The Gap → The Opportunity
The problem was straightforward: Our recruiting reports lived in spreadsheets scattered across drives. Leadership couldn't see hiring velocity in real time, and we had no unified view of funnel health or capacity. Forecasting was guesswork, and by the time we spotted a problem, we'd already missed our plan.
The opportunity was already in front of us: Greenhouse had robust reporting capabilities we weren't leveraging. Team Ohana tracked our headcount plan. Lattice captured early performance signals. I saw a path to connecting these tools into a decision-friendly recruiting lens — no new vendors, no complex data engineering, just smart use of what we had.
How I Built It (With the Tools We Had)
- Started with Greenhouse standard reports and built prototype dashboards in Sheets to validate what mattered most to leadership
- Migrated high-value views into Tableau for drill-down capability and real-time refresh; kept simpler snapshots in Greenhouse native dashboards
- Synced recruiting progress to our headcount plan in Team Ohana weekly, creating a single source of truth for delivery
- Established a weekly operating rhythm with talent acquisition and hiring managers to review metrics, flag blockers, and adjust course
Operating Framework
Funnel Performance
Stage-by-stage conversion tracking to identify where candidates drop off and where we're investing interview time ineffectively.
Velocity & Aging
Time-to-fill metrics (median and p75) by role family, plus a real-time view of aging requisitions that need attention.
Quality Signal
Post-hire proxy metrics linking scorecard rigor to 90-day manager feedback and time-to-ramp, creating a quality feedback loop.
Capacity & Plan Tracking
Weekly view of hiring plan delivery by function, with pipeline health indicators to forecast where we'll land.
Dashboard Gallery
Funnel Performance by Function
Hiring Plan vs. Progress
Time-to-Fill & Aging Requisitions
Source Effectiveness & Speed
Quality Signal Loop (Post-Hire Proxy)
Insights → Decisions
TTF spikes in Staff SWE roles — we rebalanced interview load and pre-booked panels, reducing median by 11 days.
Offer declines clustered in GTM — we adjusted base ranges and tightened speed-to-offer, lifting acceptance 9 pp.
Screen → HM drop-off widened to 47% — we retrained hiring managers on rubrics and calibrated role expectations.
Referrals yielded +11 pp higher acceptance — we launched a focused referral sprint with incentives and manager outreach.
Aging reqs >45 days concentrated in R&D — we added dedicated outbound sourcing and enforced panel SLAs.
Interviewer feedback SLA improved to 78% ≤48h through reminder nudges and load balancing across panels.
Quality loop data validated our structured interview approach — rubric scores ≥4.0 correlated with 90-day success.
Business Impact
41
Median TTF (days)
from 62 days
85%
Offer Acceptance
from 71%
94%
Plan Delivery
against headcount plan
+18%
Throughput
candidates/week
−29%
Aging Reqs >45d
improved velocity
Weekly
Decision Speed
exec view adopted
KPI Sample Dataset
Sample KPI Snapshot (Greenhouse Summary Example)
| Week Start | Function | Open Reqs | Median TTF | p75 TTF | Offers | Accepts | Accept % | Cands/Wk | SLA ≤48h % |
|---|---|---|---|---|---|---|---|---|---|
| 2024-10-07 | R&D | 18 | 48d | 63d | 7 | 6 | 85.7% | 52 | 81% |
| 2024-10-07 | GTM | 12 | 35d | 47d | 5 | 4 | 80.0% | 38 | 76% |
| 2024-10-07 | CS/PS | 5 | 32d | 42d | 3 | 3 | 100% | 24 | 79% |
| 2024-10-07 | G&A | 2 | 29d | 38d | 1 | 1 | 100% | 12 | 73% |
| 2024-09-30 | R&D | 20 | 51d | 68d | 6 | 5 | 83.3% | 48 | 78% |
| 2024-09-30 | GTM | 14 | 38d | 51d | 4 | 3 | 75.0% | 35 | 74% |
| 2024-09-23 | R&D | 22 | 54d | 71d | 5 | 4 | 80.0% | 44 | 75% |
| 2024-09-16 | GTM | 13 | 36d | 49d | 6 | 5 | 83.3% | 41 | 77% |
| 2024-08-26 | R&D | 24 | 58d | 74d | 4 | 3 | 75.0% | 39 | 71% |
| 2024-08-19 | CS/PS | 7 | 35d | 46d | 2 | 2 | 100% | 21 | 76% |
| 2024-08-12 | GTM | 15 | 42d | 56d | 5 | 3 | 60.0% | 37 | 69% |
| 2024-07-29 | R&D | 26 | 62d | 79d | 3 | 2 | 66.7% | 36 | 68% |
Illustrative data for portfolio demonstration.
