Sandra Oudshoff
5 min read
Humanizing Data Strategy is a refreshing addition to the world of data books. That shouldn't be surprising, given that Feng himself is a unique figure in the data space—check out his rap on data governance for proof. Is there a more fitting term for people working in data governance than "Data Sherpas"?
The book offers a fresh perspective on how companies can build and implement data strategies that are not only effective but also people-centric. Feng emphasizes the importance of embedding human elements into data strategy, ensuring that initiatives are not only technologically sound but also aligned with the needs, behaviors, and values of the people involved—whether employees, customers, or other stakeholders.
At the heart of Feng's approach is his "5 Cs" framework, which serves as a guide to humanizing data strategy. Here's a summary:
1. Competence – The essence of data literacy: empowering everyone with the right knowledge and skills. It's about teaching data to business people—and business to data people. 2. Collaboration – Embracing transparency, accountability, and shared goals, while fostering a culture of teamwork. 3. Communication – Tailoring your message to the audience, focusing on both business value and personal benefits. 4. Creativity – Building a data environment where people are motivated and inspired to improve and innovate. 5. Conscience – Encouraging critical thinking and human judgment to ensure data is used securely, ethically, and in compliance with regulations.
Among the book's most valuable takeaways are: the importance of cross-functional collaboration in data initiatives, the need for clear data governance that balances security with accessibility, the value of an iterative, agile approach to data strategy, the crucial role of communication in translating data insights into business value, and the necessity of strong data leadership that extends beyond technical expertise.
That said, Humanizing Data Strategy is not about radically new or groundbreaking ideas. The "5 Cs," for instance, overlap significantly with the key skills needed in the age of AI. Also, as a reader, I sometimes felt disoriented and unsure of the overall structure—chapters cover a wide range of topics, often briefly and without clear connections. A summary at the end of each chapter would have greatly helped.
Despite this, the book remains highly relevant for anyone involved in data management, analytics, or business strategy. It touches on a broad spectrum of topics essential for a truly human-centric data approach—from career paths, talent lifecycles, and HR's role, to data quality, data democratization, ethics, and storytelling.
Chapter 7, in particular, provides a valuable checklist of questions to "human-proof" your data strategy. These prompts can help shift the perception of humans from being the weakest link in data to becoming the very foundation—the cement—of your data strategy. With the rise of AI and GenAI, we need a data strategy that is not only effective but also ethical, inclusive, and firmly aligned with broader organizational goals.
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