of an Integrated and Fully Evolved BI Solution
Lower BI expenditures
Companies that consolidate multiple BItools into a standardized andenterprise-wide portfolio, have 36%lower BI expenditures
36%More timely information
Companies that have enhancedbusiness user access to information,have 10% more timely information tocreate actionable insights
10%
Companies with flexible informationsystems have 24% higher usage ofbusiness intelligence to manage in theirbusiness processes
24%Higher usage More ROI
10x 1
13.01Greater than
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A Shift Is Occurring: Non-Data ScientistsAre Getting Involved
Who in your organizationanalyzes data using advancedanalytics (predictive, text,Web analytics)?
Who in your organizationanalyzes data using advancedanalytics (predictive, text,Web analytics)?
BusinessAnalysts
DataScientists
BusinessUsers
75%
56%
50%
Source: TDWI; 2016
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https://www.youtube.com/watch?v=ofq7ygnWpbw
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Types of Business Problems Solved with Predictive
¡ PredictiveMaintenance
¡ Load Forecasting¡ Inventory/demand
Optimization¡ Product
Recommendation¡ Price Optimization¡ Manufacturing
Process Opt.¡ Quality Management¡ Yield Management
Operations
¡ Fraud and AbuseDetection
¡ Claim Analysis¡ Collection and
Delinquency¡ Credit Scoring¡ Operational Risk
Modeling¡ Crime Threat¡ Revenue and Loss
Analysis
Fraudand Risk
¡ Cash Flow andForecasting
¡ BudgetingSimulation
¡ Profitability andMargin Analysis
¡ Financial RiskModeling
¡ Employee RetentionModeling
¡ Succession Planning
Financeand HR
¡ Life Sciences¡ Health Care¡ Media¡ High Education¡ Public Sector/
Social Sciences¡ Construction and
Mining¡ Travel and
Hospitality¡ Big Data and IoT
Others
¡ Churn Reduction¡ Customer
Acquisition¡ Lead Scoring¡ Product
Recommendation¡ Campaign
Optimization¡ Customer
Segmentation¡ Next Best Offer/
Action
Sales andMarketing
Applying Predictive to Real Business Problems
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Digital Transformation changes key aspects of the Rail Business
DIGITIAL CUSTOMERENGAGEMENT¡ Reservation & ticketing¡ Omni Channel¡ Personalized engagement¡ Dynamic pricing¡ Social engagement
INTELLIGENT OPERATIONS¡ Transportation Management¡ Timetable Recovery¡ Service Level Management¡ Fuel Management¡ Yard Management¡ Networked Logistics
PROACTIVE SAFETY ANDMAINTENANCE¡ Asset Management¡ Predictive Maintenance¡ Internet Of Things
CONNECTED & ENGAGEDWORKFORCE¡ Tracking and Reporting¡ Self Service¡ Expense Management¡ Mobile Instructions¡ Contingent labour
DIGITAL MANUFACTURING¡ Connected Manufacturing¡ Predictive Quality¡ Machine Data Management
REAL TIME FINANCIAL& OPERATIONAL
INSIGHTS
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LOSTREVENUE
LOSTREVENUE
The Cost of Neglecting Predictive Analytics
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BIG DATAGIVESSHOPPERSFASHIONADVICE TOFIT THEIRSTYLE
¡ Digital Catalog (estimated savings $ 1.5 + million)
¡ Customer Services: 360 degree view of each customer
¡ Purchase history
¡ Automatic suggestion of products, styles, colors, etc.
¡ Real-time inventory information (retailer, outlet anddepartment store)
¡ Giorgio Armani S.p.A. is an Italian fashion house foundedby Giorgio Armani which designs, manufactures, distributesand retails couture, ready-to-wear leather goods, shoes,watches, jewellery, accessories, eyewear, cosmetics andhome interiors.
¡ The brand markets these products under several labels,from the most expensive to the most accessible – ArmaniPrive, Giorgio Armani, Emporio Armani, Armani Collezioni,AJ | Armani Jeans, AX | Armani Exchange.
¡ Armani have used SAP Predictive Analytic to develop:
¡ Up and Cross-sell models for product recommendation forcustomers – classification models for productrecommendations (e.g. Armani clothing, accessories,jewellery, leather goods, perfume, jeans, etc)
¡ Customer segmentation – behavior and value ofsegmentations
PREDICTIVEHELP ARMANITO DELIVERBETTERSERVICES TOTHEIR LOYALCUSTOMERS
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A B C
SAPAnalyticsSolutions
SAPAnalyticsSolutions
Better Decision Making
Understanding Customers
Improving Performance
Driving New Revenues
Acting in Real Time
Why Now?
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Thank You!!!
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