The Planning Fallacy

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The Planning Fallacy

People are usually overly-optimistic when estimating the time required to complete a task.

Similar psychology:

Likely impacts:

Discomfort & Frustration

Input Quality

Conversion Rates

Last updated: 23/09/2026

How to utilise this in your designs

When users set goals, you could contextualise each option with what it realistically involves, so the planning fallacy doesn't push them toward an unrealistic target.

Example from

Cal AI

Try pre-filling plan questions with users' past performance, so their estimates are anchored in real data rather than planning-fallacy optimism.

Dark UI for race time estimation with tabs for 5km, 10km, Half Marathon; blue-highlighted 5km; editable time selector set at 0h 27m 39s; orange pen highlights time input.

Example from

Runna

You could offer users the choice to review today in the past tense or plan tomorrow, as reflecting on what really happened may temper the planning fallacy.

On a pink UI, bold text prompts “Let’s get started by planning today,” with progress dots. Arrows highlight “When will you wake up?” and “When did you wake up?” screens. A pink “Start Planning” button is below.

Example from

Structured

When users postpone a task, you could show exactly how that shifts their schedule, resetting expectations before an optimistic plan quietly slips further.

Example from

Planta

Try adding a forced pause at the halfway point of a lesson, as a milestone that resets planning-fallacy expectations and reminds users why they started.

Mobile UI with purple progress bar, back arrow, and a purple character saying "Halfway to your results!" Below, "Did you know?" with a white box, blue magnifying glass icon, and calming mindset tips.

Example from

Ahead

Possible impacts

Setting realistic expectations upfront could help users stay motivated, avoiding the deflating moment when a task overruns their planning-fallacy estimate.

As seen in:

Ahead You're halfway through, take a pause

Progress indicators and milestones might reduce user frustration, as the planning fallacy leaves people surprised when a process takes longer than expected.

As seen in:

Runna Contextual default options

When a process drags past what users planned for, they may rush or accept defaults; realistic time estimates could help maintain the quality of their answers.

As seen in:

Cal AI Clearer expectations

Runna Contextual default options

You could reduce drop-off in long flows, e.g., sign-ups, since users who underestimate the time needed, due to the planning fallacy, may simply give up.

As seen in:

Airbnb Why not extend your trip?

Letaido Try it without connecting your tools

Written by Peter Ramsey

Consultant to 100+ companies

Published: 27/08/2023

How to utilise this in your designs

When users set goals, you could contextualise each option with what it realistically involves, so the planning fallacy doesn't push them toward an unrealistic target.

Example from

Cal AI

Try pre-filling plan questions with users' past performance, so their estimates are anchored in real data rather than planning-fallacy optimism.

Example from

Runna

You could offer users the choice to review today in the past tense or plan tomorrow, as reflecting on what really happened may temper the planning fallacy.

Example from

Structured

When users postpone a task, you could show exactly how that shifts their schedule, resetting expectations before an optimistic plan quietly slips further.

Example from

Planta

Try adding a forced pause at the halfway point of a lesson, as a milestone that resets planning-fallacy expectations and reminds users why they started.

Example from

Ahead

Possible impacts

Setting realistic expectations upfront could help users stay motivated, avoiding the deflating moment when a task overruns their planning-fallacy estimate.

As seen in:

Ahead You're halfway through, take a pause

Progress indicators and milestones might reduce user frustration, as the planning fallacy leaves people surprised when a process takes longer than expected.

As seen in:

Runna Contextual default options

When a process drags past what users planned for, they may rush or accept defaults; realistic time estimates could help maintain the quality of their answers.

As seen in:

Cal AI Clearer expectations

Runna Contextual default options

You could reduce drop-off in long flows, e.g., sign-ups, since users who underestimate the time needed, due to the planning fallacy, may simply give up.

As seen in:

Airbnb Why not extend your trip?

Letaido Try it without connecting your tools