Ten interesting things we read this week

Some of the most interesting topics covered in this week's iteration are related to 'Robo penetration in India', 'When firms lose their mojo', and 'dominating category as a flawed strategy'

Published: May 27, 2018

g_106097_reading_bg_280x210.jpgImage: Shutterstock
 
At Ambit, we spend a lot of time reading articles that cover a wide gamut of topics, including investment analysis, psychology, science, technology, philosophy, etc. We have been sharing our favourite reads with clients under our weekly ‘Ten Interesting Things’ product. Some of the most interesting topics covered in this week’s iteration are related to ‘Robo penetration in India’, ‘When firms lose their mojo’, and ‘dominating category as a flawed strategy’.
 
Here are the ten most interesting pieces that we read this week, ended May 25, 2018.
 
1) How many factory workers in India have lost their jobs to robots? [Source: Livemint]
The number of robots deployed by Indian firms has witnessed a 200-fold increase since the turn of the 21st century. Yet, the stock of industrial robots in India in 2016 at 16,026 accounts for barely 0.1% of India’s industrial workforce. These finding by Sunil Mani, professor and director at the Centre for Development Studies (CDS), Thiruvananthapuram are based on the latest data from the International Federation of Robotics (IFR) and the Annual Survey of Industries (ASI). His analysis shows that the density of robots per 10,000 manufacturing workers has increased from less than 1 in 2000 to almost 10 in 2016. Note that the IFR defines an industrial robot as an “automatically controlled, reprogrammable, and multipurpose [machine]”.

The use of robots in India, as elsewhere, has been largely concentrated in tasks which are very difficult for human workers to do, Mani’s research suggests. A large chunk of industrial robots deployed in the country have been in the auto industry to perform two very specific tasks—arc and spot welding—which are hazardous for workers to perform. The other task where robots are increasingly being used is that of machine tending or handling, which also involves risks for human workers. Robots performing these two tasks account for 84% of industrial robots deployed in the country today.

India’s experience in this regard is no different from that of other countries. Globally, the large-scale use of industrial robots began in the 1970s in tasks related to welding—arc and spot welding —largely in the auto industry. Since then, the only other task where the use of robots has increased significantly is machine handling and tending. The evidence so far suggests that robots are unlikely to replace all kinds of industrial workers. Rather, specific tasks within certain occupations are more likely to be automated.

Mani’s research appears to be in sync with the latest reports on automation and jobs published recently by the World Bank and the Asian Development Bank (ADB). While the World Bank has argued that the jobs threat from automation is grossly exaggerated in its draft World Development Report 2019, the ADB in its Asian Development Outlook 2018 report has pointed out that automation affects only certain tasks in certain industries, and that job losses because of automation can often be offset by rising demand for goods and services which create new jobs. Nonetheless, the development of artificial intelligence (AI) could lead to new kinds of robots, which are more flexible, and are able to perform tasks that were hitherto considered non-automatable, Mani argues.

2) DNA uploaded to websites lets gene genie out of the bottle [Source: Financial Times]
A swab can turn you into a snitch. By taking a DNA test and allowing its results to be uploaded into a genetic database, you risk exposing the miscreants among your relatives. This seems to have happened in the case of the Golden State Killer, who murdered 12 people and raped at least 50 across California in the 1970s and 1980s. A DNA sample taken at the time did not turn up a match on forensic databases and the trail went cold. But a recent reopening of the case saw the sample uploaded to a genealogy website. This long shot resulted in a partial match, allowing investigators to eventually home in on a suspect through the DNA of his distant relatives. The breakthrough, which happened last month, raises fresh questions about genetic privacy. About one in 25 American adults has taken a genetic test, primarily for reasons of health or family history. But your genes are not yours alone: they encode, in part, secrets that other blood relatives might prefer to keep under wraps, such as adoption or uncertain paternity.

