Tag: Incentives

The Power of Incentives: Inside The Hidden Forces that Shape Behavior

“Never, ever, think about something else when you should be thinking about the power of incentives.”

— Charlie Munger

According to Charlie Munger, there are only a few forces more powerful than incentives. In his speech “The Psychology of Human Misjudgment,” he reflects on how the power of incentives never disappoints him:

Well, I think I’ve been in the top 5% of my age cohort all my life in understanding the power of incentives, and all my life I’ve underestimated it. And never a year passes but I get some surprise that pushes my limit a little farther.

Sometimes the solution to a behavior problem is simply to revisit incentives and make sure they align with the desired goal. Munger talks about Federal Express, which is one of his favorite examples of the power of incentives:

The heart and soul of the integrity of the system is that all the packages have to be shifted rapidly in one central location each night. And the system has no integrity if the whole shift can’t be done fast. And Federal Express had one hell of a time getting the thing to work.
And they tried moral suasion, they tried everything in the world, and finally somebody got the happy thought that they were paying the night shift by the hour, and that maybe if they paid them by the shift, the system would work better. And lo and behold, that solution worked.

If you’re trying to change a behavior, reason will take you only so far. Reflecting on another example where misaligned incentives hampered the sales of a superior product, Munger said:

Early in the history of Xerox, Joe Wilson, who was then in the government, had to go back to Xerox because he couldn’t understand how their better, new machine was selling so poorly in relation to their older and inferior machine. Of course when he got there, he found out that the commission arrangement with the salesmen gave a tremendous incentive to the inferior machine.

Ignoring incentives almost never works out well. Thinking about the incentives of others is necessary to create win-win relationships.

We can turn to psychology to obtain a more structured and thorough understanding of how incentives shape our actions.

The Science of Reinforcement

The science of reinforcement was furthered by Burrhus Frederic Skinner (usually called B.F. Skinner), a professor of psychology at Harvard from 1958 to 1974.

Skinner, unlike his contemporaries, refused to hypothesize about what happened on the inside (what people or animals thought and felt) and preferred to focus on what we can observe. To him, focusing on how much people ate meant more than focusing on subjective measures, like how hungry people were or how much pleasure they got from eating. He wanted to find out how environmental variables affected behavior, and he believed that behavior is shaped by its consequences.

If we don’t like the consequences of an action we’ve taken, we’re less likely to do it again; if we do like the consequences, we’re more likely to do it again. That assumption is the basis of operant conditioning, “a type of learning in which the strength of a behavior is modified by [its] consequences, such as reward or punishment.” 1

One of Skinner’s most important inventions was the operant conditioning chamber, also known as a “Skinner box,” which was used to study the effects of reinforcers on lab animals. The rats in the box had to figure out how to do a task (such as pushing a lever) that would reward them with food. Such an automated system allowed Skinner and thousands of successors to study conditioned behavior in a controlled setting.

What years of studies on reinforcement have revealed is that consistency and timing play important roles in shaping new behaviors. Psychologists argue that the best way for us to learn complex behaviors is via continuous reinforcement, in which the desired behavior is reinforced every time it’s performed.

If you want to teach your dog a new trick, for example, it is smart to reward him for every correct response. At the very beginning of the learning curve, your failure to immediately respond to a positive behavior might be misinterpreted as a sign of incorrect behavior from the dog’s perspective.

Intermittent reinforcement is reinforcement that is given only some of the times that the desired behavior occurs, and it can be done according to various schedules, some predictable and some not (see “Scheduling Reinforcement,” below). Intermittent reinforcement is argued to be the most efficient way to maintain an already learnt behavior. This is due to three reasons.

First, rewarding the behavior takes time away from the behavior’s continuation. Paying a worker after each piece is assembled on the assembly line simply does not make sense.

Second, intermittent reinforcement is better from an economic perspective. Not only is it cheaper not to reward every instance of a desired behavior, but by making the rewards unpredictable, you trigger excitement and thus get an increase in response without increasing the amount of reinforcement. Intermittent reinforcement is how casinos work; they want people to gamble, but they can’t afford to have people win large amounts very often.

Finally, intermittent reinforcement can induce resistance to extinction (stopping the behavior when reinforcement is removed). Consider the example of resistance outlined in the textbook Psychology: Core Concepts:

Imagine two gamblers and two slot machines. One machine inexplicably pays off on every trial and another, a more usual machine, pays on an unpredictable, intermittent schedule. Now, suppose that both devices suddenly stop paying. Which gambler will catch on first?

Most of us would probably guess it right:

The one who has been rewarded for each pull of the lever (continuous reinforcement) will quickly notice the change, while the gambler who has won only occasionally (on partial reinforcement) may continue playing unrewarded for a long time.

Scheduling Reinforcement

Intermittent reinforcement can be used on various schedules, each with its own degree of effectiveness and situations to which it can be appropriately applied. Ratio schedules are based on the number of responses (the amount of work done), whereas interval schedules are based on the amount of time spent.

  • Fixed-ratio schedules are used when you pay your employees based on the amount of work they do. Fixed-ratio schedules are common in freelancing, where contractors are paid on a piecework basis. Managers like fixed-ratio schedules because the response to reinforcement is usually very high (if you want to get paid, you do the work).
  • Variable-ratio schedules are unpredictable because the number of responses between reinforcers varies. Telemarketers, salespeople, and slot machine players are on this schedule because they never know when the next sale or the next big win will occur. Skinner himself demonstrated the power of this schedule by showing that a hungry pigeon would peck a disk 12,000 times an hour while being rewarded on average for only every 110 pecks. Unsurprisingly, this is the type of reinforcement that normally produces more responses than any other schedule. (Varying the intervals between reinforcers is another way of making reinforcement unpredictable, but if you want people to feel appreciated, this kind of schedule is probably not the one to use.)
  • Fixed-interval schedules are the most common type of payment — they reward people for the time spent on a specific task. You might have already guessed that the response rate on this schedule is very low. Even a rat in a Skinner box programmed for a fixed-interval schedule learns that lever presses beyond the required minimum are just a waste of energy. Ironically, the “9-5 job” is a preferred way to reward employees in business.

