Ponencia de SAP en la Conferencia Esri España 2018

1. PUBLIC
Paramjeet Sachdev (Pammy), SAP
October 24, 2018
SAP Spatial in
Retail

2. Integrated with
Apps
Server
Desktop
APIs
* Targeted but not yet integrated
Running On …
across the stack
Business
Networks*
BI
Digital
Core
HANA
ArcGIS
Esri ArcGIS: 2018 Pinnacle Award Winner for Global Integration
Maps & Spatial Analysis inside SAP or Custom Apps
SAP Business Data in Esri Map-Centric Apps

3. 3PUBLIC© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ
The Challenge: Silos create an incomplete picture
 Business data
 Master data
 Analytical data
Enterprise
Applications
 Geographical
data and layers
 Networks
 Maps and
topologies
GIS Systems
 Diagrams
 2D & 3D
 Animations
Engineering
Systems
 Streaming
 Telemetry
 Location, health
and status
Sensors &
Devices
 Land use
 Weather &
climate data
 Surface
condition data
Satellite &
Drone Imagery
 Social networks
 Photos & Videos
 Bio-metrics
Unstructured

4. The Solution: SAP HANA Platform
Enterprise Applications GIS Systems Engineering Systems Sensors & Devices Satellite & DroneUnstructured
SAP HANA Platform
Application Development Advanced Analytical Processing Data Integration and Quality
SAP, ISV and Custom Applications
All Devices
Database Management
Web Server JavaScript Fiori UX
Graphic
Modeler
Application Lifecycle
Management
Data
Virtualization
ELT &
Replication
Data Quality Hadoop & Spark
Integration
Admin &
Security
High Availability &
Disaster Recovery
Multi-Tier
Storage
Openness
Spatial Graph Predictive Search
Text
Analytics
Streaming
Analytics
Series
Data
Business
Functions
Advanced
Compression
Data ModelingMulti-tenancyMulti-Core &
Parallelization
Columnar OLTP
+ OLAP

5. Why customers choose SAP HANA for Esri
The Next Generation Geodatabase Platform
Performance
Simplify
Democratize
Innovative
Scalable
Experience in-memory first performance
improvements for your GIS and location intelligence
workloads
Seamless integration of spatial & SAP enterprise data
on one platform
Spatially enable the entire enterprise through the
SAP HANA platform
Leverage other advanced engines like graph, machine
learning, text analysis for better insights, improved
decision making, and drive innovation
Consume, store, process, and analyze extreme
volumes of spatial & enterprise data
Leverage SAP HANA in various scenarios with Esri including
Geodatabase, side car GIS accelerator, geo-analytics hub
Virtualize, federate, and process data whereever it may be
Leverage strong integration history and customer use
cases between Esri and SAP HANA
SAP HANA supports the latest Esri innovations including
Utility Network Model, ArcPro 2.1, Enterprise 10.6, and Esri
Insights
Deploy OGC compliant SAP HANA platform on-premise, in
the cloud, as a service, or both
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3
4
5
6
7
8
9
Flexible
Smart
Proven
Modern
Open10

6. 6PUBLIC© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Trends & Disruptors in Retail
https://www2.deloitte.com/uk/en/pages/consumer-business/articles/retail-trends-2016.html
• Enabling Technologies, including Mobilisation
• Analytics & Big Data
• IoT / 4th Industrial Revolution
• SMAC (Social Media, Mobility & Consumerization,
Analytics & Big Data, Cloud Computing)
• SoLoMo (Social Media, Localisation Services,
Mobility & Consumerisation)
• Changing Demographics
• Rise of the Individual
• Social Media / Awareness
• Climate Change
• Economic Interconnectedness
• Resource Stress
• Urbanization

7. 7PUBLIC© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ
3 Top Characteristics to Win in Retail
Source: Deloitte Retail Showcase 2016 (https://www2.deloitte.com/uk/en/pages/consumer-business/articles/retail-showcase.html)

8. 8PUBLIC© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Enriching the Retail Journey
Auto-update loyalty
and load preferences:
profile, types of meal,
allergens, etc. without
bothering customer or
batch jobs
Prepare
Shopping
List
Update
Shopping list Stretch list
Recommendations
How to
get it?
Check inventory / Net
Margin analysis
Log-in
Auto-Load
preferences Delivery…
Availability
& location Substitutes…
Use predictive &
association algorithms on
transaction data to add items
to the shopping list as value
added Recommendations
Spatial engine is used to
identify nearby stores. Availability
of items is checked in every store. The shopping list with 360
degree customer
information is sent to
delivery in real-time & routes
optimized
Use graph models to
identify similar recipes
and suggest products,
considering also
promotions
Use recommendations
algorithms to suggest
products bought by similar
customers Check real-time inventory for
this store. Locate the
corresponding store aisle
If availability is low, it is
possible to find
substitutes