Genealogists, geneticists, lawyers and privacy advocates now recognize that the growing public enthusiasm for tracing family trees is seeding multiple ethical dilemmas. Some even wonder if there could be a Facebook-style privacy backlash. While the genetic database helped catch the Golden State killer and netting a murderous sadist would be a positive social use of genetic data, the information that led to the arrest was furnished for a different purpose. The question is - Is it appropriate for companies or other organisations hosting DNA databases to become, however informally, agents of the state?

Sheldon Krimsky, a bioethicist and professor at Tufts University who co-authored the book Genetic Justice, argues that even hospital databases might now be open to speculative trawling: “Should the police be permitted a warrant just to go on to non-FBI databases to find suspects? That is a big problem area.” That is why big commercial DNA-testing companies generally resist law enforcement requests. The website 23andMe says its policy is not to provide information unless legally obliged, while Ancestry.com said it had received no such requests. GEDmatch, the open-source website which led police to the Golden State killer, makes clear that uploaded information can be accessed by third parties. Concerned participants, it adds, can delete their genetic information.

Comments left on a genealogy website bear out the unintended consequences that can stem from intended use of genetic genealogy — whether the outing of anonymous sperm donors or disputed paternity. One post reads: “I’ve identified a second cousin, discovered her biological father and found a half-sibling who was her brother. The half-sibling brother just discovered he has a son who he knew nothing about.” The gene genie is out of the bottle: our DNA has been reduced to another identifier, like our face, email address and social media profile, to be tagged and triangulated by strangers.

3) When people philosophies of firms lose their mojo and need an urgent reboot
[Source: Livemint]
Why do companies which had a great HR credo suddenly find themselves desperately seeking a reboot of their people philosophies? Of course, there are ups and downs in every company’s life. But how does yesteryear’s killer strategy suddenly become so weak? The biggest elephant in the room, according to the author, is the issue of employee heavyweights not punching their weight, but simply warming their seats. If the problem employee is a newbie, the solution is usually straightforward: a seamless parting of ways. The matter becomes complicated, however, when the culprits are those who have been with you forever; those who joined when the organization was a nobody, who partnered in the growth journey; were feted and celebrated and reaped bountiful rewards. Slowly, as the years went by, the ennui, the complacency, the over-confidence, the desire for status quo, or sheer laziness, took over.

Many a time, these heavyweights are complacent, seemingly waiting for the maturing of their deferred benefits or lucrative stock options. “Vesting in peace” is how many cynical subordinates would call out such superiors. And it is these venerables who will have to be called out first, because any meaningful change for organizational speed, responsiveness and energy has to be driven from the top.

Another reason for a sagging employee covenant is when the organizational purpose is no longer strong enough or does not resonate with employees. While it is fashionable these days to talk about organizational purpose for new age millennials, the author says it has always been organizations with a purpose stronger than just the commercial aspects of profitability and margins that have been able to create a strong employee value proposition. In the 1990s and 2000s, many organizations in then sunrise industries like information technology and ITES (information technology enabled services) leveraged this very well. While organizational health was paramount, these organizations successfully ingrained in employees a sense of the larger cause: India Inc. The rare market opportunities that presented themselves were to be utilized, not squandered, for the larger good of the nation itself.

The same opportunity now presents itself to start-ups. A cause larger than just the commercial aspect is a great way to align employees and build a strong employer value proposition even if it’s not as exalted as national interest! Nilofer Merchant, in her book “11 Rules For Creating Value In The Social Era”, says, “Money motivates neither the best people nor the best in people. Purpose does.” Organizations may have great purpose and great people but they also need great enablers. The sales and manufacturing may excel, so also quality and R&D, but have you as an organization worked to create world-class enabler teams, those departments which administer the organization—the finance, HR, IT, training teams—and keep its internal wheels turning? Has the company acquired world-class talent into these functions, talent with truly a customer mindset? Are they held to the same levels of excellence and benchmarks that the company expects of its front-line players? Or are they treated just as an overhead?