While the design of scheduling can be a powerful technique for continuing or amplifying a specific behavior, we may still fail to recognize an important aspect of reinforcement — individual preferences for specific rewards.

Experience suggests that survival is propelled by our need for food and water. However, most of us don’t live in conditions of extreme scarcity and thus the types of reinforcement appealing to us will differ.

Culture plays an important role in determining effective reinforcers. And what’s reinforced shapes culture. Offering tickets to a cricket match might serve as a powerful reward for someone in a country where cricket is a big deal, but would be meaningless to most Americans. Similarly, an air-conditioned office might be a powerful incentive for employees in Indonesia, but won’t matter as much to employees in a more temperate area.

What About Punishment?

So far we’ve talked about positive reinforcement — the carrot, if you will. However, there is also a stick.

There is no doubt that our society relies heavily on threat and punishment as a way to keep ourselves in line. Still, we keep arriving late, forgetting birthdays, and receiving parking fines, even though we know there is the potential to be punished.

There are several reasons that punishment might not be the best way to alter someone’s behavior.

First of all, Skinner observed that the power of punishment to suppress behavior usually disappears when the threat of punishment is removed. Indeed, we all refrain from using social networks during work hours, when we know our boss is around, and we similarly adhere to the speed limit when we know we are being watched by a police patrol.

Second, punishment often triggers a fight-or-flight response and renders us aggressive. When punished, we seek to flee from further punishment, and when the escape is blocked, we may become aggressive. This punishment-aggression link may also explain why abusing parents come from abusing families themselves.

Third, punishment inhibits the ability to learn new and better responses. Punishment leads to a variety of responses — such as escape, aggression, and learned helplessness — none of which aid in the subject’s learning process. Punishment also fails to show subjects what exactly they must do and instead focuses on what not to do. This is why environments that forgive failure are so important in the learning process.

Finally, punishment is often applied unequally. We are ruled by bias in our assessment of who deserves to be punished. We scold boys more often than girls, physically punish grade-schoolers more often than adults, and control members of racial minorities more often (and more harshly) than whites.

What Should I Do Instead?

There are three alternatives that you can try the next time you feel tempted to punish someone.

The first we already touched upon — extinction. A response will usually diminish or disappear if it ceases to produce the rewards it once did. However, it is important that all possible reinforcements are withheld. This is far more difficult to do in real life than in a lab setting.

What makes it especially difficult is that during the extinction process, organisms tend to look for novel techniques to obtain reinforcement. This means that a whining child will either redouble her efforts or change tactics to regain the parent’s attention before ceasing the behavior. In this case, a better extinction strategy is to combine methods by withholding attention after whining occurs and rewarding more desirable behaviors with attention before the whining occurs.

The second alternative is positively reinforcing preferred activities. For example, people who exercise regularly (and enjoy it) might use a daily run as a reward for getting other tasks done. Similarly, young children learn to sit still by being rewarded with occasional permission to run around and make noise. The main principle of this idea is that a preferred activity, such as running around, can be used to reinforce a less preferred activity. This idea is also called the Premack principle.

Finally, prompting and shaping are two actions we can use together to change behavior in an iterative manner. A prompt is a cue or stimulus that encourages the desired behavior. When shaping begins, any approximation of the target response is reinforced. Once you see the approximation occurring regularly, you can make the criterion for the target more strict (the actual behavior has to match the desired behavior more closely), and you continue narrowing the criteria until the specific target behavior is performed. This tactic is often the preferred method of developing a habit gradually and of training animals to perform a specific behavior.

***

I hope that you are now better equipped to recognize incentives as powerful forces shaping the way we and others behave. The next time you wish someone would change the way they behave, think about changing their incentives.

Like any parent, I experiment with my kids all the time. One of the most effective things I do when one of them has misbehaved is to acknowledge my child’s feelings and ask him what he was trying to achieve.

When one kid hits the other, for example, I ask him what he was trying to accomplish. Usually, the response is “He hit me. (So I hit him back.)” I know this touches on an automatic human response that many adults can’t control. Which makes me wonder how I can change my kids’ behavior to be more effective.

“So, you were angry and you wanted him to know?”

“Yes.”

“People are not for hitting. If you want, I’ll help you go tell him why you’re angry.”

Tensions dissipate. And I’m (hopefully) starting to get my kids thinking about effective and ineffective ways to achieve their goals.

Punishment works best to prevent actions whereas incentives work best to encourage them.

Let’s end with an excellent piece of advice that has been given regarding incentives. Here is Charlie Munger, speaking at the University South California commencement:

You do not want to be in a perverse incentive system that’s causing you to behave more and more foolishly or worse and worse — incentives are too powerful a control over human cognition or human behavior. If you’re in one [of these systems], I don’t have a solution for you. You’ll have to figure it out for yourself, but it’s a significant problem.

Footnotes

Under One Roof: What Can we Learn from the Mayo Clinic?

The biologist Lewis Thomas, who we've written about before, has a wonderful thought on creating great organizations.

For Thomas, creating great science was not about command-and-control. It was about Getting the Air Right.

It cannot be prearranged in any precise way; the minds cannot be lined up in tidy rows and given directions from printed sheets. You cannot get it done by instructing each mind to make this or that piece, for central committees to fit with the pieces made by the other instructed minds. It does not work this way.

