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Using What-If Analysis

How to use multiple scenarios to explore different retirement assumptions — comparing outcomes side by side.

2 min read


In brief

Create multiple scenarios with different assumptions — retirement age, spending levels, growth rates — and compare projected outcomes side by side to understand which variables have the largest effect on whether your money lasts.

Before you start

You need at least one existing scenario before you can duplicate it for comparison. If you have not yet created a scenario, see Creating Scenarios first. Retirement involves uncertainty — what-if analysis is the process of exploring different combinations of assumptions to understand the range of possible outcomes.

Steps

  1. Navigate to Scenarios and open your base scenario — the one with the assumptions you consider most likely.
  2. Select Duplicate to create a copy. Give the duplicate a name that identifies the variable you are changing — for example, "Retire at 63" or "Lower growth rate".
  3. Open the duplicate and change one or two variables:
    • Retirement age — each additional year of work means one more year of contributions and one fewer year of withdrawals
    • Annual spending — even small changes compound significantly over 25–30 years
    • Growth rate — the difference between 4% and 6% growth is substantial over long periods
    • Inflation rate — higher inflation erodes purchasing power faster
  4. Select Run to generate the updated projection.
  5. Repeat steps 2–4 for each scenario you want to compare. Example set:
    • Scenario A: Retire at 60, spend £35,000/year
    • Scenario B: Retire at 63, spend £35,000/year
    • Scenario C: Retire at 60, spend £30,000/year
  6. Navigate to the Dashboard to view all scenarios side by side.

What to check afterwards

On the Dashboard, compare the following across scenarios:

  • Fund depletion age — the age at which assets reach zero. Does changing the assumption push this meaningfully?
  • Final asset value — how much is projected to remain at your life expectancy?
  • Risk bands — if using Monte Carlo, compare the p10 (poor case) bands across scenarios.

Use this comparison to identify which assumptions have the largest effect on projected outcomes and where your projection is most sensitive to change.

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