After the bleak time we had in the financial markets last week, I thought I’d switch gears and blog about a psychological concept. The “Stimulus” in the title of this post refers to emotional and not fiscal stimulus. The Yerkes-Dodson Law is a century old idea from behavioral psychology that still has relevance today.
Quite simply, the Yerkes-Dodson Law illustrates the impact that emotional arousal has on the performance of tasks. For very simplistic tasks, arousal has a linear relationship with performance. That is, the greater the stress, the greater the performance. However, for complex tasks, performance follows a parabolic curve. At too low a level of arousal, an individual can become bored or unfocused. At too high a level, an individual can become stressed and overwhelmed. There is typically a midpoint of arousal that leads to optimum levels of task performance.
Yerkes and Dodson were Harvard physicians that were looking to understand the relationship between stress and learning. Their experiments looked at the effect of electric shocks on mice that were performing a task. If mice performed the task (entering a box through a white door) incorrectly they would receive a shock as corrective feedback. The experiment demonstrated that a small shock was insufficient to be a motivator for learning. Large shocks would prove too stressful or disorienting, again leading to poor results. It was the “medium” shocks that had the most positive effect on task performance.
While Yerkes-Dodson is an older finding, it has been validated by numerous, more recent research. It was replicated with rats by (Broadhurst, 1957) and people (Anderson, 1994; Dickman, 2002). Similar findings with squirrels were achieved in a 2008 University of Chicago study. It is a well accepted concept in behavioral psychology.
Let’s look at some real life examples of Yerkes-Dodson in action. A recent article in Wired talked about how car safety devices could counterintuitively make driving less safe. Such new features as adaptive cruise control and automatic braking could lull people into a very relaxed state that would lower their vigilance and driving performance. At the opposite end of the spectrum (e.g. rush hour traffic in midtown Manhattan) drivers can become overwhelmed by the high levels of stimulus, unable to focus on the multitude of concurrent threats.
In the world of aviation safety, much has been written about the plight of air traffic controllers. Given too little stimulation (e.g. night shifts at a low traffic airport) and they can become inattentive and ultimately sleepy. Given too much stimulation (e.g. prime time at a busy airport) they can become overloaded, making bad decisions, missing important alerts and even panicking.
You may be thinking that all of this is obvious and intuitive. But there are important takeaways and considerations for the design of work in an increasingly automated and technology intensive world. First, the job function of monitoring takes on increasing importance in a 24/7 world of mission critical technology services. Examples of theses functions are systems, network and security monitoring. While there are benefits to automating theses functions, most environments still have exceptions that need to be handled by a human operator. Too high a level of automation turns people into listless robots, unable to respond effectively when the rare exception occurs. Too high a volume of issues creates the same negative scenario experienced by the overloaded air traffic controller.
In addition to operational personnel, knowledge workers face the same threat from poorly optimized work environments. There is a growing trend of “hyperspecialization” of work, with tasks being fragmented in smaller slices. This trend is gaining traction both within enterprises as well as with outsourced services. Thomas Malone of MIT explains the trend in this short video. As he explains, there are clearly potential benefits such as access to expertise and reduced labor costs with this approach. However, with Yerkes-Dodson in mind, we can predict that too much segmentation of tasks will create an environment that will not result in optimal performance. It will lead to an un-stimulating environment that is not conducive to the performance of complex knowledge work.