Forming, storming, norming, performing, and …chloroforming?

In 1965, Bruce Tuckman proposed a “developmental sequence in small groups.” According to his influential theory, most successful groups go through four stages with rhyming names:

1. Forming: Group members get to know each other and define their task.
2. Storming: Through argument and disagreement, power dynamics emerge and are negotiated.
3. Norming: After conflict, groups seek to avoid conflict and focus on cooperation and setting norms for acceptable behavior.
4. Performing: There is both cooperation and productive dissent as the team performs the task at a high level.

Fortunately for organizational science, 1965 was hardly the last stage of development for Tuckman’s theory!

Twelve years later, Tuckman suggested that adjourning or mourning reflected potential fifth stages (Tuckman and Jensen 1977). Since then, other organizational researchers have suggested other stages including transforming and reforming (White 2009), re-norming (Biggs), and outperforming (Rickards and Moger 2002).

What does the future hold for this line of research?

To help answer this question, we wrote a regular expression to identify candidate words and placed the full list is at this page in the Community Data Science Collective wiki.

The good news is that despite the active stream of research producing new stages that end or rhyme with -orming, there are tons of great words left!

For example, stages in a group’s development might include:

• Scorning: In this stage, group members begin mocking each other!
• Misinforming: Group that reach this stage start producing fake news.
• Shoehorning: These groups try to make their products fit into ridiculous constraints.
• Chloroforming: Groups become languid and fatigued?

One benefit of keeping our list in the wiki is that the organizational research community can use it to coordinate! If you are planning to use one of these terms—or if you know of a paper that has—feel free to edit the page in our wiki to “claim” it!

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Also posted on the Community Data Science Collective blog. Although credit for this post goes primarily to Jeremy Foote and Benjamin Mako Hill, the other Community Data Science Collective members can’t really be called blameless in the matter either.