What is sustainability data?

Data is the bedrock of a resilient businesses

Sustainability data is the foundation to know "how" companies use resources, such as energy, water, waste, and how those activities affect people, environment and the business itself. The data might show us a way to cut down on waste, which also helps the bottom line, or spot discrepancies in operations between two or more business sites.

Sustainability data is operational information, the same transactions, and consumption records that organizations generate in the course of normal business activity. The difference lies in how the data is structured and classified.

Sustainability data is categorized under the ESG framework

Environmental Data: This is often the most data-intensive category. It includes, but is not limited to:

Greenhouse Gas (GHG) emissions (Scope 1, 2, and 3)
Energy consumption (electricity, heating, fuel)
Water usage and discharge
Waste generation and recycling rates
Resource consumption (raw materials, packaging)
Pollution and environmental incidents
Land use and biodiversity impacts

Social Data: This relates to an organization's impact on its stakeholders, including:

Employee health and safety metrics
Workforce diversity and inclusion statistics
Labor practices and human rights in the supply chain
Community engagement and investment
Customer welfare and product responsibility
Training and development hours

Governance Data: This focuses on how an organization is led and managed, such as:

Corporate policies on sustainability and ethics
Board oversight of ESG issues
Risk management processes related to sustainability
Stakeholder engagement mechanisms
Transparency in reporting and disclosure
Executive compensation linked to sustainability targets

The quality problem

Raw data is only as useful as the structure behind it. An energy invoice, a waste collection receipt, a supplier disclosure, these become meaningful sustainability data when they are consistently defined, accurately converted, and can be traced back to their original source.

When organizations collect sustainability data in different formats, using different definitions and different assumptions, comparing results becomes unreliable. This matters not just for reporting, but for decision-making; spotting inefficiencies, tracking progress over time, and understanding where resource consumption actually occurs across a value chain.

Structured sustainability data

Well-governed sustainability data has a few key properties.

It is preferably activity-based, grounded in actual transactions and consumption events, not estimated from financial spend.
It is consistently classified, each data point uses the same categories and units across locations, entities, and time periods.
It is traceable, you can follow the data back to its source.
And it is reusable, structured once, it can serve multiple reporting purposes, stakeholders, without being reformatted each time.

This last point matters more than it might seem. Organizations today face requests for sustainability data from customers, investors, auditors, and regulators. Often in different formats and at different levels of detail. Data that is well-structured from the point of collection can meet those requests without starting from scratch each time.

The Klappir approach

The Klappir Platform is built around a structured data model that classifies every resource transaction consistently, across locations, legal entities, and organizational boundaries. Rather than collecting data for one specific report or framework, the platform creates a governed data foundation that multiple outputs can draw from.

This approach also extends across organizations. When suppliers, partners, and subsidiaries use the same data structure, sustainability data can flow between them reliably, without custom templates, manual reconciliation, or data quality guesswork.

Sustainability data, at its most useful, is not a compliance artifact. It is a shared operational record of how resources move through an organization and its value chain.