How TIME and Statista Determined Arabia's Top Companies of 2026

—Photo-illustration by TIME; Elijah-Lovkoff—Getty Images The research project " Arabia’s Top Companies 2026 " is a comprehensive analysis conducted to identify the top performing companies in the GCC countries (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, United Arab Emirates).

The study is based on three primary dimensions: Employee Satisfaction, Revenue Growth and Sustainability Transparency (ESG).

Methodology The first dimension, Employee Satisfaction, was investigated based on survey data from a large sample of over 20,000 employees in the region.

The evaluation encompassed direct recommendations of verified employees as well as indirect evaluations from industry peers.

The second dimension, Revenue Growth, was assessed using data from Statista’s revenue database, which contains company growth data for the last three years.

The companies had to meet certain criteria to be considered for the evaluation, including generating a revenue of at least $50 million USD in 2025.

Additionally, the companies had to demonstrate positive revenue growth in the last three years.

Both relative and absolute growth were considered in the evaluation.

The third dimension, Sustainability Transparency, was evaluated based on ESG data among standardized KPIs from Statista’s ESG Database and targeted data research.

To formulate a comprehensive ESG index, multiple Key Performance Indicators were collected.

For the environmental evaluation, this included the 2024 carbon emissions intensity and reduction rate compared to 2022, as well as the Carbon Disclosure Project (CDP) score.

The social dimension assessed the share of women on the board of directors and the existence of a human rights policy.

The governance dimension evaluated whether a company had a Corporate Social Responsibility (CSR) report adhering to the Global Reporting Initiative (GRI) guidelines and a compliance or anti-corruption guideline.

Once the data was collected and evaluated, it was consolidated and weighted within a scoring model.