Sensitivity Analysis

Identify which inputs drive your project’s financial performance by testing how each variable affects key outputs.

Sensitivity Analysis in Aire

Sensitivity analysis identifies which assumptions matter most to your project. Vary inputs one at a time across realistic ranges while holding others constant. The result: a clear ranking of variables by their impact on NPV, IRR, LCOE, or any output you track.

If electricity price changes by 20%, how much does NPV move? If construction costs vary by ±15%, what happens to IRR? Sensitivity analysis quantifies these relationships and shows where to focus your attention.

What You Learn

Sensitivity analysis answers critical questions about your project:

• Which single input has the greatest impact on project returns?
• How much does project economics change if interest rates rise 2%?
• What happens to LCOE if equipment costs vary by ±20%?
• Where should I focus during commercial negotiations?
• Which variables determine whether the project meets hurdle rates?

Instead of producing a single forecast, sensitivity analysis maps how outputs respond to input changes across realistic ranges.

Key Components

Base Scenario: A complete project model with all terms, calculations, and blocks defined—this is your starting point

Input Variables: The terms you test—each with a base value, lower bound, and upper bound representing realistic variation

Output Metrics: The KPIs you monitor—typically NPV, IRR, payback period, LCOE, or other calculated financial terms

How It Works

Aire executes your full project model repeatedly with different input values. Each run recalculates every term, cascades through blocks, and produces complete financial outputs.

The analysis varies one input at a time while holding others constant—this isolates each variable’s individual impact.

Tornado Analysis: Test each input at its lower and upper bounds. Calculate the range of output variation. Rank inputs by impact. This produces the data for tornado charts showing which variables matter most.

Stepped Analysis: Divide each input’s range into multiple steps (typically 6 points from lower to upper bound). Run the model at each step. Record output values. This produces line charts revealing the full relationship between inputs and outputs, including non-linearities and thresholds.

Every calculation is a complete model run—no approximations, no interpolations. Changes cascade through all dependencies with 64-decimal precision. Parallel execution keeps it fast.

Reading the Results

Sensitivity analysis produces three types of outputs:

Tornado Charts: Horizontal bars show the output range caused by each input. Bar width = impact magnitude. Inputs ranked by importance—widest bars at top. If interest rate produces the widest bar on an NPV tornado chart, interest rate matters more than other tested variables.

Line Charts: Plot output values against input values across the full range. Straight lines mean linear relationships. Curved lines reveal non-linearities—regions where small input changes create disproportionate output swings. Inflection points indicate thresholds where project viability shifts.

Data Tables: Exact values for every input-output combination at each step. Use these to find specific threshold values where viability changes, export precise numbers for reports, or identify target input values that achieve desired outputs.

Selecting Inputs

Test inputs that are:

• Uncertain: Variables where the true value isn’t known precisely (commodity prices, interest rates, degradation curves)
• Controllable: Parameters you can influence through design or negotiation (system capacity, financing structure)
• Material: Values that plausibly affect the outputs you care about

Avoid testing:

• Correlated inputs together (their combined effect will be overstated)
• Unrealistic ranges that would never occur in practice
• Inputs with negligible effect on key outputs

Start with 6-10 critical inputs. Tornado charts become hard to interpret with more than 15 variables.

Selecting Outputs

Focus on outputs that define project success:

• Financial metrics: NPV, IRR, equity returns, payback period
• Economic metrics: LCOE, unit production cost, revenue per unit
• Risk metrics: Debt service coverage ratio, cash-on-cash return

Start with 2-4 key metrics. Avoid tracking intermediate calculations unless they directly inform decisions.

Use Cases

Risk Assessment

Question: “Which uncertainties matter most to this project?”

Run sensitivity analysis with realistic bounds for uncertain inputs. The tornado chart ranks risks by financial impact—focus mitigation efforts on the top variables.

Negotiation Priorities

Question: “Should I negotiate equipment costs or financing terms?”

Compare the impact of a 10% cost reduction versus a 1% rate improvement. The tornado chart quantifies which negotiation delivers more value.

Viability Thresholds

Question: “At what point does this project fail to meet our hurdle rate?”

Use stepped analysis and data tables to identify specific threshold input values where IRR drops below requirements or NPV turns negative.

Stakeholder Communication

Question: “How do I explain project risks to investors?”

Tornado charts communicate financial sensitivity clearly without requiring stakeholders to understand formulas or modeling details. Show which variables drive outcomes and by how much.

Understanding Limitations

One-at-a-Time Testing: Sensitivity analysis varies one input while holding others constant. It doesn’t capture correlations or interactions between variables. If two inputs move together in reality, their combined effect won’t appear in the analysis.

Equal Probability Assumption: All values within the input range are treated equally. The analysis doesn’t reflect whether extreme values are likely or rare—a ±20% cost variation is tested the same whether that range represents 90% confidence or 50% confidence.

Point-in-Time Snapshot: Results reflect your model’s current state. As terms or blocks change, rerun the analysis to ensure results remain current.

Range Compression in Tornado Charts: Tornado charts show total range but don’t reveal the shape of the relationship. Use line charts to check for non-linearities that tornado charts might oversimplify.