QSRA for NEOM Trojena: Schedule Risk Analysis on Saudi Arabia's Mountain Mega-Project

A $19 billion mountain resort in the Saudi Arabian desert loses the Asian Winter Games, cancels $6 billion in contracts, and faces a schedule so far behind that recovery looks mathematically improbable. The question every stakeholder should have asked years earlier is not "are we on track?" but "what is the probability that we will finish on time, and what does the data say?"

QSRA for NEOM Trojena applies Quantitative Schedule Risk Analysis to model how duration uncertainties, discrete risk events, and correlation between work packages affect the completion date of Saudi Arabia's most ambitious mountain tourism destination. Using Monte Carlo simulation, the analysis produces probability-based forecasts at confidence levels such as P50, P80, and P90, replacing single-point schedule dates with a defensible range of outcomes.

The value of QSRA on a project like Trojena is not hindsight. It is the ability to quantify schedule exposure before contracts are signed, before the games are awarded, and before billions are committed to a timeline that the model shows has a 15% chance of being met.

Here is how QSRA would be structured for the Trojena programme, step by step.

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Why NEOM Trojena Demands QSRA

Trojena is a 60 square kilometre mountain tourism destination under construction in NEOM's Tabuk Province, at elevations between 1,500 and 2,600 metres above sea level. The scope includes a 270,000 square metre ski village, over 30 kilometres of slopes, multiple ultra-luxury hotels, a freshwater lake formed by three engineered dams, tunnel systems, and supporting infrastructure across terrain that has never hosted construction at this scale.

The original budget of approximately $19 billion surged by over $10 billion after a 2023 cost review found the project had fallen below its internal rate of return. In early 2026, NEOM terminated three major contracts worth over $6 billion, including the $4.7 billion dam and lake package awarded to Webuild and a $1 billion tunnel contract with Hyundai. The 2029 Asian Winter Games, which were to be hosted at Trojena, were relocated to Almaty, Kazakhstan.

This is exactly the scenario QSRA is designed to prevent. A properly executed schedule risk analysis, run at the feasibility stage and updated quarterly, would have flagged the probability of missing the 2029 deadline years before contracts were cancelled. Without QSRA, the programme relied on deterministic dates that carried no information about the likelihood of achievement.

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Schedule Health Check: The Foundation

Every QSRA begins with a schedule health check. The risk model is only as reliable as the logic network it sits on. For a programme the size of Trojena, with multiple concurrent contractors and interdependent work fronts, the schedule must meet strict quality criteria before Monte Carlo simulation can produce meaningful results.

Step 1: Remove Hard Constraints

Hard date constraints in Primavera P6 override the logic network, forcing activities to start or finish on fixed dates regardless of predecessor completion. In a mega-project schedule with hundreds of activities across dam construction, tunnel boring, ski village structural works, and hotel fit-out, hard constraints mask genuine float and create false critical paths. Replace them with soft constraints or logic-driven relationships so the simulation can flex the schedule realistically.

Step 2: Fix Open-Ended Logic

Activities without successors (open ends) are invisible to the critical path calculation. On a programme like Trojena, open ends often appear in enabling works, temporary facilities, and interface activities between contractors. Every activity must have at least one predecessor and one successor to ensure the network flows continuously from notice to proceed through to operational readiness.

Step 3: Validate the Critical Path

The deterministic critical path should trace a logical sequence through the highest-risk work fronts. For Trojena, this likely runs through the dam and lake construction (which creates the centrepiece freshwater reservoir), the ski village structural steel erection, and the tunnel systems connecting the resort zones. If the critical path instead runs through low-risk administrative activities, the logic needs repair before simulation begins.

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Categorising Risks for the Trojena Programme

QSRA separates uncertainty into two categories. Both must be modelled to capture the full range of schedule outcomes.

Estimated Duration Uncertainties

These are the natural variations in how long activities take, modelled as three-point estimates (minimum, most likely, maximum) applied to activity durations. On Trojena, high-altitude construction introduces uncertainties that do not exist at sea level: weather windows are narrower, logistics are constrained by mountain access roads, and labour productivity drops at elevation. Earthworks for the dam foundations, tunnel boring through variable rock formations, and structural steel erection at altitude all carry wide duration ranges that must be captured with appropriate probability distributions such as PERT or triangular.

