← HR Metrics·Talent Acquisition
Diversity Hire Rate
Percentage of diverse candidates hired
How it’s computed
COUNT(diverse_hires) / COUNT(total_hires)
What the evidence shows
Evidence (effect sizes, priors, validity) is syncing from Principia.
What this metric can show you
Diversity Hire Rate can tell roughly 26 pre-built stories — each a designed scene the data either confirms or it doesn’t. Bring your numbers and the Story Finder runs every one of these shapes against them.
specific to talent acquisition
New hires are ramping slower than they used to
onboarding · T1
No villain stage — the funnel is the funnel
ta-funnel · T1
On this pace, you miss the plan
ta-funnel · T1
The hiring engine is stalling
ta-funnel · T1
The leak has an address
ta-funnel · T1
There's one job family we can't close
offer-competitiveness · T1
You're losing them at the close
ta-funnel · T1
Your biggest source isn't your best
quality-of-hire · T1
universal shapes — any single metric can take these
A few large values are doing the talking
any focus · T1
A one-time event, not a trend
any focus · T1
It doesn't track — the premise is false
any focus · T1
It's concentrated — one group stands apart
any focus · T1
Scenes are pre-built; your data is the toggle. Browse the full deck or watch one play end-to-end in The Quiet Exodus.
Run it on your data
This metric is computed in the People Analytics Toolbox on your own numbers. See pricing — posted, no quotes.
sources: toolbox:metrics-catalog
What the literature says
The measurement literature behind this signal — sourced, so you can defend it.
“HBR found that companies whose leaders exhibit at least three inherent and three acquired diversity traits, out-innovate and out-perform others. Employees at these companies are 45 percent likelier to report that their firm’s market share grew over the previous year and 70…”
— Predictive HR Analyticsmatch 60%
“Workplace diversity is about hiring and retaining employees of different characteristics and walks of life. Companies can increase its diversity in terms of ethnicity, age, gender, education, socioeconomic background, sexual orientation, and religious beliefs. Research have…”
— People Analytics Text Mining with Rmatch 59%
“No woman who works in our company is a mother and we have realized [this segment may] be very important for us” Rennella says. The lesson? Hire the customer you want to attract and let them teach you how they’d like to be sold to. (4) Earnings Before Interest and Taxes (EBIT)…”
— People Analytics Text Mining with Rmatch 59%
Resources: Predictive HR Analytics · People Analytics Text Mining with R