Jump directly into a structured baseline challenge
Launch Motel Business Simulator with 46 coastal rooms, weekend getaway pricing, and seasonal occupancy shifts.
Quick answer
Beachside Motel starts with a relatively large inventory, high base rate, strong room quality, and a seasonal demand problem: peak weekends can look excellent while quieter weekdays leave rooms, payroll, and maintenance capacity underused. Establish a full-month baseline before reacting to one busy weekend. Test one rate, promotion, channel, staffing, or room-quality decision at a time, and keep it only when monthly profit and cash improve without sacrificing condition, service, or reviews.
Know the exact starting model
These are simplified simulator assumptions, not real lodging forecasts. They create a repeatable seasonal-capacity case.
| Starting input | Beachside Motel value | Decision implication |
|---|---|---|
| Setup value | $190,000 | A large opening commitment makes cash discipline important before expansion or heavy promotion. |
| Room inventory | 46 rooms | There is room to capture peaks, but unsold weekday capacity still carries operating costs. |
| Base nightly rate | $159 | The second-highest model rate must be supported by condition, service, reputation, and location fit. |
| Starting room quality | 76 points | Good initial condition can defend price, but heavy peak use accelerates maintenance pressure. |
| Variable-cost factor | 22% | More occupied rooms create costs as well as revenue, so occupancy alone is incomplete evidence. |
| Suggested staff | 4 front desk, 6 housekeeping, 2 maintenance, 1 manager | Peak coverage is useful, but payroll must also be supported during quiet periods. |
City and location also change rent, demand, local spending, booking-channel mix, and weekday/weekend multipliers. The Beachfront location multiplies weekend demand by 1.32 but weekday demand by only 0.88, while rent rises by a 1.42 factor. Keep city, location, challenge, term, and random events matched when comparing decisions.
Calculate the lodging evidence
- Occupancy
rooms sold ÷ 46 × 100. Selling 35 rooms gives 76.1% occupancy.- Average daily rate (ADR)
room revenue ÷ rooms sold. Use realized revenue after the chosen rate strategy and promotion.- Revenue per available room (RevPAR)
ADR × occupancy rate. At a $159 ADR and 76.1% occupancy, RevPAR is about $121.- Short-run room contribution
(room revenue − channel fees − room-linked utilities) ÷ rooms sold. The simulator displays this before fixed costs.
Separate peak strength from monthly health
Record weekday and weekend rooms sold separately. A strong blended occupancy number can hide weak weekdays, and one event can make a poor strategy appear successful. Also compare RevPAR, contribution, channel-fee share, payroll, maintenance, profit, and cash.
A useful seasonal strategy earns enough during peaks to cover quieter capacity without damaging the rooms or depending on unprofitable discounts. If weekend profit improves but condition and reviews fall, the operation may be consuming the asset that creates future demand.
Run a six-step seasonal experiment
- Write one decision question. Example: “Will Weekend Stay Deal improve monthly profit without lowering room contribution or condition?”
- Precommit the evidence. Choose monthly profit as the outcome, weekday/weekend occupancy and ADR as drivers, and cash, condition, service, and reviews as guardrails.
- Record the controls. Note city, location, challenge, starting cash, base rate, amenities, campaign, staff, refresh level, and rooms.
- Run a complete baseline month. Record the monthly report and every random event. Do not judge the strategy from a single weekend.
- Change one lever. Adjust only the rate strategy, weekend offer, direct-booking perk, amenity level, refresh setting, one staff role, or one campaign.
- Compare and repeat. Explain the mechanism, check every guardrail, name a limitation, and repeat before making the change permanent.
Use the controlled experiment guide to plan matched runs and the results-analysis guide to separate outcomes, drivers, guardrails, and outside events.
Four useful Beachside Motel tests
| Decision question | Change only | Primary evidence | Stop or reverse when |
|---|---|---|---|
| Does a weekend offer create profitable demand? | Weekend Stay Deal | Weekend rooms sold, ADR, contribution, monthly profit | Discounted volume fails to increase profit or strains condition and service. |
| Can peaks support Dynamic Premium? | Rate strategy | ADR, occupancy, RevPAR, lost bookings, profit | Lower conversion costs more than the higher realized rate earns. |
| Can more bookings stay direct? | Direct Booking Perk | Direct mix, channel-fee share, contribution, profit | The promotional rate costs more than the avoided fees. |
| Is room recovery the true constraint? | Refresh level or weak-room renovation | Condition, unavailable rooms, lost bookings, reviews, cash | Spending produces no repeatable availability or profit improvement. |
Fair-test warning: concerts, tournaments, travel reviews, construction, water-heater failures, inspection warnings, and commission increases can change results. Record events and rerun the comparison instead of crediting the selected lever automatically.
