Long-Horizon Scenario Planning

This use case explains how to build long horizon scenarios for capital projects and infrastructure portfolios in Model Reef.

You will:

  • Extend models to long horizons suitable for infrastructure and capital intensive assets.

  • Combine capex, operations and funding over 10 to 30 year periods or more.

  • Use scenarios to test macro, regulatory and strategic uncertainties.

  • Connect long dated cashflows to valuation and funding decisions.

Model Reef is not a macroeconomic forecast generator. It applies structured long horizon assumptions that you define or import.

When to use this pattern

Use this pattern when:

  • You manage infrastructure or capital projects with long economic lives.

  • Decisions depend on outcomes across decades rather than a few years.

  • You need to examine long term funding, reinvestment and value.

  • You want a systematic way to compare long range scenarios.

It builds on:

  • Capex Program Modelling

  • Multi Phase Project Cash Flows

  • Funding and Drawdown Structures

  • Build a Multi Scenario Valuation Pack


Architecture overview

1

Time structure

  • Model start and end dates chosen to cover full asset life.

  • Appropriate base frequency, typically monthly or quarterly during build and early operations, with reporting aggregation for later years.

2

Drivers and assumptions

  • Long term demand, price and volume paths.

  • Operating cost trajectories and efficiency improvements.

  • Reinvestment and replacement capex cycles.

  • Funding and refinancing assumptions.

3

Scenario logic

  • Alternative macro or regulatory environments.

  • Different technology and cost curves.

  • Policy, demand or price shocks at selected points in time.

4

Outputs

  • Long dated P&L, Balance Sheet, Cashflow and Cash Waterfall.

  • Valuation metrics that reflect full asset life behaviour.


1

Set an appropriate model horizon and periodicity

Configure the model to cover the required horizon, for example:

  • Construction period, ramp up and 20 to 30 years of operation.

Set base model frequency to monthly or quarterly, depending on how much detail you need in early periods, then use reporting aggregation to view annual or multi year results.

Model Reef will continue to apply variable and driver rules across the extended horizon without additional formulas.

2

Build long term demand, price and cost trajectories

In the Data Library, construct long horizon drivers for:

  • Demand or utilisation, for example traffic, throughput or usage.

  • Price paths, including indexation, escalation caps and floors.

  • Operating cost trends, including inflation and efficiency improvements.

  • Macro or regulatory factors that you want to overlay, such as carbon prices, subsidies or capacity constraints.

Where you have detailed projections for early years but only bands or ranges for outer years, you can:

  • Anchor long term assumptions to broad bands and use smoothing or interpolation.

  • Apply conservative tapering or saturation behaviour to demand growth.

These drivers will feed into revenue and cost variables across the full horizon.

3

Include reinvestment, replacement and major maintenance

For long lived assets, it is important to incorporate:

  • Major periodic maintenance.

  • Replacement of key components at defined intervals.

  • Capacity expansions or refurbishments.

Use Asset variables and capex schedules to model these reinvestments, separate from initial capex. For each asset class, define:

  • Life and replacement cycle.

  • Typical replacement cost as a percentage of initial capex.

  • Timing rules for when replacements occur.

This ensures that long term cashflows include realistic reinvestment patterns rather than assuming the initial asset lasts indefinitely.

4

Extend funding and refinancing structures

Use Funding and Drawdown Structures to represent long term financing by:

  • Extending debt schedules to match or outlast initial project phases.

  • Adding refinancing events at appropriate maturities.

  • Changing interest rate and margin assumptions at refinancing dates.

  • Incorporating long term gearing targets or de gearing strategies.

This will produce long horizon cashflows that include:

  • Debt service and refinancing.

  • Changes in leverage over time.

  • Interactions between funding and valuation.

5

Design long horizon scenarios

Define a small number of structured scenarios, for example:

  • Base case built around current best estimates.

  • Downside case with lower demand, higher costs and adverse regulatory outcomes.

  • Upside case with stronger demand, favourable price or cost trends.

  • Stress cases focused on specific shocks, such as delayed projects or sudden price changes.

For each scenario, adjust:

  • Demand and price trajectories.

  • Operating cost and efficiency assumptions.

  • Reinvestment schedules and costs.

  • Funding conditions and discount rates.

Use consistent scenario narratives so that differences are clear and explainable.

6

Analyse long horizon outputs and valuation

Use reports and dashboards to examine:

  • Long term revenue, cost and margin trends.

  • Capex and reinvestment patterns across the horizon.

  • Cashflow profiles and periods of stress.

  • Balance Sheet evolution, including asset and debt balances.

Connect these to the valuation engine to calculate:

  • NPV and IRR metrics that account for full life behaviour.

  • Terminal value where the model horizon does not extend to true end of life.

  • Sensitivity of value to long term assumptions.

Use outputs to inform capital allocation, project selection and funding strategy.


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Check your work

  • The time horizon is long enough to capture major reinvestment and refinancing cycles.

  • Outer year assumptions are plausible and documented, not simply extrapolated.

  • Scenario differences reflect coherent narratives, not arbitrary parameter changes.

  • Valuation and decision making use bands and ranges, not a single point estimate.


Troubleshooting

chevron-rightModels feel too fragile in far future yearshashtag

Simplify outer year assumptions and focus on broad ranges rather than precise values; use scenario bands rather than detailed forecasts beyond a certain point.

chevron-rightRun time and complexity increase with very long horizonshashtag

Consider reducing base frequency after initial years by using reporting aggregation or building separate outer horizon models with coarser granularity.

chevron-rightStakeholders focus on point forecasts rather than uncertaintyhashtag

Present results in terms of scenario envelopes and key sensitivities, and document the scenario narratives alongside the numbers.


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