We were happy to be invited to speak at Milano Arch Week 2019 on applying Behavioural Design to urban planning or as they liked to refer to it ‘Urban Regeneration’. We are happy that architects are opening up to our practice of Behavioural Design to build cities that work for people living in it and to use architecture to modify public behaviour.
Our talk included Behavioural Design examples from my Instagram feed. Some of the examples we referred to were the Ballot Bin that gets cigarette smokers to stub their cigarette buds at the Ballot Bin because they are motivated to vote for their choice, whether the choice is about your favourite football player or some other topical question. We were asked about Bleep horn reduction system as a Behavioural Design nudge to reduce drivers’ honking. We spoke about how the Bureau of Energy Efficiency (BEE) in India has made it mandatory for appliances to come with star ratings and how it’s nudging people to choose higher star rated appliances so that people can save money and in doing so also consume lower power and contribute towards climate crisis in a positive manner. Some of the other examples we spoke about were Behavioural Design nudges to reduce overspeeding, getting people to – use trash bins in the outdoor, use sanitizers in hospitals, use stairs instead of escalators, and many more. If you’re curious to know more, click here.
Recently it was reported that a 9W 697 Mumbai-Jaipur flight was turned back to Mumbai after take off as, during the climb the crew forgot to select the bleed switch to maintain cabin pressure. This resulted in the oxygen masks dropping. Thirty out of 166 passengers experienced nose and ear bleeding, some also complained of headache.
Aviation safety experts say such an incident was “extremely rare” as turning on the bleed switch is part of a check-list that pilots are expected to mandatorily adhere to. If turning on a switch that regulated cabin pressure is part of standard protocol, how could the pilots make such a simple, common-sensical error. And more importantly how can such errors be avoided in the future?
Traditional thinking suggests increasing the training of the pilots so that it makes them better and thereby avoid such errors. But training is not a full-proof method of ensuring human errors don’t get repeated. That’s because as long as humans need to rely on their memory to ensure the cabin pressure switch is turned on, errors are bound to happen. Sure check lists work. But that’s still a manual method of ensuring that the switch is turned on. And after repeatedly performing the tasks on the checklists over multiple flights, checklists themselves become routine habitual tasks done without much thinking. Also given that there are multiple tasks pilots need to perform in the 3-4 minutes after taking off, the chance of errors happening during those critical moments becomes high.
So instead of the pilot having to rely on their memory or routine check-lists, the answer to avoid such human errors lies in implementing simple behavioural design nudges. For example, if there was a continuous audio-visual reminder that the bleed switch had not been turned on, it would draw the pilot’s attention and it would be highly likely they would have turned it on. Such an audio-visual reminder was not present in this kind of an older generation of aircraft, and therefore the chance of human error increased.
The Japanese have a term for such error-proofing – poka yoke. This Japanese word means mistake proofing of equipment or processes to make them safe and reliable. These are simple, yet effective behavioural design features that make it almost impossible for errors to occur. The aim of error-proofing is to remove the need for people to think about the products or processes they are using. Some examples of behaviourally designed products used in everyday life are the microwave oven that doesn’t work until the door is shut or washing machines that start only when the door is shut and remains shut till the cycle is over. Elevator doors now have sensors that cause them to not close when there is an obstruction. This prevents injury to someone trying to enter as the doors are closing.
Human behaviour cannot be trusted to be as reliable as a machine. In fact, human behaviour is far from perfect. Yes, the people who operate expensive and complicated machines may be the best trained, but human errors in the form of simple error, lapse of judgment or failure to exercise due diligence are inevitable. According to Boeing, in the early days of flight, approximately 80 percent of accidents were caused by the machine and 20 percent were caused by human error. Today that statistic has reversed. Approximately 80 percent of airplane accidents are due to human error (pilots, air traffic controllers, mechanics, etc.) and 20 percent are due to machine (equipment) failures.