Discrete Risk Events

These are specific events that may or may not occur, modelled with a probability of occurrence and an impact on duration if they do. For Trojena, the risk register should include: contractor mobilisation delays following contract re-tendering after the $6 billion cancellation, unforeseen geotechnical conditions in dam foundations at 2,000+ metre elevation, design changes driven by scope reduction as NEOM reassesses the programme, regulatory approvals for environmental permits on the freshwater lake system, and supply chain disruptions for specialist mountain construction equipment. Each risk event is assigned a probability (e.g., 40% chance of geotechnical surprises) and a duration impact (e.g., 3 to 9 months delay).

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Risk Mapping: Connecting Risks to the Schedule

Risk mapping assigns each uncertainty and risk event to the specific schedule activities it affects. The mapping must reflect the programme's actual structure, not generic assumptions.

Series relationships: Dam construction, lake filling, and ski village commissioning are sequential. A delay in dam completion pushes lake formation, which pushes the snow-making system commissioning, which pushes the ski slope operational readiness. The entire chain must be mapped as a series dependency so the simulation captures the cascading delay effect.

Parallel relationships: Hotel construction across the six planned properties (Raffles, Anantara, W, JW Marriott, Collective, and Ritz-Carlton Reserve) can proceed simultaneously. A delay on one hotel does not necessarily delay the others, but all must complete before the resort can open. Map these as parallel paths converging at the operational readiness milestone.

Resource-driven relationships: Mountain access roads serve both the dam site and the ski village construction zone. If logistics capacity on these roads is constrained, both work fronts compete for the same resource. Map this as a shared resource constraint that the simulation can model as a bottleneck.

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Correlation: Why It Matters on Multi-Contractor Programmes

Correlation links related uncertainties so the simulation reflects reality. On Trojena, many risks are not independent. If Webuild's dam construction runs late due to geotechnical conditions, the same geological formation affects the tunnel boring by Hyundai. If labour productivity drops during summer months at high altitude, it drops across all contractors simultaneously, not just one.

Without correlation, the Monte Carlo simulation assumes that when one contractor runs late, another runs early, and the delays cancel out. This produces an artificially narrow output range that significantly understates the programme's true schedule risk. IQRM recommends correlation coefficients between 0.3 and 0.5 for activities sharing the same contractor, geography, or resource pool.

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Monte Carlo Simulation Settings

IQRM recommends running 5,000 to 10,000 iterations for a programme of Trojena's complexity. Each iteration samples from every assigned distribution and risk event, calculates the resulting schedule, and records the completion date. After thousands of iterations, the results converge into a probability distribution of completion dates.

Safran Risk is the recommended tool for this analysis. It imports native Primavera P6 schedules, supports PERT, triangular, and uniform distributions, handles correlation matrices, and produces the S-curves and tornado charts needed for executive reporting. For a programme with multiple contractor schedules feeding into a master programme, Safran Risk's ability to model inter-project dependencies is critical.

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Interpreting the QSRA Outputs

The S-Curve (Cumulative Distribution Function)

The S-curve shows the probability of completing the programme by any given date. For Trojena, if the deterministic completion date is Q4 2028, the S-curve might show that this date sits at P15, meaning there is only a 15% probability of finishing by then. The P50 date might fall in Q2 2030, and the P80 in Q4 2030. This single chart would have told NEOM's leadership in 2022 that committing to a 2029 Winter Games deadline carried enormous schedule risk.

The Tornado Chart (Sensitivity Analysis)

The tornado chart ranks which risks and uncertainties have the greatest impact on the completion date. On Trojena, the top drivers would likely include: dam and lake construction duration uncertainty, contractor remobilisation timelines after contract cancellations, geotechnical conditions in tunnel and foundation works, and design finalisation for the revised scope. Decision-makers use the tornado chart to prioritise risk responses where they will have the greatest effect on schedule confidence.

