Our Company Schema contains many different fields to represent the number of employees associated with the company record. These fields are calculated using different methods, which can result in different counts for the same company.
As of v25.0, we've made some improvements to keep counts consistent across the following fields:
- Sum of values for
- The last month in
- Sum of values in the last month in
There can still be some discrepancies, the most common are explained below.
This information comes from a user-selected dropdown value obtained from the company’s primary social media profile, such as LinkedIn or Facebook. Sometimes this range is far from the real count of employees, however the function of this field is to preserve the raw selected value as selected on those platforms.
Data Build Timing
employee_count_by_country aggregations are generated using all available data at the time of our monthly builds. Typically we begin building our monthly release data mid-month, targeting a launch at the beginning of the upcoming month. As a result these fields will represent work history data collected up until roughly two weeks prior to the release of our monthly dataset.
In comparison, while the
employee_count_by_month_by_role aggregations are generated at the same time, those fields will only display data where we have a complete month of work history represented (each
“yyyy-mm” period represents the headcount as of the final day of the period), as a result the totals may differ slightly.
A quick note: In previous dataset versions we had included that final “partial data” month in the time series fields. We’ve decided to remove this stub period due to user feedback.
Multiple Job Levels
employee_count_by_month_by_level field presents a summary of the
job_title_levels, which is itself a “one-to-many” field highlighting the seniority levels for a person’s job title. If a person role has multiple levels (ex: the job title “founder and ceo” would have tags for both "cxo" and "owner"), that person is counted multiple times (once for each level).
Comparisons to LinkedIn Employee Counts
Because we generate our counts bottom-up as aggregations of the underlying person record data associated with company record, you can expect a slight discrepancy between PDL’s employee counts and those represented on LinkedIn company pages.
Specifically, we’ve incorporated additional profile cleaning and data validation steps that we believe make our counts more accurate representations of the true workforces of represented companies. For example, favorable discrepancies can emerge from a reduced rate of person profile and work experience duplication, stricter fuzzy matching on work experience to corresponding canonical companies, and separate accounting for subsidiary company records for corporate conglomerates.
Updated about 2 months ago