Another instance of how systems could be made safe by applying behavioural design is of airplane emergency evacuations. During the emergency landing of the Emirates flight EK521 at the Dubai airport in 2016, passengers were running to get their bags from the overhead cabins, instead of evacuating the plane. Only when the airplane staff began yelling at them to leave their bags and run, did the passengers finally pay heed to their calls and evacuate. Just a few minutes after the evacuation, the plane caught fire. It was a near miss situation. Had even a few passengers waited to get their bags from the overhead cabins, many of them would have got engulfed in fire. Again the natural instinct to correct such a situation would be to train people to evacuate and get them to listen to the flight’s safety instructions. But behavioural science studies have proven that such efforts are time-consuming, money-draining, unscalable and most importantly ineffective at changing human behaviour. In such an emergency situation, if the overhead cabins were automatically locked, with a label “Locked due to emergency”, passengers would not waste time trying to open them. That would in turn get passengers to behave in the desired manner and evacuate faster.
Sometimes behavioural design nudges are intuitive. Other times they are counter-intuitive. In a fire-drill experiment by behavioural scientist Daniel Pink, he found that placing an obstacle like pillar in the middle of a doorway got people to exit a hall 18% faster than without the pillar. The pillar was an obstacle but it split up people into two streams at the exit. That got people to use each side of the door, which in turn made the flow of people exiting the hall a lot smoother and faster. When the pillar wasn’t there to separate them at the exit, people bottle-necked at the door making the exit slower. Likewise, behavioural design could go a long way to design safer buildings, machines and systems and reduce human errors.
We found the connection between Psychology and Physiology so intriguing that we did more research and found more studies done on it. Intuitively it makes sense – the mind affects the body and the body affects the mind, but chancing upon hard scientific evidence makes it even more convincing.
So Becca Levy and colleagues at Yale got senior citizens over the age of 70 to take a special hearing test. A sequence of three ascending pitches for each ear was played. Each time a senior citizen heard a tone, they were supposed to raise their hand. The average score was 3.53 out of 6.
Next the seniors were asked to write the first five words that came to mind when they thought of an old person. The researchers noted how each senior responded and categorized each answer. The first category was from very positive (e.g. compassionate) to very negative (e.g. feeble). The second category was from external (e.g. white hair) to internal (e.g. experienced). The researchers got two sets of data – hearing test and attitude profile of each senior.
Three years later, the same seniors were invited to take the same hearing test again. This time the average score dropped. But not all participants’ hearing deteriorated equally. Those seniors who used negative and external descriptors to describe old age were worse off. Even after isolating other factors that would diminish hearing e.g. medical condition, the researchers found that the negative and external descriptors were responsible for a 0.7-point drop in a senior’s score – amounting to eight years of normal aging – in just three years. Even participants who scored a full 6 in the first round, and had used negative and external descriptors, experienced worse off diminished hearing.
This proves that negative and external feelings about old age can actually make people physically age faster. The effect is not limited to hearing alone, but to memory loss, cardiovascular weakness and even a reduction in overall life expectancy by an average of 7.5 years.
Hearing decline predicted by Elders’ stereotypes – Becca Levy, Martin Slade, Thomas Gill – Journal of Gerontology: Psychological Sciences 61B (2006): 82-88
Longevity increased by positive self-perceptions of aging – Becca Levy, Martin Slade, Suzanne Kunkel and Stanislav Kasl – Journal of Personality and Social Psychology 83 (2002): 261-70
Longitudinal benefit of positive self-perceptions of aging on functional health – Becca Levy, Martin Slade and Stanislav Kasl – Journal of Gerontology: Psychological Sciences 56B (2002): 409-17
Improving memory in old age through implicit self-stereotypes – Becca Levy – Journal of Personality and Social Psychology 71 (1996): 1092-1107
That’s what happened in South Africa when a bank wanted to push personal loans to fifty thousand of its customers. In a field experiment conducted by Bertrand, Karlan, Mullainathan, Shafir and Zinman, the bank crafted several variations of the loan offer letter.