What it needs is for the air to be made right. If you want a bee to make honey, you do not issue protocols on solar navigation or carbohydrate chemistry, you put him together with other bees (and you’d better do this quickly, for solitary bees do not stay alive) and you do what you can to arrange the general environment around the hive. If the air is right, the science will come in its own season, like pure honey.

One organization which clearly “gets the air right” is the much lauded Mayo Clinic in Rochester, Minnesota.

The organization has 4,500 physicians and over $10 billion in revenue from three main campuses, and it is regularly rated among the top hospital systems in the United States in a wide variety of specialities, and yet was founded back in the late 20th century by William Worrall Mayo. Its main campus is in Rochester, Minnesota; not exactly a hub of bustling activity, yet its patients are willing to fly or drive hundreds of miles to receive care. (So-called “destination medicine.”)

How does an organization sustain that kind of momentum for more than 150 years, in an industry that's changed as much as medicine? What can the rest of us learn from that?

It's a prime example of where culture eats strategy. Even Warren Buffett admires the system:

A medical partnership led by your area’s premier brain surgeon may enjoy outsized and growing earnings, but that tells little about its future. The partnership’s moat will go when the surgeon goes. You can count, though, on the moat of the Mayo Clinic to endure, even though you can’t name its CEO.

Pulling the Same Oar

The Mayo Clinic is an integrated, multi-specialty organization — they're known for doing almost every type of medicine at a world class level. And the point of having lots of specialities integrated under one roof is teamwork: Everyone is pulling the same oar. Integrating all specialities under one umbrella and giving them a common set of incentives focuses Mayo's work on the needs of the patient, not the hospital or the doctor.

This extreme focus on patient needs and teamwork creates a unique environment that is not present in most healthcare systems, where one's various care-takers often don't know each other, fail to communicate, and even have trouble accessing past medical records. (Mayo is able to have one united electronic patient record system because of its deep integration.)

Importantly, they don't just say they focus on integrated care, they do it. Everything is aligned in that direction. For example, as with Apple Retail stores (also known for extreme customer focus), there are no bonuses or incentive payments for physicians — only salaries.

An interesting book called Management Lessons from the Mayo Clinic (recommended by the great Sanjay Bakshi) details some of Mayo's interesting culture:

The clinic ardently searches for team players in its hiring and then facilitates their collaboration through substantial investment in communications technology and facilities design. Further encouraging collaboration is an all-salary compensation system with no incentive payments based on the number of patients seen or procedures performed. A Mayo physician has no economic reason to hold onto patients rather than referring them to colleagues better suited to meet their needs. Nor does taking the time to assist a colleague result in lost personal income.

[…]

The most amazing thing of all about the Mayo clinic is the fact that hundreds of members of the most highly individualistic profession in the world could be induced to live and work together in a small town on the edge of nowhere and like it.

The Clinic was carefully constructed by self-selection over time: It's a culture that attracts teamwork focused physicians and then executes on that promise.

One of the internists in the book is quoting as saying working at Mayo is like “working in an organism; you are not a single cell when you are out there practicing. As a generalists, I have access to the best minds on any topic, any disease or problem I come up with and they're one phone call away.”

In that sense, part of the Mayo's moat is simply a feedback loop of momentum: Give a group of high performers an amazing atmosphere in which to do their work, and eventually they will simply be attracted by each other. This can go on a long time.

Under One Roof

The other part of Mayo's success — besides correct incentives, a correct system, and a feedback loop — is simply scale and critical mass. Mayo is like a Ford in its early days: They can do everything under one roof, with all of the specialities and sub-specialities covered. That allows them to deliver a very different experience, accelerating the patient care cycle due to extreme efficiency relative to a “fractured” system.

Craig Smoldt, chair of the department of facilities and support services in Rochester, makes the point that Mayo clinic can offer efficient care–the cornerstone of destination medicine–because it functions as one integrated organization. He notes the fact that everyone works under one roof, so to speak, and is on the payroll of the same organization, makes a huge difference. The critical mass of what we have here is another factor. Few healthcare organizations in the country have as many specialities and sub-specialities working together in one organization.” So Mayo Clinic patients come to one of three locations, and virtually all of their diagnoses and treatment can be delivered by that single organization in a short time.

Contrast that to the way care is delivered elsewhere, the fractured system that represents Mayo's competitors. This is another factor in Mayo's success — they're up against a pretty uncompetitive lot:

Most U.S. healthcare is not delivered in organizations with a comparable degree of integrated operations. Rather than receiving care under one roof, a single patient's doctors commonly work in offices scattered around a city. Clinical laboratories and imaging facilities may be either in the local hospital or at different locations. As a report by the Institute of Medicine and the National Academy of Engineering notes, “The increase in specialization in medicine has reinforced the cottage-industry structure of U.S. healthcare, helping to create a delivery system characterized by disconnected silos of function and specialization.

How does this normally work out in practice, at places that don't work like Mayo? We're probably all familiar with the process. The Institute of Medicine report referenced above continues:

“Suppose the patient has four medical problems. That means she would likely have at least five different doctors.” For instance, this patient could have (1) a primary care doctor providing regular examinations and treatments for general health, (2) an orthopedist who treats a severely arthritic knee, (3) a cardiologist who is monitoring the aortic valve in her heart that may need replacement soon, (4) a psychiatrist who is helping her manage depression, and (5) and endocrinologist who is helping her adjust her diabetes medications. Dr. Cortese then notes,”With the possible exception of the primary care physician, most of these doctors probably do not know that the patient is seeing the others. And even if they do know, it is highly unlikely they know the impressions and recommendations the other doctors have recorded in the medical record, or exactly what medications and dosages are prescribed.” If the patient is hospitalized, it is probably that only the admitting physician and the primary care physician will have that knowledge.

