Loss Aversion in a Package

We bought a set of two HP ink cartridges (black and color) and they came in this packaging.

Even if we know that we were supposed to get two cartridges and paid for two, seeing the packaging with three slots (two with the cartridges and one empty) creates the feeling that “something is missing”. It’s like there were supposed to be three and you only got two.

This packaging is a waste of materials and induces a negative affect (feeling) in clients. Why HP? Why?

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Unlearning in Behavioral Science

Recently I came across various materials* which state that many of the things I learned in grad-school at Erasmus University aren’t as I’ve learned them. Among them are the bodies of knowledge on choice overload, priming, ego-depletion etc. (Just as a note, Erasmus Research Institute of Management is in top 3 European research institutes in its field, so I got top level education from highly qualified professors.)

* This piece by Jason Collins I found particularly interesting. 

Nowadays, there is serious doubt casted upon ego-depletion, studies on priming have been challenged on a wide scale, apparently, choice overload doesn’t manifest each and every time and, it seems that, the endowment effect doesn’t manifest in isolated groups of hunter-gatherers, which means that it is not an innate (evolved) human feature.

It looks like I have to unlearn many of the things I have learned.

That’s interesting.

Yet, I can’t simply delete from memory knowledge (information) on ego-depletion (just as an example). Even if I could delete information from my memory, in the case of priming there is no clear list or criterion on which results hold and which don’t.

The situation isn’t as grim as it seems at first glance, particularly for the applied part of behavioral science.

The fact that not every result found in a scientific study (lab or field) doesn’t hold in different contexts is not exactly news. Moreover, people who profoundly understand behavioral science know that there are some strong and some weak phenomena. For example, we know that loss aversion and mental accounting are strong phenomena and we also know / knew that priming is a weak one.

When doing applied behavioral science work, you want to rely on the strong phenomena. Sure, you can use weaker ones such as priming, but you can’t rely on them.

For example, when designing an intervention intended to keep a space clean, it is essential to rely on convenience of trash-cans and social proof (social imitation – more broadly). Yes, you can dispense a citrus scent (olfactory priming) to promote cleanness, but that is more of an add-on and not the core of the intervention.

We knew that priming studies aren’t exactly at the top of reliability and replicability, but most behavioral science specialists have learned about ego-depletion and many (most?) took it as a given.

Apparently it is not.

However, this doesn’t bring huge changes to applied behavioral science work. The most important practical learning from the entire body of knowledge on self-control and ego-depletion is:

Design is more powerful than self-control

And it holds true.

Maybe the self-control issues that we face are not due to ego-depletion; they could be due to fatigue, forgetfulness, lack of (availability of) attention etc. Yet, how we solve them remains unchanged.

The fact that choice overload doesn’t manifest every time and failures of choice architecture aren’t exactly news, either.

Choice architecture works ONLY when there is no clear pre-existing preference (i.e. the chooser faces ambiguity).

I have been saying this in my training on choice architecture since 2013 (when I joined the field).

If in shop A (men) shoes come in sizes 40-45 and in shop B they come in sizes 41-49, I will buy 43 in either shop, simply because that is my shoe size.

For more on this topic read To Be Clear on Ambiguity 

  

Fewer options to choose from is simply easier for the consumer (chooser), but choice is about a lot more than being simple to choose.

Take the example of Total Wine shop(s). This is what they say on their “about” page:

Our typical store carries more than 8,000 different wines from every wine-producing region in the world, including more than 2,000 wines not available in any other store. (source)

Through the lenses of choice overload 8000 different wines sounds crazy. According to the choice overload principle they should have went out of business a long time ago. Here are a few explanations why they’re still doing well.

First, when wanting to be “the place to go to for wines”, you need to have lots of wines.

Second, many wine enthusiasts seek variety and want to explore. (Others simply want to get drunk and probably have an existing preference for the wine with the best alcohol/ price ratio).

Third, a wine bottle is a low-impact purchase. If you buy something you don’t like it’s just a few (more) dollars spent for an interesting* experience.

*interesting is a word used when you don’t like something and either you don’t admit it or you don’t want to say it out-loud.

For full fairness, Total wine uses choice architecture and offers a lot of structured choice.

Just as a rhetorical question:

Why do we put choices about houses, retirement plans in the same category with ones about jams, wine and coffee?

This, however, is another story.

Coming back to the applied part of behavioral science: We have to test if our interventions work or not, thus we can assess in each particular case how the number of choices offered influences the outcome.

