Greg Wong, Director Analytics, Greater China July 26, 2016Retail Trends 2016, Redefining convenience...

Greg Wong, Director Analytics, Greater ChinaJuly 26, 2016

Drive Insight from Retail Analytic andLeverage Predictive to Change the Game

© 2016 SAP SE or an SAP affiliate company. All rights reserved. 3Internal

www.forbes.com (2016-Jan)

2016 Retail and Consumer Products Trends (from PWC)

1 Brand entrants are more focused2 Stores shrink3 Giants personalize and localize4 “Frenemies” collaborate5 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 assales 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 agreater 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-storeexperience and the way in which checkout is managed.

4 Personalization : consumers increasingly demand personalised products and services that are relevant to them.

Why Retailers Must Restructure In 2016Rapid Internet market share gains.Aggressive U.S. expansion of low price internationalretailers Primark, Aldi and LidlSurge in off-price store openingsConsumers prioritize new technologyCommunication with Millennials

A Japanese Enterprise use Advance Analytic to drive business


Grupo Merza: Improving Wholesale and RetailInsights with Analytic Solutions from SAP

CompanyGrupo Merza

HeadquartersMichocan, Mexico

IndustriesRetailWholesale distribution

Products and ServicesFood and beverage distribution,transportation and logistics, andfinancial services

Employees4,500

Web Sitewww.grupomerza.com

PartnersSAP® Services organizationSAP’s Data Science organizationCisco Systems Inc.

Objectives� Analytic insight with little IT support� Insight into market baskets across products, categories, andstores� Less risk in wholesale customer loans� Efficient, effective IT operations

Resolution� Deployed SAP Lumira® software for data access from anysource and the SAP HANA® platform for real-time analysis� Deployed the SAP® Sales Insights for Retail analytic applicationto gain point-of-sale insight and SAP Predictive Analysissoftware to calculate loan risk� Completed the implementation project in eight weeks� Worked with SAP’s Data Science organization to define a retailanalytics strategy, optimize solutions, and train users

Benefits� Faster decisions with self-service data visualization� Deeper insight into how promotions and product assortmentimpact market baskets� Better loan policy for wholesale customers

“With analytics tools from SAP, Grupo Merza is becoming a data-driven organization. With better data access and deeper point-of-saleinsight, we can see who our customers are and what they want.”

Alfonso Cedillo, CIO, Grupo Merza

40%–70%Faster processing of transactionaldata and report delivery with SAPHANA

1 scorecardTo track on-time payments oncustomer credit with SAPPredictive Analysis

4 weeksTo deploy SAP Lumira withoutconsulting services

37387 (15/04) This content is approved by the customer and may not be altered under any circumstances.


Business Value of an Integrated and Fully Evolved BI Solution


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

¡ Department Stores (Mexico)

¡ + 100 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 andmaintain adequacy of inventory in stores

BIG DATAGIVESLIVERPOOLMOE HIGHVALUEPRODUCTSSALES ANDLOWINVENTORYhttp://www.liverpool.com.mx/


Optimal model selectedautomatically

Automated and simplified by SAP Predictive Analytics

3 Months3 Months

1 Week1 Week

DataConnections

DataManipulation

VariableReduction &

Sampling

Predictivemodel

creation

Scoring &Validation

ModelInterpreta

-tion

Applicationto business

Simple GUI Automated Automated Simplified Applicationto business

Greatly Improve your Time to Value

https://www.youtube.com/watch?v=sIbUAvrO70A&list=PL4B_3KgKZMUI7hU74LDkJCULP6fF3orR9

What is SAP Predictive Analytics?

BIG DATAGIVESSHOPPERSFASHIONADVICE TOFIT THEIRSTYLE

16https://www.youtube.com/watch?v=3gVKUYY6pdI

¡ 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


Types of Business Problems Solved with Predict ive

¡ Predictive

Maintenance

¡ Load Forecasting

¡ Inventory/ demand

Optimization

¡ Product

Recommendation

¡ Price Optimization

¡ Manufacturing

Process Opt.

¡ Quality Management

¡ Yield Management

Operations

¡ Fraud and Abuse

Detection

¡ Claim Analysis

¡ Collection and

Delinquency

¡ Credit Scoring

¡ Operational Risk

Modeling

¡ Crime Threat

¡ Revenue and Loss

Analysis

Fraudand Risk

¡ Cash Flow and

Forecasting

¡ Budgeting

Simulation

¡ Profitability and

Margin Analysis

¡ Financial Risk

Modeling

¡ Employee Retention

Modeling

¡ 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


Compared with the control group,7t imes increase in response rate

Each year because of fraud causedlost has decreased USD $ 1B

Response Rateincreased 5 times

Customer Churn & Cross-SellM odels over 700

Campaign response rateincreased 260%

M onthly Churn Ratedecreased 3%

Campaign Response Rateincreased 220%

Sales PredictabilityIncreased 10%

Retail

Bank

Telco

Sales increased by 8.5%，ROI increased 14%

Integrat ion of more than 5billion raw data from diff.

State agencies

OthersCovering 20,000 different

social communit iesEvery year over 400

incidents, fuel and t iresCosts reduction 3%

Predictive Analytic help corporation bring in high ROI


Financial

Telcom

Retails

e-Comm

CreditInvestigation

M edia

PublicSector

Energy &M anufacturing

Success With Over 500 Leaders Around the World


Predictive Future

¡ It will embed into any application to make the application become moreintelligence

¡ 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 graduallyout perform in the market! Just like automation.

¡ No matter what, technology will become useful if it can be manage bybusiness people.

Thank you

Greg Wong, Director Analytics, Greater China July 26, 2016Retail Trends 2016, Redefining convenience...

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