The author shares how one CEO told her how his organizational satisfaction survey and culture just kept dipping year on year in spite of many new measures being introduced. Finally, he decided to make the journey a participatory one. Cross-hierarchy teams with even the junior-most employees were given the mandate to change part of the culture. And these teams, led many a time by those who were not in actual positions of hierarchy, actually helped. The natural leaders came up, participation led to empowerment and ownership of problems, and the tide actually turned. “When leaders throughout an organization take an active, genuine interest in the people they manage, when they invest real time to understand employees at a fundamental level, they create a climate for greater morale, loyalty, and, yes, growth,” said Patrick Lencioni, author of “The Five Dysfunctions of a Team”.

4) Why dominating your category might be a flawed strategy [Source: HBR]
Of the many contributions Jack Welch has made to business wisdom, one of his most famous was “Be #1 or #2 in every market.” That advice served GE well in shaping its portfolio of businesses and its strategy for many years, but it’s not clear to the authors that it is as relevant any more. It may, in fact, according to them be a dangerous strategy in today’s business environment. Take the cereal business, for example. General Mills actually grew from #2 to #1 in market share the last few years. But the cereal category declined $4 billion dollars from 2000 to 2015, so it didn’t matter. In fact, total sales at General Mills has declined for 15 of the last 16 quarters. General Mills highlights three things that are the root of the problem of the axiom “Be #1 or #2 in your category.”

The first problem is it encourages managers to focus most of their attention on market share and not enough on the category itself. It assumes your category will continue to be relevant and grow so you can be a big fish in a big and growing pond. But what happens when your category is not growing – or even declines? Being number one in a declining market isn’t a great place to be. Few companies are willing to consider that their category’s best days are behind it and lay out a radically different strategy to win in the midst of category decline or exit the category entirely. Categories grow when they go from niche (e.g., some people use it some of the time) to mass (e.g., many people use it much of the time). Similarly, categories decline when categories hit their peak and are replaced by better, more innovative categories.

The second problem is that the definition of a “category” is often inaccurately defined, which creates blind spots from unexpected competitors. Most companies think of their category from a manufacturing lens. The truth is the cereal category is much more accurately defined through the eyes of the consumer. Their category is really “ready to eat cereal (what) eaten for breakfast and snacks (when) by sugar and carb loving consumers (who) sold by huge brands in the middle of huge stores (how).” That’s a mouthful that no Nielsen or Euromonitor data will truly reflect, but that’s closer to the truth and better prepares you to compete. General Mills doesn’t compete with just Kellogg’s cereal (what), but a growing number of breakfast and snack categories (when), with a shrinking consumer base in the face of anti-sugar and anti-carb trends (who) and smaller brands, sold in smaller format stores and e-commerce (how). Meals like breakfast are giving way to snacks. Big brands are giving way to smaller brands. Grocery is giving way to food service and e-commerce.

The third problem is that few companies actually have a category strategy. They have pricing, product, brand, portfolio and corporate strategies. But very few actually give real thought to how to grow the category in a holistic manner of breakthrough product innovation and breakthrough business model innovation. The first step in strategy has to be to assess whether the category is growing or declining, then choose your strategy tool kit accordingly. Most traditional strategy axioms like “create a competitive moat,” “the low-cost producer wins,” “execution trumps strategy,” and “the customer is always right” makes sense when your category has a tailwind you can count on. But if your category is declining or about to decline, your moat, your leadership in cost, and your execution will all look silly at best and could be a big write-down at worst. As Peter Drucker said: “There is nothing so useless as doing efficiently that which should not be done at all.” And in a declining category, you should still treat all customers with empathy and respect, but you shouldn’t be listening to most of them.

Companies like General Mills have three choices: a) You can exit and enter a better category via a merger or acquisition; b) You can re-invent the category through category creation and category design strategies, or c) You have to change your stripes, and radically shift your business model. It is still possible to win in a declining category. But you likely need to trade out your mass-marketing business model for a niche, premium, and specialty model and scale strategies for a superconsumer strategy. All three strategies have higher odds of success than trying to do the same mass marketing model in a declining category.

