Inn or Out: Yield Management in Hotels - Simulation Game Custom Case Solution & Analysis

Evidence Brief: Inn or Out Yield Management

This brief extracts material facts regarding the hotel yield management simulation. The data points focus on capacity constraints, pricing segments, and the financial consequences of inventory decisions.

Financial Metrics

Total Room Capacity: 300 rooms.
Leisure Segment Rate: 150 per night.
Business Segment Rate: 250 per night.
Displacement Cost (Walking a Guest): 350 per instance (includes 100 penalty plus 250 for alternative lodging).
Variable Cost per Occupied Room: 30 per night.
Contribution Margin (Leisure): 120 per room.
Contribution Margin (Business): 220 per room.

Operational Facts

Booking Window: 90 days prior to arrival.
Segment Behavior: Leisure travelers book early and are price sensitive. Business travelers book late and are less sensitive to price.
Inventory Type: Perishable. Unsold rooms have zero value after the night ends.
Demand Uncertainty: Historical data shows a standard deviation of 15 percent in business demand and 10 percent in leisure demand.
Cancellation Rates: Average 5 percent for business and 12 percent for leisure segments.

Stakeholder Positions

General Manager: Focuses on RevPAR (Revenue Per Available Room) and high occupancy.
Revenue Manager: Prioritizes maximizing total yield through segment fencing and protection levels.
Front Office Manager: Concerned with guest satisfaction and the operational friction of walking guests when overbooked.

Information Gaps

Specific seasonal variance data for the upcoming 12 months is absent.
Competitor pricing responses to discount levels are not modeled.
The exact impact of brand damage from overbooking beyond the immediate 350 cost is not quantified.

Strategic Analysis

The core strategic question is how to allocate fixed room inventory between early-booking leisure guests and late-booking business guests to maximize total revenue while managing the financial risk of overbooking.

Core Strategic Question

Determine the optimal protection level for high-value business inventory.
Calculate the overbooking limit that balances the cost of empty rooms against the cost of guest displacement.
Identify the threshold where leisure discounts stop contributing to bottom-line growth.

Structural Analysis

Applying the Expected Marginal Shorthand Revenue (EMSRb) framework reveals that the hotel frequently commits too much inventory to leisure guests too early. The high displacement cost (350) relative to the business rate (250) suggests that aggressive overbooking is more dangerous than aggressive room protection. The current 100 difference between segments warrants a strict protection level for the final 45 to 60 rooms based on historical business demand volatility.

Strategic Options

Option	Rationale	Trade-offs
Yield Maximization	Protect 80 rooms for late-booking business travelers.	Higher ADR (Average Daily Rate) but risks lower occupancy if business demand fluctuates downward.
Occupancy Focus	Accept all leisure bookings until 90 percent capacity is reached.	Ensures high utilization but leads to significant dilution by displacing 250-rate business guests.
Dynamic Overbooking	Set overbooking limit at 105 percent of capacity based on 8 percent weighted cancellation average.	Minimizes empty rooms but requires high operational readiness for guest displacement.

Preliminary Recommendation

The hotel must adopt the Yield Maximization strategy. The math of the simulation favors protecting high-margin business demand. The 100 premium paid by business travelers outweighs the risk of a 5 to 10 percent vacancy rate on the margin. Protecting 75 rooms for the business segment is the optimal starting point based on current standard deviations.

Implementation Roadmap

The transition from occupancy-based management to yield-based management requires a 90-day phased execution. Strategy execution will focus on inventory controls and staff readiness.

Critical Path

Week 1 to 2: Establish baseline demand forecasts using three-year historical averages and adjust for current market trends.
Week 3 to 4: Implement automated booking limits in the Property Management System to freeze leisure sales once the protection level is reached.
Week 5 to 8: Train front desk staff on the recovery protocol for walked guests to minimize brand damage.
Week 9 to 12: Daily audit of the booking curve to adjust protection levels in real-time as business demand materializes.

Key Constraints

Forecast Accuracy: The strategy fails if business demand drops below two standard deviations of the mean.
Staff Capability: Front desk teams must handle overbooking situations without escalating local management intervention.

Risk-Adjusted Implementation Strategy

To mitigate the risk of empty rooms, the hotel will use a tiered release system. If business bookings do not reach 40 percent of the protected block by 14 days prior to arrival, 20 percent of those rooms will be released back to the leisure segment at a mid-tier price point. This creates a safety valve for revenue while maintaining the primary focus on high-yield guests.

Executive Review and BLUF

BLUF

The Grand Hotel must shift from an occupancy-centric model to a yield-driven model by protecting 25 percent of inventory for high-margin business travelers. Current operations prioritize filling rooms too early, which dilutes revenue by favoring 150 leisure rates over 250 business rates. By implementing a protection level of 75 rooms and a controlled overbooking limit of 5 percent, the hotel will increase RevPAR by an estimated 12 percent. Success depends on the discipline to reject low-value bookings even when occupancy looks low 30 days out.

Dangerous Assumption

The analysis assumes business demand is price inelastic up to the 250 threshold. If competitors drop rates significantly, the business segment may migrate, leaving the protected 75-room block empty and unrecoverable.

Unaddressed Risks

Market Saturation: If a new competitor enters the market during the 90-day implementation, the historical demand curves become obsolete. Probability: Low. Consequence: High.
Operational Burnout: Frequent overbooking to reach 100 percent occupancy places extreme stress on night-shift staff. Probability: High. Consequence: Moderate.

Unconsidered Alternative

The team did not evaluate a Minimum Length of Stay (MLOS) requirement for leisure guests. Implementing a two-night minimum for the 150 rate during peak business periods could naturally filter for higher-value bookings without requiring hard inventory blocks, potentially increasing total folio spend in ancillary services like food and beverage.