They tested lots of variations in features of a direct mailer sent to 53,000 potential customers with formal jobs in urban and semi-urban parts of South Africa. Some of the features varied were proposing uses of the loan, presenting more examples of loans – like loan amount, tenure, rate, payable amount, etc.; displaying interest rates in different ways, showing competitors rates and showing a picture of a pretty woman.
The letters included different interest rates (ranging from 3.25% to 7.75% per month); some featured comparison to a competitor’s rate; others a lucky draw – ten cell phones up for grabs each month; still others a photo of either a man’s or a woman’s pleasant, smiling face. The versions were randomly assigned and mailed off.
To start with the obvious one – customers were significantly more likely to apply for low-rate loans. But two other factors were influential in getting customer response, though they had nothing to do with the terms of the loan. One – the number of loan examples. Mailers with four examples of loans attracted far fewer applicants than mailers with just one example. Presenting more options drove away customers. Showing one loan example instead of four attracted as many additional applicants as dropping the interest rate by about a third!
Second, adding a picture of a pleasant, smiling face of a woman had the same effect on men as lowering the loan’s interest rate by 25%. Surely no customer would say that his decision to borrow boiled down to the picture in the corner of the mailer, but the data was there to prove it. Having a picture of a pretty woman logically doesn’t make for a better financial offer, but what happened is that the men were attracted to the woman and therefore signed up for the loan. And interestingly customers (in South Africa) didn’t respond any differently when the race of the woman was varied. The effect of a woman’s photo on women didn’t make much of a difference as it did on men.
No man would consciously sign up for a higher interest loan just because the offer letter had a picture of a woman on it, right? But male customers made errors in evaluating the attractiveness of the loan because they didn’t focus on the important data. Instinct took over. That’s why its best to A/B test Behavioural Design solutions to know which ones work. Without testing, you will never know what works, what doesn’t and which could be the best solution.
Source: Marianne Bertrand, Dean Karlan, Sendhil Mullainathan, Eldar Shafir and Jonathan Zinman – What’s advertising content worth? A field experiment in the consumer credit market – Quarterly Journal of Economics 125 (1), February 2010.
Drinking water is essential to human health. The amount one should drink varies from person to person based on gender, age, height, weight, physical activity, sweat levels, metabolism level, body temperature, humidity levels, external temperature, altitude, quantity and quality of food intake, quantity and quality of other fluids’ intake and host of other details. When you don’t get enough water, every cell of your body is affected. You lose a lot of electrolytes, including sodium, potassium and chloride, which are essential to your body’s functions. Pretty much all of your cellular communications revolve around sodium and potassium, including muscle contractions and action potentials. Fatigue, lethargy, headaches, inability to focus, dizziness and lack of strength are all signs of dehydration. Nature has given us a powerful alert system – thirst. But in our busy chaotic lives we often ignore it and forget to drink water.
Behavioural Design vs awareness
There is enough information about why we should drink more water, yet most people feel they don’t drink enough. Education doesn’t change behaviour.
Behavioural change requires a different approach. Drinking water regularly is a good habit. Habits are essentially automatic in nature, where one does not consciously think about the action. In other words, habits are auto-pilot behaviours. For a behaviour to become a habit, it requires three things to come together – trigger, action and reward. When the loop gets completed, the habit sets into place. For example, over a period of time we have gotten used to waking up in the morning (trigger), brushing our teeth (action) and feeling fresh (reward). To create good habits, initially conscious effort is required. However, we humans are lazy, so the lesser the effort to get the habit started, the better. Eg. We forget to drink water during the day. So if there’s a trigger like a reminder from the water bottle, we’re likely to drink water. Over time the action of opening the water bottle because of the reminder can become auto-pilot i.e. become a habit. This approach led us to create a water bottle that glowed and beeped that gently nudged people to drink water 16% more.
