McKinsey’s recent article “The missing data link: Five practical lessons to scale your data products” has hit on something I’ve been advocating for years: treating data as a product rather than a project or resource. While I’m typically wary of consultancy research (aren’t we all?), this piece validates much of what we’ve observed in the field about the transformative power of data product thinking.

Over the last twenty years, the analytics landscape has evolved dramatically but one fundamental truth remains: organizations still struggle to translate data into meaningful action. In today’s AI-augmented environment, the challenge isn’t accessing data-—it’s determining which insights actually matter and how to implement them effectively within your organization.

Given the time and expense associated with implementing a large-scale solution, it’s worth considering whether building small programs around specific problems and then scaling up is the right approach for your organization.