Hiring Funnel Maths

Scenario

Example organisation: a manager must hire four engineers by the end of the quarter. He opens the roles and waits. Ten weeks later he has one offer accepted; interviewers are exhausted and the team's delivery has dropped because of interview load.

What you see on the team

• Hiring targets missed every quarter.
• Interviewers overloaded at random times, sometimes four interviews a week.
• No idea which stage loses candidates.
• Hiring treated as something that happens to the team.

The common mistake

Treating hiring as opening a role and hoping, instead of a pipeline you plan backwards from the target, using conversion rates at each stage.

Why it happens

Hiring has long delays and low conversion rates that are easy to underestimate: many applicants for each hire, and interviewer time is the hidden cost. Without numbers, managers start too late and can't tell whether the problem is sourcing, screening, interviews or closing.

The playbook

Work backwards from the target, with your own conversion rates (or industry-typical ones to start):

hires_needed = 4
# Conversion from each stage to the next (example rates - use your own data)
stages = [
    ("applicants / sourced", 0.15),   # -> recruiter screen
    ("recruiter screen", 0.50),       # -> technical screen
    ("technical screen", 0.40),       # -> onsite loop
    ("onsite loop", 0.35),            # -> offer
    ("offer", 0.75),                  # -> accepted
]
needed = float(hires_needed)
plan = []
for name, rate in reversed(stages):
    needed = needed / rate
    plan.append((name, needed))
for name, n in reversed(plan):
    print(f"{name:22} {n:6.0f}")

onsites = dict(plan)["onsite loop"]
tech_screens = dict(plan)["technical screen"]
hours = onsites * 5 * 1.5 + tech_screens * 1.25   # 5 interviews x 1.5 h incl. notes; screens 1.25 h
print(f"\ninterviewer hours this quarter: {hours:.0f} "
      f"(~{hours / 12:.0f} h/week across the panel for 12 weeks)")

applicants / sourced      508
recruiter screen           76
technical screen           38
onsite loop                15
offer                       5

interviewer hours this quarter: 162 (~13 h/week across the panel for 12 weeks)

Track conversion at every stage and compare with your plan. A leak tells you what to fix:

Plan interviewer capacity as part of team capacity, and spread load across a trained panel.

Start early: from opening a role to a new hire's first day often takes months once notice periods are included.

What to say

To your director, at the start of the quarter:

"To make four hires, our funnel says we need about 500 applicants, 38 technical screens and 15 onsite loops — roughly 160 interviewer-hours this quarter, about 13 a week across the panel. I'd like a dedicated sourcer for six weeks and to reduce the team's roadmap slightly this quarter to cover interviews."

Trade-offs

• Industry-typical rates are only a starting point; your own data matters most.
• High interview load slows delivery; budget for it explicitly rather than hoping it fits.
• Lowering the bar to fill roles costs more later than a delayed hire.

Signals it's working

• Hiring plans are made backwards from targets, with numbers.
• Conversion per stage is known, and leaks are fixed one at a time.
• Interviewer load is planned and fair.
• Hiring targets are met more often, without bar changes.

Key points

• Plan hiring backwards: hires → offers → onsites → screens → applicants.
• Track conversion per stage to find and fix leaks.
• Budget interviewer hours as team capacity.
• Start early; hiring plus notice periods takes months.