5) Gibson left to fret as millennials turn their back on rock music [Source: Financial Times]
The kids who turned 13 in 1994 were the first millennials, a generation that is being blamed for turning its back on rock as analysts look for explanations for Chapter 11 bankruptcy filing by Gibson Brands, maker of the Les Pauls, Flying Vs and Epiphones favoured by guitar gods from Jimmy Page to Slash of Guns N’ Roses. Research suggests that in the age of rap and electronic dance music, annual growth in the $542m US industry would slow down to just 0.1% between 2017 and 2022. But a closer look suggests executives and financiers, currency markets, and regulators may bear more blame for Gibson’s troubles than rappers and DJs. “I’ve been in the guitar business my entire life and I think it’s doing great,” said Sterling Ball, whose father Ernie started making strings for the likes of the Rolling Stones’ Keith Richards in 1962. Millennials were still buying guitars, he said, but Gibson’s fate has more to do with its strategic errors. “I can attribute part of [my] bald spot to scratching my head over some of the decisions they made over the years,” Mr. Ball said.

When the 116-year-old Nashville company filed in a Delaware bankruptcy court, it also said it would wind down its Gibson Innovations unit. The poor performance of the headphones and home entertainment business it bought for $135mn from Philips in 2014 was the single biggest cause of its filing, industry executives believe. Henry Juszkiewicz, Gibson’s chairman and chief executive, had dreamt of creating “the world's top music lifestyle company” but the debt Gibson took on to fund the diversification ended up rendering his 36% equity stake worthless. Just months after closing the deal with Philips, a sharp devaluation of the euro demolished profit margins at a company that was paying dollars for its materials but selling mostly to Europe. After disagreements about its pricing strategy, Mr. Juszkiewicz took hands-on control, but the damage was done. According to Brian Majeski, editor of The Music Trades, a music industry journal: “The Gibson bankruptcy really has nothing to do with the guitar business at all: it’s basically the collapse of consumer electronics.”

There were other headwinds too. In 2017, the Convention on International Trade in Endangered Species imposed unexpected restrictions on shipping rosewood across borders. The wood is widely used in guitar fingerboards, and as countries rushed to adapt, Gibson found itself effectively shut out of Europe for months. That said, guitar industry bears see other threats growing, from low-cost competition from Asian manufacturers to second-hand sales on sites such as Reverb. The industry is also watching its largest retailer nervously. Two weeks before Gibson’s Chapter 11 filing, S&P Global Ratings cut its credit rating for Guitar Center, which accounts for about one-third of the US retail market, to “selective default” after it reshuffled debt taken on in its 2007 private equity buyout by Bain Capital.

Gibson’s lenders hope it can emerge from Chapter 11 with a clean balance sheet and a focus on a core business that is healthy. The Music Trades estimates that US retail sales of guitars rose 8.8 per cent last year. Sales fell sharply in the financial crisis but have bounced 61 per cent since 2009, as the price of the average guitar has advanced from $361 to more than $500. With a third of the US market, Gibson is second only to Fender Musical Instruments, whose chief executive this week pointedly observed that the maker of the Stratocaster was enjoying “steady growth”. But even Gibson’s core business has been growing, albeit more modestly, according to IbisWorld, which estimates that its US guitar sales rose 1.8 per cent to $178m in 2017. With Gibson’s future uncertain, inspiration may come from one unexpected industry bright spot. The number of ukuleles sold in America has shot up from 500,000 in 2009 to 1.75mn last year. “We lived through an era of instant gratification,” Mr. Ball explains: “I think there is a return to something that’s analogue, that requires some effort and they know is going to last a while.”

