SlideShare a Scribd company logo
Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 1/26
Exponential Information Systems
to support a Data-Driven
Digital Transformation
Yves Caseau
Group CDIO, Michelin
NATF (National Academy of Technologies of France)
http://informationsystemsbiology.blogspot.com/
https://twitter.com/ycaseau DATAQUITAINE
February 10th, 2022 – v0.2
Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 2/26
 Part 1: Digital Transformation
Driving the software revolution to adapt constantly to the customer’s environment
 Part 2: Exponential Information Systems
Software excellence matters – Build your foundations
 Part 3: Data-Driven Ambition
Enterprise-wide flows, Customer-time freshness, Future-proof unified semantics
 Part 4: Exponential Technologies Ambition
Artificial intelligence and machine learning to drive more value from data
Outline
Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 3/26
Information Systems as Core Digital Capabilities
 Digital transformation is a
business transformation, across
the value chain
 IS as a backbone (Part 2)
 Shared “digital core” … but each
digital world has its own
ecosystems: (IT ≠ Digital)
 Digital continuity creates value
Alibaba & Amazon example:
 Digital Supply Chain Meets
Demand Management
 AI to grow new knowledge from
end-to-end processes
Digital Employee
Support Systems:
Infrastructure, Data, Identity & security, orchestration, API, ….
Product
Development
Supply
Chain
Manu-
facturing
Services
&
Solutions
Sales &
CRM
Digital continuity
Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 4/26
4
Product Development and Knowledge Engineering
AI as a tool to capture, share and scale process and product
knowledge
Hybrid AI, from DeepMind (cf. Part 4) –
to ML-augmented finite element simulation
AI and generative ML techniques to re-invent product expertise
Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 5/26
Industry 4.0 : Digital Manufacturing, Digital Twin & Digital Workspaces
 AI in Manufacturing to
absorb complexity
 cope with variability
 cope with manufacturing
process complexity
 Augmented humans and
augmented environments
 machine vision &
sensors for enhanced
perception
 End to End
process
optimization
Merck Example
Middleware / HA/ Containers
Shared
Datalake
Shared
Expert
Services
Infrastructucture / Security
Middleware / HA/ Containers
Middleware / HA/ Containers
Middleware / HA/ Containers
Digital Core (App Server / CICD)
Digital Twin
Digital Twin
Digital Twin
Information
Systems
PLM
ERP
MPM
Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 6/26
Digital Customer Journeys
 Events, Insights and Context
 Co-operation Agents/ Digital is built on a virtuous loop
 Insights are fed by events, events fed by conversations, conversations fed by content
Daily
Yearly
Life
Time
Customer
Journey
(Sales / Service ) Agent
CDP
3rd Party
Data
Process
Data
Engagement
DMP
Advice /
Recommendation
Service /
Assistance
Content
Insights
Mining
Reactive
care
Conversations
feedback
events
requests
Web/
Mobile/
Social
02.04.2021 Retain for: 90d
v. Croc / t. fraudet / a. LemblÉ / t. signarbieux
Steering committee api transformation < N° >
d3
Group Martech Stack at Michelin
Apostrophe
MediaMath
BlueConic
inRiver
Wedia
????
Salesforce
Didomi
?????
?????
WordPress
Salesforce
Marketing
Cloud
Rul.ai
Sprinklr
Pixel
MediaMath??
Excel Sheet
Qualtrics
Pixlee??
CloudImage??
Flutter
Apostrophe
Apostrophe
Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 7/26
7
Support Hybrid Way of Working : remote collaboration
DIGITAL WORKPLACE
Augmented collaboration : “Kolmogorov compression”
The smarter the AI, the more succinct the context synchronization
Cognitive Agents: From ontologies to “GPT-3 + semantics”
knowledge management and augmentation
Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 8/26
Part II
Exponential
Information
Systems
8
Yves Caseau - Lean Software Factories and Digital Transformation – 2021 9/17
Entreprise 3.0
“Holomorphism”
Open
Platforms
Antifragile
Customer
Homeostasis
Recognition &
Response
Network
of Teams
Massively
Transformational
Purpose (MTP)
Orientation
Client
Scalability
On-demand
Algorithms
& Automation
Continuous
Learning
Experimentation
Interfaces
Autonomy
Agility
Short steps
Communities
& Crowds
E3.0
Customer
Orientation
Yves Caseau - Lean Software Factories and Digital Transformation – 2021 10/17
Exponential Information Systems Principles
 Digital Homeostasis
 Outside-in
 Reactive
 Open frontiers
 Accelerate Takt Time
 Automation
 Short release cycles
 Living System
 In/out breathing
 Continuous architecture
(emergence)
Outside-In
Customer focus
EDA
Data-Driven
Multimodal
CICD
Elastic
Resources
Algorithms
Continuous
Refresh / Refactor
Sustainable
Growth
SRE
AI4Ops
API
Yves Caseau - Lean Software Factories and Digital Transformation – 2021 11/17
Architect for Change : Multimodal Architecture
 Four zones illustration:
different rates of change,
different software ecosystems
 Extension of bi-modal IT
pattern (but everything must
change)
 Edge is the software domain
that is not controlled by IT but
where it must project its
services
 The supporting integration
capabilities is a key enabler
for digital transformation
Enterprise Integration Capabilities
Business capabilities
• Records
• Transactions
• Business
Intelligence
CORE
Renewal
every 10 years
Engagement capabilities
• Mash-up
• Contextual
• Conversations
• Personalization
MATRIX
Renewal
every 5 years
Edge capabilities
• Smartphones
• Social Platforms
• Connected
Objects
• Etc.
EDGE
Fast & imposed
Renewal
Imported
Capabilities
• AI/ ML
• NLP/Semantics
• IOT
Exponential Cloud
Renewal
every 3 years
API
API
API
Yves Caseau - Lean Software Factories and Digital Transformation – 2021 12/17
Lean Software Factories
 Lean & Agile: short-term delivery
of small value increments, long-
term iterative learning
 Lean thinking : continuous
management of technical debt to
develop « situation potential »
(tomorrow’s agility)
 Lean practices : right on the first
time, continuous learning through
kaizen
 Product mode : short-term
delivery of small value increments,
long-term iterative learning
Agile Manifesto
• Sprints
• Focus on user
• Cross-functional
teams
• Coevolution of
code/design
SCRUM
• Rites
• Retrospectives
Lean
• Kanban
• Kaizen
• 5S and
waste
removal
CICD
Continuous
Integration
Extreme Prog.
Continuous
Delivery
DEVOPS
Continuous Testing
Infrastructure
as Code
Dev & Ops
cross-functional
teams
Product
Lifecycle
• Test-driven
• Code is valuable
Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 13/26
Software Craftmanship – Embedded Agility
 “Show & Share” : Develop and value software excellence
through peer reviews
 Make Code Reviews more pleasurable and more efficient:
Coding standards and Pair-programming
“Love your code” : code elegance as a support for business
agility (code that one likes to modify)
13
Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 14/26
Part III
Data-Driven
Company
14
What we need to build this ambition:
• Digital continuity & Unified data models, to break siloes and
create enterprise-wide flows
• Data lakes & APIs, to foster open innovation and data
democratization
• AI-ready software stacks, to leverage the outside innovation
flow, and access to large and elastic computing resources.
Data -Driven Innovation
Define &
Produce Data
Store &
Forward
Data
Analytics
Data
Services
Data Products
Creating
Value
from
Data
Data strategy
Internal data
External data
Datalakes
Data Fabric
See
Understand
Predict
Service
exposure
Virtual Goods
Data API
Exchange
Platform
Empower our customers
Data
Intelligence
Adapt
Automation
Data
Collection
Architecture
Infrastructure
Create value for Michelin processes Create value for our customers
Turn data into assets that enable us to make better decisions, to deliver better operations and
to offer better solutions to customers and partners
Mindset: distributed and emergent innovation
Data collection/ training sets
AI-friendly software environments
Lab Culture (Data Science)
Perseverance
Constant
flow of
software
It takes
time to
build
skills
Data-Driven Innovation
Yves Caseau - Event-Driven Architecture for Smart Systems – 2020 16/19
Data Infrastructure
Collection Flow Infrastructure
Storage
Infrastructure
Referentials
Datalake(s)
« Hot »
Analytics
Platforms
« Cold »
Analytics
Platforms
Events
External
Sources
IOT / Video
Integration
Service
Platforms
AI & ML
Services
Classification
Forecast
NLP / Semantics
Planning
Optimization
Distributed
Data Ledgers
Sharing
Distribution
Synchronisation
Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 17/26
Data Infrastructure Principles
 CAP Theorem : it is a new world 
 Eventual consistency
synchronized with Business Processes
 Right-time architecture (events)
High Availabilty & Scale
 Data Quality emerges from QoS &
Synchronized Process Design
 Quality of User Experience matters
 Excellence requires focus and
perseverance
 Break data siloes with federated
models and pivot objects
 Shared semantics (AI ready)
 Rosetta stone for standards and
platform strategy
Pivot Business Objects Data Quality & Processes
Yves Caseau - Event-Driven Architecture for Smart Systems – 2020 18/19
Event-Driven Enterprise Architecture
 Hot & Cold Interplay
 Cf. LSTM architecture
 Bio-mimicry : combine cortex with
reflexes
 Smart routing of events as
distributed system control
 Where we plug the AI toolbox
 Reactive (reflexes) and Reflective
(learning from event patterns)
 Hierarchical event model
 Events and Business Process
duality
 Outside-In thinking to design
companies as platforms
Event Model Complex Event Processing Beyond Lambda
Yves Caseau - Event-Driven Architecture for Smart Systems – 2020 19/19
Data Meshes
 Distributed Agility
 Scalable Event-Driven
 Think of data as evolving flows
 “Lambda architecture” is built-in 
(data lakes as nodes – temporal decoupling)
 Modularity / Federation
 “Architectural Quanta” based on “distributed
domain driven architecture”
 More an art (experience) than a science –
CAP vs transactions.
 “Data as product”
 Align people (governance) and systems
(flows)
 Change management as #1 priority
 Discoverable, self-describing, inter-operable,
trustworthy
Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 20/26
Part IV
Artificial Intelligence
and
Machine Learning
20
Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 21/26
Exponential Tech: Software Engineering Matters
 Data Engineering (flows) and
platforms
 Lessons from Google, Criteo,
Amadeus, etc.
 Ecosystems / rate of change /
integration
 Software engineering
because of integration and
speed of change
 Future data is better than past
 Continuous learning /
enrichment cycle /
 Speed of cycle is critical
Iterative
Developement of
AI Practice
Speed of learning
depends on
computing power
Smart
Algorithms
Smart
Engineering Smart
Services
Service
Usage
Growing
Large
Datasets
Distributed Software
Engineering Practices
Management Vision
& Grit
Ease to collect Trust &
Acceptability
21
Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 22/26
Leveraging the Diversity of the AI Toolbox
 Todai Robot Example
 Systems of systems brings
 Resilience (biomimicry)
 Multi-scale
 Explainability
 From AlphaGo to AlphaFolds
 Large-scale Intelligent Agents
communities
 Game theory to reason about
competition and cooperation
 Reinforcement learning
 Transfer learning, GAN,
recurrent networks
 Generative Approaches,
Randomization (MCTS)
Meta-Heuristics Hybrid Machine Learning Systems of Systems
Yves Caseau - Event-Driven Architecture for Smart Systems – 2020 23/19
Designing Systems of (Smart) Systems
 Individual and collective
learning
 Hybrid AI required
 Time horizons (reflexes to LTP)
 Explainable / certifiable / black-box
 “Prediction is the essence of
intelligence”. Yann Le Cun
 Requires a “model of the world”
 Deep Learning for perception
 Anticipation requires system
engineering and adaptive
learning
Event-Driven Architecture
Vision
Perception
Communication
Neighbors
Robots
Information
System
Autonomous
Robot
React
Reflexes
Plan
Execute
Think
Decisions
Sensors
Goals
Individual
Memory
Forecast
Learn
adapt
Collective
Memory
Behaviors
Rules
Valuation
Patterns
Analysis
Machine
Learning
Behaviors
Rules
Valuation
Patterns
Human
worker
Cloud
hosting
Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 24/26
TRAINING SETS
 “Data is the new code ?” (P. Haren & H. Verdier @ NATF)
… with training protocols 
 Importance of benchmarking ( Netflix, Allstate, UPS, …)
Learning curve / communities /
nested guild structure at Michelin
Training sets as a KPI for advanced data capabilities
Yves Caseau - Exponential Information Systems for Digital Transformation – 2019 25/23
AI @ Michelin : Some Examples
 Quantitative Identification
of aggressiveness of mine
roads using computer vision technology
 Stone density and size identification
 Plotting over the mine area map with heat
signatures
MVP
Productionized
 Predict the volumes of the
replacement market for the
next 5-year horizon
Productionized
Product to scan tyres using
tyre image, extract
dimensions and other details (SI, LI,
etc.) in order to recommend the right
Michelin tyre for online consumers to
increase sales
MVP
Product to use AI to recommend
tyres to e-retail customers
 Blackcircles POC: Model performance is promising, and
areas of improvement identified.
 Consumer segments generated from the model along with
the recommendations were new and useful insights
POC results
validated
Generative Adversarial
Network
 ''Application of GAN for Reducing Data
Imbalance under Limited Dataset'' accepted
for VISAPP 2022 conference authored by
Gaurav Adke
Technology
Enablers
Predict raw material prices
for next 1 year horizon
Deployed the product for 7 raw materials
(6PPD, TMQ, CBS, TBBS, ZNO, Insoluble
Sulphur, COCL2 )
Productionized
Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 26/26
 Digital transformation is homeostasis :
Perpetual change to leverage best the possibilities of “exponential tech” in order
to match the expectations of a fast-changing world
 Data Science & Systems Engineering have never been so exciting …
Exponential revolution is happening now 
 The main risk is not to create too little value with data,
It is to leave the field of disruption to some (possibly unknown) competitors
Conclusion