When doing applied behavioral science we have to take into account the bigger picture.

For example, if in a coffee shop reframes the “bring your own cup” discount into a surcharge for paper-cups behavior shifts towards the desired direction: fewer paper cups used. However, it may also lead to a decrease in clients who simply don’t like the idea of paying explicitly for paper cups, even if the total price is the same as at the coffee shop across the street where the paper cup is included.

Moreover, clients who intended, but forgot to bring their own cup will feel bad (due to loss aversion) for having to pay for a paper cup. Moreover, they will experience regret, which is one of those emotions you don’t want to have associated with your business.   

One of the beauties of science is that it evolves and if we are to be professionals in a field of (applied) science we need to keep up with it and, occasionally, unlearn things. 

Look Beyond What You See! Loosing on One Hand, sometimes, Comes with Larger Gains on the Other

Not very long ago, I wrote a post regarding the not so fortunate habit of small entrepreneurs of focusing on loses on small mental accounts and ignoring the wider picture: Shooting yourself in the foot with loss aversion and mental accounting.

Recently I came across a very interesting article about the psychology of returning products (open in a new tab and read later).

Getting returns can be the worst thing possible for a small-shop keeper because she loses the profit on a previous transaction and, often, has to incur a larger loss due to the impossibility of re-selling the returned product. Moreover, receiving returned products involves some additional costs such as a dedicated employee, shipping etc.

In my country of birth – Romania – for several years after the fall of communist dictatorship, many shop keepers held a no return policy even if the product was faulty. In many cases this happened even after it was illegal to do so. Merchants didn’t want to take any loss on previous transactions.

Yet, according to the article mentioned above, things aren’t as bad as a (psychology naïve) shop keeper might think. Actually, making easier for customers to return a product (even if it has no “technical” fault), is good for business. Longer time spans in which a buyer can return a product and no questions asked policy are, in fact, good for business.

The psychological mechanisms at play are numerous and rather complex:

Endowment effect: the longer I have a product the more I value it because it’s mine,

Managing anticipated regret: because it is easy to change my decision – return the product – I feel less potential future regret with the purchase, thus I go along with it,

The affect heuristic: I don’t feel bad when I return a product, thus I like the merchant more etc.

In a nutshell, adopting more customer friendly return policies will increase the number of occasional transactions that are unprofitable (bring loses), but overall, more people will buy and profits will increase.

On a different line of thought, in Romania (my country of birth) smoking was banned in all public indoor spaces (except for jails). I know that in most civilized countries such bans existed for many years, but we’re a bit behind.

When the bill was still under debate, many restaurant and bar owners complained that if such a ban would be enforced they will lose a lot of business.

While it is very plausible that some smokers will go less frequently to bars and restaurants, there is another side to the story. Many of the 75% of Romanians who don’t smoke avoided going into smoky bars and restaurants. Some of them might go out more often and restaurants and bars can get business from them.  

We don’t know yet how restaurant and bar businesses will be affected by this complete ban on smoking (the law will be enacted starting March), but judging by the base rates – 25% of the population smokes while 75% doesn’t – I think that there is a good chance that the ban will be good for business.

The two situations described in this post: returning products and a complete ban on smoking in restaurants and bars can be seen as unrelated. Yet, there is an underlying commonality: We humans have a (bad) tendency to think that what we see is all there is. When a change takes place, we focus on the immediate imaginable things that will happen.

Both shopkeepers and restaurant owners focus(ed) on the immediate losses their businesses (would) suffer. Only after scientific research and deliberate thinking the opportunities (gains) became visible.

Look beyond what you see!

4 Behavioral Science Reasons Why Recently Dead Artists’ Album Sales Sky-Rocket

A couple days ago, David Bowie passed and (apparently) his albums sell like warm bread during a famine. Nothing New! A few years ago, after Michael Jackson’s death the same thing happened (though, then with Michael Jackson albums; Bowie’s albums didn’t sell any better than before MJ’s death).

While from a Normative Economics point of view, this sky-rocketing sales phenomenon might seem irrational or, at least, puzzling, in fact, there are very good reasons (explanations) that come from behavioral science.

1: SALIENCE – Huge Media Exposure. While many music fans knew about David Bowie (read any recently dead musician), his name and music wasn’t in the media all that much in recent times. However, because he was (used to be) famous, the media from the USA to Romania and from the UK to Singapore mentioned his death accompanied by some kind of eulogy on his remarkable career.

