Hawthorne Effect: Definition, How It Works, and How to Avoid It

Key Takeaways

  • The Hawthorne effect refers to the increase in the performance of individuals who are noticed, watched, and paid attention to by researchers or supervisors.
  • In 1958, Henry A. Landsberger coined the term ‘Hawthorne effect’ while evaluating a series of studies at a plant near Chicago, Western Electric’s Hawthorne Works.
  • The novelty effect, demand characteristics and feedback on performance may explain what is widely perceived as the Hawthorne effect.
  • Although the possible implications of the Hawthorne effect remain relevant in many contexts, recent research findings challenge many of the original conclusions concerning the phenomenon.

The Hawthorne effect refers to a tendency in some individuals to alter their behavior in response to their awareness of being observed (Fox et al., 2007).

This phenomenon implies that when people become aware that they are subjects in an experiment, the attention they receive from the experimenters may cause them to change their conduct.

Hawthorne Experiments

The Hawthorne effect is named after a set of studies conducted at Western Electric’s Hawthorne Plant in Cicero during the 1920s. The Scientists included in this research team were Elton Mayo (Psychologist), Roethlisberger and Whilehead (Sociologists) and William Dickson (company representative).

Western Electric’s
 Hawthorne Plant in Cicero during the 1920s

There are 4 separate experiments in Hawthorne Studies:

  1. Illumination Experiments (1924-1927)
  2. Relay Assembly Test Room Experiments (1927-1932)
  3. Experiments in Interviewing Workers (1928- 1930)
  4. Bank Wiring Room Experiments (1931-1932)

Illumination Experiment

The first and most influential of these studies is known as the “Illumination Experiment”, conducted between 1924 and 1927 (sponsored by the National Research Council).

The company had sought to ascertain whether there was a relationship between productivity and the work environments (e.g., level of lighting in a factory).

During the first study, a group of workers who made electrical relays experienced several changes in lighting. Their performance was observed in response to the minutest alterations in illumination.

What the original researchers found was that any change in a variable, such as lighting levels, led to an improvement in productivity. This was true even when the change was negative, such as a return to poor lighting.

However, these gains in productivity disappeared when the attention faded (Roethlisberg & Dickson, 1939). The outcome implied that the increase in productivity was merely the result of a motivational effect upon the company’s workers (Cox, 2000).

Their awareness of being observed had apparently led them to increase their output. It seemed that increased attention from supervisors could improve job performance.

Relay Assembly Test Room Experiment

Spurred by these initial findings, a series of experiments were conducted at the plant over the next eight years. From 1928 to 1932 Elton Mayo (1880–1949) and his colleagues began a series of studies examining changes in work structure (e.g., changes in rest periods, length of the working day, and other physical conditions.) in a group of five women.

The results of the Elton Mayo studies reinforced the initial findings of the illumination experiment. Freedman (1981, p. 49) summarizes
the results of the next round of experiments are as follows:

“Regardless of the conditions, whether there were more or fewer rest periods, longer or shorter workdays…the women worked harder and more efficiently.”

Analysis of the findings by Landsberger (1958) led to the term the Hawthorne effect, which describes the increase in the performance of individuals who are noticed, watched, and paid attention to by researchers or supervisors.

Hawthorne Effect in Research

In a separate study conducted between 1927 and 1932, six women working together to assemble telephone relays were observed (Harvard Business School, Historical Collections).

Following the secret measuring of their output for two weeks, the women were moved to a special experiment room. The experiment room, which they would occupy for the rest of the study, had a supervisor who discussed various changes to their work.

The subsequent alterations the women experienced included breaks varied in length and regularity, the provision (and the non-provision) of food and changes to the length of the workday.

For the most part, changes to these variables (including returns to the original state) were accompanied by an increase in productivity. The researchers concluded that the women’s awareness of being monitored, as well as the team spirit engendered by the close environment improved their productivity (Mayo, 1945).

Subsequently, a related study was conducted by W. Lloyd Warner and Elton Mayo, anthropologists from Harvard (Henslin, 2008).

