#askSAP Analytics Innovations Community Call: Delivering the Intelligent Enterprise with Machine Learning

PUBLIC
David Judge, Richard Mooney, Geneva Briner & Timo Elliott
Delivering the Intelligent Enterprise
with Machine Learning
#askSAP Analytics Innovations Community Webcast

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#askSAP Analytics Innovations Community Call Webcast Series
• Quarterly series for the Analytics community
hosted by SAP Analytics
• An opportunity for you to direct the discussion, get
your questions answered, and end the session
with some useful advice
• Live and interactive 90 minutes
• Connect on topics before, during, and after the
call via twitter using #askSAP

Today’s speakers
Moderator:
Timo Elliott
Innovation Evangelist
David Judge
Vice President, Predictive Analytics
and Machine Learning
Richard Mooney
Managing Director,
Advanced Analytics
Machine Learning and
SAP Leonardo
SAP Predictive
Analytics
Geneva Briner
Partner Development Director
for SAP Analytics & Data
Accenture Enterprise
Predictive Analytics
Applications

Machine Learning and SAP Leonardo
David Judge
and Machine Learning, SAP

Market trends – Digital transformation
Emerging systems of intelligence
By 2018, 75% of enterprise
and ISV development will
include AI or ML.
– IDC
(IDC FutureScape: Worldwide
Analytics, Cognitive/AI, and Big Data
2017 Predictions, 2016)
By 2019, APIs will be the
primary mechanism
to connect data, algorithms,
and decision services.
– IDC
(IDC FutureScape: Worldwide Analytics,
Cognitive/AI, and Big Data 2017
Predictions, 2016)
By 2019, natural-language
generation will be a standard
feature of 90% of modern BI
platforms.
– Gartner
(Predicts 2017: Analytics Strategy &
Technology, 2016)
Embedded machine learning,
analytics providing built-in
guidance
Conversational applications: the
new user experience
Artificial intelligence and machine
learning, IoT, insights

Intelligently connecting people, things and businesses.
Integration Mobile
Collaboration
Big Data
Business process
innovation
Connected data
Design thinking
Microservices
APIs
Real-time
analytics
Natural
language
IoT NetworksMachine
learning
Experiences

8PUBLIC© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ 8© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ PUBLIC
The digital innovation system that enables you to innovate
at scale to confidently redefine your business.

Machine learning is the reality behind artificial intelligence
 Big Data (for example, business networks,
cloud applications, the Internet of Things,
and SAP S/4HANA)
 Massive improvements in hardware
(graphics processing unit [GPU] and
multicore)
 Deep learning algorithms
 Computers learn from data without
being explicitly programmed.
 Machines can see, read, listen,
understand, and interact.
What is machine learning?
Why now?

How enterprise data is transformed into business value
with machine learning
Input Machine learning Output
Train
model
Prepare
data
Apply
model
Capture
feedback
Text
Image
Video
Speech
… and more
Services
(e.g. Invoice processing, profile
matching)
…and more
Applications
(e.g. Cash Application)

SAP Leonardo Machine Learning enables the intelligent enterprise
76% of the world’s
transaction revenue
25 industries
12 lines of business
The world’s largest
business network
Lifecycle
management
Applications
Business services
Functional services
SAP Cloud Platform and SAP HANA
Re-imagine business
processes with digital
intelligence
Increased customer
satisfaction with
superior service
Increase revenue with
superior sales targeting
and execution
Improving quality time
at work for employees
Enabling product,
process and business
model innovations
Business Outcomes
SAP Leonardo
Machine Learning

SAP’s machine learning solution portfolio
• Service ticketing
• Customer retention
• Brand impact
• Resume matching
• Cash application
• S/4HANA sourcing and
procurement – predict contract
consumption
• Fraud management
Applications
N
N
N
N
N
New intelligent applicationN
SAP Predictive
Analytics
SAP HANA platform / (DBaaS)
SAP HANA
platform
N
SAP Analytics Cloud
Business services
Functional services
SAP Cloud Platform On premise
N
N
Users
Analyst
Developer
Third party

SAP Leonardo Machine Learning has great traction
Successful customer deployments. Recognized industry leadership.
Industry RecognitionCustomers
Forrester: Positioned as Leader
“SAP draws a straight-line from predictive
models to business applications.”
Hurwitz: Victor
“Fast time to value and ability
to support very large data sets.”
Dresner: Top Vendor
“The top vendors for advanced and predictive
analytics include SAP.”
The Forrester Wave™: Predictive Analytics
And Machine Learning Solutions, Q1 2017

#askSAP Q&A

SAP Predictive Analytics and Predictive
Analytics Integrator
Richard Mooney
Advanced Analytics, SAP

SAP Predictive Analytics
Input Machine learning Output
Train
model
Prepare
data
Apply
model
Capture
feedback
Text
Image
Video
Speech
… and more
Services
(e.g. Invoice processing, profile
matching)
…and more
Applications
(e.g. Cash Application)