More Related Content

Similar to DataAquitaine February 2022

A technical Introduction to Big Data Analytics
A technical Introduction to Big Data AnalyticsA technical Introduction to Big Data Analytics
A technical Introduction to Big Data Analytics
Pethuru Raj PhD
 
CRTC Cloud- Scott Sadler
CRTC Cloud- Scott SadlerCRTC Cloud- Scott Sadler
CRTC Cloud- Scott Sadler
KrisValerio
 
Customer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTX
Customer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTXCustomer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTX
Customer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTX
tsigitnist02
 
CL2015 - Datacenter and Cloud Strategy and Planning
CL2015 - Datacenter and Cloud Strategy and PlanningCL2015 - Datacenter and Cloud Strategy and Planning
CL2015 - Datacenter and Cloud Strategy and Planning
Cisco
 
Real-time Visibility at Scale with Sumo Logic
Real-time Visibility at Scale with Sumo LogicReal-time Visibility at Scale with Sumo Logic
Real-time Visibility at Scale with Sumo Logic
Amazon Web Services
 
BusinessIntelligenze - On Cloud BI (English)
BusinessIntelligenze - On Cloud BI (English)BusinessIntelligenze - On Cloud BI (English)
BusinessIntelligenze - On Cloud BI (English)
BusinessIntelligenze
 
