Data management related to social and environmental risks and impacts, as well as the ongoing evaluation of company performance through indicators that ensure compliance with measures associated with these variables, has become essential. This is especially true as reporting is now an unavoidable standard in various industries.
Today, there are immense challenges for those responsible for managing information related to reporting. Gathering and systematizing data associated with social, environmental, and governance measures can be a difficult challenge to overcome. Often, there are "gray areas" where there are definitely no adequate systems to collect data, let alone cross-reference and analyze them for later reporting.
Moreover, when there are deviations in management systems, it becomes very complex to have timely information to be able to adopt the necessary corrective or repair measures to comply with ESG commitments.
Nowadays, generating information, valuing it, and making decisions based on this analysis is a requirement that is becoming increasingly common in global markets. This is the case in the United States and the European Union, which demand that large companies report more and better information on governance, and environmental and social management.
In this way, it is necessary to build management systems that incorporate Digital Transformation as a tool for creation, data collection, analysis, measurement, and compliance.
These systems must be built strategically to ensure that they are aligned with the company's vision and strategy, with the aim of becoming mobilizing levers, contributing to business optimization, and enabling sustainable management based on social and environmental pillars, and of course, growing the business.
In this way, the digitization of ESG variable management will allow companies to monitor and follow metrics, identify trends and patterns, evaluate the impact of sustainable practices on business results, report in real time, and effectively communicate to stakeholders. Obviously, it will also enable informed decision-making with different scenarios, risk maps, opportunities, all with solid data.
In conclusion, data analytics is a powerful tool to leverage ESG variables and reporting effectively and contribute to optimizing and making the business more profitable.
Explore the implications of integrating generative AI into data strategy, including its impact on business objectives, accessibility of new use cases, and ethical considerations. Learn how to align data strategy with business goals, unlock innovative use cases, and balance innovation with responsibility in the generative AI era.
Explore the importance of managing expectations in digital transformation. Learn about common expectation distortions and how to bridge the gap between high hopes and the realities of change. Effective communication and understanding complexities are key to success in digital transformation initiatives.
Learn why understanding your audience is crucial and how it's akin to having one quarterback for a winning team. Avoid the pitfall of trying to please everyone and create a message that's specific, relevant, and valuable.
