In data we trust… Too easily

The biggest problem with energy and carbon data isn’t that it’s missing. It’s what we think is reliable.

Most organisations genuinely believe they have their numbers under control. Spreadsheets, smart meters, and automated reports give the reassurance that everything adds up. But scratch beneath the surface, and you’ll often find gaps, inconsistencies, and figures that can’t be traced back to the source. The data looks solid, but can you rely on it and more importantly, will it pass an independent audit process? When it comes to energy data, quality will always trump quantity.

The illusion of reliability

We live in the era of data. Most of us are surrounded by more information than we can process, and we’ve come to assume that volume equals truth. But we rarely stop to ask where the data comes from, how it’s managed, or what quality checks exist behind it.

Many of the processes we still use to gather and manage data were designed long before digital systems — some even before the advent of the personal computer. Over time, we’ve layered technology on top, automated the routines, and made them faster. But we haven’t always made them better.

This is especially evident in how we handle energy and carbon information. The systems most organisations use are patchy at best, far below the standard we’d ever accept for financial data.

What finance gets right

Executives in well-run businesses expect accuracy, traceability, and confidence in their financial reporting. Every figure is tied to a source. Every record is auditable. 

Imagine managing company finances using only monthly bank statements — with no insight into what those transactions comprised, no ledger, and no verification. Most of us would call that unthinkable and predict the business wouldn’t last long. Yet that’s precisely how many are still managing their energy and carbon performance.

Yet, in our experience, most organisations have plenty of data. The problem is that it’s often siloed, inconsistent, outdated or unverified. You’d never accept unverified figures when acquiring a new business. You’d check every assumption, every claim, every piece of supporting data before signing the deal. If anything didn’t add up, you’d walk away. The same scrutiny needs to be applied to our energy data.

Moving from assumption to assurance

The first step is straightforward enough: structure. Following an established framework such as ISO 50001 is a good start. It gives us a system for collecting, validating, and reporting energy and carbon data. But structure alone isn’t enough. Data quality has to be actively managed.

This means having the right systems that make the data visible, trustworthy, and insightful for planning, monitoring, and reporting purposes, as well as validating what’s already there. 

Because in the end, sustainability decisions are only as good as the data behind them. Treating energy and carbon data with the same rigour as financial data isn’t bureaucracy — it’s credibility. Because the real risk isn’t having too little data, it’s trusting data that can’t be trusted.