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Generally, it is clear that things that make life less boring are a priority for the poor. This may be a television, or a little bit of something special to eat—or just a cup of sugary tea. Even Pak Solhin had a television, although it was not working when we visited him. Festivals may be seen in this light as well. Where televisions or radios are not available, it is easy to see why the poor often seek out the distraction of a special family celebration of some kind, a religious observance, or a daughter’s wedding. In our eighteen-country data set, it is clear that the poor spend more on festivals when they are less likely to have a radio or a television. In Udaipur, India, where almost no one has a television, the extremely poor spend 14 percent of their budget on festivals (which includes both lay and religious occasions). By contrast, in Nicaragua, where 56 percent of rural poor households have a radio and 21 percent own a television, very few households report spending anything on festivals. The basic human need for a pleasant life might explain why food spending has been declining in India. Today, television signals reach into remote areas, and there are more things to buy, even in remote villages. Cell phones work almost everywhere, and talk time is extremely cheap by global standards. This would also explain why countries with a large domestic economy, where a lot of consumer goods are available cheaply, like India and Mexico, tend to be the countries where food spending is the lowest. Every village in India has at least one small shop, usually more, with shampoo sold in individual sachets, cigarettes by the stick, very cheap combs, pens, toys, or candies, whereas in a country like Papua New Guinea, where the share of food in the household budget is above 70 percent (it is 50 percent in India), there may be fewer things available to the poor.

An interesting insight into the mindsets of the poor. Even when purchasing higher quality food might boost their physical and mental health, which translates to increased financial income in the future, most of them would opt to rather spend on entertainment, whether it be a TV (or mobile phone nowadays) or festivals.

It might be easy to dismiss this as irrational behavior on their part due to lack of education, but many of us whom have had higher educations also make the same mistakes. Have you ever stayed up late to catch a TV show or get caught in an addictive game, thus hampering your performance at work the next day? Or have you made some poor diet choices which impacts your overall physical health from time to time?

The key difference is that healthy food is a much smaller percentage of our disposable income as compared to the poor, and that we still have significant percentage of our income for entertainment as compared to them. The human need for entertainment is strong. And who are we to begrudge others whom spend their hard-earned cash on ways to pass their days more easily?

This urge to reduce the poor to a set of clichés has been with us for as long as there has been poverty: The poor appear, in social theory as much as in literature, by turns lazy or enterprising, noble or thievish, angry or passive, helpless or self-sufficient. It is no surprise that the policy stances that correspond to these views of the poor also tend to be captured in simple formulas: “Free markets for the poor,” “Make human rights substantial,” “Deal with conflict first,” “Give more money to the poorest,” “Foreign aid kills development,” and the like. These ideas all have important elements of truth, but they rarely have much space for average poor women or men, with their hopes and doubts, limitations and aspirations, beliefs and confusion.

Introducing this book titled “Poor Economics”, which is a detailed read and study about the environment and motivations of poor people. To start off, most of us tend to think in very simple terms about poor people. These thoughts are usually driven by our internal ideologies. And so we tend to think in binary terms. “They did not work hard enough”, “They are lazy” or the other extreme “They just need 1-off cash transfer and all their problems will be solved”.

This books covers the complexities and showcases the nuances in determining the right policies. Whats important is to note that there are a confluence of factors that affect each and every one, and that solutions that deal with 1 person or community cannot necessarily be generalized all the time, despite our desire to do so.

