The Economics of Reusable Data Products

Most organizations have invested heavily in making data available. The harder problem, and the one that determines whether those investments actually pay off, is making data reusable. When capabilities are rebuilt from scratch for every new project, the result is duplicated pipelines, inconsistent metrics, and a data team that's always busy but never scaling.

This e-Book makes the economic and strategic case for treating reusable data products as long-lived enterprise assets. Drawing on research from McKinsey and IBM, it gives data leaders a practical framework for where reuse creates value, what makes it succeed or fail, and how to build the foundations that make reuse the default.

What you'll find inside:

• The business case in concrete terms: How organizations have cut data delivery costs by 30–40% and accelerated time to value by up to 90% by reusing existing data products rather than building from scratch
• Technical and organizational foundations: Why standardized schemas, strong metadata, and clear ownership determine whether reusable data products are sustainable, and how misaligned funding and culture undermine it even when the technology is solid
• How the Quest Trusted Data Management Platform operationalizes reuse: How the Automated Data Product Factory surfaces existing assets before a new build begins, so reuse becomes the default and not an afterthought

You'll also find cross-industry patterns and lessons from financial services, retail, technology, and the public sector, plus a concise set of leadership takeaways for data leaders ready to move from fragmented delivery to a reuse-first operating model.