When something is (very) salient, people tend to give it attention and even buy it.

2: SCARCITY. We are all suckers for things that are scarce. ONLY 1(2) ticket(s) left! When someone dies, they’re gone forever (famous quote by Captain Obvious), hence people want to not miss out on the last few albums by Bowie (or whoever).

This is particularly interesting. The fact that scarcity (not miss out on the occasion) motivates people to buy is well known for decades. The interesting twist is that music by a certain artist or any kind of information-product cannot run out. David Bowie’s music is already in digital format, which means that it can be multiplied endlessly. It goes the same with music from any other singer, with books, movies etc.

While the death of a singer means that (s)he will not produce more music, it does not mean that existing music will run in short supply. In fact, the music pieces that made someone famous (usually) are quite old by the time of the artist’s death. Thus, what is bought by many people is, in fact, old products.

Just as a note: New music by dead singers was released after their deaths… that is: previously unreleased old recordings (mixes).

3: SOCIAL CONTAGION. When the news gets out that lots of people are doing (buying) something, other people will follow (imitate) and do (buy) the same thing. This is more the case when the others have something in common with the decision maker (buyer). In this case, they are all Bowie fans.

4: STATUS ENHANCING THROUGH (COSTLY) SIGNALING. While owning a Bowie album was rather banal for most music fans, owning one of the (last) albums sold after his death is something worthy of talking about with friends, acquaintances, prospective mates (girlfriends / boyfriends) etc. In a nutshell, buying a Bowie album these days will give the buyer a reason (pretext) to brag (self-advertise) to relevant others.

RIP David Bowie and all other singers & artists who passed away! 

The Self-Defeating Fight against Vaccination Refusal

In reaction to the persisting decrease of vaccination rates in developed countries, public authorities, the media and non-profits counteract with information campaigns. In my opinion, this approach is self-defeating because it ignores the phenomenon’s behavioral realities.

1. Raising awareness is typical for information campaigns.

Articles with headlines such as Wealthy L.A. Schools' Vaccination Rates Are as Low as South Sudan's are well intended, but ignore the effect of social proof. When unsure what to do, people use others’ behaviors as cues for their own behavior. When faced with information on the increasing number of parents who refuse vaccination, others might interpret the message as: it’s OK not to vaccinate your children since others are doing this.

In many developed countries the overall situation is not as dramatic as some headlines indicate. The ideal vaccination rate is 95%+ which ensures herd immunity. The actual vaccination rates are somewhere in the 80-90% range. Healthcare professionals are worried mainly because of the trend and because of the real danger of losing the herd immunity.  As I understand the societal benefits of vaccination are not linear. Simply put, the societal benefit of improving vaccination rates from 80% to 85% is smaller than getting it from 90% to 95% (where heard immunity is achieved).

While from an epidemiological point of view a vaccination rate of 80% is worrisome news, from a behavioral science perspective things aren’t as dramatic. While most news focus on the increasing number of children who are not vaccinated, the upside is that the very large majority of children (in the USA) are vaccinated.

Saying that 20% of children are not vaccinated can be reframed as 80% are getting vaccines!   

In other similar situations, this type of simple reframing proved extremely effective in achieving behavioral change. Just as an example, many people have no problem buying a ham that is 97% fat free, but they would be very reluctant to purchase ham that is 3% pure fat.

Couple this reframing with social proof and you have a nice tool for reaching the goal of increasing vaccination rates.

Whereas headlines need to be dramatic in order to get clicks (or sell newspapers), public information campaigns need to be effective in achieving behavioral change – in this case get more children vaccinated.

Instead of relying on alarmist messages, why not simply say that the great majority (80%) of parents (in USA) do vaccinate their children.

Social proof and reframing of information can be used in even less favorable circumstances. A few months ago, I heard on the radio a commercial aimed at increasing the flu-vaccination rate. Unfortunately, the commercial said something like: “If you are one of the 65% of Americans who don’t get the shot, you can get the flu”.

Beyond the obvious errors in communication (from a behavioral science perspective), the reality of the numbers seems discouraging. When only (approx.) 35% of people get a vaccine, it is hard to leverage social proof – the great majority of people is not doing what is desired.

There is, however, a silver lining: 35% of the US population (311 million) is roughly 100 million people. Very likely, saying that over 100 million people (fellow Americans) get the flu shot is more convincing than 65% of Americans don’t get the flu shot.

