What it is
Fall-off rate is the percentage of candidates who accept a job offer, verbally or in writing, and then never actually start, or leave within the first few days without formal notice. It differs from a decline, where a candidate says no before accepting anything, and from ordinary early turnover, where someone starts and leaves weeks or months later for reasons the employer can at least see coming. A fall-off is defined by the gap between a yes that felt final and a start date that never happens, or happens and unravels almost immediately.
Agencies usually track it as a rate: fall-offs as a share of placements made, or of offers accepted, over a given period, often split by client, role type or consultant. Some desks separate it into two flavours: a no-start, where the candidate never appears on day one at all, and an early fall-off, where they show up and quit inside the first week or two. Both count against the same number, because both mean the placement fee, the guarantee period and the client relationship are all exposed at once.
An accepted offer is a forecast, not a placement, until someone actually turns up on day one.
Why it matters
Fall-off is more common, and more expensive, than most desks assume. Research tracking real placement data at scale has found genuine no-call, no-shows sitting in the low single digits of accepted offers, a floor rather than a ceiling, since broader candidate surveys on reneging after acceptance report figures many times higher once softer forms of pulling out are included. What the data agrees on is timing: close to half of all candidate ghosting happens specifically in the window between offer acceptance and first day, not earlier in the process and not after someone has actually started.
That timing is what makes fall-off so costly. By the point a candidate accepts, most of the cost of the hire, the sourcing, the interviews, the offer negotiation, the client management, has already been spent, so a fall-off wastes work that is largely unrecoverable rather than work that can simply be redirected. For the agency it also triggers exactly the exposure a guarantee period exists to cover: a replacement search or a rebate, on a role the client already considered filled. Track fall-off rate over time and by client, and it becomes a leading indicator of where guarantee terms, candidate vetting or start-date follow-up need tightening, not just a number to report after the fact.
How boilr handles it
boilr treats an accepted offer as a live risk, not a closed deal. The placement sits in the BD pipeline as placed but pending until the start date actually passes, the same logic it applies to counter-offer risk, rather than being marked done the moment a candidate says yes. Any signal suggesting the candidate has not actually resigned, is still active on their current employer's systems, or shows a job-change update pointing somewhere else, gets flagged so the consultant can check in before the client finds out the hard way.
Every fall-off that does happen is recorded in the Company Brain against the client, the role and the consultant, so a pattern, a specific client whose offers keep collapsing, a role type that consistently falls through, becomes visible across the whole desk rather than staying anecdotal. Over time that history feeds back into how the next placement at a similar account is handled: a tighter follow-up cadence between acceptance and start, a longer guarantee period where the risk warrants it, or simply a heads-up before the CV goes out.
