DEI Recruiting Strategy: Be Data-Driven and Set Targets
Being focused is critical to being effective. Being data-driven will bring about change faster.
Subscribe to Searchlight Blog
To close the diversity gap, recruiting must be data-driven
Data transparency and goal-setting can start a sea change around diversity. In 2014, a software engineer at Pinterest, Tracy Chou, invited anyone from any tech company to contribute to a publicly-hosted database on their employer's diversity numbers, particularly around gender. After looking at the hard numbers, trend-setting companies like Google, Facebook, and Microsoft were pressured to release diversity reports, and Tracy's own employer, Pinterest, shared their diversity goals publicly for the first time. Swaths of companies followed suit, creating a wave of higher standards of accountability.
But goal setting and target setting for DEI have always been controversial. Will setting goals and targets open companies up to accusations of reverse discrimination?
The thing is, establishing realistic, achievable, and relevant goals tied to accountability is the tried and true way of achieving business outcomes. While I appreciate the nuances of being in the people business, I believe that recruiting and HR should be more data-driven and benefit from the same data revolution as experienced by sales, marketing, customer success, etc.
What gets measured get managed. McKinsey and LeanIn's “Women in the Workplace 2015” found that companies that set gender targets from 2012 to 2015 saw growth in female representation, while those without formal targets lost ground. In the UK, the report found that a country that sets diversity targets for boards has 22% of boards that reflect the demographic composition of the country's labor force and population.
Goals and objectives are most impactful when they're aligned with the company's unique culture, business success, and current demographics. Here's how 3 different companies approached goal-setting around diversity.
Michael Kieran, Head of Talent of Tray.io, cuts through the noise by choosing “a main single target to aim at because this can change behavior faster.” His primary metric is the percentage of their employee base that is non-male and non-white. They measure progress towards this metric every quarter.
In Michael's words, measuring a single metric around non-male, non-white employees brings Tray.io closer to his ultimate goal of creating a jumping-off point for underrepresented groups. "I want to look back and be able to count how many people's careers launched at Tray because they became more hire-able in the future."
To craft a diversity target custom to your organization, Zapier’s Recruiting Operations Lead Supreet Hundal, recommends measuring your current demographic numbers. Data hygiene and talent analytics software may feel like a lot of overhead, but it's worth it. “Without data, it’s hard to know where we actually are against where we should be,” Supreet shared. “But with benchmarks, we can create targets and align on which groups to partner with, [and] which communities to invest money in.”
Zapier set a goal to match the diversity of the U.S. population based on the most recent census. As a global company, they chose the United States because it has one of the most robust census datasets in the world. Seeing their current numbers versus the target helped Zapier identify specific departments and levels within the company that needed the most help. Trying to impact the whole company at once can be pretty tough to move the needle.
John Foster, Chief People Officer of TrueCar, brought on a consultant to conduct quantitative and quantitative research on what diversity means for TrueCar. Besides helping TrueCar find the biggest areas of opportunity to set diversity goals, running the research study also helped for leadership readiness by helping managers understand where biases exist, improve manager buy-in around the need for diversity, and defining the problem and trends in the company today. A tip here when working with consultants is to keep them accountable to hard numbers wherever possible and strengthen their quantitative findings with context like sample size.