   

2. Doctors are spokespeople in pro-vaccination campaigns.

The use of medical doctors as authority figures (recommenders) in communication has a long history. Doctors (or actors dressed as doctors) have recommended anything from detergent to cigarettes and from pharmaceutic drugs to diets.

While in many commercials using medical doctors as recommenders proved to increase the communication’s effectiveness, in the case of pro-vaccination (or anti anti-vaccination) campaigns is not exactly appropriate.  

Doctors’ presence and messages are reassuring for people who favor vaccination. However, those who are reluctant to vaccination don’t perceive doctors as authority figures, thus the message’s impact is severely diminished.

Simply put, in the eyes of (some) people who refuse vaccination, regular medicine is not trustworthy and so are medical doctors. Maybe herbalists, alternative healers etc. would be more credible.  

3. The rational message favoring vaccination is inadequate for tackling highly-emotional (false) concerns.

Strongly related to using medical doctors as advocates for vaccination is the messaging of pro-vaccination endeavors. Doctors dressed in their uniforms speak about the scientifically proven benefits of vaccination and talk about the serious dangers of not using this simple and effective prevention tool.

Although correct, this rational message is highly ineffective for those who oppose vaccination. Many anti-vaccination arguments have a high emotional load. Nobody (falsely) claims vaccines to cause kidney-failure – a serious condition with a low emotional load / fear-factor. Yet, all anti-vaccination advocates mention that vaccines can cause autism – a condition that has a high emotional component or fear-factor. By the way, vaccines don’t cause autism, but at one point someone made a false claim they did and the research has been proven to rely on faked data and the paper was later retracted. Yet, the legacy of fear left by that paper stands.

4. Vaccination’s benefits are Non-Events & the Availability Heuristic

The benefit of vaccination is very difficult to observe because it is a non-event – something that doesn’t happen. We humans are terrible at understanding non-events and in the case of vaccination things are even worse than in other situations.

Taking a step side-ways, I think we can all agree that a fire-fighter who goes into a burning building and saves a person (or cute puppy) is a hero worthy of public praise.

At the same time, the huge majority ignores other people who (indirectly) save many more lives from fires – the fire-safety inspectors: The bureaucrats who come with checklists and regulations, who generally are grumpy and somehow annoying because they keep insisting on even small features of compliance to fire-safety regulations.

These people save lives not by entering burning buildings, but by ensuring the conditions to prevent fires altogether and / or decrease the damage caused by fires.

The vaccination situation is somehow similar. Preventing a disease is not the same with curing one. A doctor who cured a patient with smallpox will receive many thankyou notes and will be held in high regard, but the nurse who gave thousands of anti-smallpox vaccines, thus preventing the disease, is still anonymous.

Earlier I mentioned that the situation is somehow similar. The high effectiveness of mass vaccination in preventing diseases, in fact, makes it more difficult to see the benefits of vaccination.

Let’s go back to the firefighter – fire-safety inspector illustration. The (paradoxical) reason for complying with fire-safety regulation is that there are enough (?!) fires to make the danger salient in our minds. Either in real life or in movies, fires are frequent enough to remind us that preventive action is needed.

In the case of vaccination things are a bit different. In developed countries recent cases of smallpox, poliomyelitis etc. are extremely rare. Mass vaccination led to having two-three generations free of such diseases and their devastating consequences. While during our (great-) grandparents’ childhood it was common for families to lose one or more children to diseases such as poliomyelitis, nowadays such instances are (almost) inexistent.

This is when the availability heuristic comes into play and distorts decision making on accepting vaccination.

The availability heuristic means that we judge the probability of an event based on the salience and frequency of memories of that event. We know of a lot of killings by firearms and very few suicides by guns, thus we perceive that there are more killings than suicides by firearms. The reality, however, is different: there are more suicides than killings by guns (at least in the US).

Because instances of terrible diseases that are prevented by vaccines are extremely rare and inconspicuous, we erroneously perceive the risk of not vaccinating a lot smaller than it actually is.

Here’s where movie makers can lend a hand. Instead (alongside) of scaring people with terrorist plots, doomsday scenarios etc. they could include more instances of people suffering and dying from poliomyelitis, smallpox etc.

5. Costs are in the present and benefits are in the future

   

Most people prefer 100$ now over 110$ in one year from now. This is an illustration of a psychological phenomenon called discounting future outcomes.

