Book Club: The Code Economy: The DNA of Business

“DNA builds products with a purpose. So do people.” –Auerswald, The Code Economy

McDonald’s is the world’s largest restaurant chain by revenue[7], serving over 69 million customers daily in over 100 countries[8] across approximately 36,900 outlets as of 2016.[9] … According to a BBC report published in 2012, McDonald’s is the world’s second-largest private employer (behind Walmart with 1.9 million employees), 1.5 million of whom work for franchises. …

There are currently a total of 5,669 company-owned locations and 31,230 franchised locations… Notably, McDonald’s has increased shareholder dividends for 25 consecutive years,[18] making it one of the S&P 500 Dividend Aristocrats.[19][20]

According to Fast Food Nation by Eric Schlosser (2001), nearly one in eight workers in the U.S. have at some time been employed by McDonald’s. … Fast Food Nation also states that McDonald’s is the largest private operator of playgrounds in the U.S., as well as the single largest purchaser of beef, pork, potatoes, and apples.  (Wikipedia)

How did a restaurant whose only decent products are french fries and milkshakes come to dominate the global corporate landscape?

IKEA is not only the world’s largest furniture store, but also among the globe’s top 10 retailers of anything and the 25th most beloved corporation. (Disney ranks number one.) Even I feel a strange, heartwarming emotion at the thought of IKEA, which somehow comes across as a sweet and kind multi-national behemoth.

In The Code Economy, Auerswald suggests that the secret to McDonald’s success isn’t (just) the french fries and milkshake machines:

Kroc opened his first McDonald’s restaurant in 1955 in Des Plaines, California. Within five years he had opened two hundred new franchises across the country. [!!!] He pushed his operators obsessively to adhere to a system that reinforced the company motto: “Quality, service, cleanliness, and value.”

h/t @simongerman600

Quoting Kroc’s1987 autobiography,

“It’s all interrelated–our development of the restaurant, the training, the marketing advice, the product development, the research that has gone into each element of the equipment package. Together with our national advertising and continuing supervisory assistance, it forms an invaluable support system. Individual operators pay 11.5 percent of their gross to the corporation for all of this…”

The process of operating a McDonald’s franchise was engineered to be as cognitively undemanding as possible. …

Kroc created a program that could be broken into subroutines…. Acting like the DNA of the organization, the manual allowed the Speedee Service System to function in a variety of environments without losing essential structure or function.

McDonald’s is big because it figured out how to reproduce.

source: Statista

I’m not sure why IKEA is so big (I don’t think it’s a franchise like McDonald’s,) but based on the information posted on their walls, it’s because of their approach to furniture design. First, think of a problem, eg, People Need Tables. Second, determine a price–IKEA makes some very cheap items and some pricier items, to suit different customers’ needs. Third, use Standard IKEA Wooden Pieces to design a nice-looking table. Fourth, draw the assembly instructions, so that anyone, anywhere, can assemble the furniture themselves–no translation needed.

IKEA furniture is kind of like Legos, in that much of it is made of very similar pieces of wood assembled in different ways. The wooden boards in my table aren’t that different in size and shape from the ones in my dresser nor the ones in my bookshelf, though the items themselves have pretty different dimensions. So on the production side, IKEA lowers costs by producing not actual furniture, but collections of boards. Boards are easy to make–sawmills produce tons of them.

Furniture is heavy, but mostly empty space. By contrast, piles of boards stack very neatly and compactly, saving space both in shipping and when buyers are loading the boxes into their cars. (I am certain that IKEA accounts for common car dimensions in designing and packing their furniture.)

And the assembly instruction allow the buyer to ultimately construct the furniture.

In other words, IKEA has hit upon a successful code that allows them to produce many different designs from a few basic boards and ship them efficiently–keeping costs low and allowing them to thrive.

From Anatomy of an IKEA product:

The company is also looking for ways to maximize warehouse efficiency.

“We have (only) two pallet sizes,” Marston said, referring to the wooden platforms on which goods are placed. “Our warehouses are dimensioned and designed to hold these two pallet sizes. It’s all about efficiencies because that helps keep the price of innovation down.”

In Europe, some IKEA warehouses utilize robots to “pick the goods,” a term of art for grabbing products off very high shelves.