We chose to do an experiment in an office of one of our corporate clients. The administration department of that company would keep filled-water-bottles on the desk of each employee every morning and refill it once every evening. So we bought the same type of water bottles for our experiment so as to not draw any suspicion amongst participants. And we created two versions of caps. In the first version of the cap, we fitted a chip which recorded the number of times the water bottle was opened. In the second version of the cap, we fitted a chip which recorded the number of times the water bottle was opened and in addition, the cap now glowed and beeped once after every two hours of the water bottle being opened. If the bottle wasn’t opened, then the cap would glow and beep after an hour. When the water bottle was opened, the cap would sense it and stop glowing. In both versions the chip was hidden inside the caps.
Creating prototypes of both versions of water bottle caps took longer and was costlier than we expected (planning fallacy). We could only produce a total of 70 water bottle caps over more than a year. Thirty-five pieces of each version – first version with recording chip without glow and beep and second version with recording chip with glow and beep. Because of being able to produce 70 water bottle caps we chose to randomly select thirty-five participants from the office employees who wished to participate in our experiment.
In week 1 we gave them our similar looking water bottles with the first version of the cap with recording chip hidden in it. In week 2 we replaced the caps with the second version of the cap with the recording chip with the glow and beep. We accounted for data from Monday morning to Friday night in both weeks. We then compared the data of how many times the water bottle was opened with the numbers of hours the employees had spent in office on each day of Week 1 (no glow and beep) and Week 2 (glow and beep). Had we been able to conduct the experiment amongst a larger set of sample, we would have chosen the typical control group and treatment group, but due to the above mentioned capacity, time and money constraints we did a before-and-after format for this experiment.
In week 2 employees opened the water bottles 16% more than in week 1. It means the employees were not sufficiently hydrated with regular water bottles even though they were kept on their desk right in front of their eyes. The simple Behavioural Design of glow and beep water bottle caps got employees to drink 16% more frequently than without the Behavioural Design nudge.
Frequently asked questions
Q. How much water does one need?
A. Scientific studies are inconclusive on the amount of water required by an adult. Some say its 3 litres. Some say 2.5 litres. Some (Mayo clinic) say for men its 3 litres and for women its 2.2 litres. But fact is that calculating how much water you need depends upon your gender, age, height, weight, physical activity, sweat levels, metabolism level, body temperature, humidity levels, temperature, altitude, quantity and quality of food intake, quantity and quality of other fluids intake and host of other reasons. It’s extremely difficult to calculate real time hydration levels accurately.
Q. Why didn’t we create a bottle that could calculate how much water each individual person needed?
A. To do that we’d need to know people’s gender, age, height, weight, physical activity, sweat levels, metabolism level, body temperature, humidity levels, temperature, altitude, quantity and quality of food intake, quantity and quality of other fluids intake and host of other details. It’s extremely difficult to calculate real time hydration levels accurately. Sensors and software that can capture all of the above seamlessly are very expensive as of date. Measuring only some of the inputs would lead to an inaccurate result that would be misleading. So we used a simple rule of thumb of drinking water every two hours to stay hydrated.
Q. What’s the best way to judge whether you are hydrated or dehydrated?
A. The most scientific and simplest way to judge whether you are hydrated or dehydrated is to look at the colour of your urine. If your urine is crystal clear it means you’re probably drinking too much water. If its light or mild yellow it means your drinking an adequate amount of water. If its proper yellow or darker it means you need to drink more water. If its brown you need to visit a doctor.
Mild Dehydration Affects Mood in Healthy Young Women – Lawrence E. Armstrong, Matthew S. Ganio, Douglas J. Casa, Elaine C. Lee, Brendon P. McDermott, Jennifer F. Klau, Liliana Jimenez, Laurent Le Bellego, Emmanuel Chevillotte and Harris R. Lieberman – The Journal of Nutrition – 21 December, 2011.