Vaccinations’ (non-event) benefits occur in the future (1-20 years) and, subsequently, are discounted in the present. The discomforts of vaccination– parents have to take their child to the clinic to get the shot, normal minor side-effects (fever, local swelling etc.) – are in the present.

The false dangers of vaccination allegedly occur very soon after getting the shot (in the present, not in the distant future).  

While it is impossible to change the nature of non-events and to eliminate the discounting of future outcomes, there are several things that can be done.

First, to tackle time discounting we can bring the benefits in the present. Naturally, vaccination’s benefits cannot be brought in the present (more so since they are non-events), but decreasing costs (hassle) in the present could be a great approach. In addition, although it might seem unethical, we could offer incentives in the present for getting vaccinated.

Second, to tackle the issue of non-events, we could try to make the immediate benefit more concrete by offering tangible rewards. As mentioned earlier, we could increase the frequency and salience of the dangers of non-vaccination and movies are the best way (at least in my view).

Workshops & Seminars on Using Behavioral Science in Health & Wellness  

 

Do I Really Need a Financial Incentive to Recommend a Service / Product?

Shortly after my wife and I moved to the USA, I noticed an announcement in the apartment building we live in that said: “recommend a friend to move here and you get 250$ when they sign the rental contract” (citing from memory). From an economic point of view this made perfect sense: you bring a client to a business and you get something in return.

Only later I realized that this type of incentive made sense when I saw it simply because, at the time, we barely knew anyone on this side of the Atlantic. A few months later, two former colleagues from Erasmus University moved from The Netherlands to the Washington DC area and they were looking for a place to live. We wanted to help them and showed them around the neighborhood. They were curious about the place we lived in and they came over to our place. To make a long story short, I got a business card from the leasing office of the building and gave them the information. The leasing officer (a very nice lady) mentioned that the offer of 250$ was still valid, so if our “friends” leased an apartment from them, we would get the incentive.

That was the moment when it struck me that this type of incentive scheme was faulty. Although I wouldn’t mind getting 250$, my motivation for recommending the apartment building wasn’t financial. We can pay the rent and I think, considering market conditions, that we get a reasonably good deal. We wanted our former colleagues to enjoy the same price-quality ratio. Moreover, the prospect of getting some cash out of the whole thing made me feel guilty. I truly, deeply hate the multi-level marketing approach. The relationship with our former university colleagues was social, not economical.  In fact, as someone who recently made the move from The Netherlands to the USA, we knew the costs and inconveniences it involved. If anything I would have preferred for our former colleagues to get the 250$.

Our former colleagues picked an apartment in a different neighborhood and the 250$ never left the real-estate company.

A similar case happened with a meal-delivery service we use. At the recommendation of my friend Arjan Haring (from The Netherlands) we tried Hello Fresh – a meal delivery service. In a nutshell, we pay each week 70$ and we receive a box with ingredients for three meals for two. This (type of) service is fantastic for foodies such as myself and my wife. We enjoy cooking and eating new stuff, but aren’t actively looking for new recipes and ingredients.  For our food experience, Hello Fresh is a blessing.

As we were very excited about this service, we talked about it with our few acquaintances in the US. Most of them seemed intrigued and curious about it.

In the first month(s) of using this service, Hello Fresh had an option for existing clients to “give a box” for free. It was an (a)typical approach for bringing in new business based on (existing) customer recommendations.

A bit later, however, they changed this “give a box for free” approach to a split incentive scheme. Basically, if we recommend the service to a “friend” and she subscribes, we get 30$ discount for our next order and the recipient gets 40$ off their first order.

While there is some economic sense in this split benefit approach, I began feeling uncomfortable recommending Hello Fresh. I wouldn’t mind 30$, but the financial incentive doesn’t match my motivation for recommending the service.

I recommend something because I want others to enjoy the service we think is great, not to make money out of it.

While in the case of Hello Fresh there might be some evidence-based reason for changing the approach to generate leads from existing clients from “give a free box” to split-benefit, there’s a big lesson to learn, particularly for marketers.

If you want to leverage your existing clients’ social relationships for your business, you need to understand their nature: SOCIAL.

Most people make a reasonably good distinction between social norms and market norms. The element that makes multi-level marketing utterly disgusting is that it perverts social relationships into (wannabe) market / business relationships.

Social relationships are based on imitation, reciprocity, status and alliances. Once you understand this, you can properly leverage them for your business’ benefit.