Read the dashboard in order
- Cash: can the motel absorb a quiet period or repair?
- Weekday and weekend rooms sold: where is demand concentrated?
- Occupancy, ADR, and RevPAR: is the rate-volume combination working?
- Contribution and break-even rooms: does each booking help cover fixed costs?
- Service capacity and lost bookings: is coverage blocking profitable demand?
- Condition, satisfaction, and reviews: is the guest promise being protected?
- Cost shares and monthly profit: where did the revenue go?
Diagnose six connected patterns
- Weekend occupancy high, monthly profit weak: quiet days or fixed costs absorb the peak gain.
- Occupancy up, contribution down: a discount or expensive booking mix is buying low-value volume.
- Lost bookings and weak service: restore coverage before adding rooms.
- Strong reviews and weak weekdays: test one targeted demand or rate lever before expansion.
- Profit up and condition down: deferred upkeep may be financing the apparent improvement.
- High RevPAR and high channel fees: test direct conversion before buying more reach.
Use a strict five-room expansion gate
The simulation charges $27,500 to add five rooms and increases staffing requirements with inventory. For Beachside Motel, that is a 10.9% capacity increase that must earn across more than a few peak days. Require repeated comparable periods with profitable lost bookings, healthy service capacity, stable condition and reviews, and enough cash for the purchase plus ongoing payroll, utilities, and maintenance.
Precommit this stop rule: do not expand when quiet-period utilization is weak, existing rooms are unavailable, service coverage is below need, demand depends on deep discounts or costly channels, or the investment removes the cash buffer. Recover existing inventory and improve the weekday/peak mix first.
Run a 50-minute classroom investigation
- Minutes 0–7: introduce occupancy, ADR, RevPAR, contribution, seasonality, and the danger of judging a month from its busiest days.
- Minutes 7–12: assign the same city, location, Beachside model, challenge, and decision question. Students make a prediction.
- Minutes 12–23: teams run one baseline month and record weekday/weekend evidence plus random events.
- Minutes 23–34: teams change one assigned lever and run a matched comparison.
- Minutes 34–43: students calculate occupancy and RevPAR changes, diagnose the main constraint, and test guardrails.
- Minutes 43–50: teams present a claim-evidence-reasoning recommendation and one limitation or follow-up run.
For shared devices, assign operator, recorder, calculator, and skeptic roles. For no-device access, use the 35-room, $159 ADR example above and ask which weekday, weekend, channel, cost, and quality evidence is missing before a rate recommendation can be defended.
Extend the activity with the lodging revenue management lesson, collect evidence with the printable motel worksheet, and assess reasoning with the business simulation rubric.
Keep the recommendation responsible
The simulator is a fictional learning model. It omits taxes, financing, insurance, labor agreements, accessibility requirements, safety codes, licenses, environmental risks, privacy obligations, consumer-protection rules, and many other real constraints. Its prices, staffing counts, costs, and forecasts are not professional advice.
Real lodging prices and promotions should be truthful and transparent; required fees should not be hidden; accessibility and nondiscrimination obligations matter; guest and payment data need appropriate safeguards; and worker safety, wages, hours, heat exposure, and working conditions must follow applicable law. This page provides learning links, not incentives to click ads, and advertising outcomes never affect the simulation score.
Compare every Motel Simulator model
Beachside Motel tests seasonal peak capture without overbuilding for the busiest days. Compare it with four different rate, quality, inventory, and demand profiles:
- Budget Motor Inn — contrast the high-rate seasonal case with the lowest-cost value model.
- Family Roadside Motel — use steadier roadside demand as a reference.
- Airport Express Motel — compare weekend leisure peaks with weekday airport demand.
- Boutique Lodge — compare seasonal capacity with a smaller premium-service strategy.
See the full model comparison in the Motel Simulator overview and classroom guide, or browse the complete business simulation strategy guide directory.