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I just published an article on UX Booth about behavior design in health and would love to start a conversation about it with anyone who is interested — designers, health practitioners, technologists, etc. etc.
An excerpt about Fogg’s behavioral model is below, but you can get the full version of the article here. Please check it out, especially if you are working on any design project related to behavioral change.
Fogg’s behavioral model
BJ Fogg is the founder of the Persuasive Technology Lab at Stanford University and is widely regarded as an expert in behavior design. His behavioral model – the Fogg Behavior Model (FBM) – states that three components simultaneously affect behavior: Motivation, Ability, and Trigger. These are mapped to a linear graph, below:
Motivation, on the y axis, is the willingness that people have to do the behavior. Ability, on the x axis, is their ability to do so. Finally trigger, a region bounded below (by the orange line), is a call to action or prompt for them to do so. Fogg says that the best design way to facilitate behavioral change is to “put hot triggers in the path of motivated people.”
His model is powerful because it boils the complex interactions between man and machine into something simple. Further, each component of his model can be broken down, allowing designers to better scrutinize cause and effect. For instance:
Motivations include pleasure, pain, hope, fear, social acceptance, and social rejection.
Ability is directly affected by training as well as the perceived ease of the target behavior.
Triggers can be facilitated, signaled, or sparked depending on the level of ability or motivation the person has with the target behavior in mind.
In practice, the Behavior Model helps designers determine the right kind of trigger to use in – or what kind of trigger is missing from – their work. For example, if someone ignores their goal (motivation) of doing daily push-ups (within their ability), a mobile application might to remind them to do so (trigger).
In the last week, I reached out to the most knowledgeable people in my network on entrepreneurial careers to get their perspective on a career question that has occupied my mind for some time now:
Would you recommend a college graduate to work at a growth-stage startup or corporate company in the high-technology industry (or even another stage) if he wants to start his own company in the future?
Here is how they answered:
Thanks for the good words and the superb question. Really, there’s no right answer to what you’re asking. Totally depends.
I know someone who just graduated from high school and is going to work for a startup. It’s the right thing for him. And I’ve known recent college grads who go to work for a big company – works well for them.
- Aron Solomon, Founder of Svbstance.is
As a very general guideline, I believe it depends on your timeframe: if you are thinking about launching your own venture in the near term, a growth-stage startup is probably the way to go (i.e. learn the ‘nitty gritty’ up close and quickly); if you are thinking more medium/longer-term, a corporation may be the better bet (i.e. more likely to provide a formal training program, better understand systems & structures, establish a broader professional network, etc.). In the end, you should do a fair bit of due diligence on the company (if you study a company before you invest a few thousand dollars in its stock, how much should you do before investing the start of your career?).
- Bruce Bachenheimer, Clinical Professor of Management and Director of Entrepreneurship at Pace University
Yes, that [growth-stage startup] is the best way to learn.
- Vivek Wadhwa, VP of Academics and Innovation at Singularity University
i’d go small. easier to model something closer to what you want to do.
- Jon Bischke, Founder of Entelo
Growth stage by FAR. You will learn so much more, be tested, have to adjust and get a real sense of what building something is like.
Working at a large established firm only gives you experience with large orgs, and you will probably be responsible for some specific set of functions rather than the more broad sweeping work a startup would require.
After reading Predictably Irrational by Dan Ariely, I can no longer look at economics and psychology the same way ever again. I became a believer in behavioral economics.
While I am a classically-trained economics major taught the idea that economic theory should assume human rationality, Dan Ariely demonstrated that this line of thinking is outdated. Through his claims backed up by countless experimental evidence, real-world examples, and anecdotes, he proved that economics is so much more insightful and useful if its theories were based on the way people actually behave instead of the way we assume they behave. With each experiment and theory he proposed and elaborated on, he won me over to the field of behavioral economics just a little more. Once I finished the book, I was a firm believer. Behavioral economics made so much more sense than classical economics because it actually incorporated real examples of human behavior. After all, the reason I was drawn to economics in the first place was because of the question: “Why do people make certain economic and financial decisions? (and why not?)” It was no surprise I found the answers to those questions in behavioral economics after all.