6) Cheap innovations are often better than magical ones
[Source: Financial Times]
Tim Harford discusses in this piece how technological inventions of the past century – internet, electricity, the aeroplane and the telephone would all have seemed miraculous and inexplicable to earlier generations. Each of them exemplified what a technological breakthrough is supposed to look like, deservedly winning attention as they appeared. However, he says, we need to be careful, not to overlook much simpler technological advances. The lightbulb is a safer and more controllable source of artificial light than the candle or the oil lamp, but what really makes it transformative is its price - the cost of illumination has fallen approximately 400-fold in the past two centuries. Supercomputers and space travel get all the press. Merely being cheap doesn’t. But being cheap can change the world.

His favourite example is paper: the Gutenberg press radically reduced the cost of producing writing, but it was of little use without an accompanying fall in the cost of a writing surface. Compared to papyrus, parchment or silk, one of paper’s most important properties was that it cost very little. With all this in mind, what are today’s technological advances that we may be overlooking or misunderstanding because they are cheap rather than magical? The obvious answer: sensors. We are surrounded by inexpensive sensors — in our phones, increasingly in our cars — continually taking in information about the world. A new book suggests a different, albeit related, answer. Prediction Machines by Ajay Agrawal, Joshua Gans and Avi Goldfarb argues that we’re starting to enjoy the benefits of a new, low-cost service: predictions. Much of what we call “artificial intelligence”, say the authors, is best understood as a dirt-cheap prediction.

Predictions are everywhere. Google predicts that when one types “technology indis…” we are looking for information about Clarke’s third law; Amazon makes a prediction about what we might buy next, given what we bought already, or searched for, or placed on our wishlist. A prediction may literally be a forecast about the future, or more generally it may be an attempt to fill in some blanks on the basis of limited information. Not all such predictions are very good, but not all of them need to be, he says. The tiny keyboards on our smartphones turn out to be quite serviceable when combined with modestly accurate predictions — from suggesting an entire one-phrase email reply (“I agree with you”) to subtly expanding the “H” and shrinking the surrounding keys on a touchscreen if the phone thinks that “H” is the more likely target for a fat-thumbed typist.

Errors in predictive text tend to be trivial and easy to correct, so a high error rate does not matter much. Clumsy text predictors can be released into the world so that they may learn. A high error rate in a self-driving car is not so easy to forgive. As Mr. Agrawal and colleagues point out, sufficiently accurate predictions allow radically different business models. If a supermarket becomes good enough at predicting what I want to buy — perhaps conspiring with my fridge — then it can start shipping things to me without my asking, taking the bet that I will be pleased to see most of them when they arrive. Since good predictions reduce uncertainty, we may also see less demand for things that help us deal with uncertainty. If that smart fridge can arrange just-in-time delivery of meal ingredients by predicting my requirements, it can be much smaller as a result.

Another example is the airport lounge, a place designed to help busy people deal with the fact that in an uncertain world it is sensible to set off early for the airport. Route-planners, flight-trackers and other cheap prediction algorithms may allow many more people to trim their margin for error, arriving at the last moment and skipping the lounge. Then there is health insurance; if a computer becomes able to predict with high accuracy whether you will or will not get cancer, then it is not clear that there is enough uncertainty left to insure. All this seems a useful way to look at the fast-changing world of machine learning. Some automated predictions are already marvellously good, but many are changing the world not because they are omniscient, but because they’re good enough — and cheap.

7) Karl Marx 2.00 [Source: Indian Express]
On Karl Marx’s 200th birthday, Amartya Sen, a Nobel laureate in economics and professor of economics and philosophy at Harvard University, throws light on his philosophies. His philosophy has often been narrowly defined as ideas being determined by economic conditions. Marxian analysis remains important today not just because of Marx’s own original work, but also because of the extraordinary contributions made in that tradition by many leading historians, social scientists and creative artists — from Antonio Gramsci, Rosa Luxemburg, Jean-Paul Sartre and Bertolt Brecht to Piero Sraffa, Maurice Dobb and Eric Hobsbawm (to mention just a few names). One does not have to be a Marxist to make use of the richness of Marx’s insights — just as one does not have to be an Aristotelian to learn from Aristotle.

