Overview of Sustainability Trends and Data Challenges
Sustainability has become a strategic imperative for organizations, but companies are lacking in effectively utilizing sustainability data to drive their sustainability strategies.
Key challenges include:
Siloed data sets and manual spreadsheets leading to quality gaps and inconsistencies
Limited insights due to missing context and difficulty synthesizing the full picture
Difficulty in connecting sustainability data to drive change and impact the bottom line or product innovation
AWS Sustainability Data Fabric
AWS provides a Sustainability Data Fabric solution framework to help organizations integrate and manage sustainability data:
Collect and connect data from diverse sources
Purpose-built data management capabilities for sustainability (e.g., quality checks, cataloging, processing)
Integration with other systems and AWS services
Flexibility and extensibility to add more use cases over time
Role of AI in Sustainability
AWS provides AI-driven capabilities to help with:
Visualization and natural language generation to tell a stronger sustainability story
Productivity improvements by automating data collection and insight generation
Innovation by using AI to assist in decision-making and product development
Cargill Ocean Transportation's Journey
Cargill Ocean Transportation, a leading freight trading organization, is on a journey to decarbonize its operations by 2050.
Key elements of their approach:
Defined clear goals and a path to achieve them, investigating new technologies
Implemented data-driven decision making, leveraging energy efficiency and carbon intensity data
Automated processes to reduce manual effort and improve data quality and frequency
Developed an AI chatbot to provide self-service access to sustainability data
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