Technology Vision 2008 at ICCG HD08
Technology Vision 2008 at ICCG HD08Technology Vision 2008 at ICCG HD08
Technology Vision 2008 at ICCG HD08
niklaus
 
Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...
Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...
Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...
Denodo
 
Digital Business Transformation for Energy & Utility company
Digital Business Transformation for Energy & Utility companyDigital Business Transformation for Energy & Utility company
Digital Business Transformation for Energy & Utility company
Ilham Ahmed
 
Digital Twin: A radical new approach to IoT
Digital Twin: A radical new approach to IoTDigital Twin: A radical new approach to IoT
Digital Twin: A radical new approach to IoT
Dimitri Volkmann
 
Data Virtualization. An Introduction (ASEAN)
Data Virtualization. An Introduction (ASEAN)Data Virtualization. An Introduction (ASEAN)
Data Virtualization. An Introduction (ASEAN)
Denodo
 
¿Cómo las manufacturas están evolucionando hacia la Industria 4.0 con la virt...
¿Cómo las manufacturas están evolucionando hacia la Industria 4.0 con la virt...¿Cómo las manufacturas están evolucionando hacia la Industria 4.0 con la virt...
¿Cómo las manufacturas están evolucionando hacia la Industria 4.0 con la virt...
Denodo
 
Networked Enterprise transformation and resource management in future interne...
Networked Enterprise transformation and resource management in future interne...Networked Enterprise transformation and resource management in future interne...
Networked Enterprise transformation and resource management in future interne...
Brian Elvesæter
 
Presentation on How to build your Windows Azure Practice
Presentation on How to build your Windows Azure PracticePresentation on How to build your Windows Azure Practice
Presentation on How to build your Windows Azure Practice
Microsoft Private Cloud
 
Global IT BPM Market Perspective by Dolat Capital with special coverage on cl...
Global IT BPM Market Perspective by Dolat Capital with special coverage on cl...Global IT BPM Market Perspective by Dolat Capital with special coverage on cl...
Global IT BPM Market Perspective by Dolat Capital with special coverage on cl...
Mohit Agarwal, CFA
 
Next Generation Data Center - IT Transformation
Next Generation Data Center - IT TransformationNext Generation Data Center - IT Transformation
Next Generation Data Center - IT Transformation
Damian Hamilton
 
IBM Private Cloud Platform - Setting Foundation for Hybrid (JUKE, 2015)
IBM Private Cloud Platform - Setting Foundation for Hybrid (JUKE, 2015)IBM Private Cloud Platform - Setting Foundation for Hybrid (JUKE, 2015)
IBM Private Cloud Platform - Setting Foundation for Hybrid (JUKE, 2015)
Denny Muktar
 
Envisioning the Future Enterprise
Envisioning the Future EnterpriseEnvisioning the Future Enterprise
Envisioning the Future Enterprise
WSO2
 
Secure, Strengthen, Automate, and Scale Modern Workloads with Red Hat & NGINX
Secure, Strengthen, Automate, and Scale Modern Workloads with Red Hat & NGINXSecure, Strengthen, Automate, and Scale Modern Workloads with Red Hat & NGINX
Secure, Strengthen, Automate, and Scale Modern Workloads with Red Hat & NGINX
NGINX, Inc.
 
Smart city IT operations- manage solutions complexity
Smart city IT operations- manage solutions complexitySmart city IT operations- manage solutions complexity
Smart city IT operations- manage solutions complexity
Mohit Mehrotra
 

Similar to DataAquitaine February 2022 (20)

A technical Introduction to Big Data Analytics
A technical Introduction to Big Data AnalyticsA technical Introduction to Big Data Analytics
A technical Introduction to Big Data Analytics
 
CRTC Cloud- Scott Sadler
CRTC Cloud- Scott SadlerCRTC Cloud- Scott Sadler
CRTC Cloud- Scott Sadler
 
Customer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTX
Customer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTXCustomer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTX
Customer Presentation - IBM Cloud Pak for Data Overview (Level 100).PPTX
 
CL2015 - Datacenter and Cloud Strategy and Planning
CL2015 - Datacenter and Cloud Strategy and PlanningCL2015 - Datacenter and Cloud Strategy and Planning
CL2015 - Datacenter and Cloud Strategy and Planning
 
Real-time Visibility at Scale with Sumo Logic
Real-time Visibility at Scale with Sumo LogicReal-time Visibility at Scale with Sumo Logic
Real-time Visibility at Scale with Sumo Logic
 
BusinessIntelligenze - On Cloud BI (English)
BusinessIntelligenze - On Cloud BI (English)BusinessIntelligenze - On Cloud BI (English)
BusinessIntelligenze - On Cloud BI (English)
 
Technology Vision 2008 at ICCG HD08
Technology Vision 2008 at ICCG HD08Technology Vision 2008 at ICCG HD08
Technology Vision 2008 at ICCG HD08
 
Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...
Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...
Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...
 
Digital Business Transformation for Energy & Utility company
Digital Business Transformation for Energy & Utility companyDigital Business Transformation for Energy & Utility company
Digital Business Transformation for Energy & Utility company
 
Digital Twin: A radical new approach to IoT
Digital Twin: A radical new approach to IoTDigital Twin: A radical new approach to IoT
Digital Twin: A radical new approach to IoT
 
Data Virtualization. An Introduction (ASEAN)
Data Virtualization. An Introduction (ASEAN)Data Virtualization. An Introduction (ASEAN)
Data Virtualization. An Introduction (ASEAN)
 
¿Cómo las manufacturas están evolucionando hacia la Industria 4.0 con la virt...
¿Cómo las manufacturas están evolucionando hacia la Industria 4.0 con la virt...¿Cómo las manufacturas están evolucionando hacia la Industria 4.0 con la virt...
¿Cómo las manufacturas están evolucionando hacia la Industria 4.0 con la virt...
 
Networked Enterprise transformation and resource management in future interne...
Networked Enterprise transformation and resource management in future interne...Networked Enterprise transformation and resource management in future interne...
Networked Enterprise transformation and resource management in future interne...
 
Presentation on How to build your Windows Azure Practice
Presentation on How to build your Windows Azure PracticePresentation on How to build your Windows Azure Practice
Presentation on How to build your Windows Azure Practice
 
Global IT BPM Market Perspective by Dolat Capital with special coverage on cl...
Global IT BPM Market Perspective by Dolat Capital with special coverage on cl...Global IT BPM Market Perspective by Dolat Capital with special coverage on cl...
Global IT BPM Market Perspective by Dolat Capital with special coverage on cl...
 
