The 90-day ramp assumption is not derived from data. It is inherited from convention, inserted into financial models because every other model uses it, and never tested against the actual cohort performance of the business being acquired. It is the most expensive unchallenged assumption in growth-stage SaaS investing.

A typical growth-stage SaaS business models new hire productivity at 90 days to first independent close, with full quota attainment by month six. These numbers rarely come from an analysis of what the company's own hires have historically achieved. They come from industry benchmarks derived from averages across businesses with different products, different markets, and different onboarding architectures.

The actual cohort data tells a different story almost every time. In the assets SLAM has assessed, the median time to first autonomous close ranges from five to nine months. The median time to full quota attainment for hires who survive past month six is closer to twelve months than six.

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The ramp assumption in the model is the ramp for the survivors, calculated generously. That is not the ramp for the next cohort.

Request a cohort analysis of every sales hire in the last twenty-four months. For each hire, record: start date, date of first independent close, date of first quarter at full quota attainment, and whether they are still employed. Do not accept an aggregate average. Demand the individual cohort data.

Two things will usually become visible immediately. First, the headline ramp number is calculated from the survivors, excluding hires who left before reaching productivity, which inflates the average materially. Second, the definition of "independent close" often includes deals where a manager was heavily involved but not formally credited, compressing the apparent ramp further.

Ramp Fiction is not usually a deliberate misrepresentation. It is motivated arithmetic. The CRO presenting a 90-day ramp to the board is reporting what they believe is achievable rather than what the evidence shows has been achieved.

The incentive to believe it is obvious: a shorter ramp assumption produces a more aggressive revenue model and a cleaner acquisition thesis. Nobody is rewarded in the investment process for producing a longer ramp assumption.

The calculation is straightforward. Take the number of planned new hires in the post-acquisition growth plan. Multiply by the average ACV per rep per quarter. Multiply by the gap between the modelled ramp and the observed median ramp, expressed in quarters. That is the Year 1 revenue shortfall attributable to Ramp Fiction alone.

In a mid-market SaaS business planning to hire ten new salespeople post-close at an ACV of £150k per rep per quarter, a four-month ramp gap produces a Year 1 shortfall of approximately £1.5M to £2M. This number is not in the investment model. It should be.

Risk Classification: Execution Risk (primary) / Process Risk (secondary)
Behaviour Observed
The post-acquisition headcount plan is built on a ramp assumption that has never been validated against the company's own historical cohort data, and that excludes early attrition from its calculation.
Why This Happens
The 90-day convention is inherited from industry norms, not derived from evidence. The incentive structure of the investment process rewards aggressive ramp assumptions.
Investment Risk
Year 1 revenue shortfall attributable to ramp gap is calculable and frequently material. In SLAM assessments, the observed median ramp is typically two to four months longer than the modelled assumption.
Implication for the Investment Committee
Request individual-level cohort data for all hires in the last twenty-four months, including those who left before reaching productivity. Recalculate the ramp assumption from observed median, not reported average. Adjust the Year 1 revenue model accordingly.
Valuation Risk HIGH
Forecast Risk MEDIUM
Execution Risk HIGH