Mild dehydration impairs cognitive performance and mood of men – Matthew S. Ganioa, Lawrence E. Armstronga, Douglas J. Casaa, Brendon P. McDermotta, Elaine C. Lee, Linda M. Yamamotoa, Stefania Marzano, Rebecca M. Lopez, Liliana Jimenez, Laurent Le Bellego, Emmanuel Chevillotte and Harris R. Lieberman – British Journal of Nutrition – Volume 106 / Issue 10 / November 2011, pp 1535-1543
Lawrence E. Armstrong – an international expert on hydration who has conducted research in the field for more than 20 years (professor of physiology in UConn’s Department of Kinesiology in the Neag School of Education)
‘We’re only human’ is a term associated with humans of course, but more so with accidents. But if that were our attitude we wouldn’t be able to learn much on how to prevent them in the future. And thankfully that’s not what happened after the train accident on 6th March, 1989 in Glasgow, Scotland.
That afternoon the train driver, pulled out of Bellgrove station and within half a mile, ploughed head-on into a train travelling in the opposite direction. The driver of the other train died along with another passenger. The driver who caused the accident had to be cut free from the wreckage and lost a leg in the accident.
So how and why did the accident happen?
It was the guard’s responsibility to check that all passengers were either on or off the train and that the signal on the station indicated that it was safe for the train to proceed. The guard admitted that he had not checked the signal, partly because it wasn’t easy from his position at the back of the train and he knew the driver would be able to see it clearly from the front. He rang the usual two bells to give a ready-to-start signal. But the signalman confirmed that the signal was red during the whole time. On the other hand, for the driver, the red signal would have been visible for another 13 or 14 seconds, even after pulling away, but he still didn’t notice it. In the final investigation report, the driver got the majority of the blame for the accident, with the guard cited as a contributory factor, because ultimately it is the driver’s responsibility to check that it is safe to proceed.
The accident happened because the driver had built up a simple habit. When he heard the two bells, he acknowledged it and set off without checking the signal himself.
A Behavioural Design solution was used later to prevent such accidents from happening. A reminder switch was put in the driver’s cabin that cut power to the train, when it was activated. Drivers were made to turn it on when they stopped at a station as an extra safety check. Now if they heard the two bells and tried to apply power immediately, the train wouldn’t move. They had to turn off the reminder switch, and that prompted them to check the signal first. But a system, which halts the train automatically, if the driver jumped the red signal, would be an even better Behavioural Design solution.
Source: Making Habits Breaking Habits by Jeremy Dean
We spoke on ‘Overcoming behavioural biases in investing’ at CafeMutual’s conference for financial advisors in Mumbai on 23rd Feb, 2018. We first introduced Behavioural Design and then followed it up with few examples of behavioural biases in investing, along with possible Behavioural Design solutions to overcome them. The feedback we got from the audience and co-speaker CEOs ranged from ‘thumbs up’ to ‘fantastic insights’ to ‘rocking presentation’. Honestly it was business as usual, but the feedback was great probably because behavioural science is relatively new for people and Behavioural Design nudges are simple, low cost, practical and effective at changing investor behaviour. While we’ve come up with few Behavioural Design nudges to manage our own investing behaviour, we’ve not even scratched the surface in coming up with Behavioural Design solutions for changing investor behaviour for clients. The journey has just begun. Looks like we’ll be creating lots of Behavioural Design nudges for changing investor behaviour – at communication level and product level – for both first-time and evolved investors. Fun.
Imagine you have units of ABC mutual fund. You consider switching to XYZ mutual fund, but don’t. One year passes and you find that you would have made Rs1 lakh more if you had switched to XYZ mutual fund. How would you feel? Now imagine another scenario where you have units of ABC mutual fund, and during the year you switched to XYZ mutual fund. One year passes and you find that you would have made Rs1 lakh more had you kept ABC mutual fund. How would you feel? Which condition would make you feel worse?
Studies by Nobel-winning behavioural scientist Daniel Kahneman and his colleague Amos Tversky have found that 92% of people find the second condition worse. The mistake of an action seems worse than a mistake from inaction. It generates more regret because the first condition is like an opportunity lost whereas the second condition is an actual loss. The second condition translates to seeing oneself as a loser, but not the first. The monetary loss is followed by a psychological loss from admitting you made a mistake. That’s why losses cause a lot of pain.
