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Copyright©2018byTheBostonConsultingGroup,Inc.Allrightsreserved.
Key topics
on AI and
strategy
5
What is AI?
Where to apply it?
Why is it difficult?
What about tomorrow?
How to move forward?
2
Copyright©2018byTheBostonConsultingGroup,Inc.Allrightsreserved.
Key topics
on AI and
strategy
5
What is AI?
Where to apply it?
Why is it difficult?
What about tomorrow?
How to move forward?
3
Copyright©2018byTheBostonConsultingGroup,Inc.Allrightsreserved.
AI creates prescriptive insights from high volumes of
unstructured, real-time data
Artificial Intelligence
•  Financial reports
•  Geo analysis
•  Heat maps
•  ....
PrescriptiveDescriptive
Business
Intelligence
Traditional Analytics
Machine learning
•  Campaign
Management
•  Sentiment
analysis
•  ....
•  Efficient
personalization
•  Context-aware (e.g.
mobile )
recommendations
•  Next best action
•  Fraud detection
•  Churn prediction
•  ....
Structured
Low Volume
Batch Load
Unstructured
High Volume
Real Time
Type
of Data
Type of Insights
Predictive
Optimization
•  Stock allocation
•  Logistics network
optimization
•  …
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Copyright©2018byTheBostonConsultingGroup,Inc.Allrightsreserved.
How we understand AI from a user-centric view
Structured data
Speech/text
Optical patterns/obj.
Physical agents
Digital agents
Communication
Offering: products and services
Processes: vertical and horizontal
AI building blocks
AI platforms and services
AI infrastructure and algorithms</>
Note: Unstructured data most typically sensor (visual or language) driven and classified as such
Source: AI@BCG
DATA PROCESSING ACTION
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Copyright©2018byTheBostonConsultingGroup,Inc.Allrightsreserved.
No shortage of AI application areas in business
 Personalization
 Cross sell and Up
Sell
 Churn and
Retention
 Customer
Experience
 Customer
Acquisition
 Sentiment Analysis
 Data-driven
Marketing
 Pricing and Promo
Effectiveness
 Feature
Optimization
 Assortment
Optimization
 Control Tower
 Sales/Ops/
Planning
 Predictive
Preventive
Maintenance
 Manufacturing
process
optimization
 Energy efficiency
 Procurement
 Branch Network
 Real Estate
Footprint
 Infrastructure
Capacity and
Utilization
 Routing engine
 Sales Territory
Design
 Credit Risk
Assessment
 Fraud/Anomaly
Detection
 Project Risk
Management
 Claims
Management
 Back-office
process automation
 Workforce
Deployment Design
 War gaming/
Scenario Simulation
 Competitive
Intelligence
 Performance
Management
Customer Product / Price Operations Network Risk Enterprise
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Copyright©2018byTheBostonConsultingGroup,Inc.Allrightsreserved.
A fundamental transformation in action
“We will evolve
from a mobile first to an AI
first world”
“In five years, there's no doubt in my
mind that cognitive [solutions], AI,
will impact every decision made … If
it is digital, it will be cognitive”
“The development of AI and big data
will bring fundamental changes to
the already internetized
manufacturing and financing
industries, and give birth to new
technologies and resources”
Every manager needs
an intuitive understanding of
AI to steer companies today
Sundar Pichai
CEO, Google
Virginia Rometty
CEO, IBM
Artificial Intelligence Panel
WEF 2017
Jack Ma
Founder of Alibaba
Source: AI@BCG
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Copyright©2018byTheBostonConsultingGroup,Inc.Allrightsreserved.
Thinking beyond tomorrow.
Shifting
Value Creation
Building Competitive
Advantage
User Centric
Approach
Where will AI create,
destroy, or shift value in
your industry?
How to build a competitive
advantage from AI tools ?
What is the impact of AI
on the your offering to yp
going to be and how to
prepare?
Source: AI@BCG
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Copyright©2018byTheBostonConsultingGroup,Inc.Allrightsreserved.
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Copyright©2018byTheBostonConsultingGroup,Inc.Allrightsreserved.
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Copyright©2018byTheBostonConsultingGroup,Inc.Allrightsreserved.
The 10/20/70 rule to drive impact.
What does success look like ?
Modelling
•  Performance of the algorithms
•  Data engineering
70%
20%
Processes and resources
•  Change management
•  Insertion in business process
•  Data quality and availability
10%
Technologies
•  Data and computation platform
•  Visualization and restitution tools
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Copyright©2018byTheBostonConsultingGroup,Inc.Allrightsreserved.
 New
Strategic objectives and time to impact should steer AI priorities
Strategic objectives of internal and external innovation units Description
 Mergers & Acquisitions (M&A)
Acquisition of developed companies
with existing business
 Internal Research and Development
Internal product development
 Business Incubation
(Incubator and Accelerator)
Support of and cooperation with start-up
companies in early stages
 Tech Transfer
Scouting/identification and transfer of
innovation/technology by external sources
into corporate (e.g., IP licensing)
 Strategic partnerships
Partnerships/joint ventures that
drive incremental revenue for BU
 Incubator (“Hatch”)
Create new and sustainable business
models along a structured approach
 CVC1
Equity investments to assess and access
new growth opportunities
 1–3 years  4–6 years  7–10 years
 Partnerships
 Business Incubation
(Incubator and Accelerator)
 Mergers
and acquisitions
 Internal research and development
 CVC1
 Adjacent
 Core
 Incubator (“Hatch”)
 Tech transfer
 Time to impact for
BU
 Proximitytocore
business
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Copyright©2018byTheBostonConsultingGroup,Inc.Allrightsreserved.
However, analytics transformations are difficult for
most companies
Talent crunch
 Top talent is crucial but
scarce and very difficult for
traditional corps to attract
20x
More demand
than supply of
skilled data
scientists
Technology paralysis
 Companies invest in tech and
flashy algorithms but 70% is
business transformation
~30%
is tech and
algorithms
Industrialization gap
 Most analytics efforts get
stuck in lab mode and never
generate bottom-line impact
<15%
of all big data
investments
reach production
Source: BCG
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Copyright©2018byTheBostonConsultingGroup,Inc.Allrightsreserved.
BCG approach is to think big, start small, grow fast
What if...
Start with the business
opportunity
Build, test, iterate
Scale to solution
Transform organization
§  Business first
§  Value focus
§  Lean technology
§  Right design
§  Practical
application of AI
and Big data
§  Well defined use
cases
§  Iterative
technology
scale up
§  Purpose fit
tools from
existing
technologies
§  New ways of
working
§  Analytics and
business strategy
in lock-step
§  Right organization
and processes
§  Transformative
Analytics as BAU
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