SAP Predictive Analytics – machine learning
Train model
Prepare data Apply model
Capture feedback
• Build accurate, robust predictive
models quickly
• Enable citizen data scientists to
successfully build and deploy
predictive models
• Lights out management of large
deployment of predictive models
• Optimized for SAP HANA and
Hadoop/Spark

SAP Predictive Analytics integrator
Machine learning platform for data scientists and business
analysts to create, manage, and monitor predictive models
to answer to business issues
(PAI)
Framework for SAP developers
to embed machine learning algorithms
in SAP applications
SAP S4/HANA
SAP Analytics Cloud
C4C

enables SAP S/4HANA™ to easily embed predictive capabilities
 SAP S/4HANA LOBs can create and ship
predictive use cases specific to their
business processes and demonstrate the
value of the digital core
 Customers/ Partners can use the
ppredictive content delivered out of the box
by SAP S/4HANA or create predictive
scenarios specific to their unique business
needs using SAP Predictive Analytics.
 No coding required to update or improve
models
APL
PAL
R

Demo

#askSAP Q&A

Accenture Enterprise Predictive Analytics
Applications Geneva Briner
Partner Development Director for SAP
Analytics & Data, Accenture

Accenture and SAP Analytics partnership
CO-INNOVATION CO-DELIVERY
JOINT GO-TO-MARKET AND
SERVICES
Joint go-to-market, consulting, and
implementation services to help
clients with analytics strategy, drive
use case development and
deployment, integrate SAP Predictive
Analytics, and more
ENTERPRISE ANALYTICS
APPLICATIONS
Integrate more than 50 proven enterprise
analytics applications using SAP
Leonardo, SAP Predictive Analytics, and
SAP HANA across finance and
accounting, supply chain, procurement,
human capital management, and sales
and customer service
Accenture and SAP expand current
co-development program to include
intelligent analytics solutions powered
by SAP Leonardo
ACCELERATE SAP PRODUCT
ENHANCEMENTS
CO-DEVELOPMENT
Copyright © 2017 Accenture. All rights reserved.

Accenture Enterprise Predictive Analytics Applications
Representative top use cases of over 50 apps
Supply Chain
Inventory Optimizer
Demand Planning
Procurement Analytics
Stock Management
Warranty Analytics
Spare Parts Inventory Optimization
Predictive Asset Management
Transportation Optimization
Finance & Accounting
Payables Optimizer
Intelligent Collections
Intelligent Order
Sales Forecaster Analytics
Period Close Accelerator
Travel & Expense Analytics
Fraud Management
Pricing and Contract Compliance
Human Capital Management
Employee Engagement
Learning Recommendation
Recruiting Analytics
Scheduling / Staffing Mix
Absenteeism
Talent Supply Analytics
Attrition Prediction & Retention
Diversity Analytics – Talent
Development
Customer Management
Customer Segmentation
Customer Churn
Sales Forecasting
Channel Optimization
Branding and Social Media
Pricing & Promotion Analytics
Marketing Effectiveness

50% 23% 75%
Reduction in
excess inventory
Estimated reduction of excess
stock for
end-of-life parts
Improvement of fill
rate with an optimal inventory
investment
CUSTOMIZEDINVENTORY
PLANNING
OPTIMALTARGET
ANDSAFETYSTOCK
OPTIMALREORDER
FREQUENCY
Ongoing reduction in obsolete
stock buildup
TRIGGERPOINTFORRE-
ORDERING
Advanced inventory optimization through applied intelligence
50%

Agile analytics accelerating speed-to-value
1) Review key gaps in
supply chain health
KPI needs attention
2) Analyse predefined
scenarios
Advanced request
3) Execute data modelling
and data discovery
4) Analyse results and
propose best solution
Share visualized result
5) Inventory optimization
benefits achieved
Decision needed
Supply Chain Director Inventory Planner
• Optimize inventory
• Supply availability
• Ensuring KPIs set by SCD
• Propose optimal Inventory policy
/ norms
• Scenario definition
• Estimate optimal inventory parametersCHALLENGES
Data Scientist

Accenture Inventory
Optimizer Demo

#askSAP Q&A

• Visit #askSAP Community Call Parent Page – www.sap.com/asksap
• Access webcast replay –
• Watch for announcement of next #askSAP Webcast by June 20)
• Try SAP Predictive Analytics – Free Trial
• Join SAP Leonardo Community – Sign up
• Attend What’s New in Predictive Analytics Webinar, June 29 – Register Now
• Learn more
• SAP Leonardo
• SAP Predictive Analytics
• SAP and Accenture Partnership
Resources

Thank you.
David Judge,
& Machine Learning, SAP
david.judge@sap.com
@dhjudge
Richard Mooney,
Head of Product Management,
Advanced Analytics, SAP
richard.mooney@sap.com
@richardjmooney
Geneva Briner,
Partner Development Director for
SAP Analytics & Data, Accenture
geneva.l.briner@accenture.com
@genevabriner
Timo Elliott
Innovation Evangelist
SAP
timo.elliott@sap.com
@timoelliott

#askSAP Analytics Innovations Community Call: Delivering the Intelligent Enterprise with Machine Learning

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