In Predictably Irrational, professor Ariely, who teaches psychology and behavioral economics at Duke University, sums up his important takeaway in the following quote:
“We are all far less rational in our decisionmaking than standard economic theory assumes. Our irrational behaviors are neither random nor senseless–they are systematic and predictable. So wouldn’t economics make a lot more sense if it were based on how people actually behave? That simple idea is the basis of behavioral economics.”
Several biases that explain how human behavior deviate from rationality support his conclusions. Some of these biases include relative thinking, anchoring, zero price effect, social norms, arousal, procrastination and self-control, endowment effect, paradox of choice, effect of expectations, power of price, and dishonesty.
In the rest of this article, I discuss the biases that I found most interesting to me, all of which are applicable to the world of business.
Relative thinking
Dan Ariely reasons that humans rarely choose things based on absolute terms. Rather, humans always draw a comparison with other things and try to draw out a difference between their advantages in order to determine the value of a thing.
One example of a company that takes advantage of this psychological bias is The Economist. When you arrive on their home page, an ad pops up asking you to subscribe to the magazine. On first glance, the ad seems pretty straightforward.
Credit goes to Dan at his blog.
The one-year web-only subscription costs $59. The second offer lists the print subscription price of $125. So far, nothing seems suspicious.
Then the third option is a print and web subscription for $125–the same price as the second offer except this time the option includes both the print and web versions of the magazine.
Looking at the options on hand, why would anyone want to purchase the print subscription when you can purchase the print and web subscription for the same price? But on second thought, the most likely response Ariely thought The Economist marketers were trying to elicit from consumers was to skip the web subscription entirely and purchase the print and web subscription.
The reason why this marketing strategy likely worked is because The Economist made it easier for consumers to compare the print and web subscription and the print-only subscription. When consumers had to choose from the print- and web-only subscriptions, they had no point of comparison. After the Economist marketers created the print and web subscription at the same price as the print subscription to create a point of comparison for consumers, it got easier. The print and web subscription seemed like a better deal than the print-only subscription because it seemed like the best deal out of the three subscription options even though the web-only subscription might be a better fit for their needs.
In more theoretical terms, when given three options–A, A- (similar to A but worse), and B (which is distinct from A but equally attractive)–people almost always choose A because it is better than A-.
The zero price effect
The “zero price effect” is the idea that anything priced at zero/free invokes an irrational excitement from the consumer.
Ariely, along with Shampanier and Mazar, conducted one experimented using Lindt truffles and Hershey’s Kisses, asking which one the participant would rather pick given the price. When the truffle was $0.15 and the Kiss was $.01, 73% of the participants chose the truffle over the Kiss. However, when the truffle was $0.14 and the Kiss was free, 69% chose the Kiss over the truffle. Traditional economic theory would not allow for this result since the relative expected pleasure that the participant receives from their purchase should be equal in the two experiments. Hence, the price reduction shouldn’t have caused any change in behavior.
The reason for this irrational behavior, Ariely theorizes, is because when a consumer makes a standard transaction, he considers the upsides and downsides. However, when a product is free, he forgets about the downsides. The product seems substantially more valuable than it really is. Humans are ultimately loss-averse creatures. The idea of “free” bypasses the loss-averse trigger humans have so that the decision to take the “free” product appears completely risk-free.
One real-world example of this behavior was the response to Amazon’s free shipping. When Amazon established this shipping policy, it saw significant sales increases everywhere except for France. Then, when headquarters realized it was because the French division set their shipping at 1 franc ($0.20) instead of free, they changed it to free. Almost immediately afterwards, the French division saw sales increases.
Procrastination and self-control
While procrastination does not explicitly seem related to economics, it has a lot to do with efficient decision-making (or lack thereof) which traditional economic theory assumes humans can do.
Ariely conducted an experiment with his class once which involved separating his class into three groups, each required to write 3 papers. The first group was required to commit to dates by which they would turn in each paper. Late papers received a penalty of 1% per day it was late while there was no penalty for turning papers in early. The most rational thing to do would be to choose to commit to turning all 3 papers in on the last day of class. The second group was not given any deadlines, so all three papers were due on the last day of class. The third group was required to turn in their papers on the 4th, 8th, and 12th weeks.