Many of the inequalities of income and power we witness today do not arise from a system of fair equality of opportunity or work to the advantage of the least well-off. This leads liberals to interpret working-class resentment against elites as a complaint about injustice. If this is the only basis of anger against elites, the solution is to double down on the project of expanding opportunity and improving the economic prospects of the least well-off. But this is not the only way of interpreting the populist backlash against elites. The hubristic attitudes toward success that invite this backlash could well be fueled by the sense of entitlement that Rawls’s philosophy affirms, even as it rejects moral desert. For consider: Even a society that is perfectly just, as Rawls defines justice, admits certain inequalities—those that result from fair equality of opportunity and that work to the advantage of the least well-off. Imagine how, consistent with Rawlsian principles, a wealthy CEO could justify his or her advantages to a lower-paid worker on the factory floor: I am not worthier than you nor morally deserving of the privileged position I hold. My generous compensation package is simply an incentive necessary to induce me, and others like me, to develop our talents for the benefit of all. It is not your fault that you lack the talents society needs, nor is it my doing that I have such talents in abundance. This is why some of my income is taxed away to help people like you. I do not morally deserve my superior pay and position, but I am entitled to them under fair rules of social cooperation. And remember, you and I would have agreed to these rules had we thought about the matter before we knew who would land on top and who at the bottom. So please do not resent me. My privileges make you better off than you would otherwise be. The inequality you find galling is for your own good.

On ensuring a level playing field. Even in an idealistic world with a complete level playing field in terms of opportunity, differences in talent are as arbitrary as any other inequalities that might arise. And that is the main issue with meritocracy. In a fully just world, there will be those that, under the guise of meritocracy, that would be left out due to inequalities in talent. And the biggest contention with that is that we should not associate human worth with one’s success, which is a notion that meritocracy nudges us towards.

Despite their differences, these traditional versions of political meritocracy—from the Confucian to the Platonic to the republican—share the notion that the merits relevant to governing include moral and civic virtue. This is because all agree that the common good consists, at least in part, in the moral education of citizens. Our technocratic version of meritocracy severs the link between merit and moral judgment. In the domain of the economy, it simply assumes that the common good is defined by GDP, and that the value of people’s contributions consists in the market value of the goods or services they sell. In the domain of government, it assumes that merit means technocratic expertise. This can be seen in the growing role of economists as policy advisors, the increasing reliance on market mechanisms to define and achieve the public good, and the failure of public discourse to address the large moral and civic questions that should be at the center of political debate: What should we do about rising inequality? What is the moral significance of national borders? What makes for the dignity of work? What do we owe one another as citizens? This morally blinkered way of conceiving merit and the public good has weakened democratic societies in several ways. The first is the most obvious: Over the past four decades, meritocratic elites have not governed very well. The elites who governed the United States from 1940 to 1980 were far more successful. They won World War II, helped rebuild Europe and Japan, strengthened the welfare state, dismantled segregation, and presided over four decades of economic growth that flowed to rich and poor alike. By contrast, the elites who have governed since have brought us four decades of stagnant wages for most workers, inequalities of income and wealth not seen since the 1920s, the Iraq War, a nineteen-year, inconclusive war in Afghanistan, financial deregulation, the financial crisis of 2008, a decaying infrastructure, the highest incarceration rate in the world, and a system of campaign finance and gerrymandered congressional districts that makes a mockery of democracy. Not only has technocratic merit failed as a mode of governance; it has also narrowed the civic project. Today, the common good is understood mainly in economic terms. It is less about cultivating solidarity or deepening the bonds of citizenship than about satisfying consumer preferences as measured by the gross domestic product. This makes for an impoverished public discourse.

Sandel follows up later in his book and shares his views on how the reliance of meritocracy in our political system has crowded out fundamental conversations on morality and the public good. The fact that the economy has become the main focus and is analogous to the common good has impacted our societies by driving a further gap between economic numbers and the actual lives of citizens.

While I might not subscribe to such a “doom and gloom” outlook from Sandel, it is true that the focus on economics via the technocratic merit model might weaken public discourse on many other issues. Nevertheless, it is undeniable that society has made progress on social issues. And while we should always strive to do better, we should not be be overtly critical and overlook any progress in the past decades.

Having such a “doom and gloom” approach does invoke a lot of anxieties in young people and probably leads to the increasingly divisive politics that we see. Yet, it is also a fact the inequality has grown to unprecedented levels, and that we do not seem to be having significant political discourse on this. When the meritocratic ideal is then proposed for the average person to subscribe to, they probably see this disconnect in terms of economic outcomes via inequality and it becomes much harder for them to have that trust in leaders who push the meritocracy ideal.

