Services marketing: protecting capacity before maximising occupancy.

SUPPORTED DECISIONChoose a booking rule that maximises expected contribution under an explicit quality constraint, rather than uniform first-come-first-served occupancy.

Key distinctions

Three conditions before calculating.

01

Perishable capacity

The decision bears on a slot, a seat, a room or a specialist hour that disappears after the period. Average demand hides the peaks; capacity must be confronted with distributions by day, location and service class.

02

Marginal contribution

Two requests using the same hour can create different contributions and different risks. Net price, handling cost, no-show probability, actual duration and retention effect must all be brought back to the same capacity unit.

03

A quality reserve

The last points of occupancy are not free. They increase waiting, overtime, errors and rework. A reserve is rational when the expected cost of an overload exceeds the contribution of the flexible slots sacrificed.

Method

Building an economic and revisable booking rule

  1. 01Unify the capacity unit

    Express all demand in minutes, hours, room-nights or comparable slots; correct average durations by segment and include no-shows, cancellations and rework.

  2. 02Class the demand

    Group requests by expected contribution, urgency, flexibility and cost of refusal; the classes must be identifiable before allocation, without using a prohibited or unjustifiable characteristic.

  3. 03Protect the classes and the service

    Reserve volumes for high-value classes, then set a safety capacity derived from the cost of overload, and test several demand levels rather than a single central schedule.

  4. 04Revise with actual refusals

    Track refused demand, waiting time, overtime, contribution and repeat purchase; a rule that increases revenue but durably damages quality must be tightened.

ORIGINAL ASSET

Capacity protection by demand class

The chart compares a first-come allocation, an economic allocation and an allocation protected by five safety slots.

SCENARIO 01

First come

€6,650
Urgent20Scheduled50Flexible30
SCENARIO 02

Full allocation

€7,350
Urgent30Scheduled50Flexible20
SCENARIO 03

Protected capacity

€7,150
Urgent30Scheduled50Flexible15Reserve5

The reserve is rational if the expected overload cost exceeds €200 per week.

CSVDownload the service-capacity model↓
ILLUSTRATIVE EXAMPLE · SIMULATED DATA

Five safety slots cost €200 but protect the week

01 · SITUATION

A team has 100 slots. Demand is 32 urgent cases at €110 of contribution, 70 scheduled at €65 and 40 flexible at €40. First-come-first-served serves 20 urgent, 50 scheduled and 30 flexible.

02 · CALCULATION

First-come: 20 × 110 + 50 × 65 + 30 × 40 = €6,650. Full economic allocation: 30 × 110 + 50 × 65 + 20 × 40 = €7,350. With five safety slots: 30 × 110 + 50 × 65 + 15 × 40 = €7,150.

03 · DECISION

The reserve is adopted if the expected weekly cost of delays, rework and overtime exceeds €200. The rule still improves contribution by €500 against first-come-first-served.

Acceptance conditions

What must be true to act.

  1. 01

    Demand and contribution are expressed per homogeneous capacity unit.

  2. 02

    A priority rule can be applied before delivery and explained.

  3. 03

    The cost of overload is compared with the contribution of the sacrificed slots.

  4. 04

    Quality, refusals, lead time and repeat purchase are tracked alongside the occupancy rate.

Limits

What this analysis does not prove.

  • A high contribution does not justify illegitimate discrimination between customers.
  • Historical durations and no-shows can change after a price or journey modification.
  • A single-period model does not capture every loyalty and reputation effect.

References

Works cited.

  1. Talluri, K. T. & Van Ryzin, G. J. (2004), The Theory and Practice of Revenue Management.
  2. Campbell, D. & Frei, F. (2011), “Market Heterogeneity and Local Capacity Decisions in Services”, M&SOM, 13(1), 2–19.
  3. Lovelock, C. H. (1983), “Classifying Services to Gain Strategic Marketing Insights”, Journal of Marketing, 47(3), 9–20.