The document outlines how IBM's Watson is transforming the automotive industry through cognitive computing, distinguishing its capabilities from traditional analytics and artificial intelligence. It discusses Watson's various applications in improving quality, safety, and operational efficiency across automotive processes, as well as detailing a structured cognitive journey for businesses. Key highlights include Watson's ability to process vast amounts of unstructured data, enhance decision-making, and create new partnerships between humans and computers.

1. How is Watson Changing the Future of the Automotive Industry?
July 19, 2016

2. 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. 3
Agenda
Time Topic Presenter
10:00:00 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. 4
Watson and Cognitive
Capabilities

5. Data Explosion is Driving the Need for Cognitive Computing
5
5

6. 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 offerings
Watson

7. Reasoning
They 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.
Learning
They 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.
Understanding
Cognitive 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.

8. 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

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

10. Cognitive systems rely on collections of data and information
Examples include:
Analyst reports
tweets
Wire tap transcripts
Battlefield docs
E-mails
Texts
Forensic reports
Newspapers
Blogs
Wiki
Court rulings
International crime database
Stolen vehicle data
Data, information, and expertise create the
foundation.
80% of data is dark (unstructured) and
unused by traditional analytics

11. 11
How does Watson work?
11

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13. 13
13

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

15. The portfolio of Watson capabilities…
15
Relationship
Extraction
Questions
&
Answers
Language
Detection
Personality
Insights
Keyword
Extraction
Image Link
Extraction
Feed
Detection
Visual
Recognition
Concept
Expansion
Concept
Insights
Dialog Sentiment
Analysis
Text to
Speech
Tradeoff
Analytics
Natural
Language
Classifier
Author
Extraction
Speech to
Text
Retrieve
&
Rank
Watson
News
Language
Translation
Entity
Extraction
Tone
Analyzer
Concept
Tagging
Taxonomy
Text
Extraction
Message
Resonance
Image
Tagging
Face
Detection
Answer
Generation
Usage
Insights
Fusion
Q&A
Video
Augmentation
Decision
Optimization
Knowledge
Graph
Risk
Stratification
Policy
Identification
Emotion
Analysis
Decision
Support
Criteria
Classification
Knowledge
Canvas
Easy
Adaptation
Knowledge
Studio
Service
Statistical
Dialog
Q&A
Qualification
Factoid
Pipeline
Case
Evaluation
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.

16. Cognitive systems combine data, information and expertise.
16
Organized Data Watson APIs
Enable new kinds of engagement
Create better products
Improve your processes and operations
Leverage expertise
Enable new business models

17. As the Watson technology evolves and deepens, so too are the ways
it’s being put to work in the world.
17
36
Countries
50,000
Students
in Melbourne
5.5M
Citizens
in Singapore
5
Languages
Learned by Watson
160
Universities
offering Watson courses
400+
Partners
Powered by Watson
1.1M
Patients
at Bumrungrad
29
Industries
80K
Developers
building with Watson

18. 18
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In 20 years, Cognitive Systems
will be to computing what
transaction processing is
today...

19. Examples
19

20. 20
Cognitive for Automotive

21. IBM Watson - The technology draws on five distinct fields of study:
21
Big Data &
Analytics
Data Mining,
Optimization,
Text Analytics
Artificial
Intelligence
Machine
Learning,
Natural
Language
Processing,
Algorithms &
Theory
Cognitive
Experience
HCI, Speech,
Translation,
Machine Vision,
Visualization
Cognitive
Knowledge
Knowledge
Representation,
Ontologies,
Semantics,
Context
Computing
Infrastructure
High
Performance
Computing,
Distributed
Systems,
Programming
Models & Tools

22. Watson enables five classes of cognitive services
ASK DISCOVEREXPLORE DECIDE VISUALIZE
22

23. 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

24. The Cognitive Catalyst - Watson for Automotive
24

25. Watson for Automotive: Select Implementations
25
Client Domain Solution Status
Global Automaker Quality/Safety
Safety 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

26. 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 PD
Access, 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

27. 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 Intelligence
Provide sourcing practitioners with relevant supplier, commodity and industry
news and insights to allow a strategic competitive advantage in the
marketplace

28. 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 Advisor
Use 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

29. Customer Experience, Aftermarket, and Warranty
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Solution Description
Cognitive Fleet Advisor
Operation 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 Analytics
Ingest external and internal data from NHTSA, social media, warranty, call
center etc. to enable detection of emerging safety issues.
Technical Support Services
Supports self-service and agent-assist in answering technical questions from
customers or dealer technicians supporting the products

30. 30
Cognitive Quality &
Safety

31. The Safety/Quality problem in the auto industry
Time
#ofAffectedVehicles
Launch Curve
Business Problem
How 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

32. Early Warning - Safety and Quality
NHTSA Data Sources
Blogs/Tweets
Prior Work
Documents & Faxes
Safety/Quality
Correspondence
Call Center CRM
Federated Sources
Knowledge
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.

33. 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 modelsSafety
Transformation
Roadmap

34. Demonstrated Results: Vehicle Safety/Recalls

35. Quality and Safety Demo
35
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36. 36
The Cognitive Journey

37. 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 value
Purpose: 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
38

39. Create a Watson
demonstration using client
value
Prototype
KeyActivitiesDeliverables
User Scenario
Assess 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 Case
Define 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
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Thank You