The results were fascinating. Group 3, which had strict deadlines, received the best grades. Group 2, which had no deadlines, received the worst groups. And Group 1, which set their own deadlines, finished in the middle. The results indicated that allowing students to pre-commit to deadlines bolstered their outcomes since the students who spaced out their commitments performed well while students who gave no commitments performed poorly.
According to Ariely, “these results suggest that although almost everyone has problems with procrastination, those who recognize and admit their weakness are in a better position to utilize available tools for precommitment and by doing so, help themselves overcome it.”
This conclusion has a significant impact in fields such as financial savings and health, where it is difficult to motivate people respectively to save their earnings and show up to their medical appointments on time. In those cases, it is demonstratively better to establish methods for people to precommit to their action or have technology automatically do it for them.
Paradox of choice
The argument Ariely makes here is that we feel compelled to keep our options open even when it doesn’t really make sense. The experiment Ariley conducted with MIT students to test this was a computer game which offered players three doors: Red, Blue, and Green. You clicked to enter a room and you were given 100 clicks to start off with. Once you are in a room, each click rewarded you between 1-10 cents. You could also switch rooms, which cost a click. The rooms were also programmed to give you different levels of rewards.
In the initial experiment, players usually entered all three rooms, figured out which gave them the highest payout, and then stuck around. In the next version of the experiment, Ariely introduced a mechanism where any door left unvisited for 12 clicks would disappear permanently. Players would continuously jump around rooms, trying to keep their options open. They made approximately 15% less in rewards than before, which is lower than if they just chose any of the doors and stuck with that room.
Afterwards, Ariely increased the cost of opening a door to three cents, and there was no change. Then, he told players the exact financial reward of each door, and there was no change. He gave players the option of doing as many practice runs as they wanted before the actual experiments, and there was no change. Ariely redesigned the game so that any door could be reincarnated with one click, but there was still no change.
He concluded that the students were just so loss-averse that they did anything necessary to prevent their doors from closing even though a closed door had no real ramifications and could be reversed.
This experiment was truly fascinating because it demonstrated that people can spent so much of their time and energy trying to prevent a loss of an option when it had marginal potential impact on their outcomes.
These insights into Ariely’s theories and experiments are only the tip of the iceberg of what the book contains and really do not do his book justice. I highly recommend you reading his book yourself if his ideas listed here sound even mildly fascinating. He has a way of really pulling you in almost immediately in his book with his easy-to-understand, persuasive, and often quirky writing. I would love to meet him at some point if not just to ask him some more fine-tuned questions about the experiments in his book.
The Nest Learning Thermostat is an example of redefining the human everyday experience that I really admire and appreciate. The video demonstrates its ease of use, unobtrusive nature, aesthetics, and environmental efficiency — all elements of “good design” via Dieter Rams’ 10 Principles of Design.
Compare the Nest Thermostat to the thermostat commonly found in homes:
Creative commons via mtmiller (flickr)
The Nest Thermostat introduces a hands-off automatic approach to monitoring and changing your house’s temperature. As a result, Nest enables you to stay at your preferred temperature and save energy and money by automatically changing temperature depending on your preferences and switching on/off depending on if anyone’s in the house. On the other hand, the common thermostat requires constant manual monitoring in order to achieve the same results.
The interface design of the Nest Thermostat also lowers the barrier to use by making it simple — even delightful — to use. With a turn of the wheel, you can set your temperature and get on with your life. The thermostat stays out of your way. No more needing to set the thermostat before rushing off to work or heading to bed. Nest takes care of the rest by selecting great default settings and enabling toggling settings via your mobile phone in case you are out of the house. Compare that to the common thermostat which has numerous unlabeled or confusingly labeled buttons that makes it difficult to use without reading an instruction manual. Who reads instruction manuals nowadays anyways?
To err is human, according to Donald Norman in his celebrated book, The Design of Everyday Things. Below are some notes I took on his chapter dedicated to solving design problems associated with human error.
As humans, we make errors routinely, either making slips or mistakes. Slips are when you form a goal but mess up the performance. It’s usually a small error. Mistakes are errors in thought, meaning that you made in error during your goal formulation process in the first place.
