Energy Performance & Consumption

Extensive dataset on the world companies’ energy performance, including energy consumption breakdown by source and renewability along with consumption intensity.

Overview

This dataset is part of Datacie’s ESG collection covering climate and other environment-related indicators. Access this comprehensive compilation of companies’ energy performance data to understand, measure, and make informed decisions about climate-related risks, regulatory requirements (e.g., SFDR, EU Taxonomy, TCFD), corporate engagements, and impact investing.

Company Coverage

Company coverage

6'500+ Companies

Geographical Coverage

Coverage

Worldwide

Data History

History

Back to 2014

As reported / Standardized

Reporting type

As Reported

Most-Recent / As Reported

View

Include both views

Data Frequency

Frequency

Annual

Reporting Lag

Lag

Monthly

Delivery Format

Delivery status

Excel, API, FTP & Datafeed

Use Cases & Benefits

Asset managers -create unique and differentiated ESG portfolio strategies that align with your investors’ preferences and your firm’s positioning while generating better returns.

Commercial Banks -explain how your recommendations meet your clients’ sustainability preferences by providing them easy-to-understand, relevant ESG metrics in your communications.

Consultants -support the development of your clients’ ESG policies and methodologies with high-quality data & market insights.

Corporates -benchmark your company against your peers in terms of sustainability and understand the data that your investors use to build a fair view of your company.

Fund managers -create funds that reflect your policies on the integration of sustainability risks & impacts in your investment decision-making process or advisory services.

Institutional managers -comply with ESG regulatory requirements and provide confidence to your clients that require greater transparency around climate change.

Risk managers -derive climate risk-mitigating strategies by adjusting your exposure to certain companies and sectors.

Engaged investors -build persuasive arguments to engage effectively with corporates to raise awareness about their insufficient level of disclosures or non-compliance with key disclosure frameworks.

Researchers -empower your research with the industry’s broadest ESG content set and convince decision-makers with empirical facts and findings.

Sample data

Free sample data is available to all Datacie’s users. The sample includes the most-recently reported annual data for the following companies: Airbus SE, Accenture plc, Zalando SE, UBS Group AG and General Motors Company.

Column definition

company name

Official name of the company.
Ex: Accenture plc

reporting date

Date for which the information has been publicly available in official disclosures.
Ex: 02.2021

fiscal year

Fiscal year over which the data are measured.
Ex: 2018

total energy consumption

Total energy consumption within the organization including purchased and self-generated electricity, heating, cooling, and steam as well as fuel consumption in GWh coming from renewable non-fossil sources, namely wind, solar (solar thermal and solar photovoltaic) and geothermal energy, ambient energy, tide, wave and other ocean energy, hydropower, biomass, landfill gas, sewage treatment plant gas, and biogas.
Ex: 4'054.85 GWh

total energy consumption renewable

Total energy consumption within the organization including purchased and self-generated electricity, heating, cooling, and steam as well as fuel consumption in GWh coming from renewable non-fossil sources, namely wind, solar (solar thermal and solar photovoltaic) and geothermal energy, ambient energy, tide, wave and other ocean energy, hydropower, biomass, landfill gas, sewage treatment plant gas, and biogas.
Ex: 101.61 GWh

distilled fuel

Total energy consumption within the organization including purchased and self-generated electricity, heating, cooling, and steam as well as fuel consumption in GWh coming from distilled fuel from petroleum or crude oil, such as gasoline, diesel fuel, jet fuel, and heating oil.
Ex: 1'500 GWh

natural gas

Total energy consumption within the organization including purchased and self-generated electricity, heating, cooling, and steam as well as fuel consumption in GWh coming from natural gas such as compressed natural gas (CNG), and liquefied natural gas (LNG).
Ex: 13.59 GWh

nuclear

Total energy consumption within the organization including purchased and self-generated electricity, heating, cooling, and steam as well as fuel consumption in GWh coming from nuclear power.
Ex: 20.056 GWh

coal

Total energy consumption within the organization including purchased and self-generated electricity, heating, cooling, and steam as well as fuel consumption in GWh coming from coal.
Ex: 51.884 GWh

energy consumption intensity

Total energy consumption within the organization per million of EUR of revenue as a proxy of the energy performance per unit of output.
Ex: 0.057 GWh/€m

isin

International Securities Identification Number of the company’s most traded share classes, notes or bonds.

ticker

Ticker or trading symbol.
Ex: UBS

country

Country in which the securities are listed.
Ex: CH

exchange

Name of the exchange in which the securities are listed.
Ex: SIX Swiss Exchange

Methodology

Datacie’s Energy Performance & Consumption data solution is built from all available data sources that contain ESG information on publicly listed companies, including self-reported filings, CSR reports, press releases, corporate websites & other corporate disclosures.
As a trusted data partner, Datacie is committed to delivering competitive and error-free data products to its clients. To this end, we are leveraging our proprietary data extraction technology to capture most of the reported energy performance and consumption data from unstructured sources (websites, documents, media releases...) automatically. By construction, our technology predicts diverse quality indicators for each data point acquired; our ESG experts then review these quality indicators and carry thorough qualitative investigations of the extracted information, guaranteeing that our energy performance and consumption compilations are fully accurate and that no crucial items are missed.
After inception, the entire dataset is audited and evaluated for trustworthiness. Every data entry passes through hundreds of quality checks that automatically identify outliers and potentially misreported observations. Additional manual checks are performed on low-confident data points, ensuring that the final data product is free from poor-quality observations.
Note that all the energy measures that have been reported in other units than per gigawatt-hour (examples: joules or multiples) were standardized in gigawatt-hour when a conversion rule was disclosed or when conversion factors exist; otherwise, they were discarded from the dataset to ensure comparability across time and entities.
The dataset is currently available as reported. Datacie has created an NLP-based classification algorithm (leveraging semantic similarity & self-attention mechanisms) to map the “As Reported” breakdown of non-renewable energy sources into 5 classes when data is available: distilled fuel, natural gas, fuels extracted from natural gas processing and petroleum refining, coal, and nuclear power.

Status & Delivery

The Energy Performance & Consumption dataset is currently being compiled and prepared for our clients’ preferred usage; additional coverage (temporal and company-wise) and existing/new columns can be modified/added on demand. Contact us and be among the first to benefit from this data solution to inform your climate-related decisions with the highest quality, cost-effective data of the market.

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