There are ideas in Marx’s corpus of work that remain under-explored. One of the relatively neglected ideas is Marx’s highly original concept of “objective illusion,” and related to that, his discussion of “false consciousness”. An objective illusion may arise from what we can see from our particular position — how things look from there (no matter how misleading). Consider the relative sizes of the sun and the moon, and the fact that from the earth they look to be about the same size (Satyajit Ray offered some interesting conversations on this phenomenon in his film, Agantuk). But to conclude from this observation that the sun and the moon are in fact of the same size in terms of mass or volume would be mistaken, and yet to deny that they do look to be about the same size from the earth would be a mistake too. Marx’s investigation of objective illusion — of “the outer form of things” — is a pioneering contribution to understanding the implications of positional dependence of observations.

The phenomenon of objective illusion helps to explain the widespread tendency of workers in an exploitative society to fail to see that there is any exploitation going on — an example that Marx did much to investigate, in the form of “false consciousness”. The idea can have many applications going beyond Marx’s own use of it. Powerful use can be made of the notion of objective illusion to understand, for example, how women, and indeed men, in strongly sexist societies may not see clearly enough — in the absence of informed political agitation — that there are huge elements of gender inequality in what look like family-oriented just societies, as bastions of role-based fairness.

There is, however, a danger in seeing Marx in narrowly formulaic terms — for example, in seeing him as a “materialist” who allegedly understood the world in terms of the importance of material conditions, denying the significance of ideas and beliefs. This is not only a serious misreading of Marx, who emphasized two-way relations between ideas and material conditions, but also a seriously missed opportunity to see the far-reaching role of ideas on which Marx threw such important light. In remembering Marx on his 200th birthday, we not only celebrate a great intellectual, but also one whose critical analyses and investigations have many insights to offer to us today. Paying attention to Marx may be more important than paying him respect.

8) Why great employees leave “Great Cultures”
[Source: HBR]
Culture is often referred to as “the way things are done around here.” To be more specific, the author, Melissa Daimler has been working in HR for over twenty years, and the best companies she’s worked with have recognized that there are three elements to a culture: behaviour, systems, and practices, all guided by an overarching set of values. A great culture is what you get when all three of these are aligned, and line up with the organisation’s espoused values. When gaps start to appear, that’s when you start to see problems — and see great employees leave. These gaps, she says can take many forms. A company might espouse “work-life balance” but not offer paid parental leave or expect people to stay late consistently every night (a behaviour-system gap). It might espouse being a learning organization that develops people, but then not give people the time to actually take classes or learn on the job (system-behaviour gap). Or it tells people to be consensus-builders, but promotes people who are solely authoritative decision makers (behaviour-practices gap). She discusses each of the three aspects below.

Behaviour: A common culture-building practice is the creation of value statements. But the real test is how leaders behave; how they enact these values, or don’t. People watch everything leaders do. If leaders are not exhibiting the behaviors that reflect the values, the values are meaningless. Employees also need clarity. Given your organizational values, which behaviors consistently get rewarded? Which behaviour lead to promotion? Melissa says organizations should spend the time identifying the behaviors and skills that express each of their organizational values. For example, if one saw someone exemplifying the value of “teamwork,” what would she be doing? What would she not be doing? One organization might identify teamwork behavior as “collaborates effectively through helping others.” Another might interpret a teamwork behavior as “collaborates effectively through encouraging productive disagreements.” Both can be done, but which behavior is expected and encouraged at one company vs. another?

