Skip to main content
Heuristics

Walk Away and Restart Heuristic

If a solution to a problem is not working and cannot be refined, have the courage to abandon it and start the problem-solving process from scratch. This heuristic helps avoid sunk cost fallacy by recognizing when to pivot and restart.

THE IDEA

Walk Away and Restart Heuristic

One hopes that at this point, the solution needs just a tweak or two. However, if the solution has not had the desired impact and you’re unable to refine it so that it does, have the courage to walk away from the solution. Then start all over again to solve the problem, beginning with step one.

When to use it

  • When iterating on a product design that consistently fails user testing.

  • When developing a business strategy that hasn't met key milestones after several refinements.

  • When debugging a complex system where fixes are causing more issues than they solve.

  • When a personal project is consuming excessive time with no visible progress despite repeated adjustments.

FROM THEORY TO EVERYDAY LIFE

In practice

01

Software Development

A developer spends weeks on a feature that is not working. Instead of continuing to patch it, they decide to discard the code and redesign from scratch, leading to a more robust implementation.

02

Marketing Campaign

A marketing team launches a campaign that fails to increase sales. After attempting minor tweaks with no result, they cancel the campaign and develop a new strategy, eventually achieving their goals.

✳

A MOMENT TO REFLECT

Put it to work.

  1. What evidence would convince you that a solution is beyond repair and needs to be abandoned?

  2. How can you separate emotional attachment to a solution from objective assessment of its effectiveness?

  3. What safeguards can you put in place to ensure you make the decision to restart based on data rather than fear of losing invested effort?

Often confused with

CONTINUE THE CONVERSATION

Source texts

  • Thinking in Systems and Mental Models Think Like a Super Thinker (Dawson, Marcus P)
← More heuristics