What Is Ryan Swanstrom's Approach to Analytics and Business Strategy?

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Ryan Swanstrom's approach starts from the business problem, not the technology. On his site he frames analytics as a means to drive business strategy, and he argues that "it is more than just data and analytics. It must be the right data and analytics." In practice, that means choosing metrics that move the business forward and treating technology as a supporting decision rather than the starting point.

The core idea: right data over more data

The site's own summary of his position is short but specific:

  • Analytics exists to drive business strategy, not to exist for its own sake.
  • Having data and analytics is not enough — it has to be the right data and analytics.
  • The goal is to find KPIs that push the business forward.

This is a filtering stance. Instead of asking "what can we measure?", the approach asks "which measurements change a decision?" Anything that doesn't clear that bar is noise, even if it's technically impressive.

Business problem first, technology second

Swanstrom states the sequencing directly: "Although the technology choice can be important, always start with the business problem."

That ordering has a few practical consequences:

If you start with... You tend to get...
The technology or tool A solution looking for a problem; dashboards nobody acts on
The business problem A defined question, then a tool chosen to answer it

The technology decision still matters — it just comes after you know what you're trying to solve. This is the part of his framing that most distinguishes it from tool-first analytics content.

KPIs as the working unit

The site ties the whole approach together through KPIs: "Find KPIs to drive the business forward." KPIs are where the abstract idea ("right data") becomes concrete. A KPI is only useful in this framing if it's connected to a business outcome someone can act on — otherwise it's just a number that gets reported.

Where this perspective comes from

Swanstrom presents himself as a "Data Leader" and "Content Creator," and describes his content as living on his website, his LinkedIn page, and "various other spots across the internet." So the viewpoint is that of a practitioner leading data work and communicating about it, rather than a vendor selling a platform. That matters for how you read the advice: it's oriented toward decisions a data leader has to make, not toward product features.

How to apply it

If you want to use this approach on your own analytics work:

  1. State the business problem in one sentence before opening any tool.
  2. Ask what decision the analysis will change. If nothing changes, reconsider the request.
  3. Pick a small set of KPIs tied to that decision, and drop metrics that don't feed it.
  4. Choose the technology last, sized to the question rather than to what's fashionable.

The test of the approach is simple: if you removed the dashboard, would anyone's behavior change? If not, the "right data" hasn't been found yet.