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The next BIG thing in Supply Chain andManufacturing -Augmented Intelligence?!
Christophe Begue
Director Electronics Industry Solution Strategy and
Business Development
>80% of all data is dark and not used at all
20172013 2020
27>1890 Tabulating 1960 Programmable >2010 Cognitive
Cognitive systems are generally defined by the ability to
understand, reason, learn, and interact
UNDERSTAND
Cognitive systems can
understand unstructured
information the same
way humans do
REASON
They can reason, grasp
underlying concepts,
form hypotheses, and
infer to extract ideas
LEARN
Each data point,
interaction and outcome
helps to continuously
sharpen expertise
INTERACT
With abilities to see,
talk and hear, cognitive
systems interact with
humans in a natural way
Cognitive is underpinned by many advanced technologies and has
the power to transform business
Artificial intelligenceSimulation of human intelligence processes
Robotics
Conception, design,
manufacture, and operation
of robots
Machine
learning
systemsAbility to learn and
improve without explicit
instructions
Natural language
processing
Ability to understand human
speech as it is spoken
Deep
learning
Machine learning with artificial neural
network algorithms
Predictive
analytics
Predicting outcomes
using statistical
algorithms and machine
learning
Recommendation
engines
Analyze data and
suggest something as
per user’s interest
Cognitive Technologies
Create new ways of interacting
with customers
Reveal more powerful on-demand
business insights through real-
time access to data
Enable business model – and
ecosystem – transformation
Business Value
AI / Watson in
Supply Chain Management
Geo-spatial analytics platform leveraging hyper-local
external and internal client data to provide performance
insights and recommendations at the neighborhood/point
of sales level
Unlock pockets of growth by de-averaging
performance
Understand how time sensitive external forces
affect performance
Gain deeper insight on preferences and
purchasing behavior to better serve customers
Action through role based recommendations
So
lu
tio
n
Strategy, planning and
execution are designed at an
aggregated and averaged out
level making it difficult to see
and act to what is really
happening at the local level
The real dynamics are masked
Bu
sin
ess
Pro
ble
m
IBM Metro Pulse Powered by Watson – Hyper local data
and Dynamics to improve sales performance
Limited understanding of the outside forces
Typical analysis cannot always
sufficiently explain the
business landscape as it is
difficult to see and act to
what is shaping behavior at
the local level
Reveal what’s really happening Role based use cases to drive action
SOCIAL
PINTEREST SNAPCHAT LINKEDIN
DIGITAL
INTERACTIONCONSUMER
PERSONA
EVENT
INTERACTION
LOCAL
NEWS
WEATHER
MARKET
INSIGHTS
DEMOGRAPHICS
GEO
SPATIAL
MACHINE
SENSORMACHINE
INTERACTIONOPERATIONS
METRICS
TRADE
PLANNINGPRODUCT
SCANNER
DETAILSKU LEVEL
RETAIL STORE
SUPPLY CHAIN INVENTORY PRICING
CONSUMER INTERACTION
POS
THIRD PARTY
INTERNET OF THINGS
INTERNAL
DISTRIBUTION
CENTER
WIRELESS
LOCATION
Dynamic and hyper local signals are captured combining inside-
out enterprise view with outside-in hyper local view
© 2016 IBM Corporation
We turn that data into insights
The Weather Company, an IBM business │ WeatherFX 33
New York
Above average wind speed
causes indoor paint sales
to increase in the fall.
Atlanta
Above average wind and below
average humidity causes frozen
food dinner sales to increase in
the summer.
Los Angeles
Cooler and cloudier than
normal cause facial
cleanser sales to increase
in the spring?
Weather is highly relative.
The exact same temperature can trigger very different behaviorsdepending on your location
34
And we utilize triggers to drive higher marketing effectiveness while eliminating media waste
Triggers only serve messages to the people who are primed to receive them, eliminating the chance of media waste during sub-optimal conditions
35
Example: Sunscreen
New York, DMA
Weather Conditions
Product Featured Messaging shown Messaging shown Messaging shownNo Messaging shown No Messaging shown
#CognitiveSupplyChain
Augmenting Supply Chain Decisions
Supply ChainProfessionals
We teachWatson.
We programAdvisory.
Operation Center
Alerts
Resolution Room
We use IBM’s Cognitive
Data LakeWe utilize Enterprise
Data Sources.36
© 2016 IBM Corporation
We gain insights
from IoT.
We uploadData intoWatsonAnalytics.
We analyze data recorded
in Blockchains
Watson Q&A
© 2016 IBM Corporation 39
1 Identify &
Alert
2 Analyze &
Understand
3 Interact &
Resolve
4 Learn
© 2016 IBM Corporation40
ALERT !
Watson Supply Chain - Training
42© 2016 IBM Corporation© 2016 IBM Corporation
Visual Inspection for Industries and Maintenance
• Automotive
• Aerospace & defense
• Chemicals & Petroleum
• CPG
• Electronics
• Energy & Utilities
• Industrial products
• Life Sciences
• Maintenance
Visual Inspection – Image Analytics
Blistering Defect of Paint
LCD Panel Inspection
Mobile phone chassis inspection
Use case example - major LCD panel manufacturerCurrent situation
Take images from shopfloor Send images to inspection room
for manual inspectionFeedback sent to shopfloor for
actions
Average waiting time per inspection
per batch: 20-30 mins150 + inspection workers
Acoustic & Noise Analytics
Thank You