There are several types of slip errors:
Capture error – a frequently done activity suddenly takes the place of the one intended. Eg. When you go to your bedroom to change your clothes for dinner and you find yourself in bed.
Description error – the intended action might fit several possibilities so the person takes the wrong action. E.g. A person comes home from a work out, takes off his sweaty shirt, and intending to throw it into his laundry hamper, accidentally throws it into the toilet.
Data-driven error – focusing on the wrong piece of sensory data drives the wrong automatic action.
Associative activation error – internal thoughts and associations can trigger the wrong action. E.g. a Freudian slip.
Loss-of-activation error – forgetting to do something. E.g. Walking back to your room to get your towel to go to the shower and forgetting upon entrance to room why you walked back there in the first place.
Detecting slips is relatively easy, but only if there is feedback. If the result of the action is not visible, then the action can not be detected. Thus, designers must make feedback clearly visible.
Mistakes result from the choice of inappropriate goals — when a person makes a poor decision.
While much economic theory is based upon the model of rational human behavior, human thoughts seem more rooted in past experience than in logical deduction. They’re hardly logical, neat, and orderly.
Most everyday activities are conceptually simple. Activities like chess have wide and deep decision trees. Wide as in there are many alternatives at each point in the tree. Deep because there are lots of branches in the decision tree. Most everyday activities are shallow and/or narrow. E.g. going to a car, unlocking it, opening the door, getting into the car, inserting the key, and starting the engine is a deep structure but it is narrow. While picking ice cream from a menu at an ice cream store is shallow but wide because there are numerous options.
What’s also interesting about human behavior is that while subconscious thought matches patterns by finding the best possible match of one’s past experience to the current one, conscious thought is more slow and labored. Conscious thought requires more intensive short-term memory usage and so is limited in the amount that it is readily available. Most people can only keep track of five or six items at any one moment. Many times, mistakes are made by mismatch by taking the current situation and falsely matching it with something in the past. It’s easy to allow our subconscious to glide over these mistakes.
People frequently explain away errors as false alarms. Social pressure also compels people to make errors more frequently even if the real culprit is a design failure.
How do we address these challenges? Forcing functions are a form of physical constraint that can help by creating situations in which the actions are constrained so that failure at one stage prevents the next step from happening. E.g. starting a car has a forcing function where you must put the ignition key into the ignition switch.
Along these lines, there are three such methods that can help prevent accidents:
Interlock – forces operations to take place in proper sequence. E.g. microwave ovens that prevent people from opening the door of the oven without first turning off the power.
Lockin – keeps an operation active, preventing someone from prematurely stopping it. E.g. a “soft” switch for a computer’s power that checks to make sure all the files open are saved before shutting the computer down.
Lockout – prevents someone from entering a place that is dangerous. E.g. in the case of a fire, a barrier to prevent people from running down stairs past the ground floor all the way to the basement.
In conclusion, in order for designers to address errors, they should:
Understand the causes of the error.
Make it possible to reverse the action or “undo” it.
Make it easier to discover errors and correct them.
Change the attitude toward errors by thinking of actions as attempts at tasks, getting there by imperfect approximations.
This fall, I am enrolled in Professor Peter Robbie’s Design Thinking course at the Thayer School of Engineering, and I have already had quite a few takeaways on brainstorming and idea generation strategies from my course (along with having the great opportunity to build an amusement park ride from scratch):
Brainstorming is about quantity not quality- In the initial stage of brainstorming, one should focus on generating as many ideas as possible without discriminating against any idea. By generating a larger quantity of ideas, you have more material to work with. The breadth of possibilities is a lot larger, increasing the chance you have a remarkable idea on your hands by a significant degree.
Brainstorming is a judgement-free zone- This means not saying “no” to any idea and leaving everything on the table. If you hamper the positive generation of ideas too early on in the process by eliminating some choices, then you lose inertia and confidence in your general creative process. You can lose out on some potentially great ideas that were just disguised as bad ideas or were tangential to ideas you criticized. I typically have a gut reaction to an idea, so I have had to practice divorcing my idea generation process from my analytical and critical thinking process. This had been difficult, but I already feel more freedom and potential in my brainstorming process by doing so.