Coordinating all of these doctors takes time and energy on the part of the patient. Repeat, follow-up visits are done days later; often test results, MRI results, or x-ray results are not determined quickly or communicated effectively to the other parts of the chain.

Mayo solves that by doing everything efficiently and under one roof. The patient or his/her family doesn't have to push to get efficient service. Take the case of a woman with fibrocystic breast disease who had recently found a lump. Her experience at Mayo took a few hours; the same experience in the past had taken multiple days elsewhere, and initiative on her end to speed things up.

As a patient in the breast clinic, she began with an internist/breast specialists who took the medical history and performed an exam. The mammogram followed in the nearby breast imaging center. The breast ultrasound, ordered to evaluate a specific area on the breast, was done immediately after the mammogram.

The breast radiologist who performed the ultrasound had all the medical history and impressions of the other doctors available in the electronic medical record (EMR). The ultrasound confirmed that the lump was a simple cyst, not a cancer. The radiologist shared this information with the patient and offered her an aspiration of the cyst that would draw off fluid if the cyst was painful. But comforted with the diagnosis of the simple cyst and with the fact that it was not painful, the veteran patient declined the aspiration. Within an hour of completing the breast imaging, the radiologist communicated to the breast specialist a “verbal report” of the imaging findings. The patient returned to the internist/breast specialist who then had a wrap-up visit with the patient and recommended follow-up care. This patient's care at Mayo was completed in three and one-half hours–before lunch.

So what are some lessons we can pull together from studying Mayo?

The book offers a bunch, but one in particular seemed broadly useful, from a chapter describing Mayo's “systems” approach to consistently improving the speed and level of care. (Industrial engineers are put to work fixing broken systems inside Mayo.)

Mayo wins by solving the totality of the customer's problem, not part of it. This is the essence of an integrated system. While this wouldn't work for all types of businesses; it's probably a useful way for most “service” companies to think.

Why is this lesson particularly important? Because it leads to all the others. Innovation in patient care, efficiency in service delivery, continuous adoption of new technology, “Getting the Air Right” to attract and retain the best possible physicians, and creating a feedback loop are products of the “high level” thought process below: Solve the whole problem.

Lesson 1: Solve the customer's total problem. Mayo Clinic is a “systems seller” competing with a connected, coordinated service. systems sellers market coordinated solutions to the totality of their customers' problems; they offer whole solutions instead of partial solutions. In system selling, the marketer puts together all the services needed by customers to do it themselves. The Clinic uses systems thinking to execute systems selling that pleasantly surprises patients (and families) and exceeds their expectations.

The scheduling and service production systems at Mayo Clinic have created a differentiated product–destination medicine–that few competitors can approach. So even if patients feel that the doctors and hospitals at home are fine, they still place a high value on a service system that can deliver a product in days rather than weeks or months.

[…]

Patients not only require competent care but also coordinated and efficient care. Mayo excels in both areas. In a small Midwestern town, it created a medical city offering “systems solutions” that encourage favorable word of mouth and sustained brand strength, and then it exported the model to new campuses in Arizona and Florida.

If you liked this post, you might like these as well:

Creating Effective Incentive Systems: Ken Iverson on the Principles that Unleash Human Potential — Done poorly, compensation systems foster a culture of individualism and gaming. Done properly, however, they unleash the potential of all employees.

Can Health Care Learn From Restaurant Chains? — Atul Gawande pens a fascinating piece in the New Yorker about what health care can learn from the Cheesecake Factory.

Moving the Finish Line: The Goal Gradient Hypothesis

Imagine a sprinter running an Olympic race. He’s competing in the 1600 meter run.

The first two laps he runs at a steady but hard pace, trying to keep himself consistently near the head, or at least the middle, of the pack, hoping not to fall too far behind while also conserving energy for the whole race.

About 800 meters in, he feels himself start to fatigue and slow. At 1000 meters, he feels himself consciously expending less energy. At 1200, he’s convinced that he didn’t train enough.

Now watch him approach the last 100 meters, the “mad dash” for the finish. He’s been running what would be an all-out sprint to us mortals for 1500 meters, and yet what happens now, as he feels himself neck and neck with his competitors, the finish line in sight?

He speeds up. That energy drag is done. The goal is right there, and all he needs is one last push. So he pushes.

This is called the Goal Gradient Effect, or more precisely, the Goal Gradient Hypothesis. Its effect on biological creatures is not just a feeling, but a real and measurable thing.

***

The first person to try explaining the goal gradient hypothesis was an early behavioural psychologist named Clark L. Hull.

As with other animals, when it came to humans, Hull was a pretty hardcore “behaviourist”, thinking that human behaviour could eventually be reduced to mathematical prediction based on rewards and conditioning. As insane as this sounds now, he had a neat mathematical formula for human behaviour:

screen-shot-2016-10-14-at-12-34-26-pm

Some of his ideas eventually came to be seen as extremely limiting Procrustean Bed type models of human behavior, but the Goal Gradient Hypothesis was replicated many times over the years.

Hull himself wrote papers with titles like The Goal-Gradient Hypothesis and Maze Learning to explore the effect of the idea in rats. As Hull put it, “...animals in traversing a maze will move at a progressively more rapid pace as the goal is approached.” Just like the runner above.