9. 9PUBLIC© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Examples of SAP Co-Innovations in Retail
Customer CareMarketing &
Merchandising
Optimisation
Assets & Supply
chain
1. Demand signal mgt.
& forecasting
Demand Signal
Management (DSiM) to
better respond to
customers and sales
LINK
2. Merchandise
management
Electronic merchandise
mgmt. and information.
Providing flow of goods
and valuation from
vendor to customer.
LINK
3. Customer Lifecycle
Analysis – NBA/RTOM
Real-time analysis of
customer touchpoints to
determine next best
action and offers.
LINK
4. Customer Churn
Analysis
Automated predictive
modelling, identification
of key influencers,
propensity to churn and
drivers.
LINK
5. Live, 360∘ view of
customer / Cust exp.
Providing associates
insight to purchases,
alterations, made-to-
measure garments, and
comments…
LINK
6. Basket analysis for
placement & pricing
Tapping into point-of-
sale data to analyse
basket compositions,
identify product affinities,
and drag-along items
during promotional sales.
LINK
7. Returns Analysis &
Prediction
Local newspaper returns
& demand forecasting.
Identification of supplier
issues from online
returns e.g. wrong size.
LINK
8. Product Markdown
Analysis / Optimisation
Product markdown
analysis SKU by SKU
linked to stock,
substitutes and local
price sensitivity.
LINK
9. Dynamic Inventory
Optimisation
Big data analytics of fleet
telematics enabling new
products, services and
business models.
LINK
10. Connected &
Adaptive Logistics
Monitor and control
logistics operations
automatically and enable
smart retail
LINK
11. IOT and wearables
Driving new business
models: Under Armour
connected fitness where
customers can capture
and analyse their fitness
data on real-time.
LINK
16. Promotional
effectiveness & pricing
analysis
Promotional effectiveness
and cannibalization effect.
Real-time analysis for
east / west black Friday
promotions
LINK
12. Supply Chain
Management
Demand forecasting,
volume of sales
decomposition and
supply chain
optimisation.
LINK
13. Geospatial Analysis
Cash & Carry B2B
geospatial wholesale
analytics, insight &
optimisation.
LINK
14. Profitability
Analysis & Margin
Assurance
Analysis of granular
customer/ product
profitability to identify
category leakage and
opportunity.
LINK
15. Customer trend
analysis (& Why?)
Optimising signal
detection to detect
positive and negative
trends e.g. declining bike
sales and correlate with
local market changes,
LINK
Omni channel Loyalty & Social
media
Market &
Customer Insights
Channels
Products Customers
Supplier
collaboration
Finance & risk
analysis
Workforce
management
Range
Pricing / promotions
Stock
Placement…
Best price
Supplier evaluation
Scorecards
Profitability…
Performance
Location & clustering
Workforce
A/B testing…
Segmentation
Loyalty
Campaign mgt.
Satisfaction…
+ + + Spatial

10. 10PUBLIC© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ
The Competition?

11. 11PUBLIC© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ
In-Store Consumer Behavioural Analytics

12. 12PUBLIC© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ
In-Store Consumer Behavioural Analytics
• Hotspots / coldspots
analysis
• Queueing &
accumulation zones
• Conversion rates from
departments/shelves/are
as
• Dynamic offer
optimization in
different dimensions
• Monitoring the
perception of
promotional activities
• Detailed customer
segmentation with
targeted consumer
interaction
• Prediction of the flow of
customers to the
checkout to optimize the
employment of staff and
the customer
satisfaction

13. 13PUBLIC© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Project Iris

14. 14PUBLIC© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Run time improved:
30 days to 21 min
Rerun in 24 seconds
Signal Analysis:
30 signals to 300,000
Accuracy up to 100%
Confidence 97%
Signal Detection

15. 15PUBLIC© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ
“HANA is now becoming the heart of our company from a technology point of view”
– John Douglas. CIO.
Business Challenges
 Provide real-time insights and advanced customer profile and history in a 360
view, including social profiles to create a unique Burberry shopping experiences
 Global connectivity within the organization
Technical Challenges
 Cannot efficiently run analysis on previous cloud based solution
 Fragmented data from multiple sources with multiple gateways and firewalls
Benefits
 Near real time access to customer information and sales history
 Near real time access to stock information (local, nearby and DC)
 Consistent global brand experience

16. 16PUBLIC© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Sales Insights with Esri Insights on SAP HANA

17. 17PUBLIC© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ
“Innovation is the new
Competitive Advantage.”
Julie Sweet, CEO Accenture, North America

18. 18PUBLIC© 2018 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Meat Pack Hijack

19. Thank you.
Contact information:
Paramjeet Sachdev (Pammy)
Director Centre of Excellence, EMEA South
Email: Pammy.Sachdev@sap.com
LinkedIn: www.linkedin.com/in/pammysachdev