Turning a reservations count in spring into a September occupancy forecast, the two methods that bracket it, and what the gap to budget is worth.
Compare reservations with the same week of last year's cycle and project the rest of the cycle from last year's pickup, either scaled by the pace (multiplicative) or added on unchanged (additive). On an illustrative 500-bed scheme with 310 beds reserved against 335 a year earlier, the two methods give 449.7 and 461 beds, 89.9 to 92.2 per cent occupancy, against a 95 per cent budget: a shortfall of £117,634 to £212,317 of NOI for the year.
Worked in full in Student Housing Real Estate by Julian R. Sterling, with every figure reproduced in a free workbook.See the book on Amazon →
A student scheme sells its whole rent roll once a year for an academic year that starts in September, and whatever is unlet by the census in the autumn is usually empty until the next one. The only early evidence of how the year will land is the booking curve: how many beds are reserved by each week of the cycle, against the same week last year. Every asset manager reports the number; fewer turn it into an occupancy forecast with a range.
Mid-March, on an illustrative 500-bed scheme let on 51-week tenancies. Reservations are counted net of cancellations, on the same room-type mix in both years.
| Input | Value |
|---|---|
| Beds | 500 |
| Reserved this week | 310 |
| Reserved the same week last year | 335 |
| Let at last year's census | 486 |
| Budget occupancy | 95% |
| Bookings in the last four weeks, this year / last year | 38 / 41 |
| Achieved rent, 51 weeks | £190 a week |
| Management fee / variable cost per let bed | 4% / £900 |
1. The pace index. 310 / 335 = 0.925. The scheme is 7.5 per cent behind last year, at 62.0 per cent reserved against 67.0.
2. Two forecasts. Last year the scheme picked up 486 − 335 = 151 beds after this week.
Multiplicative: 310 × 486 / 335 = 449.7 beds, 89.9%
Additive: 310 + 151 = 461 beds, 92.2%
Excel: =Now*LY_Final/LY_Week and =Now+(LY_Final-LY_Week)
The multiplicative forecast assumes whatever is slowing bookings now, weaker demand, a new competitor, a rate card set too high, persists to the end of the cycle: the late pickup is 139.7 beds, 92.5 per cent of last year's. The additive one assumes only the early bookers are late and the rest of the market turns up as before. The truth is usually between them, and the 11.3 beds that separate them are worth £94,684 of NOI.
3. Which to believe. Look at the most recent weeks. Over the last four, the scheme took 38 bookings against 41 a year earlier, 92.7 per cent of last year's pace. Running the rest of the cycle at that rate gives 450.0 beds, 90.0 per cent, almost exactly the multiplicative figure. Recent weeks running at last year's pace or better would point to the additive one.
Each let bed contributes £9,690 of rent less the 4 per cent fee and £900 of variable cost: £8,402.4. One point of occupancy is 5 beds and £42,012 of NOI.
| Late pickup vs last year | Beds let | Occupancy | Beds vs budget of 475 | NOI vs budget, £ |
|---|---|---|---|---|
| 80% | 430.8 | 86.2% | -44.2 | -371,386 |
| 90% | 445.9 | 89.2% | -29.1 | -244,510 |
| 92.7% (recent weeks) | 450.0 | 90.0% | -25.0 | -210,253 |
| 100% | 461.0 | 92.2% | -14.0 | -117,634 |
| 110% | 476.1 | 95.2% | 1.1 | 9,243 |
To reach budget the scheme needs 165 more beds against last year's 151: the rest of the cycle has to run 9.3 per cent faster than last year's while it is currently running about 7 per cent slower. Unless something changes, the budget is gone, and March is when the response is cheapest, whether that is a targeted rate move on the room type that is behind, agents, or a nomination conversation. Whether a rate cut pays is its own calculation, in should a student housing scheme cut rent to fill beds.
Run the pace by room type, not only in total. A scheme 7.5 per cent behind overall is often level on cluster rooms and well behind on its most expensive studios, and that is a pricing problem on one line of the rate card, not a demand problem across the building.
Capitalising the shortfall. At a 5.5 per cent yield the multiplicative shortfall of £212,317 looks like £3,860,316 of value, but a bad September costs one year of NOI unless it signals a lasting fall in demand. The second mistake is comparing unlike counts: reservations gross of cancellations this year against net last year flatters the scheme; comparing calendar dates rather than the same week of the cycle, when the cycle has moved, can flatter or hide the gap.
The book follows the letting campaign from January to the November census, and the free workbook for this case includes a week-by-week letting tracker that projects RevPAB from the current booking pace.
Reservations to date compared with the same week of the previous letting cycle, on the same room-type mix and net of cancellations. On the illustrative 500-bed scheme, 310 beds reserved against 335 a year earlier is a pace index of 0.925, 7.5 per cent behind, with last year's cycle having finished at 486 beds, 97.2 per cent.
Let recent weeks decide. The multiplicative method assumes the scheme stays as far behind for the rest of the cycle (449.7 beds here); the additive method assumes late bookers turn up as last year (461 beds). If the last four weeks run at 38 bookings against 41, 92.7 per cent of last year, the evidence favours the multiplicative forecast of about 450 beds.
Budget beds less reservations to date, against last year's pickup from the same week. The illustrative scheme needs 165 more beds to reach 95 per cent against 151 picked up last year, so the rest of the cycle has to run 9.3 per cent faster than last year's while it is currently running slower.
This article is one calculation from Student Housing Real Estate. 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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