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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
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 7Internal
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.
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 8Internal
Business Value of an Integrated and Fully Evolved BI Solution
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 9Internal
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/
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 13Internal
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
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 19Internal
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
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 20Internal
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
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 21Internal
Financial
Telcom
Retails
e-Comm
CreditInvestigation
M edia
PublicSector
Energy &M anufacturing
Success With Over 500 Leaders Around the World
© 2016 SAP SE or an SAP affiliate company. All rights reserved. 22Internal
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