Next Generation Data Center - IT Transformation
Next Generation Data Center - IT TransformationNext Generation Data Center - IT Transformation
Next Generation Data Center - IT Transformation
 
IBM Private Cloud Platform - Setting Foundation for Hybrid (JUKE, 2015)
IBM Private Cloud Platform - Setting Foundation for Hybrid (JUKE, 2015)IBM Private Cloud Platform - Setting Foundation for Hybrid (JUKE, 2015)
IBM Private Cloud Platform - Setting Foundation for Hybrid (JUKE, 2015)
 
Envisioning the Future Enterprise
Envisioning the Future EnterpriseEnvisioning the Future Enterprise
Envisioning the Future Enterprise
 
Secure, Strengthen, Automate, and Scale Modern Workloads with Red Hat & NGINX
Secure, Strengthen, Automate, and Scale Modern Workloads with Red Hat & NGINXSecure, Strengthen, Automate, and Scale Modern Workloads with Red Hat & NGINX
Secure, Strengthen, Automate, and Scale Modern Workloads with Red Hat & NGINX
 
Smart city IT operations- manage solutions complexity
Smart city IT operations- manage solutions complexitySmart city IT operations- manage solutions complexity
Smart city IT operations- manage solutions complexity
 

More from Yves Caseau

CCEM2023.pptx
CCEM2023.pptxCCEM2023.pptx
CCEM2023.pptx
Yves Caseau
 
Global warming dynamic gamesv0.3
Global warming dynamic gamesv0.3Global warming dynamic gamesv0.3
Global warming dynamic gamesv0.3
Yves Caseau
 
Machine Learning for Self-Tracking
Machine Learning for Self-TrackingMachine Learning for Self-Tracking
Machine Learning for Self-Tracking
Yves Caseau
 
Lean from the guts
Lean from the gutsLean from the guts
Lean from the guts
Yves Caseau
 
Taking advantageofai july2018
Taking advantageofai july2018Taking advantageofai july2018
Taking advantageofai july2018
Yves Caseau
 
Software Pitch 2018
Software Pitch 2018Software Pitch 2018
Software Pitch 2018
Yves Caseau
 
Intelligence Artificielle - Journée MEDEF & AFIA
Intelligence Artificielle - Journée MEDEF & AFIAIntelligence Artificielle - Journée MEDEF & AFIA
Intelligence Artificielle - Journée MEDEF & AFIA
Yves Caseau
 
Big data, Behavioral Change and IOT Architecture
Big data, Behavioral Change and IOT ArchitectureBig data, Behavioral Change and IOT Architecture
Big data, Behavioral Change and IOT Architecture
Yves Caseau
 
XEBICON Public November 2015
XEBICON Public November 2015XEBICON Public November 2015
XEBICON Public November 2015
Yves Caseau
 
Smart selfnovember2013
Smart selfnovember2013Smart selfnovember2013
Smart selfnovember2013
Yves Caseau
 
Management socialnetworksfeb2012
Management socialnetworksfeb2012Management socialnetworksfeb2012
Management socialnetworksfeb2012
Yves Caseau
 
Google socialnetworksmarch08
Google socialnetworksmarch08Google socialnetworksmarch08
Google socialnetworksmarch08
Yves Caseau
 
Managing Business Processes Communication and Performance
Managing Business Processes Communication and Performance Managing Business Processes Communication and Performance
Managing Business Processes Communication and Performance
Yves Caseau
 
Smart homeamsterdamoctober2013
Smart homeamsterdamoctober2013Smart homeamsterdamoctober2013
Smart homeamsterdamoctober2013
Yves Caseau
 
Entreprise troispointzeropublicjan2015
Entreprise troispointzeropublicjan2015Entreprise troispointzeropublicjan2015
Entreprise troispointzeropublicjan2015
Yves Caseau
 
GTES UTC 2014
GTES  UTC 2014GTES  UTC 2014
GTES UTC 2014
Yves Caseau
 
The European CIO Conference - November 27th, 2014
The European CIO Conference - November 27th, 2014The European CIO Conference - November 27th, 2014
The European CIO Conference - November 27th, 2014
Yves Caseau
 
Disic mars2014
Disic mars2014Disic mars2014
Disic mars2014
Yves Caseau
 
Lean entreprisetwodotzerodauphinefev2014
Lean entreprisetwodotzerodauphinefev2014Lean entreprisetwodotzerodauphinefev2014
Lean entreprisetwodotzerodauphinefev2014Yves Caseau
 
Claire epita-février2014
Claire epita-février2014Claire epita-février2014
Claire epita-février2014Yves Caseau
 

More from Yves Caseau (20)

CCEM2023.pptx
CCEM2023.pptxCCEM2023.pptx
CCEM2023.pptx
 
Global warming dynamic gamesv0.3
Global warming dynamic gamesv0.3Global warming dynamic gamesv0.3
Global warming dynamic gamesv0.3
 
Machine Learning for Self-Tracking
Machine Learning for Self-TrackingMachine Learning for Self-Tracking
Machine Learning for Self-Tracking
 
Lean from the guts
Lean from the gutsLean from the guts
Lean from the guts
 
Taking advantageofai july2018
Taking advantageofai july2018Taking advantageofai july2018
Taking advantageofai july2018
 
Software Pitch 2018
Software Pitch 2018Software Pitch 2018
Software Pitch 2018
 
Intelligence Artificielle - Journée MEDEF & AFIA
Intelligence Artificielle - Journée MEDEF & AFIAIntelligence Artificielle - Journée MEDEF & AFIA
Intelligence Artificielle - Journée MEDEF & AFIA
 
Big data, Behavioral Change and IOT Architecture
Big data, Behavioral Change and IOT ArchitectureBig data, Behavioral Change and IOT Architecture
Big data, Behavioral Change and IOT Architecture
 
XEBICON Public November 2015
XEBICON Public November 2015XEBICON Public November 2015
XEBICON Public November 2015
 
Smart selfnovember2013
Smart selfnovember2013Smart selfnovember2013
Smart selfnovember2013
 
Management socialnetworksfeb2012
Management socialnetworksfeb2012Management socialnetworksfeb2012
Management socialnetworksfeb2012
 
Google socialnetworksmarch08
Google socialnetworksmarch08Google socialnetworksmarch08
Google socialnetworksmarch08
 
Managing Business Processes Communication and Performance
Managing Business Processes Communication and Performance Managing Business Processes Communication and Performance
Managing Business Processes Communication and Performance
 
Smart homeamsterdamoctober2013
Smart homeamsterdamoctober2013Smart homeamsterdamoctober2013
Smart homeamsterdamoctober2013
 
Entreprise troispointzeropublicjan2015
Entreprise troispointzeropublicjan2015Entreprise troispointzeropublicjan2015
Entreprise troispointzeropublicjan2015
 
GTES UTC 2014
GTES  UTC 2014GTES  UTC 2014
GTES UTC 2014
 
The European CIO Conference - November 27th, 2014
The European CIO Conference - November 27th, 2014The European CIO Conference - November 27th, 2014
The European CIO Conference - November 27th, 2014
 
Disic mars2014
Disic mars2014Disic mars2014
Disic mars2014
 
Lean entreprisetwodotzerodauphinefev2014
Lean entreprisetwodotzerodauphinefev2014Lean entreprisetwodotzerodauphinefev2014
Lean entreprisetwodotzerodauphinefev2014
 
Claire epita-février2014
Claire epita-février2014Claire epita-février2014
Claire epita-février2014
 

Recently uploaded

IMPORTANCE OF ALGAE AND ITS BENIFITS.pptx
IMPORTANCE OF ALGAE  AND ITS BENIFITS.pptxIMPORTANCE OF ALGAE  AND ITS BENIFITS.pptx
IMPORTANCE OF ALGAE AND ITS BENIFITS.pptx
OmAle5
 
CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)
CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)
CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)
eitps1506
 
The binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defectsThe binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defects
Sérgio Sacani
 
Holsinger, Bruce W. - Music, body and desire in medieval culture [2001].pdf
Holsinger, Bruce W. - Music, body and desire in medieval culture [2001].pdfHolsinger, Bruce W. - Music, body and desire in medieval culture [2001].pdf
Holsinger, Bruce W. - Music, body and desire in medieval culture [2001].pdf
frank0071
 
23PH301 - Optics - Optical Lenses.pptx
23PH301 - Optics  -  Optical Lenses.pptx23PH301 - Optics  -  Optical Lenses.pptx
23PH301 - Optics - Optical Lenses.pptx
RDhivya6
 
Introduction_Ch_01_Biotech Biotechnology course .pptx
Introduction_Ch_01_Biotech Biotechnology course .pptxIntroduction_Ch_01_Biotech Biotechnology course .pptx
Introduction_Ch_01_Biotech Biotechnology course .pptx
QusayMaghayerh
 
