Our client, a publicly-listed American multinational hospitality company, manages properties in over 40 countries under various different prestigious brands. They face the complex challenge of measuring and managing their carbon emissions data. This data is increasingly important for corporate transparency, investor relations, and potential future regulatory compliance with bodies like the SEC.
To address these mounting demands, the company needed an efficient, reliable, and scalable solution for gathering and analyzing data from their extensive network. The solution also needed to be flexible enough to adapt to changing climate disclosure requirements, particularly in the United States.
To address these challenges, the company turned to Minimum's Carbon Accounting Software. Minimum’s platform centralized, streamlined and automated the collection and analysis of the company's emissions data, allowing them to track and report emissions dynamically.
Minimum’s rigorous recording of activity data and calculation methodologies ensures full compliance and auditability, instilling confidence in the accuracy and integrity of the company's climate data.
Minimum's EDP empowered the company to conduct granular analysis of emission data by region, brand, and individual site, thereby identifying clear areas for sustainability improvement. Consequently, the company was able to craft targeted sustainability initiatives that aligned with their emission reduction goals.
As a comprehensive tool for sustainability reporting and performance management, Minimum's EDP enables companies in the hospitality sector to monitor energy usage, track carbon emissions, and scrutinize energy management. By setting sustainability goals, tracking progress, and communicating efforts, companies can reduce their carbon footprint, contribute to a more sustainable future, and improve their reputation with environmentally conscious stakeholders.
The company plans to leverage Minimum in expanding the scope of emissions sources analyzed, and continue improving data granularity and accuracy.
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