Marilu has produced a valuable and detailed tour-de-force in this very comprehensive guide to developing an enterprise-level Data Strategy that is pragmatic, agile, and communicable. It is clear that she recognizes, from her own extensive experience, that most organizations have not been able to muster the engagement and collaboration needed to produce whole-of-organization agreements about how to articulate and align the key components, that is, data management, technology, architecture, and governance.
The challenge that she set herself, and has mastered, is HOW to harness business interests in the light of the current and future data landscape and technology opportunities. Her 10-step Data Strategy Cycle is fully elucidated, and each activity and sub-activity, with its corresponding goals and objectives, is fully described. No thoughtful reader will be able to conclude that any level of instruction – who, why, what, when, and how – has been neglected. Throughout the chapters, charts, and diagrams summarize the proposed method effectively. Since my experiences have taught me that every organization, from a huge conglomerate to a new startup, benefits from conducting a Data Management Assessment, it was gratifying to see that as a foundational requirement as Part 1, Step 2, very early in the strategy lifecycle.
In my data management courses over the last decade, one of the main team exercises is outlining a data management strategy because it pulls together the component disciplines of data management and encourages enterprise-level thinking, which is vital for a Chief Data Officer. In addition, Marilu de-mystifies the crucial task of decomposing the business strategy and aligning it to data – domains, architecture, and governance. The final step in this phase is developing Key Performance Indicators, enabling executives to measure progress towards the strategic goals of the business. The Data Strategy development phases she describes collectively encompass a systematic, consistent home for every key element of what it takes to manage data assets effectively.
The Data Strategy Canvases are not only a useful mechanism to unpack complexity bite by bite, gaining agreement every step of the way, but also lend themselves as a proof-of-concept trial of ownership and stewardship roles, which are then planned and implemented through an integrated, multi-leveled roadmap.
Participants in the development of the Data Strategy will broaden and deepen their understanding of data across the organization and learn their responsibilities from the ground up. Along the way, Marilu addresses and clarifies several of our industry’s ‘terms of art,’ such as “data-driven,” “data literacy” and “digital transformation.” And she employs a rational, functional approach to answering the perennial question we often hear at conferences “What is the difference between data management and data governance?” The reader will receive an evidence-based answer in this book, as she meticulously describes roles and responsibilities wedded to phases and strategy development tasks.
If your organization has recognized the need to create a Data Strategy, I highly recommend this book! (No excuses, people, you can do it).