Most of the work Hull focused on were animals rather than humans, showing somewhat unequivocally that in the context of approaching a reward, the animals did seem to speed up as the goal approached, enticed by the end of the maze. The idea was, however, resurrected in the human realm in 2006 with a paper entitled The Goal-Gradient Hypothesis Resurrected: Purchase Acceleration, Illusionary Goal Progress, and Customer Retention. (link)

The paper examined consumer behaviour in the “goal gradient” sense and found, alas, it wasn’t just rats that felt the tug of the “end of the race” — we do too. Examining a few different measurable areas of human behaviour, the researchers found that consumers would work harder to earn incentives as the goal came in sight, and that after the reward was earned, they'd slow down their efforts:

We found that members of a café RP accelerated their coffee purchases as they progressed toward earning a free coffee. The goal-gradient effect also generalized to a very different incentive system, in which shorter goal distance led members to visit a song-rating Web site more frequently, rate more songs during each visit, and persist longer in the rating effort. Importantly, in both incentive systems, we observed the phenomenon of post-reward resetting, whereby customers who accelerated toward their first reward exhibited a slowdown in their efforts when they began work (and subsequently accelerated) toward their second reward. To the best of our knowledge, this article is the first to demonstrate unequivocal, systematic behavioural goal gradients in the context of the human psychology of rewards.

Fascinating.

***

If we’re to take the idea seriously, the Goal Gradient Hypothesis has some interesting implications for leaders and decision-makers.

The first and most important is probably that incentive structures should take the idea into account. This is a fairly intuitive (but often unrecognized) idea: Far-away rewards are much less motivating than near term ones. Given the chance to earn $1,000 at the end of this month, and each thereafter, or $12,000 at the end of the year, which would you be more likely to work hard for?

What if I pushed it back even more but gave you some “interest” to compensate: Would you work harder for the potential to earn $90,000 five years from now or to earn $1,000 this month, followed by $1,000 the following month, and so on, every single month during five year period?

Companies like Nucor take the idea seriously: They pay bonuses to lower-level employees based on monthly production, not letting it wait until the end of the year. Essentially, the end of the maze happens every 30 days rather than once per year. The time between doing the work and the reward is shortened.

The other takeaway comes to consumer behaviour, as referenced in the marketing paper. If you’re offering rewards for a specific action from your customer, do you reward them sooner, or later?

The answer is almost always going to be “sooner”. In fact, the effect may be strong enough that you can get away with less total rewards by increasing their velocity.

Lastly, we might be able to harness the Hypothesis in our personal lives.

Let’s say we want to start reading more. Do we set a goal to read 52 books this year and hold ourselves accountable, or to read 1 book a week? What about 25 pages per day?

Not only does moving the goalposts forward tend to increase our motivation, but we repeatedly prove to ourselves that we’re capable of accomplishing them. This is classic behavioural psychology: Instant rewards rather than delayed. (Even if they’re psychological.) Not only that, but it forces us to avoid procrastination — leaving 35 books to be read in the last two months of the year, for example.

Those three seem like useful lessons, but here’s a challenge: Try synthesizing a new rule or idea of your own, combining the Goal Gradient Effect with at least one other psychological principle, and start testing it out in your personal life or in your organization. Don’t let useful nuggets sit around; instead, start eating the broccoli.

Choosing your Choice Architect(ure)

“Nothing will ever be attempted
if all possible objections must first be overcome.”

— Samuel Johnson

***

In the book Nudge by Richard Thaler and Cass Sunstein they coin the terms ‘Choice Architecture’ and ‘Choice Architect’. For them, if you have an ability to influence the choices other people make, you are a choice architect.

Considering the number of interactions we have everyday, it would be quite easy to argue that we are all Choice Architects at some point. But this also makes the inverse true; we are also wandering around someone else’s Choice Architecture.

Let’s take a look at a few of the principles of good choice architecture, so we can get a better idea of when someone is trying to nudge us.

This information can then be used/weighed when making decisions.  

Defaults

Thaler and Sunstein start with a discussion on “defaults” that are commonly offered to us:

For reasons we have discussed, many people will take whatever option requires the least effort, or the path of least resistance. Recall the discussion of inertia, status quo bias, and the ‘yeah, whatever’ heuristic. All these forces imply that if, for a given choice, there is a default option — an option that will obtain if the chooser does nothing — then we can expect a large number of people to end up with that option, whether or not it is good for them. And as we have also stressed, these behavioral tendencies toward doing nothing will be reinforced if the default option comes with some implicit or explicit suggestion that it represents the normal or even the recommended course of action.

When making decisions people will often take the option that requires the least effort or the path of least resistance. This makes sense: It’s not just a matter of laziness, we also only have so many hours in a day. Unless you feel particularly strongly about it, if putting little to no effort towards something leads you forward (or at least doesn’t noticeably kick you backwards) this is what you are likely to do. Loss aversion plays a role as well. If we feel like the consequences of making a poor choice are high, we will simply decide to do nothing. 

Inertia is another reason: If the ship is currently sailing forward, it can often take a lot of time and effort just to slightly change course.

You have likely seen many examples of inertia at play in your work environment and this isn’t necessarily a bad thing.

Sometimes we need that ship to just steadily move forward. The important bit is to realize when this is factoring into your decisions, or more specifically, when this knowledge is being used to nudge you into making specific choices.

Let’s think about some of your monthly recurring bills. While you might not be reading that magazine or going to the gym, you’re still paying for the ability to use that good or service. If you weren’t being auto-renewed monthly, what is the chance that you would put the effort into renewing that subscription or membership? Much lower, right? Publishers and gym owners know this, and they know you don't want to go through the hassle of cancelling either, so they make that difficult, too. (They understand well our tendency to want to travel the path of least resistance and avoid conflict.)

This is also where they will imply that the default option is the recommended course of action. It sounds like this:

“We’re sorry to hear you no longer want the magazine Mr. Smith. You know, more than half of the fortune 500 companies have a monthly subscription to magazine X, but we understand if it’s not something you’d like to do at the moment.”

or

“Mr. Smith we are sorry to hear that you want to cancel your membership at GymX. We understand if you can’t make your health a priority at this point but we’d love to see you back sometime soon. We see this all the time, these days everyone is so busy. But I’m happy to say we are noticing a shift where people are starting to make time for themselves, especially in your demographic…”

(Just cancel them. You’ll feel better. We promise.)