They carried out their experiment on 14 men who assembled telephone switching equipment. The men were placed in a room along with a full-time observer who would record all that transpired. The workers were to be paid on their individual productivity.

However, the surprising outcome was a decrease of productivity. The researchers discovered that the men had become suspicious that an increase in productivity would lead the company to lower their base rate or find grounds to fire some of the workers.

Additional observation unveiled the existence of smaller cliques within the main group. Moreover, these cliques seemed to have their own rules for conduct and distinct means to enforce them.

The results of the study seemed to indicate that workers were likely to be influenced more by the social force of their peer groups than the incentives of their superiors.

This outcome was construed not necessarily as challenging the previous findings, but as accounting for the potentially stronger social effect of peer groups.

Hawthorne Effect Examples

Managers in the Workplace

The studies discussed above reveal much about the dynamic relationship between productivity and observation.

On one hand, letting employees know that they are being observed may engender a sense of accountability. Such accountability may in turn improve performance.

However, if employees perceive ulterior motives behind the observation, a different set of outcomes may ensue. If for instance, employees reason that their increased productivity could harm their fellow workers or adversely impact their earnings eventually, they may not be actuated to improve their performance.

This suggests that while observation in the workplace may yield salutary gains, it must still account for other factors such as the camaraderie among the workers, the existent relationship between the management and the employees, and the compensation system.


A study that investigated the impact of awareness of experimentation on pupil performance (based on direct and indirect cues) revealed that the Hawthorne effect is either nonexistent in children between grades 3 and 9, was not evoked by the intended cues, or was not sufficiently strong to alter the results of the experiment (Bauernfeind & Olson, 1973).

However, if the Hawthorne effect were actually present in other educational contexts such as in the observation of older students or teachers, it would have important implications.

For instance, if teachers were aware that they were being observed and evaluated via camera or an actual person sitting inside the class, it is not difficult to imagine how they might alter their approach.

Likewise, if older students were informed that their classroom participation would be observed, they might have more incentives to pay diligent attention to the lessons.

Alternative Explanations

Despite the possibility of the Hawthorne effect and its seeming impact on performance, alternative accounts cannot be discounted.

The Novelty Effect

The Novelty Effect denotes the tendency of human performance to show improvements in response to novel stimuli in the environment (Clark & Sugrue, 1988).

Such improvements result not from any advances in learning or growth, but from a heightened interest in the new stimuli.

Demand Characteristics

This describes the phenomenon in which the subjects of an experiment would draw conclusions concerning the experiment’s objectives, and either subconsciously or consciously alter their behavior as a result (Orne, 2009).

The intentions of the participant—which may range from striving to support the experimenter’s implicit agenda to attempting to utterly undermine the credibility of the study—would play a vital role herein.

Feedback on Performance

It is possible for regular evaluations by the experimenters to function as a scoreboard that enhances productivity. The mere fact that the workers are better acquainted with their performance may actuate them to increase their output.


Despite the seeming implications of the Hawthorne effect in a variety of contexts, recent reviews of the initial studies seem to challenge the original conclusions.

For instance, the data from the first experiment were long thought to have been destroyed. Rice (1982) notes that “the original [illumination] research data somehow disappeared.”

Gale (2004, p. 439) states that “these particular experiments were never written up, the original study reports were lost, and the only contemporary account of them derives from a few paragraphs in a trade journal.”

However, Steven Levitt and John List of the University of Chicago were able to uncover and evaluate these data (Levitt & List, 2011). They found that the supposedly notable patterns were entirely fictional despite the possible manifestations of the Hawthorne effect.

They proposed excess responsiveness to variations induced by the experimenter, relative to variations occurring naturally, as an alternative means to test for the Hawthorne effect.

Another study sought to determine whether the Hawthorne effect actually exists, and if so under what conditions it does, and how large it could be (McCambridge, Witton & Elbourne, 2014).

