Skip to content

Women do well in referral programs overall, especially for smaller teams, but don’t fare well in the technical pipeline.

This is the last blog post in our three part series exploring referral programs. Atipica has analyzed referral data from the last year across all of our clients and we’ve found some actionable insights. These findings reflect that all of the companies we work with that are actively invested in creating a more diverse workforce.

In this post, we explore the experience of women candidates of all racial and ethnic backgrounds within the referral system. We found that women do well in referral programs overall, especially on smaller teams, but don’t fare well in the technical pipeline.

Key Findings from our data:

  1. Our companies have made a difference using Atipica — 50% of employees are women across the board.
  2. In general, of the candidates who were referred, women made up 40%of the referral pool.
  3. 75% of referrals for technical roles are men, while 25% were women.

Our key findings

The Stats on Referral Programs

Given that research shows networks are homogeneous, it’s clear that hiring more diverse teams will allow companies to access their diverse referral networks.

Referred candidates are often viewed as “higher quality” candidates than other inbound or sourced candidates. Our data shows that referred candidates are, on average, hired 1 day faster than non referred candidates.

Over 20% of all employees are hired via referrals.

A company referral program can be both vital and detrimental to intentional workforce development. The financial incentives via bonuses for referrals can promote homogeneity through nepotism and in network privilege. But if you have a separate referral program for underserved and underrepresented candidates via equitable hiring practices, then it can help shape the diversity of the teams.

Gender Representation widely varies by Department and Role

Our data shows that women outnumber men in many departments, including Client Success, Healthcare, HR, Legal, Product, and Sales. However, the most populous departments, Tech, Finance, and Management, are made up of more men. Across all these departments, the number of referred candidates is made up of significantly more men than women. The department with the most number of referred candidates is Tech, where we see the lowest number of women employees, and referred candidates compared to men.

In Client Success, Sales, and Tech, men make up three times more of the referral pool than women. The only departments where referred candidates who were women outnumbered men were in other operation roles.

Breakdown of percentage of women and men referred for technical roles, and non technical roles

Key Finding: Smaller teams make more impactful referrals for women

Why is there a disparity?

This lower number of women referrals versus employees echoes the findings from this LinkedIn study on application patterns by gender.

Their data shows that women candidates are less likely to ask for a referral, and are more likely to screen themselves out of a job.

Where our analysis goes deeper is that we see that the number of referrals are relatively the same for men and women except for the largest departments. However, the hire rates for all departments happened to be greater for women than men.

Just like with Black and Latinx referrals, women, including Black and Latinx women, who are referred are getting hired at a relatively high rate, it’s just a matter of ensuring that your current employees are actively referring women.

Our recommendation: how can you combat impostor syndrome while promoting inclusive referral programs?

Insights from Linkedin’s Gender Insight Report

Atipica: Business Intelligence for the Changing Workforce

There are ways to leverage referrals to strengthen your Diversity and Inclusion efforts.

Pinterest shared the results of an initiative from 2016, where they prompted employees to refer folks from underrepresented racial and gender backgrounds in particular. During the six week period, “they saw a 24 percent increase in the percent of women referred and a 55x increase in the percentage of candidates from underrepresented ethnic backgrounds.” We encourage our companies to research initiatives such as this.

So, what’s next?

Work with us to build equity into every step of your recruiting process. We work with company leaders, DEI strategists, and recruiting teams to maximize investments in inclusion strategies and people management processes.

We’re sharing this post as our COO attends the Grace Hopper Conference in Orlando, Florida. We applaud organizations like the Anita Borg Institute, who bring women together to form stronger networks, and in turn, better representation for women of all backgrounds across industry.

In our first blog post (What referrals tell us about how networks work for People of Color — Black, Latinx, and Asian candidates), we found that candidates who are referred by a current employee increase their chances of getting hired by 12x. That varied by demographic group, but was especially true for Black candidates. We also found some troubling trends in the experience of Asian candidates, which we outlined in our post Our Data Proves There’s a “Bamboo Doorway”… Not Just a Ceiling.


Data Source on Demographics

We honor self-reported data when available, yet our approach is to fill data gaps by using patent-pending modeling and proxies to identify trends that otherwise go unnoticed.

Average Percentage Breakdown of Referrals by Demographic across our Companies

We found the demographic breakdown of all candidates at each company whose source field in our customers’ Applicant Tracking System (ATS) is “Referral” separately, and then took the average percentage of each demographic.

Hire Rates of Referrals by Department

For each company separately, we looked at all candidates whose source field in their ATS was “Referral” or something similar, and found the percentage of those that were hired. Atipica did this calculation for each department at each company separately, and then took the median for each department.

Related posts