How is Watson Changing the Future of the Automotive Industry?

July 19, 2016

The objectives of this meeting are to understand:•What is cognitive and how does it differ

from traditional analytics?•How does Watson work?•What is IBM’s Point of View for Cognitive in

Automotive?•How do you embark on a cognitive journey

Meeting Objectives…

3

AgendaTime Topic Presenter10:00:00 Registration / Welcome Tony Stone

10:15:00 Overview of Cognitive and Watson Shelley Mosley

10:45:00 Cognitive in Automotive Tony Stone

11:30:00 Cognitive Quality and Safety Amit Saha

11:50:00 The Cognitive Journey Shelley Mosley

12:00:00 Wrap Up and Close Tony Stone

12:10:00 Networking Lunch All

4

Watson and Cognitive Capabilities

Data Explosion is Driving the Need for Cognitive Computing

55

Cognitive vs. Artificial Intelligence vs. Watson

6

• It’s about “thinking for people”• Has elements of NLP, Deep Learning, and Neural Networks

Artificial Intelligence

• Includes elements of AI but is a broader idea extended to helping people think better and make more informed decisionsCognitive

• IBM’s brand for cognitive capabilities is “Watson”• We do not use “cognitive” in names of IBM products or offeringsWatson

ReasoningThey reason. They can understand information but also the underlying ideas and concepts. This reasoning ability can become more advanced over time. It’s the difference between the reasoning strategies we used as children to solve mathematical problems, and then the strategies we developed when we got into advanced math like geometry, algebra and calculus.

LearningThey never stop learning. As a technology, this means the system actually gets more valuable with time. They develop “expertise”. Think about what it means to be an expert- - it’s not about executing a mathematical model. We don’t consider our doctors to be experts in their fields because they answer every question correctly. We expect them to be able to reason and be transparent about their reasoning, and expose the rationale for why they came to a conclusion.

UnderstandingCognitive systems understand like humans do, whether that’s through natural language or the written word; vocal or visual.

There are three capabilities that differentiate cognitive systems from traditional programmed computing systems.

The Cognitive Partnership

Cognitive Excels

• Locating Knowledge

• Pattern Identification

• Natural Language

• Machine Learning

• Eliminate Bias

• Endless Capacity

Humans Excel

• Common Sense

• Imagination

• Morals

• Compassion

• Abstraction

• Dilemmas

• Dreaming

• Generalization

Watson is creating a new partnership between people and computers that enhances, scales, accelerates human

expertise

Cognitive systems rely on collections of data and information

Examples include:Analyst reportstweetsWire tap transcriptsBattlefield docsE-mailsTextsForensic reports

NewspapersBlogsWikiCourt rulingsInternational crime databaseStolen vehicle data

Data, information, and expertise create the foundation.

80% of data is dark (unstructured) and unused by traditional analytics

11

How does Watson work?

11

12 12

13 13

JeopardyWatson

Jeopardy Watson

The Watson Debut : 2011 – Watson only knew “Q&A”

The portfolio of Watson capabilities…

15

Relationship

Extraction

Questions&

AnswersLanguageDetection

Personality

Insights

Keyword Extraction

Image LinkExtraction

Feed Detection

VisualRecognition

Concept Expansion

ConceptInsights

Dialog Sentiment

Analysis

Text to Speech

Tradeoff Analytics

Natural LanguageClassifier

Author Extraction

Speech to

Text

Retrieve&

Rank

WatsonNews

LanguageTranslatio

n

EntityExtraction

Tone Analyzer

ConceptTagging

Taxonomy

TextExtraction

MessageResonance

ImageTagging

FaceDetection

Answer Generation

Usage Insights

Fusion Q&A

Video Augmentation

Decision Optimization

Knowledge Graph

Risk Stratification

Policy Identificatio

n

Emotion Analysis

Decision Support

Criteria Classification

Knowledge Canvas

Easy Adaptatio

n

Knowledge Studio Service

Statistical Dialog

Q&A Qualification

Factoid Pipeline

CaseEvaluation

Natural Language

Processing

Machine

Learning

Question

Analysis

Feature

Engineering

Ontology

Analysis

Watson that competed on Jeopardy! in 2011 was comprised of what is now a single API—Q&A—built on five underlying technologies.

Since then, Watson has grown to a family of APIs.

With more functions and APIs are being added every year.

Cognitive systems combine data, information and expertise.

16

Organized Data Watson APIs

Enable new kinds of engage-ment

Create better products

Improve your processes and operations

Leverage expertise

Enable new business models

As the Watson technology evolves and deepens, so too are the ways it’s being put to work in the world.