Following the systemic review of the available evidence on the Harthorne effect, the researchers concluded that while research participation may indeed impact the behaviors being investigated, discovering more about its operation, its magnitude and its mechanisms require further investigation.

How to Reduce the Hawthorne Effect

The credibility of experiments is essential to advances in any scientific discipline. However, when the results are significantly influenced by the mere fact that the subjects were observed, testing hypotheses becomes exceedingly difficult.

As such, several strategies may be employed to reduce the Hawthorne Effect.

Discarding the Initial Observations:

  • Participants in studies often take time to acclimate themselves to their new environments.
  • During this period, the alterations in performance may stem more from a temporary discomfort with the new environment than from an actual variable.
  • Greater familiarity with the environment overtime, however, would decrease the effect of this transition and reveal the raw effects of the variables whose impact the experimenters are observing.

Using Control Groups:

  • When the subjects experiencing the intervention and those in the control group are treated in the same manner in an experiment, the Hawthorne effect would likely influence both the groups equivalently.
  • Under such circumstances, the impact of the intervention can be more readily identified and analyzed.


  • Where ethically permissible, the concealment of information and covert data collection can be used to mitigate the Hawthorne effect.
  • Observing the subjects without informing them, or conducting experiments covertly, often yield more reliable outcomes. The famous marshmallow experiment at Stanford University which was conducted initially on 3 to 5-year-old children is a striking example.


Bauernfeind, R. H., & Olson, C. J. (1973). Is the Hawthorne effect in educational experiments a chimera? The Phi Delta Kappan, 55 (4), 271-273.

Clark, R. E., & Sugrue, B. M. (1988). Research on instructional media 1978-88. In D. Ely (Ed.), Educational Media and Technology Yearbook, 1994. Volume 20. Libraries Unlimited, Inc., PO Box 6633, Englewood, CO 80155-6633.

Cox, E. (2001).  Psychology for A-level. Oxford University Press.

Fox, N. S., Brennan, J. S., & Chasen, S. T. (2008). Clinical estimation of fetal weight and the Hawthorne effect. European Journal of Obstetrics & Gynecology and Reproductive Biology, 141 (2), 111-114.

Gale, E.A.M. (2004). The Hawthorne studies – a fable for our times? Quarterly Journal of
Medicine, (7)

Henslin, J. M., Possamai, A. M., Possamai-Inesedy, A. L., Marjoribanks, T., & Elder, K. (2015). Sociology: A down to earth approach. Pearson Higher Education AU.

Landsberger, H. A. (1958). Hawthorne Revisited: Management and the Worker, Its Critics, and Developments in Human Relations in Industry.

Levitt, S. D., & List, J. A. (2011). Was there really a Hawthorne effect at the Hawthorne plant? An analysis of the original illumination experiments. American Economic Journal: Applied Economics, 3 (1), 224-38.

Mayo, E. (1945). The human problems of an industrial civilization. New York: The Macmillan

McCambridge, J., Witton, J., & Elbourne, D. R. (2014). Systematic review of the Hawthorne effect: new concepts are needed to study research participation effects. Journal of Clinical Epidemiology, 67 (3), 267-277.

McCarney, R., Warner, J., Iliffe, S., Van Haselen, R., Griffin, M., & Fisher, P. (2007). The Hawthorne Effect: a randomised, controlled trial. BMC Medical Research Methodology, 7 (1), 1-8.

Rice, B. (1982). The Hawthorne defect: Persistence of a flawed theory. Psychology Today, 16 (2), 70-74.

Orne, M. T. (2009). Demand characteristics and the concept of quasi-controls. Artifacts in behavioral research: Robert Rosenthal and Ralph L. Rosnow’s classic books, 110, 110-137.

Further Information

Saul Mcleod, PhD

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Educator, Researcher

Saul Mcleod, Ph.D., is a qualified psychology teacher with over 18 years experience of working in further and higher education.

Ayesh Perera


B.A, MTS, Harvard University

Ayesh Perera has worked as a researcher of psychology and neuroscience for Dr. Kevin Majeres at Harvard Medical School.