To 10x Analytics, Treat It Like a Product

It’s time for Business Intelligence to evolve.

Cameron Warren
6 min readMay 3, 2022


For 8 out of 10 of you reading this sentence, analytics is a failure.

Yes, you’ve created dashboards and reports. The teams you support have KPIs and indicators about their business. They can watch numbers going up and down. But ask yourself this question:

What legitimate changes in behavior have they made based on data?

If the answer is difficult to articulate, then your analytics are weak.

Analytics, or more particularly, Business Intelligence, suffers from a serious case of what I call the “chicken-or-egg” syndrome. Which is, the struggle to distinguish outcomes from the output. For BI and Analytics professionals, there is a struggle to distinguish between building “data things” and end-user making progress in their life.

If that last sentence is confusing, it’s because the concept of building things for a real individual is something particularly foreign for data people. In 9 different analytics and data roles as an FTE and a consultant across 7 different companies, I’ve learned that analytics roles are about 95% building data pipelines, dashboards, and models, and about 5% figuring out what to actually build.

Fortunately, there is a solution to the chicken-or-egg analytics problem:

Treat analytics like a product.

The Purpose of Analytics

Too often, analytics is disseminated into the tools and practices that enable it. The definition of analytics is the process of discovering, interpreting, and communicating significant patterns in data. The way we talk about it, however, you could easily believe analytics was the process of manipulating data into visualization tools, excel reports, and Powerpoint decks.


If you’ve worked in the analytics field for even a moment you’ve seen this graph before. It’s the Analytics Maturity Curve.

Early in my career, I spent a lot of time thinking about this graph. It’s an enticing image that puts Prescriptive Analytics (ML/AI) as the ultimate end goal of every organization serious about analytics. Unfortunately, it’s about as helpful as looking at a…



Cameron Warren

Writing about how teams and individuals can more effectively use data. Follow me: @camwarrenm