A successor fund's pipeline weighted two ways, the probability of each milestone, and where the gap between them sits.
A probability-weighted fundraising pipeline multiplies each prospective commitment by the probability that it closes at its current stage, then adds them up. The calculation is trivial; the probabilities are not. On a $550m pipeline for a $400m fund, the team's own stage probabilities expect $308.3m, while the conversion rates the same firm achieved on its last fundraise expect $210.0m, and a first close of $200m falls from a near certainty to a coin toss.
Worked in full in Private Equity Investor Relations by Julian R. Sterling, with every figure reproduced in a free workbook.See the book on Amazon →
Investor relations teams are asked for one number every Monday: how much are we going to raise. The gross pipeline answers a different question, and the weighted pipeline answers the right question only if the weights come from evidence. The arithmetic below shows how much rides on that choice.
| Stage | Investors | Amount, $m | Team estimate | Last fundraise |
|---|---|---|---|---|
| Re-up, verbal | 2 | 100.0 | 95% | 90% |
| Re-up, in diligence | 2 | 80.0 | 80% | 70% |
| New, in diligence | 2 | 115.0 | 60% | 35% |
| New, second meeting | 3 | 110.0 | 40% | 15% |
| New, first meeting | 3 | 145.0 | 25% | 5% |
| Gross pipeline | 12 | 550.0 |
Gross, the pipeline is 137.5 per cent of target. That figure is the one that tends to appear in a board pack, and it means nothing on its own.
Expected commitments = Σ amounti × probabilitystage(i)
In Excel, with amounts in C and a stage lookup table in G:H:
=SUMPRODUCT(C2:C13,XLOOKUP(B2:B13,G2:G6,H2:H6))
| Stage | Amount | On team estimates | On last fundraise |
|---|---|---|---|
| Re-up, verbal | 100.0 | 95.00 | 90.00 |
| Re-up, in diligence | 80.0 | 64.00 | 56.00 |
| New, in diligence | 115.0 | 69.00 | 40.25 |
| New, second meeting | 110.0 | 44.00 | 16.50 |
| New, first meeting | 145.0 | 36.25 | 7.25 |
| Expected | 550.0 | 308.25 | 210.00 |
| As % of target | 77.1% | 52.5% |
The two columns differ by $98.25m, and 86.8 per cent of the difference sits in new investors: $85.25m against $13.0m on re-ups. Teams are roughly right about their existing investors, whom they know, and optimistic about new ones, whom they have met once.
An expected value is an average, and a fund does not close on an average. Treat each investor as an independent yes or no and enumerate all 4,096 combinations of the twelve, and you get the full distribution of the total. That gives the probability of reaching each milestone, which is what a general partner needs to plan a first close date and the management company's budget.
| Commitments of at least | On team estimates | On last fundraise |
|---|---|---|
| $200m, first close | 94.1% | 55.9% |
| $250m | 80.3% | 28.2% |
| $300m | 55.3% | 7.4% |
| $400m, target | 10.5% | 0.1% |
On the team's numbers the first close is all but certain and the target is a one-in-ten outcome. On the firm's own history, the first close is a coin toss and the target is out of reach with this pipeline. The median outcome is $305m on the first view and $210m on the second; the tenth percentile is $220m against $130m. The standard deviation of the total, $70.2m and $61.0m, is more than a fifth of the expected value either way: twelve investors are too few for the averages to settle.
Independence understates both tails. Investors are not independent: a weak quarter, a denominator problem across pensions or a key-person event moves many of them at once. Correlation widens the distribution and fattens both tails. The chance of missing the first close is higher than the enumeration says, and because the $400m target sits far above the expected total, the chance of reaching it is higher too: the enumerated 10.5 and 0.1 per cent understate it.
On historical rates the fund is $190.0m short of target. Filling that from new first meetings at a 5 per cent conversion would need $3,800m of new first-meeting pipeline. From second meetings at 15 per cent it would need $1,266.7m. Neither is a plan. The arithmetic says the effort belongs on the investors already in diligence, where a single conversion moves the total most.
The ranking follows from the gap column of the register. The largest new investor in diligence, $75.0m, is carried at $45.0m by the team and $26.25m on history: an $18.75m difference on one name, the largest in the book. That is where to spend the next month, and the first question to ask that investor is what still stands between diligence and an allocation.
Reporting the gross pipeline, or weighting it with stage probabilities nobody has tested. A team that never revisits its weights against what actually closed will carry a 25 per cent first-meeting probability for years, because nothing in the report forces the comparison. Keep a closed-funnel record: at each stage, how many investors entered and how many committed. After one fundraise that record is a better probability table than any instinct, and it is the one an investment committee will believe.
The fourteen-investor version of this case, with the exact distribution and the ranking of investors by what a stage of progress is worth, is in the free workbook for this case. For the timing side of the same problem, see does a first close cover the management company's costs, and for the record you will be selling, six ways to state the same fund's return.
The ones the firm actually achieved, stage by stage, on its last fundraise, kept in a closed-funnel record. Illustratively, in the worked case re-ups in diligence converted at 70 per cent and new investors after a first meeting at 5 per cent, against team estimates of 80 and 25 per cent. The difference moves expected commitments by $98.25m.
No. It is an average across outcomes. A fund closes on one outcome, so the useful output is the probability of each milestone. In the worked case the expected total on historical rates is $210.0m, yet the chance of reaching a $200m first close is only 55.9 per cent and the chance of the $400m target is 0.1 per cent.
Because the team knows its existing investors and has met new ones only once or twice. In the worked case re-ups are overestimated by $13.0m and new investors by $85.25m, 86.8 per cent of the total gap. The single largest gap, $18.75m, is one new investor in diligence.
The pipeline case extends chapters 10 and 17 of Private Equity Investor Relations, and is worked in the free companion files. The book takes the same case from first principles to the decision, chapter by chapter, and every figure it prints is a live formula in the free companion workbooks.
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