Simply put, if you want me to recommend your service to a friend (acquaintance, colleague etc.) help me enhance my social relationship with her/him. If you allow me to make a gift in the form of a discount, voucher or even allow me to offer them a full experience for FREE, that makes me look good, gain reputation etc. with the person with whom I am having a social relationship. This gain in strengthening my social status or relationship with someone I know (well) is, for me, more valuable than (the relatively small amount of) money you are offering as an incentive.

Marketing & Behavioral Science: www.naumof.com 

Is Overconfidence Bias All that Bad?

A while back Daniel Kahneman said in an interview that if he would have a Magic Wand he would eliminate overconfidence.

The article further elaborates on what Kahneman means: “Overconfidence: the kind of optimism that leads governments to believe that wars are quickly winnable and capital projects will come in on budget despite statistics predicting exactly the opposite.”

Source: Daniel Kahneman: ‘What would Ieliminate if I had a magic wand? Overconfidence’ 

Probably the best known example of overconfidence is that of newlywed couples who, very close to the time of getting married, unanimously say that their chances of getting divorced are zero. This, despite the statistical fact that around 50% of marriages end in divorce. If I’m not mistaken, even people who get married for the second time exhibit a similar overconfidence bias.

Without challenging the great Kahneman, I wonder if there isn’t a good (evolutionary) reason for why we’re all affected by overconfidence.

It goes without saying that the prediction: the war will be over by Christmas was wrong for both World War I and World War II. Naturally overestimating one chances of success when starting a war is detrimental – one starts a war.

However, there are lots of benign cases of overconfidence bias that have some positive impact, at least at a higher societal level.

Coming back to marriages: if, at the time of the wedding, we wouldn’t be overconfident about our marriages’ chances of success, we might never do it… and this includes those whose marriages last.

Having children is another case of overconfidence and is strongly correlated to marriage. Whether married or not, future parents underestimate the hassles they will face.

Overconfidence among (wannabe) entrepreneurs is widely known. Every entrepreneur believes she or he will bring to the world the next major business, paradigm-shifting tech product etc.

The statistical reality, however, is a lot more down to Earth. Most new businesses fail and the chance of creating the next big business is in the same order of magnitude of winning the lottery.

However, trying to start a new business brings some benefits at both societal and individual level. In order for a new business to benefit its owners it doesn’t have to be the Next Big Thing. In order for it to benefit society, it can be even a small business that works reasonably well.

With the risk of using myself as an example, when I started my first business (after successfully setting-up a student non-profit), I was wondering: How can I fail? and I got more than one answer. My first business endeavor was an utter failure. But after a while, I tried again in a different area of business and after about a year I managed to find a business model that worked (at least for a couple of years).

Without starting that first, doomed to fail business, I would have never started the one that finally worked.   

There’s a Romanian saying that would translate to English as:

You entered the game, now play.

I believe overconfidence has the role of Getting us into the Game; of getting our behinds off the couch and doing something. Even if that initial something doesn’t work, we’re in the game and we have to play, so we are forced to figure out how to manage.

I believe many people get married due to love and, of course, overconfidence. Naturally things don’t go as in the ideal scenario, but this makes us figure out ways in which we can make things work.

Many people start a business that doesn’t go as they dreamed (overconfidence strikes again), but at least some will try to figure out what and how can work. Maybe some entrepreneurs start as (delusional) dreamers who believe that they will bring The Next Big Thing, but end up having a reasonable small business that provides them with an income and pays a few employees.

I believe overconfidence plays a huge role in getting us to begin doing things. Some will end up in failure, but others will get done and will be useful. 

When to Fire a Cannon and When to Use a Precision Knife in Behavioral Design

When designing and testing a behaviorally informed intervention, there are two extreme approaches: (1) Precision Knife Approach and (2) Firing a Cannon.

In the Precision Knife Approach we design a simple intervention that uses only one or two features that vary (independent variables). We subsequently run an experiment (Randomized Control Trial – RCT) to investigate each feature’s effect on the target behavior (Dependent variable).

The Precision Knife Approach is rooted in rigorous academic research. In order to conduct proper (experimental) research, scientists need to investigate the effect on the target behavior (Dependent variable) of each feature that is manipulated (independent variable) and, if more than one, their interaction effect(s).

The advantage of using a Precision Knife Approach is that you get to know how each feature in your intervention works. You know which features used together generate positive interaction effects (i.e. 1+1 > 2) and which features used together generate negative interaction effects (i.e. 1+1 < 2). 

