Koya Talent — Operations Register

Year to date

Jan 1, 2026Jun 30, 2026

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People Ops

Active headcount30
New hires30
Exits3
Attrition rate10.0%
Time to hire29.3 days
Offer acceptance time18.5 days
Headcount by department
Engineering7
Delivery6
People Ops6
Customer Success6
Sales5

Sales

Revenue won$189,450
Pipeline value$186,940
Total leads49
Win rate60.0%
Cost per lead$2,359
Marketing spend$115,600
Revenue by lead source
Partner43700
Inbound42100
Outbound40500
Referral31750
Event31400

Project Delivery

Active projects2
Completed19
Overdue2
Over budget11
Budget variance$10
On-time completion ratenot available — no completion date in source data
Delivery load by team
AI Apps6
Automation6
Data5
Client Ops5

YTD performance shows strong sales execution (60% win rate, $189.5K revenue) and excellent project delivery efficiency (99.6% on-budget completion across 19 projects). Recruitment is robust with 30 new hires and controlled attrition at 10%. However, data quality issues across all functions and emerging operational constraints (2 overdue projects, 1 blocked project, 11 over-budget projects despite positive variance) warrant attention.

Operational risks

  • Project delivery variance: 11 of 22 projects reported as over-budget despite 0% aggregate variance suggests cost tracking inconsistencies or individual project cost control issues
  • Delivery backlog: 2 overdue projects and 1 blocked project indicate potential execution or resource constraints affecting timeline performance
  • Recruitment sustainability: 10% attrition rate paired with 30 YTD new hires suggests potential retention challenges; replacement-driven hiring may mask underlying engagement issues
  • Sales pipeline conversion: 2 closed-lost deals against 18 closed-won indicates inconsistent sales execution (60% win rate is healthy but closed-lost tracking suggests deal qualification gaps)
  • Data integrity: Multiple missing and invalid records across sales module (4 issues) could obscure true performance metrics and lead to incorrect decision-making

Recommended actions

  • Conduct project-level cost reconciliation to identify why 11 projects are individually over-budget when aggregate variance is near zero; establish cost control checkpoints
  • Investigate the 2 overdue projects and 1 blocked project to identify root causes (resource constraints, scope creep, external dependencies) and implement recovery plans
  • Implement exit interviews and engagement surveys to understand 10% attrition drivers; compare attrition by department given relatively even headcount distribution
  • Audit sales deal qualification process, particularly for closed-lost deals, and establish improved lead scoring to improve conversion consistency
  • Enforce data validation rules across people_ops, sales, and project_delivery systems; remediate missing records (especially sales deal_amount and lead_source data)
  • Monitor time-to-hire trend (29.3 days) against industry benchmarks and internal capacity to ensure recruitment velocity remains sustainable

Data quality warnings

  • Sales module contains 4 data quality issues including missing deal_amount and lead_source values—revenue attribution and lead source ROI analysis may be unreliable
  • Project delivery missing critical timeline data (1 due_date unrecorded) prevents accurate on-time completion rate calculation; on_time_completion_rate_pct and average_delay_days are null
  • People ops has 1 missing record status which may understate actual hiring volume or exit counts depending on context
  • Project delivery cost tracking shows discrepancy: 11 over-budget projects but aggregate budget variance near zero (0.02%), suggesting data aggregation or cost coding issues
  • Data quality issues span entire reporting period (YTD Jan-Jun); recommend immediate validation of source data and ETL processes before next period close