The Structure of Complex Choices

We live in a world of reviews. Product reviews, corporate reviews, movie reviews… When was the last time you bought a phone or a car before checking the reviews? When was the last time that you hired an employee without checking out their references? 

Thaler and Sunstein call this Collaborative Filtering and explain it as follows:

You use the judgements of other people who share your tastes to filter through the vast number of books or movies available in order to increase the likelihood of picking one you like. Collaborative filtering is an effort to solve a problem of choice architecture. If you know what people like you tend to like, you might well be comfortable in selecting products you don’t know, because people like you tend to like them. For many of us, collaborative filtering is making difficult choices easier.

While collaborative filtering does a great job of making difficult choices easier we have to remember that companies also know that you will use this tool and will try to manipulate it. We just have to look at the information critically, compare multiple sources and take some time to review the reviewers.

These techniques can be useful for decisions of a certain scale and complexity: when the alternatives are understood and in small enough numbers. However, once we reach a certain size we require additional tools to make the right decision.

One strategy to use is what Amos Tversky (1972) called ‘elimination by aspects.’ Someone using this strategy first decides what aspect is most important (say, commuting distance), establishes a cutoff level (say, no more than a thirty-minute commute), then eliminates all the alternatives that do not come up to this standard. The process is repeated, attribute by attribute (no more than $1,500 per month; at least two bedrooms; dogs permitted), until either a choice is made or the set is narrowed down enough to switch over to a compensatory evaluation of the ‘finalists.’”

This is a very useful tool if you have a good idea of which attributes are of most value to you.

When using these techniques, we have to be mindful of the fact that the companies trying to sell us goods have spent a lot of time and money figuring out what attributes are important to you as well.

For example, if you were to shop for an SUV you would notice that there are a specific number of variables they all seem to have in common now (engine options, towing options, seating options, storage options). They are trying to nudge you not to eliminate them from your list. This forces you to do the tertiary research or better yet, this forces you to walk into dealerships where they will try to inflate the importance of those attributes (which they do best).

They also try to call things new names as a means to differentiate themselves and get onto your list. What do you mean our competitors don't have FLEXfuel?

Incentives

Incentives are so ubiquitous in our lives that it’s very easy to overlook them. Unfortunately, this can influence us to make poor decisions.

Thaler and Sunstein believe this is tied into how salient the incentive is.

The most important modification that must be made to a standard analysis of incentives is salience. Do the choosers actually notice the incentives they face? In free markets, the answer is usually yes, but in important cases the answer is no.

Consider the example of members of an urban family deciding whether to buy a car. Suppose their choices are to take taxis and public transportation or to spend ten thousand dollars to buy a used car, which they can park on the street in front of their home. The only salient costs of owning this car will be the weekly stops at the gas station, occasional repair bills, and a yearly insurance bill. The opportunity cost of the ten thousand dollars is likely to be neglected. (In other words, once they purchase the car, they tend to forget about the ten thousand dollars and stop treating it as money that could have been spent on something else.) In contrast, every time the family uses a taxi the cost will be in their face, with the meter clicking every few blocks. So behavioral analysis of the incentives of car ownership will predict that people will underweight the opportunity costs of car ownership, and possibly other less salient aspects such as depreciation, and may overweight the very salient costs of using a taxi.

The problems here are relatable and easily solved: If the family above had written down all the numbers related to either taxi, public transportation, or car ownership, it would have been a lot more difficult for them to undervalue the salient aspects of any of their choices. (At least if the highest value attribute is cost).

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This isn’t an exhaustive list of all the daily nudges we face but it’s a good start and some important, translatable, themes emerge.

  • Realize when you are wandering around someone’s choice architecture.
  • Do your homework
  • Develop strategies to help you make decisions when you are being nudged.

 

Still Interested? Buy, and most importantly read, the whole book. Also, check out our other post on some of the Biases and Blunders covered in Nudge.

Daniel Pink on Incentives and the Two Types of Motivation

Motivation is a tricky multifaceted thing. How do we motivate people to become the best they can be? How do we motivate ourselves? Sometimes when we are running towards a goal we suddenly lose steam and peter out before we cross the finish line. Why do we lose our motivation part way to achieving our goal?

Dan Pink wrote an excellent book on motivation called Drive: The Surprising Truth About What Motivates Us. We’ve talked about the book before but it’s worth going into a bit more detail.

When Pink discusses motivation he breaks it into two specific types: extrinsic and intrinsic.

Extrinsic motivation is driven by external forces such as money or praise. Intrinsic motivation is something that comes from within and can be as simple as the joy one feels after accomplishing a challenging task. Pink also describes two distinctly different types of tasks: algorithmic and heuristic. An algorithmic task is when you follow a set of instructions down a defined path that leads to a single conclusion. A heuristic task has no instructions or defined path, one must be creative and experiment with possibilities to complete the task.

As you can see the two types of motivations and tasks are quite different.

Let’s look at how they play against each other depending on what type of reward is offered.

Baseline Rewards

Money was once thought to be the best way to motivate an employee. If you wanted someone to stay with your company or to perform better you simply had to offer financial incentives. However, the issue of money as a motivator has become moot in many sectors. If you are a skilled worker you will quite easily be able to find a job in your desired salary range. Pink puts it succinctly:

Of course the starting point for any discussion of motivation in the workplace is a simple fact of life: People have to earn a living. Salary, contract payments, some benefits, a few perks are what I call “baseline rewards.” If someone’s baseline rewards aren’t adequate or equitable, her focus will be on the unfairness of her situation and the anxiety of her circumstance. You’ll get neither the predictability of extrinsic motivation nor the weirdness of intrinsic motivation. You’ll get very little motivation at all. The best use of money as a motivator is to pay people enough to take the issue of money off the table.

