1. Source: BCG Analysis
Processingpoweranddata
Time
ACTION IN THE
REAL WORLD
ACTION IN THE
DATA WORLD
Structured system data
Online behavior
Real-time sensor data
Computer
vision
Human
language
EMERGING AI
CAPABILITIES
INTELLIGENCE USE
CASES
Pattern recognition
Real-world mobility
Natural-language
processing
Speech recognition
Predictive
maintenance
Recommendations
Advanced analytics
Make Value Creation Real
Opportunities From Digital Intelligence Making it Real: Strategy  Execution
Consolidate data sources
Achieve a single virtual view of
operations by collecting data from all
of your connected assets
Automate business processes
Integrate with back-end systems
and set up rules to proactively
trigger alerts that drive remote
actions
Visualize with preconfigured
dashboards
Transform your data into rich
visuals so you can focus on what
matters to you
Apply predictive analytics
Use advanced analytics and
machine learning to anticipate
production and service
disruptions
Transform your business
Build data-driven service
offerings, such as delivering
products-as-services or
packaging data to provide new
revenue opportunities
Connected
assets
ChiefAIOfficers

2. Value Amplify Playbook Starts With An AI Maturity Assessment
Predictive
Maintenance
Stage 1:
Reactive
Stage 2:
Informative
Stage 3:
Predictive
Stage 4: Transformative Stage 5:
Game Changer
OUTCOMES
Vision
Schedule and manage using
past operational and
routine performance data
Analyze conditions and
make informed decisions
Discover new insight, and
predict likelihood and
timeframe of failures
Transform the experience
with rea-time insight,
actions and continuous
feedback
Shape new business models
with digital ecosystem
Strategic
Intent
• Define operational rhythm
• Meet SLAs, compliance
and warranty conditions
• Orchestrate and leverage
readily available reports
and operational
observations
• Become purpose-driven
with connected, complete,
correct and connected
data
• Model asset-specific plans
based on the asset
condition
• Easy access to insights on
the whys and the trends
• Manage the Voice of the
Asset
• Instrument the assets to
provide real-time data on
factors affecting asset
condition
• Predict and schedule
maintenance for desired
operations
• Operate Asset as a Service
by altering the asset
behavior in real-time
• Take corrective actions
before a potential failure
• Predict and perform
maintenance based on the
business impact
• Launch digital services,
leveraging design, data
and delivery insight
• Create new customer
experiences and solutions,
integrating partner assets
• Monetize learning
KPIs
• Unplanned downtime
• Regulatory compliance
• Maintenance schedule,
time and costs
• Time between failures
• Spare parts inventory
• Annual budget
• Asset utilization
• Unexpected breakdowns
• Capital and resource
investment
• Global reach
• Revenue or throughput
per asset
• Customer loyalty
• Outcome-based pricing
• New markets
• Cross-selling
• Eco-system maturity
CAPABILITIES: Data, Intelligence and Actions
TECHNOLOGY APPROACH: Architecture Directions
Ammend
Insurance
Contract
Cybersecurity
Officer Req.

