Should You Measure the Value of a Data Team?

What to measure and whether you should

Data teams are sometimes asked to prove their ROI to senior leadership to justify a budget for new hires, tools, projects, or process changes. But the work of data teams is inherently unmeasurable. Often the reason for this ROI question isn’t rooted in a lack of proper metrics but rather a lack of trust and relationships with stakeholders.

Should you measure the data team’s ROI? If so, which metrics are worth considering? This post summarizes key arguments from several blog posts, podcasts, discussions from data communities, and my experience.

Arguments against measuring

Most data teams work as a support function. They help other teams make decisions and operate more efficiently, but their involvement in value creation is indirect. You can’t directly quantify (especially in advance) the impact of a new table, dashboard, or pipeline.

Improving your data models or data infrastructure doesn’t immediately return any financially measurable outcomes related to the core of your business. It doesn’t mean those improvements are not valuable. But what’s valuable is not necessarily what’s valued. Data teams often don’t get credit for their work, not because they do a poor job, but because the…