Use a list of manipulative verbs to help you explore new territory - It’s tough for you to think of everything without assistance, especially if you’re working by yourself. One tool that can come in handy is a list of verbs such as “magnify”, “divide”, and “substitute” that help you take the idea you have in your mind or on paper and transform it into something completely new. For example, if I am brainstorming new models of cars, I could “substitute” it with a wagon or “magnify” it into a truck to help me think of fresh alternatives. I will make sure I carry a list of manipulative verbs around for all my brainstorming purposes.
This list of my takeaways on brainstorming strategies is not exhaustive by any means, but it serves as the foundation for my future brainstorming purposes.
I originally wrote this article for the UnCollege newsletter, which you can find here.
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Educational content is easier to access than ever before. Free online courses are offered by Coursera and Udemy. Online listings for offline courses can be found on Skillshare and General Assembly. But even with so many competing formats of educational content, books should still be at the top of your list of self-directed learning resources.
In fact, some of the world’s most brilliant thinkers and doers relied on books for their knowledge. Elon Musk — the co-founder of Paypal, Tesla and SpaceX — attributed much of his technical prowess to reading many difficult engineering books. Reid Hoffman — the co-founder of Paypal and Linkedin — had his father read Lord of the Rings books to him when he was just 5 years old.
That’s why in this post I want to help you solve two fundamental problems: 1) the difficulty of sourcing great books and 2) screening books and picking the best ones to read.
Discovering Great Books
Fortunately, numerous online resources exist to help you source great books such as Goodreads, Amazon, and more. I profile some of these resources below.
Goodreads
Goodreads is the “largest site for readers and book recommendations in the world.” The web application is a useful resource for discovering great books based upon what you and your friends have read previously.
By rating books you have read and selecting your favorite genres, you can receive high-quality book recommendations from Goodreads through a Netflix-inspired discovery engine. Aside from your personal recommendations, your friends’ reading lists are another valuable resource for finding books you will likely enjoy reading.
Amazon
As you probably know, Amazon is a major global e-commerce company that moves massive inventories of books. Commonly recognized as a good place to buy books online, it also has several tools you must take advantage of to discover great books.
First, Amazon has a superb suggestion system based upon your browsing history, which you can access from the home screen or the books category.
Another tool Amazon has is its Recommended For You product, which always produces an interesting list of books for me.
Amazon has a Goodreads-like service as well called Shelfari, “a community-powered encyclopedia for book lovers”, which providers you with a virtual bookstore as opposed to a department store user experience.
Lastly, you can find the most popular books on Amazon by flipping through its Best Sellers lists.
What Should I Read Next?
This super-simple application enables you to type in a book you love and receive a list of suggestions for similar books. It’s a great alternative to Goodreads or Amazon if you’re looking for a one-off book recommendation.
The New York Times and The Wall Street Journal Bestseller Lists
While they might not be tailored to your personal tastes, these Bestseller Lists are an obvious resource for finding out the most popular titles of today.
Picking the Right Book
To find that next book that will keep you up late at night desperately trying to finish every page, I recommend picking your books based upon narrow criteria that reflect your values and priorities.
Here are some of the criteria that you might want to use to judge a book:
Subject matter - It can be difficult to stay focused on one subject. For example, if you look for a programming book but buy a technology history book because it sounded interesting, you might want to ask yourself which subject is more important to you. Make sure you decide on a priority list of subjects before you start your book search and stick to it.
Reviews/ratings – Both Goodreads and Amazon have reviews and ratings, which are easy tools to use to sort and filter through long lists of books.
Table of contents – Most book sellers like Amazon enable you to take a look at the table of contents before you make a purchase. Check out the table contents and see if the material is actually the subject matter you care about.
First page – Reading the first page (or couple) of a book can give you a more accurate insight of the author’s style and tone.
Books are more often than not a great — if not the best — self-directed learning resource. In this day and age of online learning, don’t forget to still take advantage of books to further your own self-education.
One of his series of posts was especially priceless, and this was his guide dedicated to helping recent college graduates map out their careers. I just wanted to share the plethora of quotes that were the highlights for me:
The first rule of career planning: Do not plan your career.
The second rule of career planning: Instead of planning your career, focus on developing skills and pursuing opportunities.