Systems:
According to Melissa, there are five key systems that are important to the overall cultural system: a) Hiring: Instead of the common default to hiring for “cultural fit” — which in practice is usually an excuse for hiring people we find likable or similar to us — we can look for behaviors that are cultural complements b) Strategy and goal setting: These activities do two things, culture-wise: rally people around similar goals while also providing guidance on outcomes employees are expected to produce c) Assessing: How are behaviors assessed? How often are they reviewed? Is feedback shared consistently, and is it weighted based on who said it? Lack of trust or questions about what behavioral standards will be used will create political and fear-based environments d) Developing: When employees feel that professional development, feedback assessments, or engagement surveys are irrelevant, it’s usually because the questions don’t tie back to what the organization actually reinforces and rewards e) Rewarding: What is the criteria to become a manager, director, vice president? What are the expected behaviors that earn a person said title? What technical and leadership skills are needed? These are all expressions of culture and values, but too often they are perceived as random.

Practices: Practices include everything from company events, running meetings, feedback processes, to how decisions are made. Do you have repeatable decision-making processes in place? Are meeting participants expected to be collaborative and consensus-driven, or is some conflict OK? What should managers talk about in performance reviews? Practices need to change as the company changes — as it grows, reorganizes, or faces new threats. Once-useful practices can quickly become stale, meaningless, or even counter-productive. If the original intent of an off-site retreat was to help teams bond, what needs to shift now that the company has tripled in size?
 
Great organizations and leaders know that the culture stuff is the hard stuff. Culture takes time to define. It takes work to execute. Yet, if the time is spent (1) really understanding the behaviors expected throughout the organization; (2) identifying the systems and processes that will continue to help those behaviors be expressed and sustained; and (3) shaping practices that help employees and the organization become better, then one can close the culture gaps, and stop the best people from saying, “I know it’s a great culture, but I am leaving.

9) Why can’t we read anymore? [Source: Medium.com
In this article, the author discusses how he’s distracted by this digital world (like many of us) while reading a book. Being a writer, he has read only four books last year and that’s because whenever he starts reading a book, he needs a something to scratch that little itch at the back of his mind— just a quick look at email on iPhone; to write, and erase, a response to a funny Tweet from William Gibson; to find, and follow, a link to a good, really good, article in the New Yorker, or, better, the New York Review of Books. He has dedicated his life one way or another to books, yet he wasn’t able to read them. Why?
 
The reason being – every new email you get gives you a little flood of dopamine. Every little flood of dopamine reinforces your brain’s memory that checking email gives a flood of dopamine. And our brains are programmed to seek out things that will give us little floods of dopamine. Further, these patterns of behaviour start creating neural pathways, so that they become unconscious habits: Work on something important, brain itch, check email, dopamine, refresh, dopamine, check Twitter, dopamine, back to work. Over and over, and each time the habit becomes more ingrained in the actual structures of our brains.

According to the author, books are not just transferors of knowledge and emotion, but a special kind of tool that flattens oneself into another, that enable the trying-on of foreign ideas and emotions. Books recreate someone else’s thoughts inside our own minds, and maybe it is this one-to-one mapping of someone else’s words, on their own, without external stimuli, that give books their power. Books force us to let someone else’s thoughts inhabit our minds completely. So, what was the problem? The author couldn’t read books because his brain has been trained to want a constant hit of dopamine, which a digital interruption will provide and this digital dopamine addiction means he has trouble focusing: on books, work, family and friends.

So, in order to get his mind adapted to accommodate reading books again, he made a few lifestyle changes. And these were: 1) No more Twitter, Facebook, or article reading during the work day; 2) No reading of random news articles; 3) No smartphones or computers in the bedroom; 4) No TV after dinner; 5) Instead, go straight to bed and start reading a book. While the author had expected to fight for concentration, it wasn’t that hard. With less digital input (no pre-bed TV, especially), extra time (no TV, again), and without a tempting digital device near at hand, there was time and space for my mind to settle into a book. He is reading books now more than he has in years. He has more energy, and more focus than he had for ages. Though he has not fully conquered his digital dopamine addiction yet, he’s getting there. Reading books is helping him retrain his mind for focus.

