Unleash the Power of Big Data with the SAP HANA Platform Big Data, Big Challenges, and Big Opportunities

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1 Unleash the Power of Big Data with the SAP HANA Platform Big Data, Big Challenges, and Big Opportunities Greg Wong, Director Analytics Centre of Excellence, SAP Greater China 2016 SAP SE or an SAP affiliate company. All rights reserved. 1

Technology Priority for CIO in 2016 Rank Investment Priority 1 BI/analytics 2 Cloud 3 Mobile 4 Digitalization/digital marketing 5 Infrastructure Data

2 Technology Priority for CIO in 2016 Rank Investment Priority 1 BI/analytics 2 Cloud 3 Mobile 4 Digitalization/digital marketing 5 Infrastructure Data Centre 6 ERP 7 Security 8 Industry-specific applications 9 CRM 10 Networking, voice and data comms 2016 SAP SE or an SAP affiliate company. All rights reserved. 2

3 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% (2016-Feb-26) 2016 SAP SE or an SAP affiliate company. All rights reserved. 3

4 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! SAP SE or an SAP affiliate company. All rights reserved. 4

6 Business Value of an Integrated and Fully Evolved BI Solution 36% Lower BI expenditures More Companies that consolidate multiple BI tools into a standardized and enterprise-wide portfolio, have 36% lower BI expenditures 10% timely information Companies that have enhanced business user access to information, have 10% more timely information to create actionable insights 24% Higher usage Companies with flexible information systems have 24% higher usage of business intelligence to manage in their business processes Greater than 10x 1 More ROI SAP SE or an SAP affiliate company. All rights reserved. 6

A Shift Is Occurring: Non-Data Scientists Are

data using advanced analytics (predictive, text,

Business Analysts 75% Data Scientists 56% Business

7 A Shift Is Occurring: Non-Data Scientists Are Getting Involved Who in your organization analyzes data using advanced analytics (predictive, text, Web analytics)? Business Analysts 75% Data Scientists 56% Business Users 50% Source: TDWI; SAP SE or an SAP affiliate company. All rights reserved. 7

9 Applying Predictive to Real Business Problems Types of Business Problems Solved with Predictive Sales and Marketing Operations Fraud and Risk Finance and HR Others Churn Reduction Predictive Fraud and Abuse Cash Flow and Life Sciences Customer Maintenance Detection Forecasting Health Care Acquisition Lead Scoring Product Recommendation Campaign Optimization Customer Segmentation Next Best Offer/ Action Load Forecasting Inventory/demand Optimization Product Recommendation Price Optimization Manufacturing Process Opt. Quality Management Yield Management Claim Analysis Collection and Delinquency Credit Scoring Operational Risk Modeling Crime Threat Revenue and Loss Analysis Budgeting Simulation Profitability and Margin Analysis Financial Risk Modeling Employee Retention Modeling Succession Planning Media High Education Public Sector/ Social Sciences Construction and Mining Travel and Hospitality Big Data and IoT 2016 SAP SE or an SAP affiliate company. All rights reserved. 9

10 Digital Transformation changes key aspects of the Rail Business DIGITIAL CUSTOMER ENGAGEMENT Reservation & ticketing Omni Channel Personalized engagement Dynamic pricing Social engagement PROACTIVE SAFETY AND MAINTENANCE Asset Management Predictive Maintenance Internet Of Things REAL TIME FINANCIAL & OPERATIONAL INSIGHTS INTELLIGENT OPERATIONS Transportation Management Timetable Recovery Service Level Management Fuel Management Yard Management Networked Logistics CONNECTED & ENGAGED WORKFORCE Tracking and Reporting Self Service Expense Management Mobile Instructions Contingent labour DIGITAL MANUFACTURING Connected Manufacturing Predictive Quality Machine Data Management 2016 SAP SE or an SAP affiliate company. All rights reserved. 10

The Cost of Neglecting Predictive Analytics LOST REVENUE

Real-time inventory information (retailer, outlet

13 Digital Catalog (estimated savings $ million) Customer Services: 360 degree view of each customer Purchase history Automatic suggestion of products, styles, colors, etc. Real-time inventory information (retailer, outlet and department store) BIG DATA GIVES SHOPPERS FASHION ADVICE TO FIT THEIR STYLE

is an Italian fashion house founded by mani which designs, manufactures, distributes and retails couture, ready-to-wear leather goods, shoes, watches, jewellery, accessories, eyewear, cosmetics and

14 Giorgio Armani S.p.A. is an Italian fashion house founded by Giorgio Armani which designs, manufactures, distributes and retails couture, ready-to-wear leather goods, shoes, watches, jewellery, accessories, eyewear, cosmetics and home interiors. The brand markets these products under several labels, from the most expensive to the most accessible Armani Prive, Giorgio Armani, Emporio Armani, Armani Collezioni, AJ Armani Jeans, AX Armani Exchange. Armani have used SAP Predictive Analytic to develop: PREDICTIVE HELP ARMANI TO DELIVER BETTER SERVICES TO THEIR LOYAL CUSTOMERS Up and Cross-sell models for product recommendation for customers classification models for product recommendations (e.g. Armani clothing, accessories, jewellery, leather goods, perfume, jeans, etc) Customer segmentation behavior and value of segmentations

15 Why Now? Better Decision Making A B C Understanding Customers SAP Analytics Solutions Improving Performance Driving New Revenues Acting in Real Time 2016 SAP SE or an SAP affiliate company. All rights reserved. 15

17 2016 SAP SE or an SAP affiliate company. All rights reserved. No part of this publication may be reproduced or transmitted in any form or for any purpose without the express permission of SAP SE or an SAP affiliate company. SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP SE (or an SAP affiliate company) in Germany and other countries. Please see for additional trademark information and notices. Some software products marketed by SAP SE and its distributors contain proprietary software components of other software vendors. National product specifications may vary. These materials are provided by SAP SE or an SAP affiliate company for informational purposes only, without representation or warranty of any kind, and SAP SE or its affiliated companies shall not be liable for errors or omissions with respect to the materials. The only warranties for SAP SE or SAP affiliate company products and services are those that are set forth in the express warranty statements accompanying such products and services, if any. Nothing herein should be construed as constituting an additional warranty. In particular, SAP SE or its affiliated companies have no obligation to pursue any course of business outlined in this document or any related presentation, or to develop or release any functionality mentioned therein. This document, or any related presentation, and SAP SE s or its affiliated companies strategy and possible future developments, products, and/or platform directions and functionality are all subject to change and may be changed by SAP SE or its affiliated companies at any time for any reason without notice. The information in this document is not a commitment, promise, or legal obligation to deliver any material, code, or functionality. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements, which speak only as of their dates, and they should not be relied upon in making purchasing decisions SAP SE or an SAP affiliate company. All rights reserved. 17

Drive Insight from Retail Analytic and Leverage Predictive to Change the Game. Greg Wong, Director Analytics, Greater China July 26, 2016

Drive Insight from Retail Analytic and Leverage Predictive to Change the Game Greg Wong, Director Analytics, Greater China July 26, 2016 Why Retailers Must Restructure In 2016 Rapid Internet market share