Alternate Wetting and Drying - Climate Smart Agriculture
Alternate Wetting and Drying - Climate Smart AgricultureAlternate Wetting and Drying - Climate Smart Agriculture
Alternate Wetting and Drying - Climate Smart Agriculture
International Food Policy Research Institute- South Asia Office
 
HUMAN EYE By-R.M Class 10 phy best digital notes.pdf
HUMAN EYE By-R.M Class 10 phy best digital notes.pdfHUMAN EYE By-R.M Class 10 phy best digital notes.pdf
HUMAN EYE By-R.M Class 10 phy best digital notes.pdf
Ritik83251
 
Pests of Storage_Identification_Dr.UPR.pdf
Pests of Storage_Identification_Dr.UPR.pdfPests of Storage_Identification_Dr.UPR.pdf
Pests of Storage_Identification_Dr.UPR.pdf
PirithiRaju
 
Juaristi, Jon. - El canon espanol. El legado de la cultura española a la civi...
Juaristi, Jon. - El canon espanol. El legado de la cultura española a la civi...Juaristi, Jon. - El canon espanol. El legado de la cultura española a la civi...
Juaristi, Jon. - El canon espanol. El legado de la cultura española a la civi...
frank0071
 
Anti-Universe And Emergent Gravity and the Dark Universe
Anti-Universe And Emergent Gravity and the Dark UniverseAnti-Universe And Emergent Gravity and the Dark Universe
Anti-Universe And Emergent Gravity and the Dark Universe
Sérgio Sacani
 
Authoring a personal GPT for your research and practice: How we created the Q...
Authoring a personal GPT for your research and practice: How we created the Q...Authoring a personal GPT for your research and practice: How we created the Q...
Authoring a personal GPT for your research and practice: How we created the Q...
Leonel Morgado
 
The cost of acquiring information by natural selection
The cost of acquiring information by natural selectionThe cost of acquiring information by natural selection
The cost of acquiring information by natural selection
Carl Bergstrom
 
AJAY KUMAR NIET GreNo Guava Project File.pdf
AJAY KUMAR NIET GreNo Guava Project File.pdfAJAY KUMAR NIET GreNo Guava Project File.pdf
AJAY KUMAR NIET GreNo Guava Project File.pdf
AJAY KUMAR
 
LEARNING TO LIVE WITH LAWS OF MOTION .pptx
LEARNING TO LIVE WITH LAWS OF MOTION .pptxLEARNING TO LIVE WITH LAWS OF MOTION .pptx
LEARNING TO LIVE WITH LAWS OF MOTION .pptx
yourprojectpartner05
 
Gadgets for management of stored product pests_Dr.UPR.pdf
Gadgets for management of stored product pests_Dr.UPR.pdfGadgets for management of stored product pests_Dr.UPR.pdf
Gadgets for management of stored product pests_Dr.UPR.pdf
PirithiRaju
 
GBSN - Biochemistry (Unit 6) Chemistry of Proteins
GBSN - Biochemistry (Unit 6) Chemistry of ProteinsGBSN - Biochemistry (Unit 6) Chemistry of Proteins
GBSN - Biochemistry (Unit 6) Chemistry of Proteins
Areesha Ahmad
 
Mechanisms and Applications of Antiviral Neutralizing Antibodies - Creative B...
Mechanisms and Applications of Antiviral Neutralizing Antibodies - Creative B...Mechanisms and Applications of Antiviral Neutralizing Antibodies - Creative B...
Mechanisms and Applications of Antiviral Neutralizing Antibodies - Creative B...
Creative-Biolabs
 
11.1 Role of physical biological in deterioration of grains.pdf
11.1 Role of physical biological in deterioration of grains.pdf11.1 Role of physical biological in deterioration of grains.pdf
11.1 Role of physical biological in deterioration of grains.pdf
PirithiRaju
 
Travis Hills of MN is Making Clean Water Accessible to All Through High Flux ...
Travis Hills of MN is Making Clean Water Accessible to All Through High Flux ...Travis Hills of MN is Making Clean Water Accessible to All Through High Flux ...
Travis Hills of MN is Making Clean Water Accessible to All Through High Flux ...
Travis Hills MN
 

Recently uploaded (20)

IMPORTANCE OF ALGAE AND ITS BENIFITS.pptx
IMPORTANCE OF ALGAE  AND ITS BENIFITS.pptxIMPORTANCE OF ALGAE  AND ITS BENIFITS.pptx
IMPORTANCE OF ALGAE AND ITS BENIFITS.pptx
 
CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)
CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)
CLASS 12th CHEMISTRY SOLID STATE ppt (Animated)
 
The binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defectsThe binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defects
 
Holsinger, Bruce W. - Music, body and desire in medieval culture [2001].pdf
Holsinger, Bruce W. - Music, body and desire in medieval culture [2001].pdfHolsinger, Bruce W. - Music, body and desire in medieval culture [2001].pdf
Holsinger, Bruce W. - Music, body and desire in medieval culture [2001].pdf
 
23PH301 - Optics - Optical Lenses.pptx
23PH301 - Optics  -  Optical Lenses.pptx23PH301 - Optics  -  Optical Lenses.pptx
23PH301 - Optics - Optical Lenses.pptx
 
Introduction_Ch_01_Biotech Biotechnology course .pptx
Introduction_Ch_01_Biotech Biotechnology course .pptxIntroduction_Ch_01_Biotech Biotechnology course .pptx
Introduction_Ch_01_Biotech Biotechnology course .pptx
 
Alternate Wetting and Drying - Climate Smart Agriculture
Alternate Wetting and Drying - Climate Smart AgricultureAlternate Wetting and Drying - Climate Smart Agriculture
Alternate Wetting and Drying - Climate Smart Agriculture
 
HUMAN EYE By-R.M Class 10 phy best digital notes.pdf
HUMAN EYE By-R.M Class 10 phy best digital notes.pdfHUMAN EYE By-R.M Class 10 phy best digital notes.pdf
HUMAN EYE By-R.M Class 10 phy best digital notes.pdf
 
Pests of Storage_Identification_Dr.UPR.pdf
Pests of Storage_Identification_Dr.UPR.pdfPests of Storage_Identification_Dr.UPR.pdf
Pests of Storage_Identification_Dr.UPR.pdf
 
Juaristi, Jon. - El canon espanol. El legado de la cultura española a la civi...
Juaristi, Jon. - El canon espanol. El legado de la cultura española a la civi...Juaristi, Jon. - El canon espanol. El legado de la cultura española a la civi...
Juaristi, Jon. - El canon espanol. El legado de la cultura española a la civi...
 
Anti-Universe And Emergent Gravity and the Dark Universe
Anti-Universe And Emergent Gravity and the Dark UniverseAnti-Universe And Emergent Gravity and the Dark Universe
Anti-Universe And Emergent Gravity and the Dark Universe
 
Authoring a personal GPT for your research and practice: How we created the Q...
Authoring a personal GPT for your research and practice: How we created the Q...Authoring a personal GPT for your research and practice: How we created the Q...
Authoring a personal GPT for your research and practice: How we created the Q...
 