17

36Countries

50,000Studentsin Melbourne

5.5MCitizensin Singapore

5LanguagesLearned by Watson

160Universitiesoffering Watson courses

400+PartnersPowered by Watson

1.1MPatientsat Bumrungrad

29Industries

80KDevelopers building with Watson

18 18

In 20 years, Cognitive Systems will be to computing what transaction processing is today...

Examples

19

20

Cognitive for Automotive

IBM Watson - The technology draws on five distinct fields of study:

21

Big Data &AnalyticsData Mining,Optimization,Text Analytics

Artificial IntelligenceMachine Learning, Natural Language Processing, Algorithms & Theory

Cognitive ExperienceHCI, Speech, Translation, Machine Vision, Visualization

Cognitive KnowledgeKnowledge Representation, Ontologies, Semantics, Context

Computing InfrastructureHigh Performance Computing, Distributed Systems, Programming Models & Tools

Watson enables five classes of cognitive services

ASK DISCOVEREXPLORE DECIDE VISUALIZE

22

Voice of the Customer and Product Development

Manufacturing, Supplier Management, and Logistics

Marketing, Sales,and Finance

Customer Experience, Aftermarket, and Warranty

Cognitive Vehicle

Cognitive Enabled Automotive Industry Value Chain

23

The Cognitive Catalyst - Watson for Automotive

24

Watson for Automotive: Select Implementations

25

Client Domain Solution Status

Global Automaker Quality/SafetySafety solution for automaker which maximized insights from multiple customer and vehicle data sources by developing world-class safety capabilities

In Production

Global Truck Manufacturer Operations Operational insights on structured and unstructured data using Watson

Bluemix . Prototype

Heavy Equipment Maker A Service/Techline Dealer Technician advisor solution to give more consistent and accurate

answers to customer questions on equipment Prototype

Asian Automaker Captive Finance Contact Center As an agent assist and operational measurement solution to help agents

and operations managers. In Production

German Automaker Captive Finance Contact Center Use Watson to help multiple tiers of the client services team as a

knowledge management platform. In Production

Heavy Equipment Maker B Service/Dealer Prototype of the Technical Service Advisor solution delivered using

Watson Bluemix. Prototype

Component Maker Supply Chain Watson enabled procurement intelligence solution for procurement specialists at automakers to optimize procurement In Production

Asian Automaker Sales Watson Bluemix services helped automaker identify key social influencers during their biggest commercial campaign. In Production

Voice of the Customer and Product Development

26

Solution Description

Engineering and Regulatory Advisor

Enables conversational dialogue in natural language and applying deep Q&A on Engineering and Regulatory data for product engineers and regulatory affairs team.

Knowledge Management for PDAccess, consolidate and enable 360 degree view of commodity, module, system information from the range of engineering artifacts (e.g. FMEAs, DVP&Rs, APQP, supplier data etc.) for Product Engineers

Knowledge capture for PD Interview employees to capture knowledge; focus on those who are separating or moving to new roles to enable knowledge harvesting.

VOC and Cognitive Product Planning

VOC Insights from external (dealer data, social data - twitter, facebook, Edmunds.com etc.) and internal data (call center, quality/warranty systems etc.) to drive product feature and functionality improvement

Manufacturing, Supplier Management, and Logistics

27

Solution Description

Cognitive Operations Management

Use natural language capabilities to deliver operational insights from structured and unstructured plant operations data for business leaders and operations teams.

Plant Equipment and Maintenance Advisor

Aggregating the asset data, maintenance data into one view allowing plant managers to better react to malfunctions within the operations of the plant using Q&A.

Procurement IntelligenceProvide sourcing practitioners with relevant supplier, commodity and industry news and insights to allow a strategic competitive advantage in the marketplace

Marketing, Sales, and Finance

28

Solution Description

Cognitive and Analytics Marketing Solutions

1-to-1 personalization and analysis of buying behavior to match customers to personas and lifecycle stages to design and optimize marketing incentive offers

Cognitive Finance AdvisorUse Q&A and to match customer with product and present the optimal offer based on equity, residual value, credit history, and other parameters to improve

Dealer Sales and Service Advisor

Use natural language capabilities to deliver assistance to dealer sales and service reps to meet customer needs

Vehicle Match and Configuration Advisor

Match potential customers to their ideal vehicle and guide them through Q&A to configure and customize

Customer Experience, Aftermarket, and Warranty

29

Solution Description

Cognitive Fleet AdvisorOperation insights to fleet managers to optimize feet performance using vehicle usage data, manufacturing insights, market analysis, and weather analytics in a single dashboard

Customer Support Services Watson enabled, self service solution using natural language Q&A to answer customer questions on product and services

Quality and Safety AnalyticsIngest external and internal data from NHTSA, social media, warranty, call center etc. to enable detection of emerging safety issues.

