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

Transcription

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

2 Why Retailers Must Restructure In 2016 Rapid Internet market share gains. Aggressive U.S. expansion of low price international retailers Primark, Aldi and Lidl Surge in off-price store openings Consumers prioritize new technology Communication with Millennials (2016-Jan) 2016 Retail and Consumer Products Trends (from PWC) 1 Brand entrants are more focused 2 Stores shrink 3 Giants personalize and localize 4 Frenemies collaborate 5 Global brands embrace social issues Retail Trends 2016, Redefining convenience (from Deloitte) 1 Profitability: this has always been important to retailers! However, the traditional model of retail has been challenged and as sales increasingly migrate online, the economics of retail are shifting. 2 Productivity: rising costs, particularly staff costs with the introduction of the National Living Wage looming, are placing a greater focus on productivity of people, productivity of stores and retail space. 3 Payment: the growing consumer uptake of mobile payment and digital wallets is challenging retailers to rethink the in-store experience and the way in which checkout is managed. 4 Personalization: consumers increasingly demand personalised products and services that are relevant to them SAP SE or an SAP affiliate company. All rights reserved. Internal 3

3 A Japanese Enterprise use Advance Analytic to drive business

4 Grupo Merza: Improving Wholesale and Retail Insights with Analytic Solutions from SAP Company Grupo Merza Headquarters Michocan, Mexico Industries Retail Wholesale distribution Products and Services Food and beverage distribution, transportation and logistics, and financial services Employees 4,500 Web Site Partners SAP Services organization SAP s Data Science organization Cisco Systems Inc. Objectives Analytic insight with little IT support Insight into market baskets across products, categories, and stores Less risk in wholesale customer loans Efficient, effective IT operations Resolution Deployed SAP Lumira software for data access from any source and the SAP HANA platform for real-time analysis Deployed the SAP Sales Insights for Retail analytic application to gain point-of-sale insight and SAP Predictive Analysis software to calculate loan risk Completed the implementation project in eight weeks Worked with SAP s Data Science organization to define a retail analytics strategy, optimize solutions, and train users Benefits Faster decisions with self-service data visualization Deeper insight into how promotions and product assortment impact market baskets Better loan policy for wholesale customers With analytics tools from SAP, Grupo Merza is becoming a datadriven organization. With better data access and deeper point-of-sale insight, we can see who our customers are and what they want. Alfonso Cedillo, CIO, Grupo Merza 40% 70% Faster processing of transactional data and report delivery with SAP HANA 1 scorecard To track on-time payments on customer credit with SAP Predictive Analysis 4 weeks To deploy SAP Lumira without consulting services 2016 SAP SE or an SAP affiliate company. All rights reserved (15/04) This content is approved by the customer and may not be altered under any circumstances. Internal 7

5 Business Value of an Integrated and Fully Evolved BI Solution 2016 SAP SE or an SAP affiliate company. All rights reserved. Internal 8

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. Internal 9

7 Department Stores (Mexico) shops Approximately 900,000 skus Data compression (8 TB to 800 GB) Analysis of slow sellers vs. fast sellers Identification in the real time Transfer between dedicated Truck more efficiency Improved high value sales and slow movers product and maintain adequacy of inventory in stores BIG DATA GIVES LIVERPOOL MOE HIGH VALUE PRODUCTS SALES AND LOW INVENTORY

8 Greatly Improve your Time to Value 3 Months Data Connections Data Manipulation Variable Reduction & Sampling Predictive model creation Scoring & Validation Model Interpreta -tion Application to business Automated and simplified by SAP Predictive Analytics Optimal model selected Simple GUI Automated Automated Simplified automatically Application to business 1 Week 2016 SAP SE or an SAP affiliate company. All rights reserved. Internal 13

9 What is SAP Predictive Analytics?

10 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 16

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12 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

13 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. Internal 19

14 Predictive Analytic help corporation bring in high ROI Retail Sales increased by 8.5%, ROI increased 14% Sales Predictability Increased 10% Campaig n Response Rate increased 220% Bank Each year because of fraud caused lost has decreased USD $ 1B Response Rate increased 5 times Compared with the control group,7 times increase in response rate Telco Cam paign response rate increased 260% M onthly Churn Rate decreased 3% Custom er Churn & Cross-Sell M odels over 700 Others Every year over 400 incident s, fuel and tires Costs reduction 3% Covering 20,000 different social com munities Integration of more than 5 billion raw data from diff. State agencies 2016 SAP SE or an SAP affiliate company. All rights reserved. Internal 20

15 Success With Over 500 Leaders Around the World Telcom Financial Retails e-comm Credit Investigation M edia Public Sector Energy & M anufacturing 2016 SAP SE or an SAP affiliate company. All rights reserved. Internal 21

16 Predictive Future It will embed into any application to make the application become more intelligence Predictive will become more generic and easy to use by anyone BI + Predictive + Business Domain is the key of success (analytic cycle) Predictive will make people getting smarter Whoever can leverage Predictive into their business whoever can gradually out perform in the market! Just like automation. No matter what, technology will become useful if it can be manage by business people SAP SE or an SAP affiliate company. All rights reserved. Internal 22

17 Thank you