Today, about 80% of organisations consider data and AI as an essential part of their strategy. However, 7 out of 10 organisations report minimal to no gains from their data & AI initiatives. With businesses heavily invested in data and AI, what makes the difference between being successful and failing with data and AI? In our Data & AI Maturity Journey track at the Applied Machine Learning Days in Lausanne 2022, we invite different companies to talk about how they became data & AI driven organisations. We share a practical — and widely applicable — maturity journey that demonstrates how organisations grow their data and AI competencies. To reach maturity, companies usually work on two axes: Analytics Capabilities — Data, People & Skills, Tools & Tech — and Business Adoption — Executive Support, Funding, Implementation. But where do you stand in this journey and how can you reach your destination? Join this session if you want to understand the phases and drivers of the data maturity journey. Get the chance to learn from other organisations that embarked on this journey before you.

1. @Applied Machine Learning Days 2022
The Data & AI Maturity Journey track
Steven Nooijen
March 2022
Becoming data-driven:
A practical journey to mature
your data & AI capabilities.

2. About me:
Steven Nooijen
• Head of Data & AI Strategy @GoDataDriven
• Management consulting & programming
• Consultant in data science since 2014
"Getting the most out of AI requires a team effort.
Consider AI to be 10% about algorithms, 20%
about technology, and 70% about business process
transformation.” - BCG https://nl.linkedin.com/in/stevennooijen

3. Who we are
OUR AMBITION
Driving Your Success With Data and AI
Part of

4. € …
_ ORGANIZE
Data & AI Strategy
and Execution
It’s 2021. You’ve invested time and
resources in data and AI. Let’s look at the
results – are you realizing business value?
_ BUILD
Data Platforms and
AI Applications
We build solutions with data and AI: from
concept to prototype and to production-
ready application.
We can be the partner that gets your
organization ready to run solutions at
enterprise scale with ease!
_ TRAIN
Online Data & AI
Learning Journeys
The data field is dynamic like no other.
Developing your skills is key to stay
ahead. GoDataDriven provides the
experience, flexibility, and digital
curriculum.
_ MANAGE
Managed Data &
AI Services
When you have your data and AI practice
up and running, you want peace of mind
that this business-critical process stays
that way. How do you ensure stability
and optimal performance?
Plan your journey to become the AI-Driven enterprise
Translate your strategy into business solutions
Make your data and AI team work
Design and build data platforms
Develop and run AI applications
AI technology at the core since 2009
Individual courses to level up your game
In-company training programs to grow your team
Curriculum available both classroom and online
Automation of best practices, tests and security
Performance optimizations and 24/7 monitoring
Cloud spend optimization
What we do

5. Trusted by national and global industry leaders
€ …

6. Topic of today:
The AI Maturity Journey
• Today, about 80% of organizations consider
data & AI as an essential part of their strategy.
• However, 70% of organisations report minimal
to no gains from their data & AI initiatives.
Ø With businesses heavily invested in data and
AI, what makes the difference between being
successful and failing with data and AI?
gdd.li/ai-maturity

7. pollev.com/gdd444

9. Our vision on Data & AI Maturity
Initialization
• Find and initiate first use cases: identify
opportunities, boot up data, people & tools
Continuous Experimentation
• Expand team, infrastructure and company
presence. Define standard ways of working
Enterprise Empowerment
• Grow AI practice across all business units and put
business in driver’s seat; buy-in required!
AI Democratization
• AI literacy in genes of company; anyone has skills
required to make AI driven decisions
gdd.li/ai-maturity

10. Mature both Analytical Capabilities & Business Adoption
Analytical
Maturity
Analytical
Capability
People & Skills
Mostly reliant on external
consultants
Senior talent in-house
No vision and strategy for
growing in-house talent
Clear career paths and training
curriculum in place
Knowledge sharing is minimal
or ad hoc
Constant knowledge sharing;
learning is part of culture
Tools &
Technology
Data
Business
Adoption
Executive
Support
Funding
Implementation
For all metrics
see whitepaper
gdd.li/ai-maturity
Drivers Immature Practice Mature Practice
Dimensions
Maturity
vs.
gdd.li/ai-maturity