Two-thirds of the students at Harvard and Stanford come from the top fifth of the income scale. Despite generous financial aid policies, fewer than 4 percent of Ivy League students come from the bottom fifth. At Harvard and other Ivy League colleges, there are more students from families in the top 1 percent (income of more than $630,000 per year) than there are students from all the families in the bottom half of the income distribution combined. The American faith that, with hard work and talent, anyone can rise no longer fits the facts on the ground. This may explain why the rhetoric of opportunity fails to inspire as it once did. Mobility can no longer compensate for inequality. Any serious response to the gap between rich and poor must reckon directly with inequalities of power and wealth, rather than rest content with the project of helping people scramble up a ladder whose rungs grow farther and farther apart.

A reflection of meritocracy in this passage. The conventional view of meritocracy in society, where education serves as a leveler for people with lower incomes, does not hold true if kids from higher income families get better access to education.

This explains why the political messaging that hard work can lead to success no longer appeals to the common people. When kids with parents of higher education and income parents get access to better preparation, resources and a better environment, it is hard to market education as a way to achieve social mobility.

Meritocracy might be a concept that sounds really appealing in principle, but there are a lot of uncontrollable factors that leads to a persons merits or level of capability.  Pushing this ideal in political messages no longer seems to get the same traction, especially with younger crowds, as it used to.

Root cause analysis is intended to determine the underlying cause of an incident, not the proximate cause. The Japanese have long followed a procedure for getting at root causes that they call the “Five Whys,” originally developed by Sakichi Toyoda and used by the Toyota Motor Company as part of the Toyota Production System for improving quality. Today it is widely deployed. Basically, it means that when searching for the reason, even after you have found one, do not stop: ask why that was the case. And then ask why again. Keep asking until you have uncovered the true underlying causes. Does it take exactly five? No, but calling the procedure “Five Whys” emphasizes the need to keep going even after a reason has been found.

A good passage from the book that details our attitudes towards underlying causes of problems. Too many times, we discover issues and trace it back to human error, and just leave it at there. However, if we were to consider the human as part of an overall system, we should then investigate the conditions and circumstances that would compel for the error to be made.

The “Five Whys” by Toyota is a good heuristic trick that can force us to go further beyond and truly understand the “root cause”.

Interesting anecdote from the design of everyday things. Shows how good intentions and lead to unintended consequences. Sometimes, we want processes to be seamless, and other times, to be have certain level of obstacles so it doesn’t become auto-pilot. When it becomes too much of a pain though, then unintended consequences such as keeping passwords in an unsafe place happens.

Today, I realize that design presents a fascinating interplay of technology and psychology, that the designers must understand both. Engineers still tend to believe in logic. They often explain to me in great, logical detail, why their designs are good, powerful, and wonderful. “Why are people having problems?” they wonder. “You are being too logical,” I say. “You are designing for people the way you would like them to be, not for the way they really are.” When the engineers object, I ask whether they have ever made an error, perhaps turning on or off the wrong light, or the wrong stove burner. “Oh yes,” they say, “but those were errors.” That’s the point: even experts make errors. So we must design our machines on the assumption that people will make errors.

A consistent theme in how we tend to think is that we will always try to “linearize” things and think along 1 single track of thought. It is just our natural bias to simplify things and we would always tend to the ideal case scenario.

In this case, we should always learn to plan for errors, mistakes for the users that we design products for. However, it is difficult to predict or forecast everything upfront. Sometimes, we just don’t know what we don’t know.

Simulation and testing helps. What we can do is always try to test iterations of a product and use that to learn more about the mental models of our users. Even then, each user would have their own interpretation of how things work. When designing a product, you can’t please everyone and at some point, you’ll just play the odds and work on the majority.

