Getting Past the Hawthorn Effect

In 1924, the National Research Council sent two engineers to supervise a series of industrial experiments at a large telephone-parts factory called the Hawthorne Plant near Chicago. The idea was that they would learn how shop-floor lighting affected workers’ productivity. Instead, the studies ended up giving their name to the “Hawthorne effect”, the notion that that the act of being observed or experimented upon changes a subject’s behavior.

The theory arose because of the unexpected behavior of the women who assembled relays and wound coils of wire in the plant. The data collected during the study demonstrated that their hourly output rose when lighting was increased, but also when it was dimmed. Simply, as long as something was changed, productivity rose. Out of this arose the notion that as long as the women knew they were being observed, there would be a behavioral change.

But Steven Levitt and John List, two economists at the University of Chicago, decided to analyze the data, which was still available, and see what they found. Contrary to the descriptions in the literature, they found no systematic evidence that levels of productivity in the factory rose whenever changes in lighting were implemented. Now that was unexpected.

It turns out that idiosyncrasies in the way the experiments were conducted may have led to misleading interpretations of what happened. For example, lighting was always changed on a Sunday, when the plant was closed. When it reopened on Monday, output duly rose compared with Saturday, the last working day before the change, and continued to rise for the next couple of days. But a comparison with data for weeks when there was no experimentation showed that output always went up on Mondays. Another of the original observations was that output fell when the trials ceased, suggesting that the act of experimentation caused increased productivity. But the experiment stopped in the summer, and when examining records after the experiment stopped it turns out that output tended to fall in the summer anyway.

It’s all very interesting, yes, but why does it matter?  It matters particularly to ethnographers because one of the central criticisms of the methodology is that our presence negates any of the findings on the basis that we alter the behavior of our participants.  As it turns out, the problem may not be as notable as the critics claim.

I will be the first to admit that our presence does shape the interactions and behavior of the participants, but only in a limited way, and those ethnographers worth their weight in salt are able to establish rapport in such a way that changes are minimal. Time is, of course, the driving factor in this. Participant observation, the foundation of ethnography, refers to a methodology in which the researcher takes on a role in the social situation under observation. The social researcher immerses herself in the social setting under study, getting to know key actors in that location in a role which is either covert or overt, although in practice, the researcher will often move between these two roles. The aim is to experience events in the manner in which the subjects under study also experience these events. Success is defined, in many respects, by the nature of the relationship that develops. As such, a good ethnographer becomes another actor rather than simply an observer, thus largely negating or minimizing the changes subjects display.

What this means for the researcher is that conducting ethnographic work means doing more than interviewing. It means learning to conduct research that involves a range of anthropologically-informed tools. For the buyer of researcher, it means questioning your vendor, thinking through what they propose and be willing to do research in a way that may make you initially uncomfortable – digging through the dirt with an HVAC installer or bar hopping with a twenty-something through NY may seem a little daunting at first, but these are the things that make for good research and, more importantly, good insights.



One thought on “Getting Past the Hawthorn Effect

  1. Very nice post! I am thinking about all the shop alongs and shoppers with eyetracking devices. And even worse, these data is then used for strategic decision-making.

    Thanks for sharing Gavin!



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