Hiring Difficulty Methodology

Overview

The Hiring Difficulty score helps users quickly compare how challenging it is to hire specific talent across different sets of regions. It's currently available in the US and Global Talent Analyst, specifically in the reports Geography Explorer and Global Dashboard. These reports are viewable at the Country or Metropolitan levels.

The score ranges from 0 (least difficult) to 5 (most difficult) and is meant to help users quickly compare and highlight regions where the talent is relatively abundant, less sought after, and more affordable—a combination that typically signals lower hiring difficulty.

Methodology

The score is calculated using a weighted combination of three labor market factors.

• Supply (primary factor). This metric adapts based on your search parameters and whether you are in the US or Global. In the US, it's defined by government-reported workforce counts. In Global, it's defined using Lightcast’s modeled workforce estimates (see here for more detail). In both, if your search includes filters where workforce data isn’t available (e.g., you include a skill filter), the score uses the number of relevant online profiles as a second-best proxy.
• Demand (secondary factor). This metric is measured by the number of unique job postings over the past 12 months that match the rest of your search parameters (e.g., region, occupation, skill, etc.). It's the most straightforward of the three factors and is consistent whether in the US or Global.
• Compensation (tertiary factor). Like Supply, this metric also adapts based on your search parameters and whether you are in the US or Global. In the US, it's defined by either the government-reported median salary or Lightcast’s compensation model (see here for more details), depending on whether or not a skill or keyword has been inputted. In Global, it uses advertised salaries from job postings. If fewer than 50 postings include salary data, or if the region has N/A due to unknown salary, the factor is neutralized to prevent skewing the score one way or another due to insignificant data.