The downside of the Precision Knife Approach is that it faces behavioral designers with a choice between simplistic interventions (i.e. one or two features) that can easily be tested and complex interventions (i.e. 4 and more features) that are incredibly difficult to test.

The difficulty of testing complex interventions (using the Precision Knife Approach) comes from how a correct experimental research design is done. If we have an intervention based on one feature, then we need two experimental conditions (test cells): Control and Intervention. Once we introduce another feature in the intervention the number of test cells doubles. If we introduce a third feature it doubles again (from 4 to 8) and so on.

Having such hyper-complex research designs is impractical for many reasons including costs of designing different variants of the intervention, acquiring a large enough sample to “fill in” all test cells etc.

The other extreme approach is the Firing a Cannon. In a nutshell, this means that when designing the behaviorally informed intervention, you put everything (reasonable) in it and, subsequently, test the entire intervention against a control (do nothing) or / and against the current material used.  

From the point of view of scientific research methodology this is really sloppy. Moreover, it comes with the risk of generating negative interaction effects (1 + 1 < 2).

From a design / practical point of view, the Firing a Cannon Approach is highly useful because behavioral design has the main goal of improving an existing situation through cost-effective and subtle means (interventions). Finding the best – most effective – intervention can be a later goal.

Moreover, the Firing a Cannon Approach requires fewer resources and smaller samples to test the effectiveness of the intervention.

Another reason for which the Firing a Cannon Approach is advantageous is the increased chances of actually getting things done or proving the worth of behavioral design.

Imagine that you go to a (prospective) client or beneficiary with a complex intervention and an extremely complicated RCT design (such as in the Precision Knife Approach). Because most people are scared of complex things, there’s a good chance that the proposition will be rejected.

Imagine that you go to a (prospective) client or beneficiary with a simple intervention using one or two features and the proposition is accepted. You implement the intervention and run the RCT. You find nothing – the intervention doesn’t work. Subsequently you meet with the beneficiary (client) and present the non-results and ask to run another try, this time using different features (tools) in the intervention. Although this is perfectly correct from a methodological perspective, (real) people are not eager to keep investing in things that don’t produce (desired) results.

In the early stages of the behavioral design process (after the research), the Firing a Cannon Approach is superior to the Precision Knife Approach. In the beginning it is important to show that cost-effective behavioral interventions produce results that are equivalent or superior to what is happening at the current stage.

If the project allows for refinement of behavioral interventions, it is possible to use the Precision Knife Approach to fine-tune the materials used.

For more on Behavioral Design take a look at www.naumof.com 

Behavioral Science Explains the Failure of Free Markets

Most of you know me as a behavioral science guy, but I have to make a confession: my initial training is in Economics and business administration. Being born in a country with a communist dictatorship, with a centralized economy and spending much of childhood and teenage years in a chaotic backwards transition to market economy, I firmly believed in the virtues for free markets.

Perhaps because of this experience and seeing what free markets can do in a society unaccustomed to how they work, made me think hard if free markets are as virtuous as I thought them to be. And the answer is ambivalent: on the one hand, yes! It is absolutely obvious that a free market economy is far better than a centralized and corrupt one. On the other hand, however, free markets can be extremely perverse and lead to severely sub-optimal results (equilibrium).

Too often free markets fail to achieve the goal of maximizing consumer benefit.

When thinking about the pros of free markets, there are two prevalent assumptions: (1) people (buyers) fully understand what they are buying and (2) people can punish sellers by not buying from them anymore.

When these two assumptions are met and when there is competition among sellers, free markets work just fine.

Consider the example of fruit and vegetables. Anyone can understand what they are, anyone can quickly assess their quality, even if not necessarily before purchasing. Since they are bought frequently anyone can punish a seller by not buying from him or her next time they are shopping. Moreover, if the product is faulty, the damage to the buyer is minimal.

Another similar example is that of hair-dresser saloons (establishments). Anyone can quickly assess if they are happy with their new haircut, with the service provided etc. Although we don’t usually visit the hairdresser as often as we buy fruit and vegetables, the purchase of such services is frequent enough to allow the buyers to punish the sellers by not going to their establishment next time they get a haircut. Again, the damage caused to the buyer if the service is faulty is relatively low (unless it’s your wedding day).

In such situations free markets work just fine with minimal (common sense) regulation.

When the two assumptions of (1) people (buyers) fully understand what they are buying and (2) people can punish sellers by not buying from them anymore are not met, free markets are disasters waiting to happen.

