Koya Talent — Operations Register
Last 30 days
Jun 1, 2026 – Jun 30, 2026
People Ops
Active headcount30
New hires5
Exits1
Attrition rate3.3%
Time to hire29.4 days
Offer acceptance time21.5 days
Headcount by department
Engineering7
Delivery6
People Ops6
Customer Success6
Sales5
Sales
Revenue won$34,200
Pipeline value$40,040
Total leads9
Win rate60.0%
Cost per lead$2,800
Marketing spend$25,200
Revenue by lead source
Partner13350
Inbound11400
Outbound9450
Project Delivery
Active projects0
Completed0
Overdue0
Over budget0
Budget variance$0
On-time completion ratenot available — no completion date in source data
The organization demonstrated strong sales performance with a 60% win rate and $34.2K revenue in June, supported by healthy hiring activity (5 new hires, 4.5% offer acceptance). However, project delivery operations appear dormant with zero active, started, or completed projects, raising concerns about execution capacity. Multiple data quality issues across all functions warrant immediate attention before relying on these metrics for strategic decisions.
Operational risks
- Project delivery pipeline is completely inactive (0 projects active, started, or completed) despite healthy sales pipeline, indicating potential execution or resourcing bottleneck
- Cost per lead ($2,800) is exceptionally high relative to average revenue per won deal (~$11,400), suggesting marketing efficiency issues or deal size variability
- Low application volume (5 applications for 5 hires) indicates potential recruiting funnel constraints; offer acceptance rate of 80% masks insufficient candidate generation
- Data quality issues in sales records (4 missing/invalid fields) and project delivery (2 missing fields) undermine confidence in KPI accuracy and decision-making reliability
- Attrition rate of 3.3% is low but with only 30 headcount, single-digit exit events have outsized percentage impact
Recommended actions
- Investigate root cause of project delivery inactivity immediately—verify whether projects are being tracked correctly, delayed pre-delivery, or reflect genuine execution gaps that could impact revenue realization
- Audit sales data quality: resolve 4 missing/invalid records and validate pipeline_value ($40.04K) and revenue_won ($34.2K) calculations before relying on sales forecasts
- Review marketing channel mix and attribution—partner channel generating highest revenue ($13.35K) while outbound cost per lead is $2,800; optimize spend allocation
- Expand recruiting funnel: increase application volume through broader sourcing given strong conversion rates and headcount needs across departments
- Implement data validation rules to prevent incomplete records in people_ops (1 missing status), sales (lead_source, deal_amount, dates), and project_delivery (actual_cost, due_date) going forward
- Cross-reference active_projects (0) against delivery team headcount (6 people) to clarify whether capacity is available or project tracking is broken
Data quality warnings
- Project delivery metrics are unreliable: all activity metrics are zero with no supporting context; on_time_completion_rate and average_delay_days are null, making trend analysis impossible
- Sales data has 4 quality issues across 9 total leads (44% error rate on records): 1 deal_amount missing, 1 lead_source missing, 1 invalid date, 1 status missing—validate revenue figures before reporting
- People ops missing 1 record status; verify this doesn't represent an incomplete hire or exit event that would distort headcount_by_department totals
- Project delivery missing actual_cost and due_date on 1 record each; unable to validate budget_variance calculation ($0) as reliable
- Null values for on_time_completion_rate_pct and average_delay_days in project delivery indicate either no historical data or calculation errors; clarify data collection methodology