What Data Really Costs: A Business Fable About Capital, Leadership, and the Operating Model Between

Three data strategies in four years. None of them wrong. All of them aimed at a destination without a map of the present.

Sarah Chen has done everything a CEO is supposed to do. She hired talented heads of data. She approved roadmaps. She funded migrations, governance frameworks, and tooling investments. She said yes to data.

What she never had was a system to know what any of it returned.

What Data Really Costs is a business fable about the six months that change how a CEO sees the data function she has been funding. When a consultant arrives and asks three questions she has never been asked:

• What decision does this enable?
• What does it cost your team to build it?
• What do you stop doing to make room for it?

This is the story of what it takes to fix that. Not technically. Financially.

You will recognize this book.

The team running at crisis capacity while appearing to function. The 134 working days lost every month to data friction no one had measured. The board conversation where the numbers didn't translate. The moment a CEO realizes she has been approving investment for years with no system to measure what it returns.

By the end, you will have the language for the thing you have been trying to explain to your board for years.

For CEOs and founders who have funded a data function and cannot explain what it returns.

For CFOs who need a financial model for a function that has never spoken their language.

For heads of data who know what the problem is and have never had the words to make leadership see it.

This is not a textbook. It is a story. But it is built on a methodology tested in real companies, with real boards, under real financial pressure.

Read it before your next board meeting.