The Future is Now with Machine Learning and Intelligent Digital Assistants

Transcription

1 The Future is Now with Machine Learning and Intelligent Digital Assistants Glenn Neuber Business Lead APJ, Innovation Center Network Silicon Valley/Brisbane

2 SAP Leonardo Digital Innovation System 2

3 The ICN Innovation Engine Agile as a start-up with the backbone of SAP Personalized Medicine Future of Work Machine Learning Conversational Applications Blockchain Multi-Modal User Experience (AR, VR,...) Neuromorphic Hardware Quantum Computing EXPLORE IDEATE VALIDATE INCUBATE SCALE 3

4 Software is becoming smarter and this changes our daily lives 4

5 Machine Learning is embedded across the SAP portfolio Available now Wave 2 Wave 3 Finance Cash Application Accounts Payable Predictive Accounting Marketing Brand Impact Customer Behavior Segmentation Sales Customer Retention Sales Forecasting Profile Completeness Service CoPilot Service Ticketing Solution Recommender Human Resources Resume Matching Learning Recommender opensap Translation Procurement Financial Advising Goods & Services Classifier Supply Chain Forecasting (IBP) Stock in Transit Platform Machine Learning Foundation Model Training Infrastructure 5

6 Example: SAP Brand Intelligence Optimize your marketing ROI through brand intelligence and sponsorship insights Select the brands to monitor View analysis in the interactive tool Estimate your brand exposure ROI Select the brand attributes you would like to monitor and the media they appear in View the statistics and compare to the other brands Estimate ROI in sponsorship contracts and optimize logo placement for maximum exposure 6

7 Example: SAP Service Ticketing Automatic classification and suggested responses of customer service tickets Categorize tickets Suggest solution Boost customer experience A Glimpse at the Solution Read ticket content, determine category, and automatically route ticket Provide potential solutions to agent Improve resolution rate, time to resolution, closure rate 7

8 SAPPHIRE NOW 2017 SAP Customer Retention Demo Link: 8

9 Example: SAP Customer Retention Incoming dynamic data from various channels Sort, classify & route events Identification of customers who are about to churn Build an overview of the customer journey Identify critical events/ churn indicators Take proactive actions to prevent customers from churning 9

10 Example: SAP Customer Retention Insights Discovery Engine 10

11 SAP Leonardo Machine Learning Platform Architecture Enable developers and partners to apply machine learning SAP Leonardo Machine Learning Applications User API Business Hub Developer Invoice Processing Profile Matching Text Image / Video Data Science Interface Python Golang Data Scientist Service Analytics... Advanced Numerical... TensorFlow Docker ML Business Services ML Technical Services Kubernetes Provisioning Infrastructure Training Infrastructure SAP Leonardo Machine Learning on SAP Cloud Platform 11

12 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 12

13 Example: HanaHaus Bot 13

14 Example: HanaHaus Bot ARCHITECTURE Reservation System Twilio Reservation System API Intent Matching Entity Extraction Memory Management HanaHaus Bot Function Execution Response Repository FAQ Handling NLP Libraries Cloud Platform 14

15 Digital Assistant Usecase: SAP Fiori Copilot Digital Assistant for SAP Applications 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. 15

16 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. 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 Applications SAP Leonardo Machine Learning Foundation S/4HANA and other backend systems 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) Delivery Approach Discovery Analysis Ideation Prototyping Action Plan Fundamentals & SAP machine learning vision Customer Vision, Goals and Needs Imagination and Inspiration Low fidelity prototypes Summary, Prioritization & Next Steps Key Deliverables Initial customer vision to machine learning Value proposition based on SAP Leonardo machine learning High level action plan 16

17 Contact Information: Glenn Neuber Business Lead APJ, Innovation Center Network Silicon Valley/Brisbane