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Confidence Levels: What They Mean for Trojena

QSRA results are reported at defined confidence levels. Each level represents the date by which the programme has a stated probability of completing.

Confidence Level	Meaning	Trojena Application
P50	50% chance of finishing by this date	Internal planning and resource allocation baseline
P80	80% chance of finishing by this date	Stakeholder reporting and milestone commitments to NEOM board
P90	90% chance of finishing by this date	International event commitments such as the Asian Winter Games

IQRM recommends P80 as the minimum confidence level for milestone commitments on mega-projects. For an international sporting event with a fixed, immovable date, only P90 or above provides a defensible commitment. Had Trojena's QSRA shown a P90 date beyond 2029, the decision to bid for the Winter Games could have been reconsidered before reputational and financial damage occurred.

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Best Practices for QSRA on Saudi Mega-Projects

Run QSRA at feasibility, not after contract award. By the time contracts are signed, the schedule baseline is locked and stakeholders have committed to dates. QSRA at feasibility gives decision-makers the chance to adjust scope, phasing, or timeline before commitments are irreversible.

Update quarterly and after every major change. A QSRA run once at the start of a five-year programme is a snapshot, not a management tool. Quarterly updates, aligned with programme reporting cycles, track whether schedule risk is increasing or decreasing. The $6 billion contract cancellation on Trojena would have triggered an immediate QSRA refresh to quantify the new completion probability.

Model the interfaces between contractors explicitly. On a multi-contractor programme, the interfaces between work packages are where delays compound. The handover from dam construction to lake filling to ski slope commissioning is a chain of dependencies that must be modelled as a connected sequence, not as isolated contractor schedules.

Never commit to a fixed date without knowing its confidence level. A deterministic completion date without a probability is meaningless for decision-making. When NEOM committed to hosting the 2029 Asian Winter Games, the question that needed answering was: "What is the P-value of a 2029 completion?" If the answer was P15, the commitment was a gamble, not a plan.

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Frequently Asked Questions

What is QSRA for mega-projects like NEOM Trojena?

QSRA (Quantitative Schedule Risk Analysis) is a Monte Carlo simulation method that models how duration uncertainties and risk events affect a mega-project's completion date. It produces probability-based forecasts at confidence levels such as P50, P80, and P90, replacing deterministic schedule dates with a range of outcomes backed by data.

How could QSRA have prevented the Trojena schedule failure?

QSRA run at the feasibility stage would have shown the probability of meeting the 2029 deadline. If the P90 date was beyond 2029, leadership would have known that committing to the Asian Winter Games carried a high probability of failure. The analysis would have quantified the gap between the target date and a realistic, risk-adjusted schedule, allowing informed decisions before reputational damage occurred.

Why is correlation important in multi-contractor QSRA?

Correlation ensures the simulation reflects that related risks move together. On Trojena, geotechnical conditions affect both the dam contractor and the tunnel contractor simultaneously. Without correlation, the model assumes delays on one package are offset by early finishes on another, producing an unrealistically narrow range of outcomes that understates true programme risk.

What confidence level should a mega-project use for event deadlines?

IQRM recommends P90 or above for fixed, immovable deadlines such as international sporting events. P80 is the minimum for stakeholder reporting and board-level milestone commitments. P50 means a coin-flip chance of missing the date, which is unacceptable for commitments with reputational or contractual consequences.

What tools are used for QSRA on Saudi mega-projects?

Safran Risk is the recommended tool for full QSRA on programmes like Trojena. It imports native Primavera P6 schedules, supports all required distribution types including PERT and triangular, handles correlation matrices for multi-contractor programmes, and produces S-curves and tornado charts for executive reporting.

How often should QSRA be updated on a programme like Trojena?

IQRM recommends quarterly QSRA updates aligned with programme reporting cycles. The model should also be refreshed immediately after major events such as contract cancellations, scope changes, baseline re-plans, or the achievement of key milestones. On Trojena, the $6 billion contract termination would have triggered an immediate QSRA refresh.

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