The cost of acquiring information by natural selection
The cost of acquiring information by natural selectionThe cost of acquiring information by natural selection
The cost of acquiring information by natural selection
 
AJAY KUMAR NIET GreNo Guava Project File.pdf
AJAY KUMAR NIET GreNo Guava Project File.pdfAJAY KUMAR NIET GreNo Guava Project File.pdf
AJAY KUMAR NIET GreNo Guava Project File.pdf
 
LEARNING TO LIVE WITH LAWS OF MOTION .pptx
LEARNING TO LIVE WITH LAWS OF MOTION .pptxLEARNING TO LIVE WITH LAWS OF MOTION .pptx
LEARNING TO LIVE WITH LAWS OF MOTION .pptx
 
Gadgets for management of stored product pests_Dr.UPR.pdf
Gadgets for management of stored product pests_Dr.UPR.pdfGadgets for management of stored product pests_Dr.UPR.pdf
Gadgets for management of stored product pests_Dr.UPR.pdf
 
GBSN - Biochemistry (Unit 6) Chemistry of Proteins
GBSN - Biochemistry (Unit 6) Chemistry of ProteinsGBSN - Biochemistry (Unit 6) Chemistry of Proteins
GBSN - Biochemistry (Unit 6) Chemistry of Proteins
 
Mechanisms and Applications of Antiviral Neutralizing Antibodies - Creative B...
Mechanisms and Applications of Antiviral Neutralizing Antibodies - Creative B...Mechanisms and Applications of Antiviral Neutralizing Antibodies - Creative B...
Mechanisms and Applications of Antiviral Neutralizing Antibodies - Creative B...
 
11.1 Role of physical biological in deterioration of grains.pdf
11.1 Role of physical biological in deterioration of grains.pdf11.1 Role of physical biological in deterioration of grains.pdf
11.1 Role of physical biological in deterioration of grains.pdf
 
Travis Hills of MN is Making Clean Water Accessible to All Through High Flux ...
Travis Hills of MN is Making Clean Water Accessible to All Through High Flux ...Travis Hills of MN is Making Clean Water Accessible to All Through High Flux ...
Travis Hills of MN is Making Clean Water Accessible to All Through High Flux ...
 

