Jonah Lehrer (2009) similarly referenced studies conducted at MIT in which students given access to large amounts of data performed poorly in predicting stock prices when compared with a control group of students with access to far less information. He notes that the prefrontal cortex of the brain has great difficulty NOT paying attention to large amounts of information which can overwhelm the ability of the brain to estimate and predict. Access to excessive quantities of information can have “diminishing returns” when conducting assessments and predicting future outcomes, he says. Lehrer comments that corporations, in particular, often fall into the “excessive information” trap and invest huge amounts of resources in collecting data that can then overwhelm and confuse the human brain, versus the intent of informing decision-making.
Lehrer describes the remarkable situation of medical doctors diagnosing back pain several decades ago. With the introduction of MRI in the 1980’s and with far greater detail available, medical practitioners hoped that increasingly better predictions of the sources of back pain would be made. The converse happened. Massive amounts of detail produced by the MRI actually worsened their assessment and predictive capabilities – poorer assessments were made. Kahneman refers to scenarios that contain a high level of complexity, uncertainty and unpredictability as “low-validity environments”. Experts can become overwhelmed by complexity in decision-making. Leadership coaches can assist greatly by developing checklists or other simple decision support tools to limit biases and confusion from data overload.
The power of simple checklists
The power of something as simple as a checklist is has been shown by Kahneman to have “saved hundreds of thousands of infants”. He gives the example of newborn infants a few decades ago, where obstetricians had always known that an infant that is not breathing normally within a few minutes of birth is a high risk of brain damage or death. Physicians and midwives through the 1950’s typically used their varying levels of medical judgment to determine whether a baby was in distress. Different practitioners used their own experience and different signs and symptoms to determine the level and extent of this distress. Looking at these different symptoms meant that danger signs were often overlooked or missed, and many newborn babies died. When Virginia Apgar, an American obstetrical anesthesiologist, was asked somewhat casually by a student how to make a systematic assessment of a newborn,
Apgar responded “that’s easy” and jotted down five variables (heart rate, respiration, reflex, muscle tone and color) and three scores (0, 1 or 2 depending on the robustness of each variable). Apgar herself began to use this rating scale in her own work. She began applying this assessment about sixty seconds after birth of all infants she handled. A baby of eight or greater was likely to be in excellent condition. A baby with a score of four or less was in trouble and needed immediate attention. What is now called the “Apgar Test” is used in every delivery room every day and is credited for saving thousands of infant lives. Indeed, a report on CNN.com as recently as March 2014 (Hudson, 2014) indicated that about one in twenty-five patients that seek treatment in US hospitals contracts an infection from the hospital, and that patients acquired some 721,800 infections in 2011. This statistic is however significantly better than previous years, about 44% from 2008 to 2012. This result came from “requiring hospitals to follow a simple checklist of best practices”. Simple checklists focused on complex situations work!
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