The region of the brain associated with evaluating negative emotions like pain and disgust is called ‘insula’. When people smell vomit or see a cockroach, the insula bursts into action. The insula also lights up when we lose money. In a study by M.P. Paulus et al, the insula was roughly three times as active after people lost money as it was after they won money. The more intensely the insula fired, the more likely the person was to pick a lower-risk option the next time.
Losing money on an investment is like smelling rotten food, it’s disgusting. We try to move away from it, wipe it off our memory and want to wash our hands off it. That explains why investors, including me, find it difficult to sell an investment when its price is down, since the notional loss will now get converted into actual loss. That makes most people like to believe that the price of the loser investment will go up one day and that’s when we’ll sell it. The thinking goes, ‘If we sell it now and it bounces back, we would have made two mistakes —one buying high and two selling low. If we hold on and it bounces back, we will feel much better.’ However, if we hold on and it doesn’t bounce back, it will be a bigger loss than had we sold it. Hanging on makes sense only if we believe that the investment has value and that value is more than the existing low price of the investment. However, that’s a tough decision which leaves most investors paralytic.
An analysis of 2 million transactions of Finnish investors by behavioural scientists Hersh Shefrin and Meir Statman, found that they are 32% less likely to sell a stock after a sharp fall in price. Professional money managers in Israel cling to their losing stocks for an average of 55 days—more than twice as long as they hold winners. A study by David Harless and Steven Peterson that looked at 97,000 trades, found that investors cashed in on 51% more of their gains than their losses, even they could have raised their average annual returns though by 3.4% points if they had held on to winners and dumped the losers. The study by Martin Weber and Colin Camerer found that among 450,000 trades in 8,000 accounts at a brokerage firm, 21.5% of clients never sold a single stock that had dropped in price. Researchers Zur Shapira and Itzhak Venezia found that new mutual fund managers sold 100% of the stocks ranked at the bottom, implying that their predecessors would have been paralyzed by their own mistakes that only a new person could clean the portfolio. Karl Case and Robert Shiller find that people trying to sell their house hold out longer when they are facing a loss, and will often take the house off the market and not sell, rather than lose money on it.
Dealing with losses is painful, but thinking about the loss differently could help. One behavioural design solution could be to find another investment that you would like to put money into. Think of the proceeds as funding the new investment by selling the loser investment. It will help you generate cash for buying the new investment and you can write off the loss to offset your capital gains and reduce your taxable income. Moreover, the learning of what went wrong should be undertaken by introspecting why the loser investment was originally bought and why its value had changed over time. If the investment still has value and potential, then holding on would make sense. If not, the faster you can sell, the lesser will be your loss.
Our propensity to label people, ideas or things based on our initial opinions of them is so high, that even two simple words have the power to influence it.
Here’s the experiment. A class of MIT students were told that their economics professor was out of town and therefore a substitute instructor would be filling in. The students received a brief bio describing him. Half the students received this version:
Mr._____ is from the Department of Economics and Social Science here at MIT. He has had three semesters of teaching experience in psychology at another college. This is his first semester teaching Economics 70. He is 26 years old, a veteran, and married. People who know him consider him to be a very warm person, industrious, critical, practical, and determined.
The second half received the same bio. Only two words had been changed:
Mr._____ is from the Department of Economics and Social Science here at MIT. He has had three semesters of teaching experience in psychology at another college. This is his first semester teaching Economics 70. He is 26 years old, a veteran, and married. People who know him consider him to be a rather cold person, industrious, critical, practical, and determined.
At the end of the class, each student filled out an identical questionnaire about the substitute instructor. Most students from the first group that received the bio describing him as ‘very warm’, loved him. They described him as good natured, considerate, informal, sociable, popular, humorous and humane. Though the students in the second group sat in the same class, same session, most of these students saw him as self-centered, formal, unsociable, unpopular, irritable, humorless and ruthless!