3. Chief AI Officer Playbook | Part 2
Predictive
Maintenance
Stage 1:
Reactive
Stage 2:
Informative
Stage 3:
Predictive
Stage 4: Transformative Stage 5:
Game Changer
CAPABILITIES
Data
(Sources, time,
quality, access)
• Manufacturers reports
• Asset features
• Failures/repairs reports
• Historical data from
operational systems
• Intermittent updates
• Asset condition data
• Correlated quality, ERP, and
operational data
• Scheduled data queries and
data polling
• Real-time, streaming data
about asset conditions,
environmental factors, and
operating conditions
• Multisite data aggregation
• Data readiness for data science
• Cognitive and feedback data
• Business process / workflow
• Organization data e.g.
operator’s skills
• Events, Smart sensing
• Ecosystem data and services
• External context (customer,
consumer)
• Real-time capability and data
discovery
Intelligence
(Interpretations,
analytics,
insights,
learnings)
• Web-based reports,
dashboards
• Data visualization of historical
and operational data
• Self-service analytics
• Asset condition monitoring
and assessment
• Statistical modeling
• Trend analysis and forecasting
• Predictions using data mining,
modeling and algorithms
across all data
• Stream analytics
• Rolling aggregates, analysis
and recommendations
• Insight at sensor and interface
levels
• Deep learning e.g. vibrations
• Real-time predictions using
current business context and
operating conditions
• Analyze current state behavior
across ecosystem and identify
opportunities
• Evaluate health of data and
algorithms and predict
adjustments
Actions
(New or change
in activities)
• Inventory assets
• Develop plans and schedule
maintenance for assets based
on past performance
• Plan and schedule resources
• Forecast and optimize
schedule and inventory
• Manage critical assets and
business operations
• Manage planned downtime
• Manage resource productivity
• Create knowledgebase
• Check health while in use
• Identify potential causes and
time window, and take
proactive actions
• Generate alerts and propose
best actions
• Support remotely
• Reliability engineering
• Self-identify alternate paths for
continuous operations
• Heal the asset while in use
• Create outcome-based
business processes and
customer experience
• Make every interaction a
source of revenue
• Productize data, intelligence,
algorithms, and business
processes
• Integrate partner services
• Create BOTs
APPROACH
Architecture
Directions
• Systems of Records
• Client/server or distributed
architecture
• Data marts
• Reporting and analytics
• Systems of Engagement
• Service-oriented architecture
• Integration
• Data warehouses
• Analytical modeling
• Systems of Intelligence
• Lambda architecture
• NoSQL
• Data lakes
• Cloud
• Systems of Learning
• Neural network and FOG
architecture
• Cognitive services
• In memory, edge analytics
• Systems of Digital Markets
• Microservices architecture
• APIs
Amend Vendor
Contracts
Cybersecurity
Officer Req.
RealTime
COE Req

4. Predictive Maintenance Use Case| Data Science in Generating Free Cash Flow
Cognitive Recommendations
What Parts have Failed?
Which Parts will Fail Before in the Next
90/180/270 Days?
Stream
Analytics
from
Sensors
Two-Class
Classification
Multi-class Regression Anomaly
Detection
Un-supervised Specialized
Libraries
(Vibration)
When Will More Than x% of the Production be
Outside Quality SLAs
Free Cash
Flow
(FCF)
Capital
Expenditure
Working
Capital
Given the Developing Trend What Scenario Is
Developing? What Are The Consequences Of
Situation X?
When will the Asset Fail?
When will The Top 10 Expensive Parts Fail?
Postpone and
Consolidate Interventions
Reduce Rework
Due To Machinery Tuning
How Many of These Type of Bearings will
Survive 10K Hours?
Reduce Intervention
Of External Experts
Reduce Spare Parts
Inventory
INSIGHTS
Confidential

5. Value Engineering Work
Six Uses of AI To Avoid Losses

6. Makes VS Buy IndustryExpertise

7. Value Amplify Chief AI Officers Roadmap
Contact Prof Giuseppe Mascarella at: giuseppe@ChiefAIOfficer.org
1. AI Assessment
• Engage with you to discover short term and long term strategic
opportunities
• Understand current business drivers and validate need for new
data-driven digital capabilities
• Discover and determine customer use case and plan key
business outcomes
Business Alignment
2. AI Roadmap Envisioning Workshop
• Define Use Case KPI’s and align to the overall organization
objectives
• AI Maturity Model and organization gaps
• Design approach in alignment with Blueprints and IP Kits
• Make the next steps actionable and achievable, with clear
ownership of deliverables
Data Collection and Solution Envisioning
3. AI PROOF OF VALUE
• Develop a pilot implementation plan
• Develop solution based on selected data through iterative
experimentation
• Conduct pilot process implementation
• Monitor and publish key KPIs
• Run the solution considering various scenarios
• Feed progress reviews with regular customer-centric measures
Pilot implementation
4. Action Management Masterminds
• Embed Digital solution capabilities into everyday operations
• Create roadmap to manage transformation as a portfolio of
linked projects
• Understand that digital transformation is never over
• Perform periodic benchmarking against industry best practices
to ensure continuous improvement
Business Value Creation