Law of triviality

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The law of triviality is C. Northcote Parkinson's 1957 argument that people within an organization commonly give disproportionate weight to trivial issues. [1] Parkinson provides the example of a fictional committee whose job was to approve the plans for a nuclear power plant spending the majority of its time on discussions about relatively minor but easy-to-grasp issues, such as what materials to use for the staff bicycle shed, while neglecting the proposed design of the plant itself, which is far more important and a far more difficult and complex task.

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The law has been applied to software development and other activities. [2] The terms bicycle-shed effect, bike-shed effect, and bike-shedding were coined based on Parkinson's example; it was popularised in the Berkeley Software Distribution community by the Danish software developer Poul-Henning Kamp in 1999 [3] and, due to that, has since become popular within the field of software development generally.

Argument

A bicycle shed Bike shed at Bletchley Park.jpg
A bicycle shed

The concept was first presented as a corollary of his broader "Parkinson's law" spoof of management. He dramatizes this "law of triviality" with the example of a committee's deliberations on an atomic reactor, contrasting it to deliberations on a bicycle shed. As he put it: "The time spent on any item of the agenda will be in inverse proportion to the sum [of money] involved." A reactor is so vastly expensive and complicated that an average person cannot understand it (see ambiguity aversion), so one assumes that those who work on it understand it. However, everyone can visualize a cheap, simple bicycle shed, so planning one can result in endless discussions because everyone involved wants to implement their own proposal and demonstrate personal contribution. [4]

After a suggestion of building something new for the community, like a bike shed, problems arise when everyone involved argues about the details. This is a metaphor indicating that it is not necessary to argue about every little feature based simply on having the knowledge to do so. Some people have commented that the amount of noise generated by a change is inversely proportional to the complexity of the change. [3]

Behavioral research has produced evidence which confirms theories proposed by the law of triviality. People tend to spend more time on small decisions than they should, and less time on big decisions than they should. A simple explanation is that during the process of making a decision, one has to assess whether enough information has been collected to make the decision. If people make mistakes about whether they have enough information, then they will tend to stop collecting information too early to adequately inform their big decisions. The reason is that big decisions require collecting information for a long time. It leaves more time to make a mistake (and stop) before getting enough information. Conversely, for small decisions, where people should stop early, they may inefficiently continue to ponder for too long. [5]

There are several other principles, well known in specific problem domains, which express a similar sentiment.

Wadler's law, named for computer scientist Philip Wadler, [6] is a principle which asserts that the bulk of discussion on programming-language design centers on syntax (which, for purposes of the argument, is considered a solved problem), as opposed to semantics.

Sayre's law is a more general principle, which holds (among other formulations) that "In any dispute, the intensity of feeling is inversely proportional to the value of the issues at stake"; many formulations of the principle focus on academia.

See also

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References

  1. ↑ Parkinson, C. Northcote (1958). Parkinson's Law, or the Pursuit of Progress. John Murray. ISBN   0140091076.
  2. ↑ Kamp, Poul-Henning (2 October 1999). "Why Should I Care What Color the Bikeshed Is?". Frequently Asked Questions for FreeBSD 7.X, 8.X, and 9.X. FreeBSD. Retrieved 31 July 2012.
  3. 1 2 Poul-Henning Kamp (2 October 1999). "The Bikeshed email". phk.freebsd.dk.
  4. ↑ Forsyth, Donelson R (2009). Group Dynamics (5 ed.). Cengage Learning. p. 317. ISBN   978-0-495-59952-4.
  5. ↑ Descamps, Ambroise; Massoni, Sebastien; Page, Lionel (June 2021). "Learning to hesitate". Experimental Economics. 388 (18): 3939–3947. doi:10.1007/s10683-021-09718-7. S2CID   237925345. In an experiment, we find that participants deviate from optimal information acquisition in a systematic manner. They acquire too much information (when they should only collect little) or not enough (when they should collect a lot)..
  6. ↑ "Wadler's Law". HaskellWiki. Retrieved 12 May 2011.

Further reading

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