Time-to-Hire Analysis

Ask why a team's hiring drags and see exactly where candidates sit waiting, stage by stage, with the biggest bottleneck flagged, so you fix the real delay instead of blaming the whole process.

Für Recruiting Operations Talent Acquisition Leaders HR Business Partners Hiring Managers
Beispiel-Prompt für den Joy-Assistenten

Analyze our recruiting data and show where [department] hiring is slowest across the funnel, with the average days at each stage and where the biggest bottleneck is.

So kann es aussehen

Ein anschauliches Beispiel. Ihr Ergebnis hängt von Ihren Quellen, Daten und Anfragen ab.

Analyze our recruiting data and show where engineering hiring is slowest across the funnel, with the average days at each stage and where the biggest bottleneck is.

I pulled the 34 engineering requisitions from the last two quarters and measured the average days candidates spend at each stage, using the recruiting data connected to your workspace. The funnel takes 43 days end to end against your 35-day target, and one stage is doing most of the damage.

Sourcing and screening are healthy. The drag is in the middle of the funnel, once a candidate reaches the hiring team.

Average days at each stage: engineering roles, last two quarters

Application review5 days
Recruiter screen4 days
Hiring manager review12 days
Onsite loop7 days
Debrief to decision9 days
Offer to accept6 days

Hiring manager review is your bottleneck at 12 days. Candidates sit for nearly two weeks between the recruiter screen and the onsite, three times longer than the recruiter screen itself takes. Debrief to decision is the second offender at 9 days, so together those two hand-off stages account for 21 of the 43 days.

The early funnel isn't the problem: application review is 5 days and the recruiter screen is 4. If you got hiring-manager review down to the 5 days sourcing runs at, engineering's time-to-hire would land at 36 days, right on your target, without touching any other stage.

Want me to split the hiring-manager review stage by team so you can see whether a few managers are driving the delay?

From "hiring is slow" to the exact stage

Time-to-Hire Analysis reads your recruiting data at the moment you ask and breaks a team's hiring down stage by stage, showing the average days candidates spend at each step and flagging the one bottleneck doing the most damage.

  1. Connect your recruiting data

    Point Joy at your applicant-tracking data. It reads stage timestamps, requisitions, and candidate flow at the moment you ask.

  2. Describe the cut you need

    Name the team and the question: where is engineering hiring slowest across the funnel, and where's the biggest bottleneck?

  3. Review the chart and the read

    Joy returns average days per stage with a written takeaway that names the bottleneck and how far it sits above the others.

  4. Use it where you work

    Copy the stage breakdown and takeaway into your hiring review or your note to the leadership team. Joy diagnoses; you drive the fix.

  5. Make it one click for your team

    Save this ask as a custom command on the assistant your team already uses, so anyone can run it in one step.

Machen Sie es sich zu eigen

Stage-By-Stage View

Average days at every step from application to accepted offer, so the delay has an address.

Bottleneck Flag

Joy calls out the single stage costing the most time instead of leaving you to eyeball it.

Chart In The Answer

The funnel lands as a chart in the chat, with the same numbers carried into the written read.

Compare & Drill

Follow up to compare against other teams or split the slow stage by role or recruiter.

By Department

Run the same funnel for sales or support to see whether the bottleneck is team-specific or company-wide.

By Seniority

Compare time-to-hire for senior versus junior roles to see where the process stretches.

By Recruiter

Split a slow stage by recruiter to find where coaching or load-balancing would help.

Offer-Decline Review

Focus on the offer stage to see how long decisions take and where candidates drop.

Frequently Asked Questions

How does AI find hiring bottlenecks?

Joy reads the stage timestamps in your recruiting data and measures the average days candidates spend at each step. Instead of a single time-to-hire number, you get the whole funnel with the slowest stage flagged, so you know exactly where the delay lives.

Can I compare one team against another?

Yes. Run the funnel for engineering, then ask Joy to compare it against sales or support. That tells you whether a bottleneck like slow hiring-manager review is specific to one team or a company-wide pattern worth a process fix.

Does this change anything in our recruiting system?

No. It's read-only. Joy reads your recruiting data at the moment you ask and returns a chart and a written read in the chat. Any process change happens in your own workflow; you copy the findings into your hiring review.

Is this a live dashboard I have to maintain?

No. Each analysis is a point-in-time answer you request when you need it. There's no standing board to keep refreshed. You ask again whenever you want an updated read on the funnel.

What data does the analysis need?

It works from your applicant-tracking data: requisitions, the stage each candidate is in, and the timestamps for when they move between stages. From those it reconstructs the funnel and measures time at each step.

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Ready to know why your hiring is slow?

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