Just two words have the power to alter our perception of another person and possibly sour the relationship before it even begins. Once we get a label in mind, we don’t notice things that don’t fit within the category. Labeling is important for us to go though the regular day bombarded with information, so that we can organize and simplify. But it also prevents us from seeing things as they are.
No wonder in job interviews, we all put our best show, and not surprisingly we just can’t see the realities of candidates. So while accessing anything look for objective data. From another point of view first impressions matter, so position yourself, your company, your brand to gain that advantage.
Source: Harold Kelley (University of Michigan) – The warm-cold variable in first impression of persons, Journal of Personality 18, no 4 (1950): 431-439.
It has taken millions of years for humans to evolve into the species we are today. But it’s been only a few decades of living with rapid technological and economic development. We have lived among and survived snakes, spiders and other species that could have led to our extinction. That’s probably why our brain has developed parts like the amygdala, which acts as an alarm system, generating fast emotions like fear when we notice anything that’s out of place or scary. The amygdala that induces the fear reflex has helped our ancestors survive and it continues to remain a vital tool in today’s daily life. When we see a face that’s scared, we take cues and act instantly; or, if we smell smoke, the amygdala floods the body with fear signals even before we are consciously aware of being afraid.
However, today, life has been changed dramatically due to money and technology. A potential economic threat makes us panic. When our investments take a sudden drop, we react and sell our investments; making ourselves poorer, not richer. But we feel more comfortable to invest when markets are rising. We do the opposite of what common sense shows us—we need to buy low and sell high to make a profit, but we buy high and sell low. In other circumstances, people avoid investing in the stock markets because they are afraid that the stock market might crash, but have no idea how rising prices eat up their savings and cause a loss of money. We are not good at assessing risk—monetary and non-monetary.
The more vivid and imaginable a risk is, the scarier it feels. Behavioural scientist, Paul Slovic, says people will pay twice as much for an insurance policy that covers hospitalization for ‘any disease’ than one that covers hospitalization for ‘any reason’. Any reason covers any disease, but ‘any reason’ seems vague, while ‘any disease’ is vivid. The vividness fills us with fear. It’s not logical. Decades of behavioural science is proving than we don’t always make rational decisions. On the contrary, we often make decisions based on emotion and therefore the decisions sometimes tend to be not rational. For example, people are scared of flying because a plane crash is vivid. Tons of people, including myself, buy air travel insurance, but if we take probability of a plane crash into account, we will find the air travel insurance not worthwhile. At the same time, driving a car without wearing a seat belt feels perfectly safe for a lot of people in India. Let’s see what the numbers have to say. Last year, no one died in India due to a plane crash compared to more than 1,50,000 people who died in road accidents in 2016. So what’s safer—flying by plane or driving on roads? Here’s another example: terrorism. Terrorism creates images of violence, gun shots, bombs, bloodshed. We feel that the risk of terrorism is uncontrollable. But did you know that only 178 civilians died due to terrorism in India this year. On the other hand, smoking kills 1 million people every year in India. Yet we feel more scared of terrorists than cigarettes. But smokers feel they are in charge and understand the consequences, that’s why the risks seem lower than they truly are.
Says Nobel-winning behavioural scientist, Daniel Kahneman, “We tend to judge the probability of an event by the ease with which we can call it to our mind. The more recently an event has occurred, or the more vivid our memory of something like it in the past, the more available an event will be in our minds and the more probable it will seem to happen again.” Clearly that’s not the right way to assess risk because the event does not become more probable just because it occurred recently. In fact, the best time to ‘value invest’ is when the markets are depressed. That’s likely to be a time when there is more bad news than good news, when corporate performances don’t look that good and when analysts don’t have nice things to say. In other words: when markets are low. However, people judge such times to be risky and stay away from stock markets, and when the markets are rising, people hear positive news all around and most investors find comfort in positive statements made by analysts. Due to this positivity and euphoria, people invest at high levels only to find that the trend doesn’t hold true for long.
Understanding risk is critical to managing money. So when you think about risk, it’s better to use a calculator instead of your heart.