Why understanding your data is so important

Many Organisations Start with the Wrong End

Many of the clients we work with come to us facing serious issues with their data; whether it’s operational, security-related, or just poorly structured. They’re eager to use observability or monitoring tools, but they often don’t understand the basics: where their data comes from, how it’s structured, or why that matters. This lack of understanding leads to common problems we break down in the sections below: Buzzwords Without the Basics, The Problem with Product-First Thinking, Using What’s Convenient Instead of What’s Useful finishing with Moving from Concept to Tangible Value.

Buzzwords Without the Basics

We hear a lot of buzzwords: data-driven management, robust data flows, data-informed decision-making. These terms imply a strong positive impact on business, but many organisations try to use poor-quality data and mismatched platforms to achieve these goals. They’re aiming for data-driven decisions without truly understanding the data itself, what they should be pulling from it and why it’s useful. That creates a backwards process; trying to squeeze value out of the data, instead of starting by understanding where the data fits and what it can really tell them.

The Problem with Product-First Thinking

These buzzwords carry weight conceptually, but in practice (across business operations) they don’t always help in a meaningful way. They often lead to a “product first, utility second” mindset. We see a lot of companies choosing a product, getting locked into it and then shaping everything else around it. The product dictates what data is examined, how it’s processed, and even what data is collected or discarded which often driven by cost or internal politics.

Using What’s Convenient Instead of What’s Useful

This leads to a situation where people work with whatever’s accessible and convenient, rather than understanding the data itself or getting real value from it. It’s a siloed approach, not a strategic one. Instead, they should start with the data, understand it deeply, see what insights can be drawn from it and then build a genuine data-driven management strategy around that.

Moving from Concept to Tangible Value

Our approach focuses on discovery across the data lifecycle, as we’ve discussed before. It’s about moving away from vague ideas and “product first, utility second” thinking. Instead, we aim for something practical and linear: work with the data, extract insights, make it more usable, format it clearly and interpret it in a way people can act on. Then determine what tools are actually needed for each piece of data, then align those with a real product strategy. That’s how you get to the heart of why understanding data truly matters.