I believe you should look at your career as a portfolio of jobs/roles/opportunities. Each job that you take, each role that you choose to fill, each opportunity you pursue, will have a certain potential return – the benefits you can get from taking it, whether those benefits come in the form of income, skill development, experience, geographic location, or something else. Each job will also have a certain risk profile — the things that could go wrong, from getting fired for not being able to handle the job’s demands, to having to move somewhere you don’t want to, to the company going bankrupt, to the opportunity cost of not pursuing some other attractive opportunity.
Once you start thinking this way, you can think strategically about your career over its likely 50+ year timespan.
The issue is that without taking risk, you can’t exploit any opportunities.
If you intend to have an impact on the world, the faster you start developing concrete skills that will be useful in the real world, the better – and your undergrad degree is a great place to start. Once you get into the real world and you’re primed for success, then you can pursue your passion.
Don’t worry about being a small fish in a big pond – you want to always be in the best pond possible, because that’s how you will get exposed to the best people and the best opportunities in your field.
Seek to be a double/triple/quadruple threat.
Become very good (top 25%) at two or more things.
If you have lived an orchestated existence, gone to great schools, participated in lots of extracurricular activities, had parents who really concentrated hard on developing you broadly and exposing you to lots of cultural experiences, and graduated from an elite university in the first 22 or more years of your life, you are in danger of entering the real world, being smacked hard across the face by reality, and never recovering.
What do I mean? It’s possible you got all the way through those first 22 or more years and are now entering the workforce without ever really challenging yourself. This sounds silly because you’ve been working hard your whole life, but working hard is not what I’m talking about. You’ve been continuously surrounded by a state of the art parental and educational support structure — a safety net — and you have yet to make tough decisions, by yourself, in the absence of good information, and to live with the consequences of screwing up.
In my opinion, it’s now critically important to get into the real world and really challenge yourself — expose yourself to risk — put yourself in situations where you will succeed or fail by your own decisions and actions, and where that success or failure will be highly visible.
When picking an industry to enter, my favorite rule of thumb is this:
Pick an industry where the founders of the industry — the founders of the important companies in the industry — are still alive and actively involved.
If you are young and want to have an impact, you want to be in an industry where there is a lot of growth and change and flux and opportunity.
Never worry about being a small fish in a big pond. Being a big fish in a small pond sucks — you will hit the ceiling on what you can achieve quickly, and nobody will care. Optimize at all times for being in the most dynamic and exciting pond you can find. That is where the great opportunities can be found.
Apply this rule when selecting which company to go to. Go to the company where all the action is happening.
Also apply this rule when selecting which city to live in. Go to the city where all the action is happening.
In a rapidly changing field like technology, the best place to get experience when you’re starting out is in younger, high-growth companies.
A few months ago, I read SPIN Selling by Neil Rackham, founder of the Huthwaite Corporation. It is the most deeply researched book you can possibly find on sales, analyzing the results of 35,000 sales calls to discern best practices over the years. This book introduced me to both the art and science behind sales. And since then, I have realized there is a lot to learn about perfecting sales.
Throughout the summer, I have spent a lot of time strengthening my skillset in sales and wanted to share a few best practices that have really worked for me:
Listen more than you talk - Listen to the customers’ needs. Listen to their stories, complaints, praises, and everything in between. Use full-body listening even over the phone in order to truly understand what the customer cares about.
Focus on the positive - Customers don’t like to talk with anyone who is bored, apathetic, and negative. They will not want to stay on the phone with you, let alone be sold on your product. Customers will want to get excited about your product and company if you’re excited. So be positive and excited.
Be honest - On the flipside to the point above, if your company can’t or won’t do something, be upfront with the customer about it. Don’t make any false promises now if you want to avoid angry customer calls later.
Thank the customer – Show your appreciation as much as you can to the customer so he/she keeps coming back. Treat your customer as well as you would treat your best friend.
Measure, measure, measure - Know how many e-mails you’re sending, calls you’re making, and deals you’re closing. By tracking the funnel, you’ll be able to measure your improvements (or declines) and know what are the driving factors behind those changes. You’ll get great insight and stay motivated to hustle.