12. Maturity drivers for the Analytical Capability
Immature Mature
People &
skills
Mostly reliant on external consultants
No vision & strategy for growing in-house talent
Knowledge sharing is minimal or ad hoc
Senior talent in-house
Clear career paths and training curriculum in place
Constant knowledge sharing; learning is part of culture
Tools &
technology
Dependent on IT for sandbox environment
Self-maintained clusters with lacking maintenance
Monolith legacy systems that can hardly be changed
Sandbox and production environment in own control
Usage of easily scalable cloud technology
Technology is built modularly and is loosely coupled
gdd.li/ai-maturity

14. Maturity drivers for the Analytical Capability
Immature Mature
People &
skills
Mostly reliant on external consultants
No vision & strategy for growing in-house talent
Knowledge sharing is minimal or ad hoc
Senior talent in-house
Clear career paths and training curriculum in place
Constant knowledge sharing; learning is part of culture
Tools &
technology
Dependent on IT for sandbox environment
Self-maintained clusters with lacking maintenance
Monolith legacy systems that can hardly be changed
Sandbox and production environment in own control
Usage of easily scalable cloud technology
Technology is built modularly and is loosely coupled
Data
Working with one-off dumps, replication of data sets
No data ownership, nor data governance program
Organization not aware of importance of good data
Integrated data, easily accessible in centralized platform
Chief Data Office in place for data governance and quality
Importance of good data demonstrated by AI practice
gdd.li/ai-maturity

16. Mature both Analytical Capabilities & Business Adoption
Analytical
Maturity
Analytical
Capability
People & Skills
Tools &
Technology
Data
Business
Adoption
Executive
Support
Bottom-up initiatives; low board
level involvement
C-level leads AI movement &
provides a purpose
AI use cases are pushed from
the AI capability
Business pull on AI capability for
new use cases
Little communication about AI
developments
AI community that activates the
organization
Funding
Implementation
Drivers Immature Practice Mature Practice
Dimensions
Maturity
vs.
gdd.li/ai-maturity

18. Maturity drivers for the Business Adoption of AI
Immature Mature
Executive
support
Bottom-up initiatives; low board level involvement
AI use cases are pushed from the AI capability
Little communication about AI developments
C-level leads AI movement & provides a purpose
Business pull on AI capability for new use cases
AI community that activates the organization
Funding
AI initiatives funded by IT
No innovation budget for experimentation
No value measurement
Business pays for AI solutions
Central budget available for research & innovation
Value based prioritization & benefit tracking
gdd.li/ai-maturity

20. Maturity drivers for the Business Adoption of AI
Immature Mature
Executive
support
Bottom-up initiatives; low board level involvement
AI use cases are pushed from the AI capability
Little communication about AI developments
C-level leads AI movement & provides a purpose
Business pull on AI capability for new use cases
AI community that activates the organization
Funding
AI initiatives funded by IT
No innovation budget for experimentation
No value measurement
Business pays for AI solutions
Central budget available for research & innovation
Value based prioritization & benefit tracking
Implemen-
tation
AI products developed in isolation without business
Hard to roll out products in organization
AI changes “come on top of” regular work
Design process in place that guarantees value impact
Business in charge of roll out and product adoption
Organization frees up resources to implement AI
gdd.li/ai-maturity

22. Our vision on Data & AI Maturity
Initialization
• Find and initiate first use cases: identify
opportunities, boot up data, people & tools
Continuous Experimentation
• Expand team, infrastructure and company
presence. Define standard ways of working
Enterprise Empowerment
• Grow AI practice across all business units and put
business in driver’s seat; buy-in required!
AI Democratization
• AI literacy in genes of company; anyone has skills
required to make AI driven decisions
gdd.li/ai-maturity

23. Maturity drivers vary in importance over time
gdd.li/ai-maturity

24. Topic of today:
The AI Maturity Journey
• Today, about 80% of organizations consider
data & AI as an essential part of their strategy.
• However, 70% of organisations report minimal
to no gains from their data & AI initiatives.
Ø With businesses heavily invested in data and
AI, what makes the difference between being
successful and failing with data and AI?
gdd.li/ai-maturity

25. WWW.GODATADRIVEN.COM
STEVENNOOIJEN@GODATADRIVEN.COM
LinkedIn: STEVENNOOIJEN

26. GoDataDriven
Maturity Audit
ü Systematic review of
the existing data operation
ü Gain insights in maturity
of the current capability
along both technical &
business domain
ü Understand if the current
capability fits future
opportunities, priorities
and requirements