the research
Buyer instability
How often do buying committee members disappear during a live sales cycle? Nobody has published the answer. This is the working, with the definitions and the limitations attached.
the question
How often does a member of a buying committee leave, change role, or lose authority between the first qualified meeting and the signature - and what does that do to the deal?
why it matters
Forecast accuracy, coverage models, and every multithreading instruction in enterprise sales rest on the assumption that the people in the room will still be in the room.
When they are not, the loss is recorded as inertia rather than disruption, so the organisation learns nothing from it.
And the same instability is the largest untapped source of pipeline in the market: a new executive is a buying event, and almost nobody treats it as one.
what already exists
Stated honestly: no published study measures this. Three bodies of work sit adjacent to it and none of them answer it.
Gartner
Documents conflict and consensus difficulty inside buying groups. It describes friction between members, not the disappearance of members.
Forrester
Sizes buying groups and maps their roles. It tells you how many people are involved, not how stable their seats are.
Spencer Stuart
Tracks C-suite tenure, including the 4.1-year average CMO tenure. It measures the exit, not its effect on an open cycle.
the arithmetic, shown in full
Two sourced inputs, one multiplication
| Input A | 10.1 months | Average enterprise sales cycle. 6sense B2B Buyer Experience Report, n≈4,000 buying decisions. |
|---|---|---|
| Input B | 24% per year | Annual voluntary and involuntary turnover, sales and marketing roles. Pave compensation dataset, n=396,000+ employees. |
| Step 1 | 24% × (10.1 ÷ 12) = 20.2% | Probability that any one committee member leaves during the cycle. |
| Step 2 | (1 − 0.202)^10 = 10.5% | Probability that all ten members are still in seat at signature. |
| Result | ≈ 90% | Probability that at least one member of a ten-person committee is gone before you close. |
The model assumes independence between members and a uniform turnover rate across roles and seniority. Both assumptions are wrong in predictable directions, which is why the limitations section below exists.
my own findings
What the live cycles show
Working set: enterprise cycles across EMEA, 2024 to 2026, reviewed for committee composition at first qualified meeting and at close or closed-lost.
- Committee change
1 in 2
cycles longer than six months saw at least one named committee member change role or leave.
- Sponsor loss
1 in 5
cycles lost the person who opened the door, defined as the individual who accepted the first meeting.
- Value drift
-31%
median change in deal value on cycles where the economic buyer changed mid-cycle.
definitions, published alongside the figures
- Committee member: an individual on the buyer side who attended two or more meetings or was named in writing as a decision input.
- Change: a title change, a reporting-line change, or an exit confirmed by the buyer, public record, or the account team.
- Cycle: first qualified meeting to signature or closed-lost stamp, whichever came first.
- Value drift: signed annual contract value against the value at the point the economic buyer changed.
The worked example: a €380K deal at a communications platform, which lost 73% of its value in six weeks and still signed.
No client is named, no individual is named, and no workforce reduction is attributed to an identifiable company anywhere on this site.
why the CRM cannot see it
Zero. Not rare - zero.
Across 1,111 closed-lost deals, 76.5% carry a reason that hides the cause. "Champion fired or moved" was selected zero times. That is the argument for why this statistic does not exist anywhere: the field that would produce it was never in the picklist.
| Reason recorded | Share of 1,111 |
|---|---|
| Unassigned | 31.4% |
| Not the Right Time | 22.9% |
| Ghosted | 13.1% |
| No show | 9.1% |
| Budget | 8.6% |
| Lost to competitor | 7.7% |
| Other, specified | 7.2% |
| Champion fired or moved | 0.0% |
Single-company CRM export, 1,111 closed-lost opportunities, 2024 to 2026. Shares rounded to one decimal.
where the evidence actually lives
- Meeting transcripts. Attendance across a cycle is a record of committee composition that nobody reads as one.
- The ghosted cohort. Deals that went silent, re-checked months later against the contact's current role.
- Email. Bounces and auto-replies date a departure more precisely than any CRM field.
- Public news. Restructuring and appointment announcements, matched to open cycles.
limitations
What this cannot support
- The 90% figure is arithmetic on two published inputs, not an observation. It inherits every weakness of both.
- Turnover is not uniform across roles or seniority, and committee departures are not independent events - a restructuring removes several seats at once.
- My own findings come from one company's cycles in four European markets. They are not a market sample and should not be quoted as one.
- Committee composition was reconstructed from meeting and email records, so quiet participants are undercounted.
- Departures are easier to detect for senior and public roles, which biases the figures upward at the top of the committee.
what I am doing next
Widening the working set beyond one company, formalising the departure-detection method so it can be run by someone else, and publishing the reason-code audit as a template.
If you carry a number and can look at your own closed-lost reasons, I want your figures. Aggregate only, anonymised, credited or not as you prefer.
citation
Storm, Sara. "Buyer instability: committee turnover during live enterprise sales cycles." sarastorm.io, 2026. https://sarastorm.io/research
Journalists and analysts: quote the arithmetic with both inputs attributed, and quote my own findings as single-company figures.
Method PDF - available on request until the next revision is published