These factories, Marston said, are dark, since no lighting is needed for the robots, and run 24 hours a day, picking and moving goods around.

“You (can) stand on a catwalk,” she said, “and you look out at this huge warehouse with 12 pallets (stacked on top of each other) and this robot’s running back and forth running on electronic eyebeams.”

IKEA’s code and McDonald’s code are very different, but both let the companies produce the core items they sell quickly, cheaply, and efficiently.

In The Code Economy, Chapter 8: Evolution, discusses the rise of Tollhouse Cookies, McDonald’s, the difference between natural and artificial objects, and the development of evolutionary theory from Darwin through Watson and Crick and through to Kauffman and Levine’s 1987 paper, “Toward a General Theory of Adaptive Walks on Rugged Landscapes.” (With a brief stop at Erwin Shrodinger along the way.)

The difficulty with evolution is that systems are complicated; successful mutations or even just combinations of existing genes must work synergistically with all of the other genes and systems already operating in the body. A mutation that increases IQ by tweaking neurons in a particular way might have the side effect of causing neurons outside the brain to malfunction horribly; a mutation that protects against sickle-cell anemia when you have one copy of it might just kill you itself if you have two copies.

Auerswald quotes Kauffman and Levin:

“Natural selection does not work as an engineer works… It works like a tinkereer–a tinkerer who does not know exactly what he is going to produce but uses… everything at his disposal to produce some kind of workable object.” This process is progressive, moving form simpler to more complex forms: “Evolution doe not produce novelties from scratch. It works on what already exists, either transforming a system to give it new functions or combining several systems to produce a more elaborate one [as] during the passage from unicellular to multicellular forms.”

Further:

The Kauffman and Levin model was as simple as it was powerful. Imagine a genetic code of length N, where each gene might occupy one of two possible “states”–for example, “o” and “i” in a binary computer. The difficulty of the evolutionary problem was tunable with the parameter K, which represented the average number of interactions among genes. The NK model, as it came to be called, was able to reproduce a number of measurable features of evolution in biological systems. Evolution could be represented as a genetic walk on a fitness landscape, in which increasing complexity was now a central parameter.

You may remember my previous post on Local Optima, Diversity, and Patchwork:

Local optima–or optimums, if you prefer–are an illusion created by distance. A man standing on the hilltop at (approximately) X=2 may see land sloping downward all around himself and think that he is at the highest point on the graph. But hand him a telescope, and he discovers that the fellow standing on the hilltop at X=4 is even higher than he is. And hand the fellow at X=4 a telescope, and he’ll discover that X=6 is even higher.

A global optimum is the best possible way of doing something; a local optimum can look like a global optimum because all of the other, similar ways of doing the same thing are worse.

Some notable examples of cultures that were stuck at local optima but were able, with exposure, to jump suddenly to a higher optima: The “opening of Japan” in the late 1800s resulted in breakneck industrialization and rising standards of living; the Cherokee invented their own alphabet (technically a syllabary) after glimpsing the Roman one, and achieved mass literacy within decades; European mathematics and engineering really took off after the introduction of Hindu-Arabic numerals and the base-ten system.

If we consider each culture its own “landscape” in which people (and corporations) are finding locally optimal solutions to problems, then it becomes immediately obvious that we need both a large number of distinct cultures working out their own solutions to problems and occasional communication and feedback between those cultures so results can transfer. If there is only one, global, culture, then we only get one set of solutions–and they will probably be sub-optimal. If we have many cultures but they don’t interact, we’ll get tons of solutions, and many of them will be sub-optimal. But many cultures developing their own solutions and periodically interacting can develop many solutions and discard sub-optimal ones for better ones.

On a related note, Gore Burnelli writes: How Nassim Taleb changed my mind about religion:

Life constantly makes us take decisions under conditions of uncertainty. We can’t simply compute every possible outcome, and decide with perfect accuracy what the path forward is. We have to use heuristics. Religion is seen as a record of heuristics that have worked in the past. …

But while every generation faces new circumstances, there are also some common problems that every living being is faced with: survival and reproduction, and these are the most important problems because everything else depends on them. Mess with these, and everything else becomes irrelevant.

