Annual utilisation hides the month that breaks the team. The capacity model built by month, the hours over an 85 per cent ceiling, and what moving the audit work buys.
Size a fund operations team on its peak month, not on its annual average. A six-person team with 9,900 practical hours a year and 7,290 hours of work is at a comfortable 73.6 per cent across the year, and at 122.4 per cent in April, when the first-quarter close and the year-end audit land together. Averaging the year hides 185.0 hours of work that no one is there to do.
Worked in full in The Private Markets COO by Julian R. Sterling, with every figure reproduced in a free workbook.See the book on Amazon →
Most capacity conversations in a management company start with a headcount ratio or an annual hours estimate, and both are annual numbers. The work is not. Quarter-end closes, the audit, investor reporting and capital events cluster, and the cluster is where errors, late reports and resignations come from. The calculation is a monthly profile of demand set against a monthly capacity, with a ceiling below 100 per cent.
| Input | Value |
|---|---|
| People | 6 |
| Practical hours a person a year, after leave, training and management | 1,650 |
| Capacity a month (6 × 1,650 ÷ 12) | 825.0 |
| Recurring work a month: cash, payments, investor queries, data | 430 |
| Capital events a month, averaged | 40 |
| Quarter-end close, in January, April, July and October | 260 |
| Year-end audit and financial statements: February, March, April | 110 / 220 / 280 |
| Planning ceiling, share of practical capacity | 85% |
Monthly utilisation = (recurring + events + close + audit) ÷ monthly capacity
April: (430 + 40 + 260 + 280) ÷ 825.0 = 1,010 ÷ 825.0 = 122.4%
Year: 7,290 ÷ 9,900 = 73.6%
In Excel, with demand by month in B2:M2 and capacity in B3:M3: =B2/B3 across, and =SUM(B2:M2)/SUM(B3:M3) for the year.
| Month | Demand, hours | Utilisation |
|---|---|---|
| January | 730 | 88.5% |
| February | 580 | 70.3% |
| March | 690 | 83.6% |
| April | 1,010 | 122.4% |
| May, June, August, September, November, December | 470 | 57.0% |
| July and October | 730 | 88.5% |
| Year | 7,290 | 73.6% |
Six months sit at 57.0 per cent. Four quarter-end months exceed the 85 per cent ceiling, and one exceeds full capacity by 185.0 hours. Against the ceiling of 701.25 hours a month, April is 308.8 hours over; January, July and October are 28.8 hours over each. Across the year the team runs 395.2 hours above the ceiling, all of them in close months.
Three responses are available, and they do very different things to the profile.
The sequence matters: move the work first, then price what is left. Moving work is free and permanent; temporary support for a residual peak is cheap; a hire is the right answer only when the quiet months themselves are rising towards the ceiling.
| Recurring hours a month | Annual utilisation | April | July, a close without audit |
|---|---|---|---|
| 350 | 63.9% | 112.7% | 78.8% |
| 390 | 68.8% | 117.6% | 83.6% |
| 430 | 73.6% | 122.4% | 88.5% |
| 470 | 78.5% | 127.3% | 93.3% |
Even at 63.9 per cent across the year, April is over full capacity. The ordinary close months show how fast the problem is spreading: July is at 78.8 per cent with 350 recurring hours, crosses the 85 per cent ceiling between 390 and 430, and reaches 93.3 per cent at 470. That excess is still small enough to move or buy. Each extra fund, investor reporting template or currency adds to the recurring line, and the recurring line lifts every month at once; when the quiet months themselves approach the ceiling, the problem has stopped being seasonal and a hire is the answer.
The common mistake is to report capacity as one annual percentage. A board that sees 73.6 per cent concludes that the team has room for another fund. A team that lives through 122.4 per cent every April concludes that it does not. Both are reading the same model; only one is reading the month. The second mistake is to treat the peak as an effort problem, solved by longer hours. Work done at 122 per cent of capacity is the work that produces late capital account statements and NAV adjustments, and those cost more than the hours saved.
Report two numbers, not one. Annual utilisation and peak-month utilisation, side by side, with the hours above the ceiling. The gap between 73.6 and 122.4 is the management decision.
The capacity model under five scenarios, with the scorecard for the administrator that shares the peak, is in the free workbook for this case. What a cheaper administrator does to the same April is worked in how much a cheaper fund administrator actually saves.
There is no regulatory figure; it is a policy choice. A common discipline is to plan to a ceiling below full practical capacity, such as 85 per cent, to leave room for incidents and ad hoc requests. In the worked case the team is at 73.6 per cent over the year, under that ceiling, yet four months exceed it and April is at 122.4 per cent.
Not necessarily. In the worked case a seventh person raises monthly capacity from 825.0 to 962.5 hours, but April still needs 1,010, so the team stays at 104.9 per cent in its peak month while annual utilisation falls to 63.1 per cent. The hire buys slack in eight quiet months to cover one busy one.
Multiply the number of people by the hours each can realistically give to the work in a year, after leave, training and management time, and spread it by month. At 1,650 hours a person, six people give 9,900 hours a year or 825.0 a month. Demand is then built by activity and month, and compared month by month.
This article is one calculation from The Private Markets COO. 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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