the future is now with machine learning and intelligent ... events/wellington 20… · customer...
TRANSCRIPT
CUSTOMER
Glenn Neuber
Business Lead APJ, Innovation Center Network Silicon Valley/Brisbane
The Future is Now with Machine Learning and Intelligent Digital Assistants
2CUSTOMER© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
SAP Leonardo Digital Innovation System
3CUSTOMER© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Machine Learning
Future of Work
Conversational Applications
Blockchain
Multi-Modal User Experience (AR, VR, ...)
Neuromorphic Hardware
Quantum Computing
EXPLORE IDEATE VALIDATE INCUBATE SCALE
Personalized Medicine
The ICN Innovation Engine
Agile as a start-up with the backbone of SAP
4CUSTOMER© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Software is becoming smarter
and this changes our daily lives
5CUSTOMER© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Machine Learning is embedded across the SAP portfolio
Finance
Marketing
Sales
Service
Human Resources
Procurement
Supply Chain
Platform
Cash Application Accounts Payable Predictive Accounting …
…Brand Impact Customer Behavior Segmentation
…
Service Ticketing
Customer Retention Sales Forecasting
CoPilot
…
…
Goods & Services Classifier …
Solution Recommender
Profile Completeness
…Resume Matching Learning Recommender openSAP Translation
Financial Advising
Forecasting (IBP) Stock in Transit
Available now Wave 2 Wave 3
Machine Learning Foundation …Model Training Infrastructure
6CUSTOMER© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Example: SAP Brand IntelligenceOptimize your marketing ROI through brand intelligence and sponsorship insights
Estimate ROI in sponsorship contracts
and optimize logo placement for
maximum exposure
Select the brand attributes you
would like to monitor and the
media they appear in
View the statistics and compare to
the other brands
Select the brands to monitor View analysis in the interactive tool Estimate your brand exposure ROI
7CUSTOMER© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Example: SAP Service TicketingAutomatic classification and suggested responses of customer service tickets
A Glimpse at the Solution
Improve resolution rate, time to
resolution, closure rate
Read ticket content, determine category,
and automatically route ticketProvide potential solutions to agent
Categorize tickets Suggest solution Boost customer experience
8CUSTOMER© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
SAPPHIRE NOW 2017 SAP Customer Retention Demo Link: https://www.youtube.com/watch?v=RVHXw21hK8w
9CUSTOMER© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Incoming dynamic data
from various channels
Sort, classify &
route events
Identification of customers
who are about to churn
Build an overview of the
customer journeyIdentify critical events/
churn indicators
Take proactive actions to
prevent customers from
churning
Example: SAP Customer Retention
10CUSTOMER© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Example: SAP Customer Retention
Insights Discovery Engine
11CUSTOMER© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
User
Profile Matching
Service Analytics
Invoice Processing
...
Image / Video
Advanced Numerical
Text
...
Data
Scientist
Developer
ML Business Services ML Technical Services
Provisioning Infrastructure
Kubernetes
Docker
TensorFlow
Training Infrastructure
SAP Leonardo Machine Learning Applications
API Business Hub
Python Golang
SAP Leonardo Machine Learning on SAP Cloud Platform
Data Science Interface
SAP Leonardo Machine Learning – Platform Architecture
Enable developers and partners to apply machine learning
12CUSTOMER© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Chatbots Usecase: HanaHaus Bot
HanaHaus:
Public Café & Co-working Space in Downtown Palo Alto by SAP
Motivation
• Enabling HanaHaus customers to interact
with the reservation system using natural language
• Simplify user experience for recurring booking
Features
• Reserve, extend, and cancel reservations through text
messages
• Answer common questions regarding HanaHaus
and the reservation process
13CUSTOMER© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Example: HanaHaus Bot
14CUSTOMER© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Example: HanaHaus Bot
Cloud Platform
Reservation
System
Twilio
HanaHaus Bot
Reservation
System API
Intent Matching
Entity Extraction
Memory Management
Function Execution
Response Repository
FAQ Handling
NLP Libraries
ARCHITECTURE
15CUSTOMER© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
Conversational (Multi-Modal) UI
Communicates in natural language via text, gesture or voice.
Enables to converse with others, within the business context.
Business Context Awareness
Offers insights based on roles, context and business situation.
Recognizes business objects on the screen or within conversations.
Quick Actions
Offers suggestions to help decide on the proper course of action.
Quick creation of business objects, prompting for minimal input.
Learns and Recommends
Starting with pre-defined business rules and gradually learning from behavioral data, recommending next best actions to the
user.
Digital Assistant Usecase: SAP Fiori Copilot
Digital Assistant for SAP Applications
16CUSTOMER© 2017 SAP SE or an SAP affiliate company. All rights reserved. ǀ
SAP Leonardo Machine Learning Discovery Service
Service Description
Machine learning technology provides new solutions to existing and new
business opportunities. We conduct an onsite workshop with you to define
an approach for your business to benefit from the capabilities of machine
learning. SAP machine learning experts provide guidance about the benefits
of machine learning and intelligent application – for potential uses cases and
line of businesses.
Delivery Approach
Applications
SAP Leonardo Machine Learning
Foundation
S/4HANA and other backend
systems
Key Deliverables
Initial customer vision to machine
learning
Value proposition based on
SAP Leonardo machine learning
High level action plan
Discovery Analysis Ideation Prototyping Action Plan
Fundamentals &
SAP machine
learning vision
Customer Vision,
Goals and Needs
Imagination and
Inspiration
Summary,
Prioritization &
Next Steps
Low fidelity
prototypes
Business Benefits
Understand the business benefits of machine learning and intelligent
applications
Define a vision and value proposition for machine learning based on SAP
Leonardo
Validate a high level action plan to maximize business benefits
Variants & Duration
Standard variant: 1 day onsite
(3 person days effort based on T&M)
Variant with extended prototyping:
2 days onsite
(6 person days effort based on T&M)
Contact Information:
Glenn Neuber
Business Lead APJ, Innovation Center Network Silicon
Valley/Brisbane