This makes religion an evolutionary record of solutions which persisted long enough, by helping those who held them to persist.

This is not saying “All religions are perfect and good and we should follow them,” but it is suggesting, “Traditional religions (and cultures) have figured out ways to solve common problems and we should listen to their ideas.”

From Ray Kurzweil

Back in The Code Economy, Auerswald asks:

Might the same model, derived from evolutionary biology, explain the evolution of technology?

… technology may also be nothing else but the capacity for invariant reproduction. However, in order for more complex forms of technology to be viable over time, technology also must possess a capacity for learning and adaptation.

Evolutionary theory as applied to the advance of code is the focus of the next chapter. Kauffman and Levin’s NK model ends up providing a framework for studying the creation and evolution of code. Learning curves act as the link between biology and economics.

Will the machines become sentient? Or McDonald’s? And which should we worry about?

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Local Optima, Diversity, and Patchwork

Local optima–or optimums, if you prefer–are an illusion created by distance. A man standing on the hilltop at (approximately) X=2 may see land sloping downward all around himself and think that he is at the highest point on the graph.

But hand him a telescope, and he discovers that the fellow standing on the hilltop at X=4 is even higher than he is. And hand the fellow at X=4 a telescope, and he’ll discover that X=6 is even higher.

A global optimum is the best possible way of doing something; a local optimum can look like a global optimum because all of the other, similar ways of doing the same thing are worse. To get from a local optimum to a global optimum, you might have to endure a significant trough of things going worse before you reach your destination. (Those troughs would be the points X=3.03 and X=5.02 on the graph.) If the troughs are short and shallow enough, people can accidentally power their way through. If long and deep enough, people get stuck.

The introduction of new technology, exposure to another culture’s solutions, or even random chance can expose a local optimum and propel a group to cross that trough.

For example, back in 1400, Europeans were perfectly happy to get their Chinese silks, spices, and porcelains via the overland Silk Road. But with the fall of Constantinople to the Turks in 1453, the Silk Road became more fragmented and difficult (ie dangerous, ie expensive) to travel. The increased cost of the normal road prompted Europeans to start exploring other, less immediately profitable trade routes–like the possibility of sailing clear around the world, via the ocean, to the other side of China.

Without the eastern trade routes first diminishing in profitability, it wouldn’t have been economically viable to explore and develop the western routes. (With the discovery of the Americas, in the process, a happy accident.)

West Hunter (Greg Cochran) writes frequently about local optima; here’s an excerpt on plant domestication:

The reason that a few crops account for the great preponderance of modern agriculture is that a bird in the hand – an already-domesticated, already- optimized crop – feeds your family/makes money right now, while a potentially useful yet undomesticated crop doesn’t. One successful domestication tends to inhibit others that could flourish in the same niche. Several crops were domesticated in the eastern United States, but with the advent of maize and beans ( from Mesoamerica) most were abandoned. Maybe if those Amerindians had continued to selectively breed sumpweed for a few thousand years, it could have been a contender: but nobody is quite that stubborn.

Teosinte was an unpromising weed: it’s hard to see why anyone bothered to try to domesticate it, and it took a long time to turn it into something like modern maize. If someone had brought wheat to Mexico six thousand years ago, likely the locals would have dropped maize like a hot potato. But maize ultimately had advantages: it’s a C4 plant, while wheat is C3: maize yields can be much higher.

Teosinte is the ancestor of modern corn. Cochran’s point is that in the domestication game, wheat is a local optimum; given the wild ancestors of wheat and corn, you’d develop a better, more nutritious variety of wheat first and probably just abandon the corn. But if you didn’t have wheat and you just had corn, you’d keep at the corn–and in the end, get an even better plant.

(Of course, corn is a success story; plenty of people domesticated plants that actually weren’t very good just because that’s what they happened to have.)

Japan in 1850 was a culturally rich, pre-industrial, feudal society with a strong isolationist stance. In 1853, the Japanese discovered that the rest of the world’s industrial, military technology was now sufficiently advanced to pose a serious threat to Japanese sovereignty. Things immediately degenerated, culminating in the Boshin War (civil war, 1868-9,) but with the Meiji Restoration Japan embarked on an industrialization crash-course. By 1895, Japan had kicked China’s butt in the First Sino-Japanese War and the Japanese population doubled–after holding steady for centuries–between 1873 and 1935. (From 35 to 70 million people.) By the 1930s, Japan was one of the world’s most formidable industrial powers, and today it remains an economic and technological powerhouse.

