Iceberg Data Lab - Climate Positive Impact
Data category
Environmental data
The data offers solutions for:
- Environmental impact analysis and insight
- Investment decisions and portfolio insight
Who are the data users?
- Corporates
- Investors
- Financial institutions
Brief description of the data offering
The Positive Impact is a tool that allows to measure companies’ contribution to transition regarding climate. It is made up of three pillars which measure and quantify positive impacts on climate due to improved performance and compensation actions carried out by companies. These indicators quantify the positive impact that these management decisions have on climate.
The three pillars of this indicator are: reduced, avoided or compensated impacts.
Where and how do you source your data?
We use only public sources to source our data and each line is updated at least once a year.
What is the cost for your data offering?
The cost depends on the number of lines subscribed and the type of analysis required, as it is tailored to our clients’ needs.
What are the key attributes that differentiates the data you offer?
Iceberg Data Lab’s metrics are based on a robust scientific methodology constantly improved by a research team and reviewed by a scientific committee. As we do not have any business or advisory relationships with issuers, there will be no conflict of interests. Besides, the model is unified for climate and biodiversity to align with the regulator’s demands.
The model reports a full coverage of scopes 1, 2, 3, upstream and downstream. Covering all scopes is important as it can be misleading to only report on a companies’ direct emissions. For example, in some cases, scope 3 downstream can represent 90% of a companies’ total emissions. A data quality level is also reported to show the level of modelled and reported data.
We have an unbeatable granularity level covering all sectors and over 2,300 products and services. Additionally, we enable to appraise different products and services in the same sector and, therefore, identifying contributors to transition. Our model is also scalable to other environmental impact measures (i.e. waste, water, impact on human health) and can easily be derived to produce new indicators.
