Hotel pickup and forecasting: a booking-pace method

Gross pickup, net pickup and booking pace

Some pickup reports count new bookings made since the last report. For inventory control, also calculate the net change: rooms on the books (OTB) in the recent snapshot minus OTB in the earlier one, for the same stay date. It captures new bookings, cancellations and stay changes. PMS treatment of room-type changes and group blocks may vary; verify it first.

In this fictional week, 13 new room nights and three cancellations produce net pickup of ten. The books move from 28 to 38. Booking pace follows this pattern at several lead times — intervals from snapshot to arrival — rather than treating today’s OTB as the full story.

Find genuinely comparable historical dates

For past Saturdays, recover both the D-14 OTB snapshot and final actual rooms sold. Match weekday, season, capacity and selling conditions. Flag an exceptional trade fair, unusual group block, renovation or major policy change before using the date as a reference.

Suppose four illustrative Saturdays gained +12, +14, +16 and +14 rooms from D-14 to arrival. The median is +14. It is a starting assumption, not a promise. A current group at risk of cancelling needs its own adjustment rather than being hidden in the average.

Turn the assumption into a rooms forecast

Here +14 is the overall future net gain from D-14 to arrival: later sales after their own cancellations, less future losses on the 38 rooms already on the books. The forecast is 38 OTB + 14 = 52 rooms; do not deduct existing-booking cancellations a second time. Against 60 available rooms, this is 86.7% forecast occupancy. Twenty-two rooms remain unbooked at D-14; +14 is not necessarily fourteen gross new bookings.

The handbook also shows the components explicitly: forecast rooms = current OTB − expected future losses on current OTB + further sales net of their own future cancellations. For example, four losses from the 38 OTB rooms and eighteen further net sales give 38 − 4 + 18 = 52. Those fictional components explain the +14 rather than being added to it.

Add a cautious and a high case when cancellation or event demand could materially change. Keep the working forecast within sellable capacity and revisit it at the next snapshot.

Every figure here is fictional and illustrates a method, not an industry benchmark.

A D-30, D-14 and D-7 tracking view

Archive snapshots instead of overwriting them. The intermediate D-21 count of 28 explains the move from 18 OTB at D-30 to 38 at D-14. Suppose D-7 OTB reaches 45. If comparable dates then gained +6, +7, +8 and +7 between D-7 and arrival, a median +7 supports a revised 52-room forecast. The number is unchanged, but its basis has been checked again.

Use the tracking file as a training exercise

Rebuild it from a PMS export or spreadsheet

Keep one record per stay date and snapshot date: the date a booking was made is not the stay night being analysed. Track usable capacity, the metric denominator, room OTB, OTB room revenue, cancellations, options and group notes separately. Net pickup is the difference between matching OTB snapshots. Add the overall future net-gain assumption and keep budget in its own column.

Check duplicates, multi-night stays and unconfirmed group blocks. Do not add group rooms already counted in OTB a second time; add only expected volume not yet recorded and keep options separate. A reservation-level export is not necessarily a room-night-by-stay-date export.

Use the forecast — and learn from its error

At 52 expected rooms, the central case leaves eight rooms likely unsold. Check visibility, restrictions and late-booking segments. If the high case approaches 60, review low-contribution offers. ADR and acquisition cost still matter; a volume forecast is not a rate instruction.

If the final actual is 50 rooms, the D-14 forecast was two rooms high. Keep the original estimate, identify cancellations or missing demand and revise the method for the next comparable dates. Do not rewrite the +14 assumption after the fact.

See a forecast used in a rate decision