Once the baseline rewards have been sorted we are often offered other ‘carrots and sticks’ to nudge our behavior. Many of these rewards will actually achieve the opposite effect to what was intended.

‘If, then’ Rewards

‘If, then’ rewards are when we promise to deliver something to an individual once they complete a specific task. If you hit your sales goals this month then I will give you a bonus. There are inherent dangers with ‘if, then’ rewards. They tend to prompt a short term surge in motivation but actually dampen it over the long term. Just the fact of offering a reward for some form of effort sends the message that the work is, well, work. This can have a large negative impact on intrinsic motivation. Additionally, rewards by their very nature narrow our focus, we tend to ignore everything but the finish line. This is fine for algorithmic tasks but hurts us with heuristic based tasks.

Amabile and others have found that extrinsic rewards can be effective for algorithmic tasks – those that depend on following an existing formula to its logical conclusion. But for more right-brain undertakings – those that demand flexible problem-solving, inventiveness, or conceptual understanding – contingent rewards can be dangerous. Rewarded subjects often have a harder time seeing the periphery and crafting original solutions.

Goals

When we use goals to motivate us how does that affect how we think and behave?

Like all extrinsic motivators, goals narrow our focus. That’s one reason they can be effective; they concentrate the mind. But as we’ve seen, a narrowed focus exacts a cost. For complex or conceptual tasks, offering a reward can blinker the wide-ranging thinking necessary to come up with an innovative solution. Likewise, when an extrinsic goal is paramount – particularly a short-term, measurable one whose achievement delivers a big payoff – its presence can restrict our view of the broader dimensions of our behavior. As the cadre of business school professors write, ‘Substantial evidence demonstrates that in addition to motivating constructive effort, goal setting can induce unethical behavior.

The examples are legion, the researchers note. Sears imposes a sales quota on its auto repair staff – and workers respond by overcharging customers and completing unnecessary repairs. Enron sets lofty revenue goals – and the race to meet them by any means possible catalyzes the company’s collapse. Ford is so intent on producing a certain car at a certain weight at a certain price by a certain date that it omits safety checks and unleashes the dangerous Ford Pinto.

The problem with making extrinsic reward the only destination that matters is that some people will choose the quickest route there, even if it means taking the low road.

Indeed, most of the scandals and misbehavior that have seemed endemic to modern life involve shortcuts. Executives game their quarterly earnings so they can snag a performance bonus. Secondary school counselors doctor student transcripts so their seniors can get into college. Athletes inject themselves with steroids to post better numbers and trigger lucrative performance bonuses.

Contrast that approach with behavior sparked by intrinsic motivation. When the reward is the activity itself – deepening learning, delighting customers, doing one’s best – there are no shortcuts. The only route to the destination is the high road. In some sense, it’s impossible to act unethically because the person who’s disadvantaged isn’t a competitor but yourself.

These same pressures that may nudge you towards unethical actions can also push you to make more risky decisions. The drive towards the goal can convince you to make decisions that in any other situation you would likely never consider. (See more about the dangers of goals.)

It’s not only the person who is being motivated with the reward that is hurt here. The person who is trying to encourage a certain type of behaviour also falls into a trap and is forced to try and course correct which, often, leaves them worse off than if they had never offered the reward in the first place.

The Russian economist Anton Suvorov has constructed an elaborate econometric model to demonstrate this effect, configured around what’s called ‘principal-agent theory.’ Think of the principal as the motivator – the employer, the teacher, the parent. Think of the agent as the motivatee – the employee, the student, the child. A principal essentially tries to get the agent to do what the principal wants, while the agent balances his own interests with whatever the principal is offering. Using a blizzard of complicated equations that test a variety of scenarios between principal and agent, Suvorov has reached conclusions that make intuitive sense to any parent who’s tried to get her kids to empty the garbage.

By offering a reward, a principal signals to the agent that the task is undesirable. (If the task were desirable, the agent wouldn’t need a prod.) But that initial signal, and the reward that goes with it, forces the principal onto a path that’s difficult to leave. Offer too small a reward and the agent won’t comply. But offer a reward that’s enticing enough to get the agent to act the first time, and the principal ‘is doomed to give it again in the second.’ There’s no going back. Pay your son to take out the trash – and you’ve pretty much guaranteed the kid will never do it again for free. What’s more, once the initial money buzz tapers off, you’ll likely have to increase the payment to continue compliance.

Even if you are able to trigger the better behaviour it will often disappear once incentives are removed.

In environments where extrinsic rewards are most salient, many people work only to the point that triggers the reward – and no further. So if students get a prize for reading three books, many won’t pick up a fourth, let alone embark on a lifetime of reading – just as executives who hit their quarterly numbers often won’t boost earnings a penny more, let alone contemplate that long-term health of their company. Likewise, several studies show that paying people to exercise, stop smoking, or take their medicines produces terrific results at first – but the healthy behavior disappears once the incentives are removed.

When Do Rewards Work?

Rewards can work for routine (algorithmic) tasks that require little creativity.

For routine tasks, which aren’t very interesting and don’t demand much creative thinking, rewards can provide a small motivational booster shot without the harmful side effects. In some ways, that’s just common sense. As Edward Deci, Richard Ryan, and Richard Koestner explain, ‘Rewards do not undermine people’s intrinsic motivation for dull tasks because there is little or no intrinsic motivation to be undermined.’