An obvious example is the banking / credit market. For the huge majority of people a loan is a difficult to understand product and not seldom banks (credit institutions) make them even more complicated than they should be. Understanding the exponential relationship between the cost of the credit and the duration of the loan is extremely difficult even for trained economists. Fully understanding the maze of interest rates and fees requires a chess-master’s mind coupled with lengthy deliberation, computations and spreadsheets. The huge majority of people who take loans do not have these abilities or afford the necessary effort and time. Instead they rely on simple / simplistic rules of thumb (heuristics) such as how much do I like the person selling this or which one has the smallest monthly payment.

Since some loans are by their very nature long term (i.e. mortgages), it is virtually impossible for the buyer (loaner) to punish the seller (bank) if the product is faulty. If you consider the duration of 20-30 years for a typical mortgage, you probably realize that many marriages don’t last that long.

Ad: Create banking services that work with human nature, not against it. 

Moreover, if the product is faulty – a loan has hidden costs or other vices, the impact on the buyer is huge. For example, between 2006 and 2008 in Romania (my country of birth) there was a frenzy of loans in Swiss francs. The people who took out those loans ended up paying more than double what they should have repaid because the exchange rate Swiss Franc to Romanian Leu (local currency) doubled. In other words, when the loan was contracted you needed 2 Romanian currency for every Swiss Franc; a few years later you needed 4 Romanian currency for every Swiss Franc. More on this here: http://naumof.blogspot.com/2015/01/the-black-swan-of-swiss-franc.html

Financial products are not the only ones that make free markets produce failures every other year and disasters every (other) decade.

Take the example of medical services. I don’t like doctors, but I have to admit that getting through medical school isn’t easy and becoming a full medical doctor requires lots of learning and training.

In the case of medical services, the client (patient) is almost always completely incompetent and incapable of evaluating the quality of the service. In some milder cases, of course, the patient can see if she recovers or not after the prescribed treatment or procedure. This, however, is not always the case.

Consider a root-canal treatment and a new “fake” tooth. It is almost like a mortgage. It should work fine for ten-twenty-thirty years, but on the moment it is extremely difficult to evaluate. It is very hard for the buyer to punish the seller if the product is faulty simply because quality is very hard to evaluate and purchasing is infrequent. Moreover, the quality of a good (root-canal) treatment includes the durability of the work.

Naturally, in case of faulty medical products (services) the impact on the buyer’s well-being is huge.

Some might disagree with me on the points made above, particularly on the medical services. Some might say that they are capable of properly evaluating the quality of medical services. In fact, in many countries, patients are asked to evaluate the doctors who treated them.

Patient evaluations are a vicious by-product of free market thinking. It is well intended, it makes some sense and it is absolutely wrong.

Without proper medical training it is extremely difficult to assess if the doctor did a good job or not. As in the case of (long term) complex loans, even people with specialized training find it difficult to properly evaluate the quality of the product or service.

Why do some people believe they can evaluate the quality of medical services?

These people do not evaluate the quality of the actual medical procedure – the medical act. They are evaluating, at best, reasonable proxies.

For example, someone who had a root-canal treatment can evaluate how clean and modern was the dental clinic (i.e. general aspect); she can evaluate how much pain she was in; she can evaluate how the doctor and staff treated her and how much empathy they shown.     

All of these are, at best, correlated with the quality of the actual root canal treatment procedure. It makes sense to assume that doctors who give a lot of attention, put in a lot of effort in the actual medical procedure would have nice looking practices, while those who don’t give a damn on their work would do the same with the aspect of their practice.

But this is, at best, a correlational, not causal relationship.

Behind these (quality) evaluations is a cognitive process called “attribute substitution” in which we answer a difficult question with the answer of an easier one. When asked the difficult question of what was the quality level of the medical procedure you went through, people give the answer to the easier question of how they felt about it (during).

People can evaluate how they felt – the quality of the experience, not the quality of the medical procedure.

Free markets and a free market way of thinking (e.g. incorporating patient evaluations in doctor’s compensation) can create vicious situations that are clearly not maximizing the benefit of the buyer.

Patient evaluation and free markets in the medical services can lead to situations in which a competent, but grumpy doctor is overtaken by an incompetent, but very agreeable one.  

Free markets fail when it is difficult for the buyer to assess quality and it is extremely difficult to punish the seller for faulty quality of the merchandise may it be goods or services.