The first step is always to ensure that there is a data management plan in place before the data is collected. Having a data management plan will outline what is being collected, where the data is coming from, how it is being collected and stored, the basis for any calculations, and the purpose and audience for the data collection. This should be agreed upon before data collection starts and updated as and when any change is necessary during the process. This plan can provide the basis for resolving any conflicts once the data is collected. Then, all parties must keep an open mind when conflicts do arise will allow all parties to see and understand everyone's perspectives.

Comparing data is an important step and adds to the reliability of the data disclosed, as well as observing the framework adopted to ensure its correct application. In addition to data, it is necessary to compare and monitor the company's evolution in order to ensure that its goals and intentions have been achieved or that there has been a change in strategy.

Align perspectives on sustainability data by establishing clear metrics, leveraging transparent data visualization, and facilitating open discussions. Focus on shared goals and rely on industry standards to resolve differences.

I believe aligning perspectives on conflicting sustainability data requires a transparent and inclusive approach. First, one must standardize data collection and interpretation using globally recognized frameworks to ensure consistency. Engaging all stakeholders—employees, partners, and communities—in open dialogues fosters trust and shared understanding. I organize regular workshops and expert consultations for bridging knowledge gaps and addressing biases. Finally, I set clear, measurable goals with progress tracking for ensuring alignment. For me, sustainability is a shared responsibility, and collaboration is the key to turning data into impactful actions.

The fact that there are contradictory interpretations of sustainability data indicates that there is a lack of standardization in the way data and indicators are collected. This is why it is necessary to manage a common Framework such as a standard or the Sustainable Development Goals, to articulate them in an information management system managing transparency, Documentation of the processes, assumptions and methodologies used, accompanied by periodic review and a regular monitoring and updating process to adjust the approach according to new findings or changes in the environment.

For instance, converging perspectives on conflicting sustainability information, facilitating dialogue between stakeholders, with a priority on common ground on objectives. Clear and transparent communication with relevant data should be used, biases recognized and corrected, and the validity of sources should be checked. Proactively foster collaborative effort to establish and rank actionable insights as well as to guide decision making for long-term sustainability objectives.

High-quality data analysis in sustainability reporting is crucial to avoid greenwashing. Data verification ensure the accuracy and reliability of sustainability reports by cross-referencing internal records with external sources like satellite imagery, emissions databases, or third-party reports.⁣ Using frameworks like the GHG Protocol, GRI, or TCFD makes companies follow a standard and avoids conflicts of interpretation, which require detailed and verifiable metrics.

To align perspectives on conflicting sustainability data, start by identifying shared goals and values among stakeholders. Facilitate open discussions to clarify assumptions and data sources, ensuring transparency. Use trusted, independent third-party assessments or tools to validate data and bridge differences. Present insights visually to make complex data more accessible, and focus on actionable steps that align with the overarching sustainability objectives. Collaboration and ongoing dialogue are key to resolving conflicts and achieving consensus.