The short answer
Boards run on numbers, not gut feeling. Four KPIs make quality measurable: qualification rate, offer acceptance rate, twelve-month retention, and hiring manager satisfaction. Together, those four show whether you're attracting the right people - not just the available ones.
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Time-to-fill measures speed, not fit
Boards often ask: how fast are we filling vacancies? Understandable - empty seats cost money. Time-to-fill measures pace, not suitability. A vacancy filled in three weeks with the wrong person is an expensive success – the cost of a bad hire is often higher than the cost of a longer process.
Anyone wanting to demonstrate quality to the board reports on what happens after the hire. How many of the people brought on board make it through probation? How satisfied is the hiring manager three months later? Those questions are about the real outcome of recruitment – not the vacancy-filled number.
Four KPIs that actually measure quality
Qualification rate: of all candidates who respond, how many meet the pre-defined requirements? A low rate means you're reaching the wrong target group, or that the role's requirements weren't communicated clearly enough. A high rate means the pre-selection is well-matched to the actual position. Offer acceptance rate: how many offers made are accepted? A low score points to a mismatch in expectations – around salary, role, or culture – that you'd rather discover earlier in the process than at the offer stage.
Twelve-month retention: how many new employees are still with you after a year? This is the most direct measure of whether someone truly fits the role and the company. Hiring manager satisfaction: one structured question to the hiring manager three months after the start date. One question is enough to spot a pattern across multiple hires.
How to track this in practice
Fictional calculation example: a manufacturing company with fifteen vacancies per year decides to track four simple fields per hire – qualification rate from the pre-selection, whether the offer was accepted, whether the employee is still there after twelve months, and one rating question to the hiring manager. After eight hires, they see that the qualification rate is high but the offer acceptance rate is low. Conclusion: the pre-selection works, but expectations are being set wrong somewhere. That is actionable information for the board.
With Red Rocket, qualification data is captured automatically. Every candidate goes through an AI pre-selection via WhatsApp, where answers are tested against hard role requirements. The system can automatically indicate that someone does not qualify – without a recruiter stepping in. In the cockpit, you see each candidate's profile, answers, score, and optionally their CV. The follow-up questions and the final hiring decision stay with the employer.
From explanation to your practice
Source and editorial note
This article offers practical considerations. Examples are fictional, not client results or forecasts. The source below provides broader context, not evidence for a particular Red Rocket outcome.
Frequently asked questions
How do I establish a qualification rate if I don't use structured pre-selection?
Then it's hard to calculate after the fact. Qualification rate only works if you set the requirements in advance. Define those criteria first - then you can measure.
We hire infrequently. Does it still make sense to track twelve-month retention?
Yes, even at low volumes. Even five hires a year adds up to usable data over three years. Start measuring now, even if the report comes later.