DataAquitaine February 2022

  • 1. Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 1/26 Exponential Information Systems to support a Data-Driven Digital Transformation Yves Caseau Group CDIO, Michelin NATF (National Academy of Technologies of France) http://informationsystemsbiology.blogspot.com/ https://twitter.com/ycaseau DATAQUITAINE February 10th, 2022 – v0.2
  • 2. Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 2/26  Part 1: Digital Transformation Driving the software revolution to adapt constantly to the customer’s environment  Part 2: Exponential Information Systems Software excellence matters – Build your foundations  Part 3: Data-Driven Ambition Enterprise-wide flows, Customer-time freshness, Future-proof unified semantics  Part 4: Exponential Technologies Ambition Artificial intelligence and machine learning to drive more value from data Outline
  • 3. Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 3/26 Information Systems as Core Digital Capabilities  Digital transformation is a business transformation, across the value chain  IS as a backbone (Part 2)  Shared “digital core” … but each digital world has its own ecosystems: (IT ≠ Digital)  Digital continuity creates value Alibaba & Amazon example:  Digital Supply Chain Meets Demand Management  AI to grow new knowledge from end-to-end processes Digital Employee Support Systems: Infrastructure, Data, Identity & security, orchestration, API, …. Product Development Supply Chain Manu- facturing Services & Solutions Sales & CRM Digital continuity
  • 4. Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 4/26 4 Product Development and Knowledge Engineering AI as a tool to capture, share and scale process and product knowledge Hybrid AI, from DeepMind (cf. Part 4) – to ML-augmented finite element simulation AI and generative ML techniques to re-invent product expertise
  • 5. Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 5/26 Industry 4.0 : Digital Manufacturing, Digital Twin & Digital Workspaces  AI in Manufacturing to absorb complexity  cope with variability  cope with manufacturing process complexity  Augmented humans and augmented environments  machine vision & sensors for enhanced perception  End to End process optimization Merck Example Middleware / HA/ Containers Shared Datalake Shared Expert Services Infrastructucture / Security Middleware / HA/ Containers Middleware / HA/ Containers Middleware / HA/ Containers Digital Core (App Server / CICD) Digital Twin Digital Twin Digital Twin Information Systems PLM ERP MPM
  • 6. Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 6/26 Digital Customer Journeys  Events, Insights and Context  Co-operation Agents/ Digital is built on a virtuous loop  Insights are fed by events, events fed by conversations, conversations fed by content Daily Yearly Life Time Customer Journey (Sales / Service ) Agent CDP 3rd Party Data Process Data Engagement DMP Advice / Recommendation Service / Assistance Content Insights Mining Reactive care Conversations feedback events requests Web/ Mobile/ Social 02.04.2021 Retain for: 90d v. Croc / t. fraudet / a. LemblÉ / t. signarbieux Steering committee api transformation < N° > d3 Group Martech Stack at Michelin Apostrophe MediaMath BlueConic inRiver Wedia ???? Salesforce Didomi ????? ????? WordPress Salesforce Marketing Cloud Rul.ai Sprinklr Pixel MediaMath?? Excel Sheet Qualtrics Pixlee?? CloudImage?? Flutter Apostrophe Apostrophe
  • 7. Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 7/26 7 Support Hybrid Way of Working : remote collaboration DIGITAL WORKPLACE Augmented collaboration : “Kolmogorov compression” The smarter the AI, the more succinct the context synchronization Cognitive Agents: From ontologies to “GPT-3 + semantics” knowledge management and augmentation
  • 8. Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 8/26 Part II Exponential Information Systems 8
  • 9. Yves Caseau - Lean Software Factories and Digital Transformation – 2021 9/17 Entreprise 3.0 “Holomorphism” Open Platforms Antifragile Customer Homeostasis Recognition & Response Network of Teams Massively Transformational Purpose (MTP) Orientation Client Scalability On-demand Algorithms & Automation Continuous Learning Experimentation Interfaces Autonomy Agility Short steps Communities & Crowds E3.0 Customer Orientation
  • 10. Yves Caseau - Lean Software Factories and Digital Transformation – 2021 10/17 Exponential Information Systems Principles  Digital Homeostasis  Outside-in  Reactive  Open frontiers  Accelerate Takt Time  Automation  Short release cycles  Living System  In/out breathing  Continuous architecture (emergence) Outside-In Customer focus EDA Data-Driven Multimodal CICD Elastic Resources Algorithms Continuous Refresh / Refactor Sustainable Growth SRE AI4Ops API
  • 11. Yves Caseau - Lean Software Factories and Digital Transformation – 2021 11/17 Architect for Change : Multimodal Architecture  Four zones illustration: different rates of change, different software ecosystems  Extension of bi-modal IT pattern (but everything must change)  Edge is the software domain that is not controlled by IT but where it must project its services  The supporting integration capabilities is a key enabler for digital transformation Enterprise Integration Capabilities Business capabilities • Records • Transactions • Business Intelligence CORE Renewal every 10 years Engagement capabilities • Mash-up • Contextual • Conversations • Personalization MATRIX Renewal every 5 years Edge capabilities • Smartphones • Social Platforms • Connected Objects • Etc. EDGE Fast & imposed Renewal Imported Capabilities • AI/ ML • NLP/Semantics • IOT Exponential Cloud Renewal every 3 years API API API
  • 12. Yves Caseau - Lean Software Factories and Digital Transformation – 2021 12/17 Lean Software Factories  Lean & Agile: short-term delivery of small value increments, long- term iterative learning  Lean thinking : continuous management of technical debt to develop « situation potential » (tomorrow’s agility)  Lean practices : right on the first time, continuous learning through kaizen  Product mode : short-term delivery of small value increments, long-term iterative learning Agile Manifesto • Sprints • Focus on user • Cross-functional teams • Coevolution of code/design SCRUM • Rites • Retrospectives Lean • Kanban • Kaizen • 5S and waste removal CICD Continuous Integration Extreme Prog. Continuous Delivery DEVOPS Continuous Testing Infrastructure as Code Dev & Ops cross-functional teams Product Lifecycle • Test-driven • Code is valuable
  • 13. Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 13/26 Software Craftmanship – Embedded Agility  “Show & Share” : Develop and value software excellence through peer reviews  Make Code Reviews more pleasurable and more efficient: Coding standards and Pair-programming “Love your code” : code elegance as a support for business agility (code that one likes to modify) 13
  • 14. Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 14/26 Part III Data-Driven Company 14
  • 15. What we need to build this ambition: • Digital continuity & Unified data models, to break siloes and create enterprise-wide flows • Data lakes & APIs, to foster open innovation and data democratization • AI-ready software stacks, to leverage the outside innovation flow, and access to large and elastic computing resources. Data -Driven Innovation Define & Produce Data Store & Forward Data Analytics Data Services Data Products Creating Value from Data Data strategy Internal data External data Datalakes Data Fabric See Understand Predict Service exposure Virtual Goods Data API Exchange Platform Empower our customers Data Intelligence Adapt Automation Data Collection Architecture Infrastructure Create value for Michelin processes Create value for our customers Turn data into assets that enable us to make better decisions, to deliver better operations and to offer better solutions to customers and partners Mindset: distributed and emergent innovation Data collection/ training sets AI-friendly software environments Lab Culture (Data Science) Perseverance Constant flow of software It takes time to build skills Data-Driven Innovation
  • 16. Yves Caseau - Event-Driven Architecture for Smart Systems – 2020 16/19 Data Infrastructure Collection Flow Infrastructure Storage Infrastructure Referentials Datalake(s) « Hot » Analytics Platforms « Cold » Analytics Platforms Events External Sources IOT / Video Integration Service Platforms AI & ML Services Classification Forecast NLP / Semantics Planning Optimization Distributed Data Ledgers Sharing Distribution Synchronisation
  • 17. Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 17/26 Data Infrastructure Principles  CAP Theorem : it is a new world   Eventual consistency synchronized with Business Processes  Right-time architecture (events) High Availabilty & Scale  Data Quality emerges from QoS & Synchronized Process Design  Quality of User Experience matters  Excellence requires focus and perseverance  Break data siloes with federated models and pivot objects  Shared semantics (AI ready)  Rosetta stone for standards and platform strategy Pivot Business Objects Data Quality & Processes
  • 18. Yves Caseau - Event-Driven Architecture for Smart Systems – 2020 18/19 Event-Driven Enterprise Architecture  Hot & Cold Interplay  Cf. LSTM architecture  Bio-mimicry : combine cortex with reflexes  Smart routing of events as distributed system control  Where we plug the AI toolbox  Reactive (reflexes) and Reflective (learning from event patterns)  Hierarchical event model  Events and Business Process duality  Outside-In thinking to design companies as platforms Event Model Complex Event Processing Beyond Lambda
  • 19. Yves Caseau - Event-Driven Architecture for Smart Systems – 2020 19/19 Data Meshes  Distributed Agility  Scalable Event-Driven  Think of data as evolving flows  “Lambda architecture” is built-in  (data lakes as nodes – temporal decoupling)  Modularity / Federation  “Architectural Quanta” based on “distributed domain driven architecture”  More an art (experience) than a science – CAP vs transactions.  “Data as product”  Align people (governance) and systems (flows)  Change management as #1 priority  Discoverable, self-describing, inter-operable, trustworthy
  • 20. Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 20/26 Part IV Artificial Intelligence and Machine Learning 20
  • 21. Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 21/26 Exponential Tech: Software Engineering Matters  Data Engineering (flows) and platforms  Lessons from Google, Criteo, Amadeus, etc.  Ecosystems / rate of change / integration  Software engineering because of integration and speed of change  Future data is better than past  Continuous learning / enrichment cycle /  Speed of cycle is critical Iterative Developement of AI Practice Speed of learning depends on computing power Smart Algorithms Smart Engineering Smart Services Service Usage Growing Large Datasets Distributed Software Engineering Practices Management Vision & Grit Ease to collect Trust & Acceptability 21
  • 22. Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 22/26 Leveraging the Diversity of the AI Toolbox  Todai Robot Example  Systems of systems brings  Resilience (biomimicry)  Multi-scale  Explainability  From AlphaGo to AlphaFolds  Large-scale Intelligent Agents communities  Game theory to reason about competition and cooperation  Reinforcement learning  Transfer learning, GAN, recurrent networks  Generative Approaches, Randomization (MCTS) Meta-Heuristics Hybrid Machine Learning Systems of Systems
  • 23. Yves Caseau - Event-Driven Architecture for Smart Systems – 2020 23/19 Designing Systems of (Smart) Systems  Individual and collective learning  Hybrid AI required  Time horizons (reflexes to LTP)  Explainable / certifiable / black-box  “Prediction is the essence of intelligence”. Yann Le Cun  Requires a “model of the world”  Deep Learning for perception  Anticipation requires system engineering and adaptive learning Event-Driven Architecture Vision Perception Communication Neighbors Robots Information System Autonomous Robot React Reflexes Plan Execute Think Decisions Sensors Goals Individual Memory Forecast Learn adapt Collective Memory Behaviors Rules Valuation Patterns Analysis Machine Learning Behaviors Rules Valuation Patterns Human worker Cloud hosting
  • 24. Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 24/26 TRAINING SETS  “Data is the new code ?” (P. Haren & H. Verdier @ NATF) … with training protocols   Importance of benchmarking ( Netflix, Allstate, UPS, …) Learning curve / communities / nested guild structure at Michelin Training sets as a KPI for advanced data capabilities
  • 25. Yves Caseau - Exponential Information Systems for Digital Transformation – 2019 25/23 AI @ Michelin : Some Examples  Quantitative Identification of aggressiveness of mine roads using computer vision technology  Stone density and size identification  Plotting over the mine area map with heat signatures MVP Productionized  Predict the volumes of the replacement market for the next 5-year horizon Productionized Product to scan tyres using tyre image, extract dimensions and other details (SI, LI, etc.) in order to recommend the right Michelin tyre for online consumers to increase sales MVP Product to use AI to recommend tyres to e-retail customers  Blackcircles POC: Model performance is promising, and areas of improvement identified.  Consumer segments generated from the model along with the recommendations were new and useful insights POC results validated Generative Adversarial Network  ''Application of GAN for Reducing Data Imbalance under Limited Dataset'' accepted for VISAPP 2022 conference authored by Gaurav Adke Technology Enablers Predict raw material prices for next 1 year horizon Deployed the product for 7 raw materials (6PPD, TMQ, CBS, TBBS, ZNO, Insoluble Sulphur, COCL2 ) Productionized
  • 26. Yves Caseau - Exponential Information Systems towards Data-Driven Digital Transformation – 2022 26/26  Digital transformation is homeostasis : Perpetual change to leverage best the possibilities of “exponential tech” in order to match the expectations of a fast-changing world  Data Science & Systems Engineering have never been so exciting … Exponential revolution is happening now   The main risk is not to create too little value with data, It is to leave the field of disruption to some (possibly unknown) competitors Conclusion

