Institution Theme Category Discussion Questions
  • Neuberger Berman
  • Social
  • Social & Human Capital
Company Year Market Source Link
Not Disclosed 2019 N/A Website

For the third straight year, in 2019 a U.S. telecommunications conglomerate was named to LinkedIn’s Top Companies list, ranking 15th. In the same year, Fortune ranked it third in its list of “Best Big Companies to Work For.” In 2018 the firm was named a Leading Disability Employer by the National Organization on Disability.
At the same time, however, MSCI was pointing to its “multiple labor controversies” and scoring it a 2.8 on Labor Management—much lower than the sector average of 6.2.
Whom to believe? It is tempting to trust the professional rating agencies over the awards. But we know there are often severe discrepancies between different agencies’ ratings of the same companies.
Alternative data can give us a new, proprietary perspective environmental, social and governance (ESG) factors, many of which are not standardized or covered in traditional company reporting. These challenges are particularly acute when it comes to “softer” social factors such as human capital management.
One source of qualitative data is the ratings employees leave on the recruitment website Glassdoor.
A more objective, qualitative source is active job postings. We can now collect almost three-quarters of all the job advertisements in the U.S. When we compare the proportion of a company’s workforce that is represented by currently live job postings with subsequent growth in Selling, General & Administrative expenses, we believe it gives us an insight into how many of those job postings relate to genuine expansion of employment and how many are due to churning of the same role. A high rate of churn implies that employees don’t believe the firm is a good place to work.
When we scraped Glassdoor ratings for the telecommunications sector, we found the company ranking well above average. Its job-postings churn ratio also compared well with its peers, putting it seventh out of 22 companies.
Case studies like this show how alternative data and data science techniques can help resolve discrepancies in traditional ESG data, and contribute to a more holistic view of a company’s exposure to ESG risks.

Related Details

  • Category'
  • N/A
  • Resolution
  • N/A
  • Vote
  • N/A
  • Rationale
  • N/A
  • Details
  • N/A