Back to basics: Human capital and labour market data (Part I of II)

Julia Asri Meigh, Head of ESG and Macro Research (New York)

Neudata Intelligence
Post feature

A misleading title perhaps, as the complexities, nuances and different varieties of employment-related datasets are anything but basic. We outline the current landscape of human capital and labour market data and summarise how traction has developed across the buyside.

THE CURRENT STATE OF EMPLOYMENT DATA – ALT DATA HYPE OR UNCRACKED CODE?

Quite possibly a rhetorical question, as cracking the alpha-generating employment data puzzle could turn out to be a continuous investigative journey into human capital nuances and financial outcomes.

Many studies have empirically proven that human capital factors impact financial performance. So far, however, buyside traction has not reflected the level of interest that these types of datasets have generated. We explore possible reasons for its modest levels of uptake and discuss:

  1. The different types of human capital and labour market datasets
  2. Alternative data sources and the competitive landscape
  3. Use cases across discretionary, systematic, ESG and macro investors
  4. Challenges and limitations across different investment strategies
  5. Different approaches that can help improve the value of these datasets

HUMAN CAPITAL AND LABOUR MARKET DATASET TYPES

We summarise the landscape of 6 different types of employment-related datasets:

  • Hiring activity data measures human capital inflows, most commonly through the aggregation of online job postings.
  • Employee profile data is primarily sourced from publicly available career pages, with LinkedIn being one of the most common and controversial sources of such. These datasets provide details on human capital inflows and outflows across companies and regions.
  • Talent data tracks the movement of ‘top talent,’ or highly skilled employees across companies. It differs slightly from employee profile data as it is focused on the career changes of talented individuals. Employee profile data, in contrast, tracks the aggregate level of staffing changes across different verticals – commonly expressed as employee headcount metrics and attrition rates.
  • Employee sentiment data measures the overall satisfaction and well-being of a workforce. These datasets are commonly extracted from crowdsourced employee review sites and human capital surveys.
  • Salary data can be extracted from a wide range of sources, which include online vacancies, surveys, crowdsourced sites, and government sources.
  • Labour relations data refers to the labour management practices of firms. While many of these datasets are aggregated from NGO and government databases, labour relations information can be found across a wide variety of sources.