Editor's Notes

  1. CRITICAL : print the version with Notes !
  2. The target The means to reach the target How to build the mean
  3. Part II : we will now consider the impact on IS Intro: SW is eating the world does not mean that IT is running the company  It means that each part of the value chain will undergo a digital transformation that requires support from IT capabilities Digital Fabric : core of IT services that are required = cf Digotal core of first Digital Manuf illustration Digital Twin and Digital Environment => world of IoT & connected objects => need support for IOT management, data and security Recall the ecosystem argument : one size does not fit all ! Each digital transformation story has its own opportunities and constraints IT is a key enabler, but digital transfo is lead by the business
  4. Introduction : Reinventing the cookie repicipe with Tensor Flow Many similar story in manufacturing – they are not public Digital transformation implies a complete reinvention of processes and services Look at Human+Machine Nike example with rurring shoes ML works much better with meta-data human expertise : training a ML is a form of knowledge capture once capture this may be shared and distributed ML training as a knowledge collaborative platform : what has happended for machine vision (with the ImageNet data set) (3) Digital supply chains take the order management data in real time => from forecasting to reactive scheduling Demand management uses the digital supply chain to provide a better experience (real time update) – the B2C standard (not for tires yet)
  5. Title : Three component of DT in manufacturing Digital to automate & optimize the manuf process (continuity) Digital Twin: more advanced optimization based on simulation (anticipation / forecast / …) the Age of IOT Digital workspace : human augmentation => the complete environt is helping (cobots, smart visualization) The age of smart objects (your world is the user interface to comuter assistance) DT is about complexity management DT is augmented humans & augmented machines Digital Twin : end to end optimization and reingineering – true transformation versus 30 years of siloed planning.
  6. Innovation in the digital world is more difficult => Lean Startup is born from analyzing failures and successes Need the customer cooperation to understand the pain point and to build a value proposition MVP : most famous term from LS Up, tool to collect feedback and accumulate knowledge (only way not to dispair) Kevin Kelly : complex smart systems are grown not designed These three loops are the summay of my 3 years as AXA head of digital = listen, do, learn
  7. The target The means to reach the target How to build the mean
  8. Part II : we will now consider the impact on IS Intro: SW is eating the world does not mean that IT is running the company  It means that each part of the value chain will undergo a digital transformation that requires support from IT capabilities Digital Fabric : core of IT services that are required = cf Digotal core of first Digital Manuf illustration Digital Twin and Digital Environment => world of IoT & connected objects => need support for IOT management, data and security Recall the ecosystem argument : one size does not fit all ! Each digital transformation story has its own opportunities and constraints IT is a key enabler, but digital transfo is lead by the business
  9. (1) La première zone « Core » regroupe les capacités « métiers » du système d’information classique en tant que support des processus métiers. Cette zone est bien sûr elle-même multimodale, de façon fractale, ce qui permet d’implémenter une transformation continue, par exemple avec l’introduction de micro-services et d’APIs internes. On retrouve ici le concept du « Operational Backbone » dont l’exposition de services recomposables au moyen d’API est considérée comme une des pièces angulaires de la transformation digitale. Une architecture de SI, qui décompose un système en sous-systèmes et modalités de composition, est fractale dans le sens ou cette décomposition s’applique de façon récursive aux sous-systèmes. (2) La zone qualifiée de « matrice » est la zone d’engagement et de composition de services. Cette zone, de type « fast IT », est construite pour un taux de changement plus élevé (3) La zone « exponentielle » représente l’ensemble des services fournis par des fournisseurs externes pour des fonctionnalités « avancées ». Cette séparation permet de mettre l’accent sur le rythme encore plus élevé de changement et sur le fait que l’entreprise utilise ces services tels qu’ils sont et ne maîtrise pas leur évolution. Penser comme une zone séparée permet de mieux visualiser le besoin d’expérimentation, de test et de protocole d’intégration (il faut expérimenter pour comprendre, et comprendre avant d’intégrer). (4) La dernière zone, dénommée « edge », représente l’environnement logiciel et numérique du client, qui est choisi par le client et construit par des acteurs multiples. L’entreprise n’est qu’un acteur parmi d’autres, voire de temps en temps un « parasite » (un petit acteur qui profite de l’effort massif d’acteurs plus gros).
  10. DevOps CICD Infrastructure as Code Mixing Dev & Ops roles and Skills Cycle : Repeated Loop
  11. Peer review at every possible scale Make the reviews more pleasurable and more efficient (3) Key insight : Agility is not only a matter of mindset and post-its, it is a property of the code Arnaud Lemaire (4) Elegance : Minimal; Intent readability and virality
  12. Data-Driven at Michelin : The three contributions of IS Break siloes Democratization Le bon environnement logiciel et matériel => cf rapport de l’ADT
  13. Key idea: not very subtle ; data is like water in the see everywhere  Data infrastructire collection Data Fabric Data consumption platforms – everywhere / where AI can be applied
  14. What is expected from IS as far as data is concerned Ability to share data every where => implies a shared semantics => Digital starts with data, but data starts with shared data model (2) Data is no longer static => need to cope with massive distribution and rates of change data quality => data freshness + Qualigy of operations (3) We live in the world of massive amounts of data that are distributed (place of use and place of creation) Right-time : pseudo-temps réel adapté aux besoins métiers
  15. So, what does it mean to apply EDA at the EA scale ? Les systèmes réactifs sont définis dans le Reactive Manifesto comme étant responsive (réaction rapide), résilient, élastique et message-driven (assemblés par envoi de messages). Une des caractéristiques des systèmes digitaux modernes est précisément leur scalabilité, qui s’appuie sur une approche par événement, une distribution massive des traitements et des outils de traitement des flux d’événement. (2) Ouverture = pub/sub + standardized API (3) Hot : flow (use cold)
  16. Part II : we will now consider the impact on IS Intro: SW is eating the world does not mean that IT is running the company  It means that each part of the value chain will undergo a digital transformation that requires support from IT capabilities Digital Fabric : core of IT services that are required = cf Digotal core of first Digital Manuf illustration Digital Twin and Digital Environment => world of IoT & connected objects => need support for IOT management, data and security Recall the ecosystem argument : one size does not fit all ! Each digital transformation story has its own opportunities and constraints IT is a key enabler, but digital transfo is lead by the business
  17. Lessons from 3 years at ADT (Big Data & AI) + NAE Conférence System engineering to handle lots of data + data flows => leverage tech constant moving edge Past data is not the new oil – contrary to what macron says – data should be a flow The technology power (CPU & skills) dictate the speed of the reinforcement learning cycle
  18. Intro : la grande révolution de Michelin est de passer du batch au fil de l’eau dans le traitement des intéraction clients. Les systèmes réactifs sont définis dans le Reactive Manifesto comme étant responsive (réaction rapide), résilient, élastique et message-driven (assemblés par envoi de messages). Une des caractéristiques des systèmes digitaux modernes est précisément leur scalabilité, qui s’appuie sur une approche par événement, une distribution massive des traitements et des outils de traitement des flux d’événement. Grand projet stratégique : passer du EDA local au EDA global (2) Ouverture = pub/sub + standardized API EDA inter entreprise + API = perte de contrôle  (de EDI to API) (3) Reactive = Fast & Smart
  19. Exemple de robot autonome dans une usine – formant une communauté Comme la maison inteligente, c’est un systeme de systèmes (1) Double apprentissage de l’individu et de la communauté – cf. Tweet récent de Elon Musk « Everyday your ⁦@Tesla gets smarter from all the data feeding into the AI system. (2) Illustration du besoin d’IA hybride (3) Idée clé de Yann LeCun : un système autonome intelligent dispose d’un modèle de son environnment et il fait des prévisions pour anticiper (pas seulement réactif). Message clé pour EDA :) (4) Utilisation des meta heuristique (reinforcement learning par ex) et de system engineering (loops) pour construire cette intelliegnce adaptative
  20. Key idea: not very subtle ; data is like water in the see everywhere  Data infrastructire collection Data Fabric Data consumption platforms – everywhere / where AI can be applied
  21. Introduction : smart home story Biomimicry : simpler systems for low level functions Need memory / multi-time -scale thinking Need planning / goals to action – smart systems develop intents dynamically Need foracasting / requires « real world modelling » … more than time series or pattern forecasting T