Clearly the Japanese people, in 1850, contained the untapped ability to build a much more complex and advanced society than the one they had, and it did not take much exposure to the outside world to precipitate a total economic and technological revolution.

Sequoyah’s syllabary, showing script and print forms

A similar case occurred in 1821 when Sequoyah, a Cherokee man, invented his own syllabary (syllable-based alphabet) after observing American soldiers reading letters. The Cherokee quickly adopted Sequoyah’s writing system–by 1825, the majority of Cherokee were literate and the Cherokee had their own printing industry. Interestingly, although some of the Cherokee letters look like Latin, Greek, or Cyrillic letters, there is no correspondence in sound, because Sequoyah could not read English. He developed his entire syllabary after simply being exposed to the idea of writing.

The idea of literacy has occurred independently only a few times in human history; the vast majority of people picked up alphabets from someone else. Our Alphabet comes from the Latins who got it from the Greeks who adopted it from the Phoenicians who got it from some proto-canaanite script writers, and even then literacy spread pretty slowly. The Cherokee, while not as technologically advanced as Europeans at the time, were already a nice agricultural society and clearly possessed the ability to become literate as soon as they were exposed to the idea.

When I walk around our cities, I often think about what their ruins will look like to explorers in a thousand years
We also pass a ruin of what once must have been a grand building. The walls are marked with logos from a Belgian University. This must have once been some scientific study centre of sorts.”

By contrast, there are many cases of people being exposed to or given a new technology but completely lacking the ability to functionally adopt, improve, or maintain it. The Democratic Republic of the Congo, for example, is full of ruined colonial-era buildings and roads built by outsiders that the locals haven’t maintained. Without the Belgians, the infrastructure has crumbled.

Likewise, contact between Europeans and groups like the Australian Aboriginees did not result in the Aboriginees adopting European technology nor a new and improved fusion of Aboriginee and European tech, but in total disaster for the Aboriginees. While the Japanese consistently top the charts in educational attainment, Aboriginee communities are still struggling with low literacy rates, high dropout rates, and low employment–the modern industrial economy, in short, has not been kind to them.

Along a completely different evolutionary pathway, cephalopods–squids, octopuses, and their tentacled ilk–are the world’s smartest invertebrates. This is pretty amazing, given that their nearest cousins are snails and clams. Yet cephalopod intelligence only goes so far. No one knows (yet) just how smart cephalopods are–squids in particular are difficult to work with in captivity because they are active hunter/swimmers and need a lot more space than the average aquarium can devote–but their brain power appears to be on the order of a dog’s.

After millions of years of evolution, cephalopods may represent the best nature can do–with an invertebrate. Throw in a backbone, and an animal can get a whole lot smarter.

And in chemistry, activation energy is the amount of energy you have to put into a chemical system before a reaction can begin. Stable chemical systems essentially exist at local optima, and it can require the input of quite a lot of energy before you get any action out of them. For atoms, iron is the global–should we say universal?–optimum, beyond which reactions are endothermic rather than exothermic. In other words, nuclear fusion at the core of the sun ends with iron; elements heavier than iron can only be produced when stars explode.

So what do local optima have to do with diversity?

The current vogue for diversity (“Diversity is our greatest strength”) suggests that we can reach global optima faster by simply smushing everyone together and letting them compare notes. Scroll back to the Japanese case. Edo Japan had a nice culture, but it was also beset by frequent famines. Meiji Japan doubled its population. Giving everyone, right now, the same technology and culture would bring everyone up to the same level.

But you can’t tell from within if you are at a local or global optimum. That’s how they work. The Indians likely would have never developed corn had they been exposed to wheat early on, and subsequently Europeans would have never gotten to adopt corn, either. Good ideas can take a long time to refine and develop. Cultures can improve rapidly–even dramatically–by adopting each other’s good ideas, but they also need their own space and time to pursue their own paths, so that good but slowly developing ideas aren’t lost.

Which gets us back to Patchwork.