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Welcome to Data as the Fourth Pillar
An Executive Guide for Scaling AI
Pre-order now from your favorite retailer
An Executive Guide for Scaling AI
This book reasons why Data should be the Fourth Pillar for every enterprise, along with people, processes and technology. It provides the Board, CEOs, and CxOs an understanding of why and how they should treat Data strategically. It provides a comprehensive success by design approach for enterprises and guides them through a Maturity Framework to accelerate their data-centric journey.
The book covers the "Why", the "What" and the "How" of achieving that goal in measurable terms. To measure the impact provided by the Data pillar, the authors introduce KPIs such as Total Addressable Value through data (TAV) and Expected Addressable Value through data (EAV). The book explores how AI and Data enable and benefit from each other. It provides a case study by Rüdiger Eck, Audi AG which brings practical insights into the concepts and frameworks presented.
This book is a key resource for business executives in SMB and Large Enterprises who need to accelerate business value to their stakeholder communities in a highly complex and hyper-competitive business landscape.
Be the Data Champions. Provide sponsorship and strategic leadership to enable the enterprise to derive long-term value through the data pillar.
The North Star goal of a Chief Data Officer would be to enable all stakeholders to enhance their business outcomes by leveraging data as a strategic asset.
CIO/CTOs, COOs, CHROs and leaders across different business functions and domains create the flywheel effect – enabling the data pillar and benefitting from it.
To understand data intensity, the authors present a three-dimensional "QCS Framework," wherein "QCS" represents "Quality, Compliance, and Speed."
A Data Operating Model (DOM) is an agile data delivery framework that enables the data pillar to provide data assets to the data consumers.
To measure the impact provided by the Data pillar, the authors introduce KPIs such as Total Addressable Value through data (TAV) and Expected Addressable Value through data (EAV).
The authors introduce the Maturity Framework, which enables organizations to assess their maturity level, set strategic goals, and systematically progress toward a scalable, AI-powered, data-centric enterprise.
The case study details Audi Production's journey to provide on-the-ground implementation feedback on what works and what doesn't - it offers practical lessons for others navigating similar terrain.
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Rüdiger is an accomplished professional in the automotive industry with a distinguished career spanning over two decades. Working for two German premium OEMs, Rüdiger has over 20 years of technical track record in global automotive production, including winning two consecutive world champion titles with the Mercedes Formula 1 team. He has spearheaded various Audi teams from the early stages of digitalization in the production industry and now directs Audi's Data and Analytics Factory for Production & Logistics, as well as 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 organizational change and bridging the gap between production and IT. His expertise and leadership continue to drive innovation and excellence in the automotive sector.