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Laborit’s Law / Law of the Least Effort: 1 clear explanation

Feb 7, 2021 | Business & Life Advice, Time Management

What is Laborit’s Law or the Law of the Least Effort?

Laborit’s Law also called the Law of Least Effort or Principle of least Effort suggests that humans prefer to carry out simple tasks that give immediate satisfaction to avoid stress or inconvenience. As a result, we postpone the most tedious activities in favor of the most straightforward ones, or worst, we procrastinate.

Laborit’s Law – The Law of Least Effort – Principle of least Effort – Illustration

Laborit's Law - The Law of Least Effort - Principle of least Effort - Illustration - ParetoAnalysis.Tools

What are the origins of Laborit’s Law?

Henri Laborit (1914-1995) was a man of many talents, a French surgeon and neurobiologist researcher, and a diverse thinker. He put a theory about the inhibition of action in which he explains how the brain organizes behaviors, i.e., action or lack of action. Laborit’s theory is that there is inhibition of action when behaviors become impossible or are deleterious to health. Our instinct makes us avoid stress and naturally prioritize easy, enjoyable, and quick tasks that generate almost immediate satisfaction and delay longer or more complex tasks.

“Take time to deliberate; but when the time for action arrives, stop thinking and go in.”– Napoleon Bonaparte

Why do we tend to start with the easy tasks first?

According to Henri Laborit, our brain is wired to do what makes us happy first. Doing the easy task first is an excellent way to score “quick wins” and “tick the box” on your to-do-list.

Reducing your to-do-list provides an incredible feeling for two reasons:
1) Achieving something always bring some satisfaction
2) Shortening the to-do-list reduces de facto the mental load and can help limit the risk of getting overwhelmed by endless to-do-list

What is wrong with starting with the easy task first?

The major downside of handling the most manageable tasks first is that it prevents the highly-value-added but tedious tasks from being completed. Research shows that individuals who execute their most difficult tasks first are generally more productive and high achieving than those who start with the easiest and work their way up. 

“The only difference between success and failure is the ability to take action.”– Alexander Graham Bell

How can I limit the downside effect of Laborit’s Law?

Establish a holistic view of your tasks. Quantify the importance of each task. Then make a short-list of the most valuable tasks or projects with a rational approach, such as a Pareto Analysis . Among these most useful tasks, execute first the most straightforward tasks, i.e., those that carry little risk. This lazy but rational and smart approach helps mitigate the instant gratification bias by focusing on items that exhibit the best tradeoff between “value-add” and “difficulty.” Completing these somehow easy but vital tasks will help you build momentum that takes you through to more challenging tasks. Reward yourself upon completion to teach your brain that it was worth the effort. Finish your to-do-list with the remaining less valuable tasks. 

An enhanced method to limit the downside effect of Laborit’s Law consists of using Eisenhower’s Urgent-Important Matrix to add a planning component in your prioritization process in addition to the “task’s value or importance” criteria.

 

Conclusion and Suggestions

In essence, Laborit explains that humans’ brains are wired to prefer carrying out simple tasks that give them satisfaction at sight rather than more complicated and stressful – but potentially more value-added – tasks. Every day social media algorithms use this human bias to grab our attention and make us procrastinate with attention-grabbing videos.

A rational and smart approach to mitigate this instant gratification bias consists of focusing on items that exhibit the best tradeoff between “value-add” and “difficulty.” For more Business & Life articles with a productivity mindset approach, visit the blog of ParetoAnalysis.tools.

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