Sample paper
Word Count: approximately 2,300 words
Recommended Baseline Budget
The ten-category deterministic baseline budget totals $4,300, built from historical trip data, supplier quotes, and market benchmarks, with accommodation ($1,800, modelled via triangular distribution across $1,600-$2,000) as the largest single category, justified by off-peak discount potential against peak-season and limited-availability price risk.
Two Risk Events
Delay in Supply Delivery: Modelled with a triangular impact distribution ($50 minimum, $100 most likely, $150 maximum) and an estimated 30% occurrence probability, reflecting supplier reliability, shipping disruption, and demand-surge risk affecting camping gear, tickets, or specialised equipment.
Price Inflation: Modelled with a triangular impact distribution ($30 minimum, $80 most likely, $120 maximum) and an estimated 20% occurrence probability, reflecting exchange rate movement and destination-specific demand-driven price volatility across transport, accommodation, and dining categories.
Contingency Recommendation
The Monte Carlo simulation's 80th-percentile total cost of $4,730, compared against the $4,300 deterministic baseline, yields a recommended contingency of $430 -- giving the project team 80% confidence the combined baseline and contingency will cover total costs, with the recommendation that contingency utilisation be monitored and periodically reassessed as the project progresses.
Risk Management
Most sensitive cost variable -- Accommodation: Recommended mitigation strategies include broad hotel market research and negotiation, exploring alternative accommodation types (apartments, vacation rentals, homestays), early booking to capture favourable rates, and negotiating flexible cancellation or rate-adjustment terms.
Most sensitive risk event -- Delay in Supply Delivery: Recommended mitigation strategies include early identification of critical supply items, diversifying the supplier base to reduce single-source dependency, building schedule buffer time around critical deliveries, maintaining proactive supplier communication, and developing contingency plans for alternative activities if supplies are delayed.
Correlation Matrix
A 0.7 positive correlation between accommodation and transportation costs reflects shared drivers -- destination popularity, seasonal demand, and connectivity -- meaning changes in one variable are likely accompanied by corresponding changes in the other. The report recommends managing these two cost elements jointly, for example through negotiated package deals, rather than treating them as independent budget lines, given their tendency to move together under shared market pressures.
Organizational Policy Alignment
Organisational policy requires an 80% probability of total project cost falling within -5% to +10% of the estimated project value. The simulation's 10th-percentile result ($4,085, approximately -5%) satisfies the lower bound, but the 90th-percentile result ($4,841, approximately +12.6%) exceeds the +10% upper threshold, indicating the project's risk profile carries a higher probability of cost overrun than organisational policy permits. Recommended remediation includes narrowing cost estimate uncertainty through further data review, strengthening mitigation for the identified risk events, considering additional contingency fund allocation, and maintaining transparent, ongoing stakeholder communication about cost uncertainty as the project develops.
Conclusion
The Monte Carlo simulation analysis supports a recommended contingency of $430 for the Holiday Project, identifies accommodation and supply delivery delay as the highest-priority risk factors for active management, and flags a modest misalignment with organisational risk policy that the project team should address through continued cost estimate refinement, targeted risk mitigation, and transparent stakeholder communication throughout project execution.
References
No formal reference list was provided in the source document.