Executive Summary
Your teams have plenty of dashboards and data, but making important business decisions seems to be getting slower, not faster.
This 'analysis paralysis' costs money in wasted engineering time and makes it harder to move quickly. While you're debating which of 50 dashboards is correct, your competitors might be shipping new features.
The way forward isn't more data, but careful curation. It's about moving from being 'data-driven' (measuring everything) to 'data-informed' (tracking a handful of important signals). This is a problem of structure and governance, not just tooling.
The problem with measuring everything
There's a common idea that to be a 'data-driven' company, you must measure everything. You've likely spent six or seven figures on the Modern Data Stack. You have the tools: Snowflake, dbt, and a BI tool like Looker or Power BI. You've hired good engineers. But often, this just means the old mess has been moved to the cloud, and you're now generating questionable data much faster.
The hope was for clarity, but the result is often confusion. What I often see is teams spending their time in meetings, arguing about which numbers are correct. This leads to a kind of dashboard sprawl, where every department has its own version of the truth. This isn't really progress, it's just confusion in a digital format.
Why having more data doesn't always lead to better insights
The core of the problem is that the organisation becomes data-rich, but insight-poor. You have more charts than ever, but seem to have less certainty. This tends to happen when a company starts mistaking activity for impact. You track every click, every event, every page view, but you can't answer a basic question like: “What is our net margin on this product?”
I see this quite a lot in scale-ups, typically around Series B to D. They can get focused on tracking vanity metrics, often because they are easy to measure, not because they are the most important. The data team can end up acting like a dashboard factory, producing reports that add more noise than signal. It's usually a problem with the system, not the people. Your team is doing exactly what was asked of them: measuring everything.
I was looking at a Looker setup for a Series C company recently. They had over 200 dashboards. A quick check showed that about 60% of them hadn't been looked at in the last six months. And yet, the data team's backlog was full of requests for more reports. In my experience, this isn't a sign of a curious organisation, but a symptom of some underlying confusion.
The solution is to focus on fewer, better metrics
The solution can feel a bit counter-intuitive. It isn't about adding more data, building more dashboards, or hiring more analysts. It's about subtraction.
The focus of your Data Strategy needs to shift from producing dashboards to curating a few key signals. This usually involves three steps, which can be challenging:
This is the shift from being data-driven to data-informed. A data-driven approach often involves chasing every piece of data. A data-informed culture, on the other hand, uses a few, trusted data points to help guide people's intuition and expertise.
Why this change can be difficult to implement
You should expect some resistance. Taking away a department head's favourite dashboard can be a political challenge, not just a technical one. People will understandably argue that their metrics are essential, and they'll defend their spreadsheets.
If you're leading this, your job is to hold the line. The goal is not to give everyone the data they want. The goal is to give the business the handful of signals it needs. This requires a bit of courage and a willingness to stick to simplicity. It might mean moving a little slower for a few weeks, to be able to move much faster for the next few years.
The reward, in the end, is clarity. I've seen board meetings get shorter. The endless debates about 'whose number is right' tend to fade away. The team starts asking better questions about the data you have, instead of just asking for more of it. You can stop getting stuck in analysis and start making faster, better-informed decisions.