A time-to-hire analysis report measures average days between each stage of the hiring funnel: application to screen, screen to interview, interview to offer, offer to start. It identifies which stages are adding the most time and whether that time correlates with better hires or just slower decisions. At aidowith.me, the Hiring Dashboard route covers this in 11 steps over about 1 hour 15 minutes. You'll export candidate data from your ATS, calculate stage-level duration averages with AI-written formulas, and generate a report that shows the top 3 bottlenecks with their business impact. The route includes a benchmark comparison: AI compares your funnel stage times to industry averages so you know which delays are normal and which are outliers worth fixing. The final report gives hiring managers a specific, role-level view of where their processes add unnecessary time.
Last updated: April 2026
The Problem and the Fix
Without a route
- You know your time-to-hire is 'too long' but you don't know which stage is causing the delay or why
- Hiring managers blame HR for slow processes, but your ATS data isn't formatted in a way that's easy to analyze
- You hired 20 people last quarter but can't tell leadership which roles took the longest or why
With aidowith.me
- Calculate average time at each pipeline stage and identify the top 3 bottlenecks in one 75-minute session
- Generate a report that shows hiring managers which stages their roles are slowest at, with specific numbers
- Compare your stage times to industry benchmarks so you know which delays are worth addressing and which are normal
Who Builds This With AI
HR & People Ops
Job descriptions, interview kits, onboarding docs built fast.
Managers & Leads
Reports, presentations, and team comms handled faster.
Founders
Move fast on pitches, pages, research. AI as your first hire.
How It Works
Export and clean ATS data
Export candidate progression data from your ATS (Greenhouse, Lever, Workday, or a spreadsheet). AI writes formulas to calculate days between each stage event from date columns in your export.
Calculate stage-level averages and identify outliers
AI generates a summary table with average days per stage, broken down by role, department, or hiring manager. It flags any stage averaging more than 5 days above the benchmark as a bottleneck.
Write the bottleneck report with recommendations
AI writes a 3-section report: top 3 bottlenecks with time data, root cause hypotheses for each, and 2 recommended process changes per bottleneck. You review and add context before sharing with leadership.
Analyze Your Hiring Funnel Today
Follow the 11-step Hiring Dashboard route at aidowith.me and build a time-to-hire analysis report with bottleneck findings in about 75 minutes.
Start This Route →What You Walk Away With
Export and clean ATS data
Calculate stage-level averages and identify outliers
Write the bottleneck report with recommendations
Compare your stage times to industry benchmarks so you know which delays are worth addressing and which are normal
"We discovered that 40% of our time-to-hire was in the 'waiting for hiring manager feedback' stage. That one data point changed how we set expectations with managers across every open role."- Recruiting operations manager, 200-person company
Questions
Export candidate stage dates from your ATS, use AI-generated formulas to calculate days between stages, build a summary table with stage averages and outliers, then have AI write the bottleneck report with recommendations. The aidowith.me Hiring Dashboard route covers all 11 steps and includes formula templates for common ATS export formats.
Industry benchmarks vary: individual contributor roles average 28-35 days, manager roles average 40-50 days, and executive searches average 60-90 days. The route includes benchmark ranges for 5 role categories so you can compare your stage times against a relevant baseline rather than a generic average that may not reflect your hiring function or industry.
At minimum: candidate ID, role, application date, date moved to each stage, and hire or rejection date. Most ATS tools can export this as a CSV. If your ATS doesn't include stage transition dates, the route shows you how to approximate stage times from calendar invite or email timestamp data as a fallback.