With skill scores computed at the individual level, and linkages between users and companies (as well as between companies and industries), we compute company and industry proficiency skill level by taking a weighted average of individual skill scores. This means that learners in whose scores we are more confident count for more in their industry’s skill proficiency score than learners in whose scores we are less confident.
To compute aggregate scores in business, technology, and data science, we take the industry or company score average in each domain’s competency. Similarly, to get the overall industry or company score for use in correlations with third-party data, we take the average of that industry or company’s business, technology, and data science scores. This leads to industries and companies making balanced progress across all business, technology, and data skills that have higher overall scores versus those which have high proficiency in a couple skills and low proficiency in all others.
Note that the Industry Skills Report estimate may not reflect the average skill proficiency of all members within a company or industry because Coursera learners are not necessarily representative of all learners in a company or industry.