10) The gambler who cracked the horse-racing code [Source: Bloomberg
Imagine you won a horse-racing jackpot of $16 million in 2001. What would you have done? Claim the prize money or leave it unclaimed? This article revolves around a gambler, Bill Benter, who did the impossible. Veteran gamblers know you can’t beat the horses. There are too many variables and too many possible outcomes. Front-runners break a leg. Jockeys fall. Champion thoroughbreds decide, for no apparent reason, that they’re simply not in the mood. The American sportswriter Roger Kahn once called the sport “animated roulette.” Play for long enough, and failure isn’t just likely but inevitable—so the wisdom goes. “If you bet on horses, you will lose,” says Warwick Bartlett, who runs Global Betting & Gaming Consultants and has spent years studying the industry.

But, Benter masterminded a system that guaranteed a profit. Benter wanted to conquer horse betting not because it was hard, but because it was said to be impossible. When he cracked it, he actively avoided acclaim. At a young age, Benter had been enraptured by “Beat the Dealer”, a 1962 book by math professor and legendary investor, Edward Thorp, that describes how to overcome the house’s advantage in blackjack. Thorp’s book was a beacon for shy young men with a gift for mathematics and a yearning for a more interesting life. Then, while working a night cleaner at McDonalds, Benter’s buddies introduced him to the man who would change his life. Alan Woods was the leader of an Australian card-counting team that had recently arrived in Las Vegas. Woods impressed Benter with his tales of fearlessness, recounting how he’d sneaked past airport security in Manila with $10,000 stuffed into his underwear. Benter joined Woods’ squad. Within six weeks, he found himself playing blackjack in Monte Carlo, served by waiters in dinner jackets. He felt like James Bond, and his earnings grew to a rate of about $80,000 a year.

In September 1985 Benter flew to Hong Kong with three bulky IBM computers in his checked luggage. Benter and Woods rented a microscopic apartment in a dilapidated high-rise and started betting on horses in Hong Kong. Benter hired two women to key the results into a database by hand so he could spend more time studying regressions and developing code. Twice a week, on race days, Benter would sit at the computer and Woods would study the racing form. Early on, the betting program Benter had written spat out bizarre predictions, and Woods, with his yearlong head start studying the Hong Kong tracks, would correct them. Between races, Benter struggled to make his algorithms stay ahead of a statistical phenomenon called gambler’s ruin. It holds that if a player with limited funds keeps betting against an opponent with unlimited funds (that is, a casino, or the betting population of Hong Kong), he will eventually go broke, even if the game is fair. All lucky streaks come to an end, and losing runs are fatal.

By the end of Benter’s first season in Hong Kong, in the summer of 1986, he and Woods had lost $120,000 of their $150,000 stake. Later, Benter and Woods had a fall-out over their partnership. Benter started focusing on his models and he hired anyone, coders, academics, journalists, who could improve his algorithms. A breakthrough came when Benter hit on the idea of incorporating a data set hiding in plain sight: the Jockey Club’s publicly available betting odds. Building his own set of odds from scratch had been profitable, but he found that using the public odds as a starting point and refining them with his proprietary algorithm was dramatically more profitable. He considered the move his single most important innovation, and in the 1990-91 season, he said, he won about $3 million.

It was then, in November 2001, that he decided to have a final punt on the Triple Trio. Benter had avoided major prizes since 1997 for fear of angering the Jockey Club’s management, but this jackpot was too big to resist. Wagering on it was something of a lark, albeit an expensive one: He spent HK$1.6 million on the 51,000 combinations. If he won, he decided, he would leave the tickets unclaimed. Club policy in such cases directed the money to a charitable trust. Today, Benter has become a philanthropist and has been donating for various causes. Also, the online betting on sports today, of all kinds, is a $60 billion industry, growing rapidly everywhere outside the U.S. – where the practice is mostly banned.
 
- Saurabh Mukherjea is CEO, and Prashant Mittal is Strategist, at Ambit Capital. Views expressed are personal

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