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In Emotional Contagion in the Workplace - Part I, I wrote about the existence of patterns that can affect productivity in ways that can’t be accurately forecast, and that emotional contagion is one of these patterns. In research published in 2010, researchers from Harvard formally demonstrated that emotions can be thought of as infectious diseases spreading across social networks, including at work.  The study looked at being "content" and "discontent" as two viruses, and found that these emotions could be "caught" from others in the social network. Key findings of the research include:

  • It was possible for individuals to spontaneously become infected (this happens more often for positive emotions);
  • Like a biological virus, individuals would return to a neutral (non-infected) state after the virus had run its' course (though this could take years).
  • Negative emotions (discontent) are twice as contagious as Positive emotions (content); but recovery is twice as fast - so on balance, the rates of discontent and content tend to be about the same in a population.
  • It's also possible to have a "superinfection", where someone who is discontent catches the content virus; or vice-versa.  

This research has significant implications for workplaces.  Many studies have focused on the link between happiness and productivity - according to one, "happier workers were 12% more productive. Unhappier workers were 10% less productive." (source) So what happens when happiness and unhappiness go viral at work?  Even with the same headcount, you get wild fluctuations in output.  Below is a very simple viral contagion model.  At the start, there are equal numbers of happy and unhappy workers (1 in 9); and the bulk of the employees are in a neutral state (78%).  The unpredictable nature of emotional contagion has some interesting effects:

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Because of the randomness / chance of the interactions,  every time you run a simulation you get a different scenario - and because of the contagion aspect, these differences can be significant, even within the same scenario.  If you overlay the figures for productivity; the productivity difference between these scenarios is significant.  The result is that it's difficult to accurately predict output from a workforce over time, even if your hiring and retention rates are constant - and that's just one of the reasons why workforce planning that focuses on headcount planning alone is of limited value.

The good news is that there are actions you can take to boost employee happiness in your organisation, and minimise the fallout of the viral contagion of negative emotions.  In part III I'll be writing about some of the ways you boost productivity, even if you can't predict it.

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