Technical Support ServicesSupports self-service and agent-assist in answering technical questions from customers or dealer technicians supporting the products

30

Cognitive Quality & Safety

The Safety/Quality problem in the auto industry

Time

# of

Affe

cted

Veh

icle

s Launch Curve

Business ProblemHow to develop a systematic, analytics based approach to identify potential quality issues sooner (move the point-of-identification left)

Strategic Impact Reduce impact to bottom line by reducing # of issues through early warning Minimize brand erosion by proactive issue identification and timely field action Improved product quality enabled by early feedback to engineering/R&D Increased commitment to customer service with higher speed-to-resolution

Challenges Engineers often rely on intuition and experience Complex data environments Potential issue discovery difficult and time consuming Time spent gathering, cleansing and organizing data for reporting Closed loop feedback systems to prevent reoccurrences

Early Warning - Safety and Quality

Email Document Management

Wikis SocialNHTSA Data

NHTSA Data Sources

Blogs/Tweets

Prior Work

Documents & Faxes

Safety/Quality Correspondence

SiebelDomainKnowledge Management

SharePointWarranty

Analytics

Call Center CRM

Federated SourcesKnowledge Repositories

Collaboration

Warranty Management System

Reporting and Analytics

Cloud

Indexing RatingTagging Correlating

Watson Explorer

Significant reduction time to finding potential safety issues from 100 days to a few days.

Safety/Quality Analytics Solution and Operating Model

Issue Identification

Predicting using Social Media and NHTSA Data

Data Platform and GovernanceManage Issues, Automate and Deliver Actionable Insights

Visualization, Trends Analysis and Feedback Loop

Automated dashboards, visualization and notifications with trends and forecast of safety issues using Cognos and Watson Analytics.

Integration with engineering platforms like Siemens TeamCenter and feedback loop in to product development.

Safety issue management using IBM Case Manager, automate business rules using ODM to deliver insights across business units

Rapid identification of emerging safety issues in Social and NHSTA data using Natural Language Processing capabilities of Watson and Social Analytics capabilities of IBM SMA

Enable a Safety analytics data lake and repository using IBM BigInsights supported by Data Governance to explore and discover safety issues.

Correlation analysis of regulatory data and customer complaints in social media to forecast emerging safety issues using SPSS advanced analytics models

1

2

34

5 Safety Transformation

Roadmap

Demonstrated Results: Vehicle Safety/Recalls

Quality and Safety Demo

35

36

The Cognitive Journey

The Watson journey is comprised of three phases

37

Software as a Service Deploy & Manage Watson

Phase 3:Deliver the Future

Cognitive Value Assessment

Deliver Cognitive Prototype

Create a Cognitive Journey

Develop a Benefits Case

Configure and Train Ingestion of Content

Q&A Development

System Training

Testing and Deployment

Phase 1:Prove the Value

Phase 2:Begin the Journey

Start Here

38

The Cognitive Value Assessment is an accelerated approach to identifying transformational opportunities and business valuePurpose: The purpose of the Cognitive Value Assessment (CVA) is to identify the initial use case(s) where IBM Watson can be leveraged to enhance interactions with end users.Objectives:• Assess current business workflows and identify target processes and pain

points to disrupt with cognitive solutions• Develop final candidate Use Cases• Prepare a high-level benefits case for identified current and future

cognitive capabilities• Prepare a Journey Map describing the client’s vision and business

transformation as enabled by cognitive technology• Establish a starting point for the cognitive journey

39

Create a Watson demonstration using client value

Prototype

Key

Activ

ities

Deliv

erab

les

User ScenarioAssess current state workflows for Watson disruption

Prioritize candidate use case(s)

Develop user scenarios / personas that would be end users in prioritized use case(s)

Benefits CaseDefine key metrics for measurement against baseline

Develop benefits hypotheses

Develop benefits case which quantifies the 3-5 year financial benefit

Cognitive Journey Map Identify phased Watson initiatives

Finalize solution design

Develop cognitive journey map which lays out the additional phases over a 3-5 year cognitive evolution

User Scenario(s) Presentation Concept DemonstrationBenefits Case Presentation Cognitive Journey Map

CVA Outputs

40

Thank You