An Executive Guide for Scaling AIVol. 01 · Edition 2025
People.
Process.
Technology. And data.
The board-level case for treating data as a first-class strategic asset —
with the frameworks, KPIs and maturity model executives need to scale AI
before competitors do.
“For three decades, enterprise strategy
has rested on people, process and technology. The argument of this book is
simple, and overdue: data is the fourth pillar — and the
ones who treat it as such will scale AI. The rest will spectate.”
This book reasons why data should be the fourth pillar for every
enterprise — alongside people, processes and technology. It gives boards,
CEOs, and CxOs a working understanding of why and how to treat data
strategically: not as IT exhaust, but as a continuously appreciating
economic asset.
The argument is laid out in three movements — the Why, the
What, and the How — in measurable terms.
To capture business impact, the authors introduce two new KPIs: Total
Addressable Value through data (TAV) and Expected Addressable Value (EAV),
and a Maturity Framework for moving deliberately from descriptive
dashboards to a scalable, AI-powered, data-centric enterprise.
A practitioner's case study by Rüdiger Eck (AUDI AG) grounds
the frameworks in production-floor reality — what works, what doesn't, and
what every CxO should ask of their own organisation on Monday morning.
Written for the people
who actually move the dial.
Three audiences. One mandate: stop treating data as a back-office cost
centre and start running it as the asset it has quietly become.
§
Persona I
Board & CEO
Be the data champions. Provide sponsorship and strategic leadership to enable the enterprise to derive long-term value through the data pillar.
¶
Persona II
Chief Data Officer
The CDO's North Star: enable every stakeholder to enhance their business outcomes by leveraging data as a strategic asset.
†
Persona III
CxOs at large
CIO/CTOs, COOs, CHROs and leaders across functions create the flywheel — enabling the data pillar and benefiting from it.
§ 02 — The Frameworks
Five ideas worth a board memo.
Theme 01 · Data Intensity
The QCS Framework
A three-dimensional way to read data intensity:
Quality, Compliance, Speed. Different
initiatives need different mixes — get the mix wrong and AI stalls.
Theme 02 · Operating Model
The Data Operating Model (DOM)
An agile data delivery framework that lets the data pillar serve data
consumers at the speed they actually need — not the speed your
data warehouse can manage.
DemandSupplyGovernancePlatformProductsOutcomes
Theme 03 · Business Value KPIs
Two new numbers your CFO will ask about.
Most enterprises measure data by how much they store. The book proposes
measuring it by what it can earn.
TAV
Total Addressable Value
The full economic value latent in your data, end-to-end.
EAV
Expected Addressable Value
What you can realistically capture given today's maturity.
Δ
The Gap
The board's roadmap — and your competitors' headstart.
Theme 04 · The Journey
A Maturity Framework — not a vibes check.
Assess where you are. Set strategic goals. Progress systematically toward
a scalable, AI-powered, data-centric enterprise.
01Foundational0–33%
02Scaled34–66%
03Automated67–100%
Theme 05 · Case Study
AUDI AG — on the production floor.
Rüdiger Eck details Audi Production's journey: on-the-ground feedback
on what works, what doesn't, and the practical lessons every operator
navigating similar terrain should expect to learn — the hard way, or
from this chapter.
Excerpt
“Without a strategic approach to data, AI initiatives fall flat. The book
connects executive vision with operational reality.”
— Dr. Joerg Storm
§ 03 — On Record
What leaders are actually saying.
“”
Attribution
The full chorus — 18 endorsements
§ 04 — Audio
The Board & CxO Briefing.
A short-form podcast where the authors and a rotating cast of operators
interrogate the ideas in the book — one episode at a time.
Sujay is a seasoned technology and business leader with 25+ years of global experience. He believes the future is being shaped at the intersection of AI, Business outcomes, Culture, and Data — the "A.B.C.D." He presently works as a Global Account Lead at Databricks.
Siddharth (Sidd) is a Chief Architect in the Field CTO Organization at Informatica. He engages senior executives at enterprise scale, providing thought leadership around data and data management.
Head of Data and Analytics Factory for Production & Logistics at Audi AG. Rüdiger is an accomplished
professional in the automotive industry with a distinguished career spanning over two decades across two
German premium OEMs — including winning two consecutive world-champion titles with the Mercedes Formula 1
team. He has spearheaded Audi teams from the early stages of production digitalisation and now directs
Audi's Data and Analytics Factory for Production & Logistics, while overseeing Volkswagen Group data
activities. With a German master's degree ("Diplom-Ingenieur") in mechanical engineering, Rüdiger has a
strong passion for managing technical and organisational change and bridging the gap between production and IT.
"Bridging the gap between production and IT" — a working operator's read on what it actually takes to make a data pillar real on a factory floor that doesn't stop for transformation programs.
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