79% of companies have sustainability data, so why aren't they using it in key decisions?

Your company is probably already measuring its sustainability impact. That is not unusual: around 79% of large companies do, and many have been collecting data for more than a decade.

But measuring is no longer the problem. The real issue is what is done with that information.

In most cases, very little. Only a minority of companies actually use that data in decisions such as operations, procurement or product design. The rest stays within reporting.

This is not just a matter of sustainability maturity; it is a structural misalignment. Companies are making decisions with a critical part of the information off the radar. And increasingly, that is starting to take its toll.

The rise of data has not changed decision-making

Over the past decade, sustainability has moved from being a reputational element to becoming a business standard. The entry into force of frameworks such as the CSRD in Europe, the development of the ESRS and the consolidation of methodologies like the GHG Protocol have pushed companies to measure, structure and report their impact in ever greater detail.

The result is an unprecedented volume of information: environmental indicators, social metrics, double materiality assessments, increasingly comprehensive emissions inventories... In many sectors, impact measurement is now as embedded as financial measurement.

However, that sophistication has not been matched in decision-making. While most large companies already report their impact, only a small share uses that data in relevant business decisions. Various sector analyses point in the same direction: sustainability reports are increasingly extensive, but they are rarely connected to operational decisions.

What happens when you decide without that information

This disconnect has very concrete day-to-day consequences:

• Purchases that appear cheaper but are more expensive in the medium term: suppliers with greater exposure to energy costs, carbon taxes or regulatory risks that end up directly hitting margins.
• Risks that appear too late: disruptions in the supply chain, cost increases or regulatory changes that are not anticipated and force a reactive, more expensive response.
• Inefficiencies that erode profitability: energy- or resource-intensive processes that go unnoticed and, once added up, represent significant deviations in operating costs.
• Missed commercial opportunities: failing to meet ESG requirements from clients, tenders or investors, and being left out of business opportunities.

Why the data does not reach the business

First, much of the data still lives outside the operational flow. It is generated by sustainability teams or through consultancies, but it is not integrated into the systems where decisions are made.

To this is added the very nature of reporting: aggregated information, produced annually and designed to explain what has already happened. A format that fits regulatory logic, but not the day-to-day operations of a company.

Complexity also plays a relevant role. Especially in areas such as Scope 3, where the data is fragmented, depends on third parties and requires processing capacity that many organisations still do not have.

From reporting to a management tool

The problem is not generating data, but how to integrate it into decision-making. That means transforming the role of data:

• From a static report to an operational input
• From annual analysis to continuous use
• From an aggregated metric to actionable information
• From explaining the past to anticipating the future

Incorporating environmental variables into real decisions (such as supplier selection or process optimisation) makes it possible to detect risks before they materialise and to find efficiency opportunities that would otherwise stay off the radar.

The role of technology: integrate, process, decide

The challenge is no longer measuring impact, but ensuring that information is used where decisions are actually made. That is where Manglai introduces a clear shift by applying artificial intelligence to turn environmental data into operational decisions.

Its approach is directly tied to efficiency. The platform automates the collection, cross-referencing and analysis of data, significantly reducing the time spent on manual tasks. What used to take weeks of work is now resolved much faster and with fewer errors, which ends up having a direct impact on costs.

From there, artificial intelligence makes it possible to detect inefficiencies that normally stay off the radar, such as processes with high consumption or suppliers with greater impact and associated risk. This makes it easier to make better decisions in procurement and the supply chain, optimising costs not only in the short term but also avoiding future cost overruns.

Want to see how it works?

You can discover Manglai's CSRD reporting solution and how it turns data into decisions.

Companies have already covered an important part of the journey. Today, the challenge is to make sure that data stops staying within reporting and becomes part of decision-making.

Because in the current context, the difference is not made by who measures, but by who is able to use that information to operate better.