Instead, the EI focused on changing how teachers made decisions in their classrooms. The reforms were built around the idea that data can be transformative, but only if people know how to use it. To change students’ lives, educators had to understand how to transform all the spreadsheets and statistics and online dashboards into insights and plans. They had to be forced to interact with data until it influenced how they behaved. By the time Dante entered the third grade, two years after the EI started, the program was already so successful it was hailed by the White House as a model of inner-city reform. South Avondale’s test scores went up so much that the school earned an “excellent” rating from state officials. By the end of Dante’s third-grade year, 80 percent of his classmates were reading at grade level; 84 percent passed the state math exam. The school had quadrupled the number of students meeting the state’s guidelines. “South Avondale drastically improved student academic performance in the 2010–11 academic year and changed the culture of the school,” a review by the school district read. The school’s transformation was so startling that researchers from around the nation soon began traveling to Cincinnati to figure out what the Elementary Initiative was doing right. When those researchers visited South Avondale, teachers told them that the most important ingredient in the schools’ turnaround was data—the same data, in fact, that the district had been collecting for years. Teachers said that a “data-driven culture” had actually transformed how they made classroom decisions. When pressed, however, those teachers also said they rarely looked at the online dashboards or memos or spreadsheets the central office sent around. In fact, the EI was succeeding because teachers had been ordered to set aside those slick data tools and fancy software—and were told instead to start manipulating information by hand.

This reminds me of something that I have seen far too often in many organizations that intend to go towards a “data driven culture”. Usually, what happens is that a group of data analysts and engineers would gather superficial requirements from business teams, and then set up all the data dashboards and metrics for the end users with little intermittent feedback in between.

For these end users, the underlying logic of all these metrics remains a black box. No attempt was made to internalize the way these metrics are calculated. The extent of going towards a “data driven culture” stops at cursory discussions over numbers at their regular weekly meetings.

Do we blame the engineers or the business users? It doesn’t make sense to as that is simply human nature. It is extremely difficult for us to internalize abstract things like numbers and metrics unless we have gone through the calculation logic ourselves. Just like in the case of this passage, only by making the teachers manipulate the information by themselves could they learn how to yield data to improve their performance.

“What I cannot create, I do not understand” – Richard Feynman. This quote seems ever more relevant in the context of this anecdote. To really achieve a strong understanding of your data, you’ll have to compel yourself to go through the details and train of logic yourself. Have fun, or not :p

People like Darlene who are particularly good at managing their attention tend to share certain characteristics. One is a propensity to create pictures in their minds of what they expect to see. These people tell themselves stories about what’s going on as it occurs. They narrate their own experiences within their heads. They are more likely to answer questions with anecdotes rather than simple responses. They say when they daydream, they’re often imagining future conversations. They visualize their days with more specificity than the rest of us do. Psychologists have a phrase for this kind of habitual forecasting: “ creating mental models.” Understanding how people build mental models has become one of the most important topics in cognitive psychology. All people rely on mental models to some degree. We all tell ourselves stories about how the world works, whether we realize we’re doing it or not. But some of us build more robust models than others. We envision the conversations we’re going to have with more specificity, and imagine what we are going to do later that day in greater detail. As a result, we’re better at choosing where to focus and what to ignore. The secret of people like Darlene is that they are in the habit of telling themselves stories all the time. They engage in constant forecasting. They daydream about the future and then, when life clashes with their imagination, their attention gets snagged. That helps explain why Darlene noticed the sick baby. She was in the habit of imagining what the babies in her unit ought to look like. Then, when she glanced over and the bloody Band-Aid, distended belly, and mottled skin didn’t match the image in her mind, the spotlight in her head swung toward the child’s bassinet.

Building mental models, envisioning the future and visualizing how things connect to each other are things that we should be doing to improve the way we do things.

In some sense, daydreaming about the future might feel like a unproductive thing to do. However, what Duhigg mentions is that your ability to visualize more specifics and scenarios in your “daydreams” would better prepare you to face unknown situations and react accordingly.

Its good to occasionally live in our own heads, absorbing information and testing it with our theory of how things work. A world with increasing external stimuli in the form of mobile devices and computers makes it difficult to daydream in more details. Nevertheless, we need to create that mental space for ourselves if we intend to visualize and build our robust mental models.