You will increase your chances for success when rewarding routine tasks using these three practices:

  1. Offer a rationale for why the task is necessary.
  2. Acknowledge that the task is boring.
  3. Allow people to complete the task their own way (think autonomy not control).

Any extrinsic reward should be unexpected and offered only once the task is complete. In many ways this is common sense as it is the opposite of the ‘if, then’ rewards allowing you to avoid its many failings (focus isn’t solely on the prize, motivation won’t wane if reward isn’t present during task, etc…). However, one word of caution – be careful if these rewards become expected, because at that point they are no different than the ‘if, then’ rewards.

Incentives Gone Wrong: Cobras, Severed Hands, and Shea Butter

“You must have the confidence to override people with more credentials than you whose cognition is impaired by incentive-caused bias or some similar psychological force that is obviously present. But there are also cases where you have to recognize that you have no wisdom to add— and that your best course is to trust some expert.”
— Charlie Munger

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There's a great little story on incentives which some of you may already know. The tale may be apocryphal, but it instructs so wonderfully that it's worth a repeat.

During British colonial rule of India, the government began to worry about the number of venomous cobras in Delhi, and so instituted a reward for every dead snake brought to officials. In a wonderful demonstration of the importance of second-order thinking, Indian citizens dutifully complied and began breeding venomous snakes to kill and bring to the British. By the time the experiment was over, the snake problem was worse than when it began. The Raj government had gotten exactly what it asked for.

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There's another story, much more perverse, from the Congolese massacre in the late 19th and early 20th century under Belgian rule — the period Joseph Conrad wrote about in Heart of Darkness. (Some of you might know the tale better as Apocalypse Now, which was a Vietnam retelling of Heart of Darkness.)

As the wickedly evil King Leopold II of Belgium forced the Congolese to produce rubber, he sent in his Force Publique to whip the natives into shape through genocidal murder. (Think of them as a Belgian Congo version of the Nazi's SS.) Fearful that his soldiers would waste bullets hunting animals, Leopold ordered that the soldiers bring back the severed hands of dead Congolese as proof that they were enforcing the rubber decree. (Leopold himself never even visited his colony, although he did cause at least 10 million deaths.)

Given that Leopold's quotas were impossible to meet, shortfalls were common. And with the incentives placed on Belgian soldiers, many decided they could get human hands more easily than meeting rubber quotas, while still conserving their ammo for hunting. An interesting result ensued, as described by Bertrand Russell in his book Freedom and Organisation, 1814-1914.

Each village was ordered by the authorities to collect and bring in a certain amount of rubber – as much as the men could collect and bring in by neglecting all work for their own maintenance. If they failed to bring the required amount, their women were taken away and kept as hostages in compounds or in the harems of government employees. If this method failed, native troops, many of them cannibals, were sent into the village to spread terror, if necessary by killing some of the men; but in order to prevent a waste of cartridges, they were ordered to bring one right hand for every cartridge used. If they missed, or used cartridges on big game, they cut off the hands of living people to make up the necessary number.

In fact, as Peter Forbath describes in his book The River Congo, the soldiers were paid explicitly on the number of hands they collected. So hands gained in demand.

The baskets of severed hands, set down at the feet of the European post commanders, became the symbol of the Congo Free State. … The collection of hands became an end in itself. Force Publique soldiers brought them to the stations in place of rubber; they even went out to harvest them instead of rubber… They became a sort of currency. They came to be used to make up for shortfalls in rubber quotas, to replace… the people who were demanded for the forced labour gangs; and the Force Publique soldiers were paid their bonuses on the basis of how many hands they collected.

Looking to bolster an economy of rubber, Leopold II got an economy of severed hands. Like the British Raj, he got exactly what he asked for.

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Joseph Heath describes another case of incentives gone wrong in his book Economics Without Illusions, citing the book Out of Poverty: And Into Something More Comfortable by John Stackhouse.

Stackhouse spent time in Ghana in the 1990s, and noticed that the “socially conscious” retailer The Body Shop was an enormous purchaser of shea nuts, which were produced in great quantities by Ghanians. The Body Shop used shea butter, produced from the nuts, to produce a variety of skin products, and as a part of its socially conscious mission, and its role in the Trade, Not Aid campaign, decided they were willing to pay above-market prices to Ghanian farmers, to the tune of an extra 50% on top of the going rate. And on top of that premium price, The Body Shop also decided to throw in a bonus payment for every kilogram of shea butter purchased, to be used for local development projects at the farmers' discretion.

Thinking that the Body Shop's early shea nut orders were a harbinger of a profitable boom, farmers began to rapidly up their production of shea butter. Stackhouse describes the result in his book:

A shea-nut rush was on, and neither the British chain nor the aid agencies were in a position to absorb the glut. In the first season, the northern villages, which normally produced two tonnes of shea butter a year, churned out twenty tonnes, nearly four times what the Body Shop wanted….Making matters worse, the Body Shop, after discovering it had overestimated the international market for shea products, quickly scaled back its orders for the next season. In Northern Ghana, it wasn't long before shea butter prices plunged.

Unfortunately, in its desire to do good in a poor part of the world, the Body Shop created a situation which was worse than when they began: Massive resources went into shea butter production only to find that it was not needed, and the overproduction of nuts ended up being mostly worthless.

These three cases above, and many more, lead us to the conclusion that people follow incentives the way ants follow sugar. It's imperative that we think very literally about the incentive systems we create. Remember that incentives are not only financial. Frequently it's something else: prestige, freedom, time, titles, sex, power, admiration…all of these and many other things are powerful incentives. But if we're not careful, we do the equivalent of creating an economy for severed hands.

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Still Interested? Learn about one company that understood and harnessed incentives correctly, or re-read Munger's discussion on incentive-caused bias in his famous speech on human psychology. Also, check out the Distorting Power of Incentives.