Tag: Red Queen Effect

Breaking the Rules: Moneyball Edition

Most of the book Simple Rules by Donald Sull and Kathleen Eisenhardt talks about identifying a problem area (or an area ripe for “simple rules”) and then walks you through creating your own set of rules. It’s a useful mental process.

An ideal situation for simple rules is something repetitive, giving you constant feedback so you can course correct as you go. But what if your rules stop working and you need to start over completely?

Simple Rules recounts the well-known Moneyball tale in its examination of this process:

The story begins with Sandy Alderson. Alderson, a former Marine with no baseball background became the A’s general manager in 1983. Unlike baseball traditionalists, Alderson saw scoring runs as a process, not an outcome, and imagined baseball as a factory with a flow of players moving along the bases. This view led Alderson and later his protege and replacement, Billy Beane, to the insight that most teams overvalue batting average (hits only) and miss the relevance of on-base percentage (walks plus hits) to keeping the runners moving. Like many insightful rules, this boundary rule of picking players with a high on base percentage has subtle second – and third-order effects. Hitters with a high on-base percentage are highly disciplined (i.e., patient, with a good eye for strikes). This means they get more walks, and their reputation for discipline encourages pitchers to throw strikes, which are easier to hit. They tire out pitchers by making them throw more pitches overall, and disciplined hitting does not erode much with age. These and other insights are at the heart of what author Michael Lewis famously described as moneyball.

The Oakland A’s did everything right, they had examined the issues, they tried to figure out those areas which would most benefit from a set of simple rules and they had implemented them. The problem was, they were easy rules to copy. 

They were operating in a Red Queen Effect world where everyone around them was co-evolving, where running fast was just enough to get ahead temporarily, but not permanently. The Red Sox were the first and most successful club to copy the A’s:

By 2004, a free-spending team, the Boston Red Sox, co-opted the A’s principles and won the World Series for the first time since 1918. In contrast, the A’s went into decline, and by 2007 the were losing more games than they were winning Moneyball had struck out.

What can we do when the rules stop working? 

We must break them.


When the A’s had brought in Sandy Alderson, he was an outsider with no baseball background who could look at the problem in a different and new light. So how could that be replicated?

The team decided to bring in Farhan Zaidi as director of baseball operations in 2009. Zaidi spent most of his life with a pretty healthy obsession for baseball but he had a unique background: a PhD in behavioral economics.

He started on the job of breaking the old rules and crafting new ones. Like Andy Grove did once upon a time with Intel, Zaidi helped the team turn and face a new reality. Sull and Eisenhardt consider this as a key trait:

To respond effectively to major change, it is essential to investigate the new situation actively, and create a reimagined vision that utilizes radically different rules.

The right choice is often to move to the new rules as quickly as possible. Performance will typically decline in the short run, but the transition to the new reality will be faster and more complete in the long run. In contrast, changing slowly often results in an awkward combination of the past and the future with neither fitting the other or working well.

Beane and Zaidi first did some house cleaning: They fired the team’s manager. Then, they began breaking the old Moneyball rules, things like avoiding drafting high-school players. They also decided to pay more attention to physical skills like speed and throwing.

In the short term, the team performed quite poorly as fan attendance showed a steady decline. Yet, once again, against all odds, the A’s finished first in their division in 2012. Their change worked. 

With a new set of Simple Rules, they became a dominant force in their division once again. 

Reflecting their formidable analytic skills, the A’s brass had a new mindset that portrayed baseball as a financial market rife with arbitrage possibilities and simple rules to match.

One was a how-to rule that dictated exploiting players with splits. Simply put, players with splits have substantially different performances in two seemingly similar situations. A common split is when a player hits very well against right-handed pitchers and poorly against left-handed pitchers, or vice versa. Players with spits are mediocre when they play every game, and are low paid. In contrast, most superstars play well regardless of the situation, and are paid handsomely for their versatility. The A’s insight was that when a team has a player who can perform one side of the split well and a different player who excels at the opposite split, the two positives can create a cheap composite player. So the A’s started using a boundary rule to pick players with splits and how-to rule to exploit those splits with platooning – putting different players at the same position to take advantage of their splits against right – or left-handed pitching.

If you’re reading this as a baseball fan, you’re probably thinking that exploiting splits isn’t anything new. So why did it have such an effect on their season? Well, no one had pushed it this hard before, which had some nuanced effects that might not have been immediately apparent.

For example, exploiting these splits keeps players healthier during the long 162-game season because they don’t play every day. The rule keeps everyone motivated because everyone has a role and plays often. It provides versatility when players are injured since players can fill in for each other.

They didn’t stop there. Zaidi and Beane looked at the data and kept rolling out new simple rules that broke with their highly successful Moneyball past.

In 2013 they added a new boundary rule to the player-selection activity: pick fly-ball hitters, meaning hitters who tend to hit the ball in the air and out of the infield (in contrast with ground-ball hitters). Sixty percent of the A’s at-bat were by fly-ball hitters in 2013, the highest percentage in major-league baseball in almost a decade, and the A’s had the highest ratio of fly ball to ground balls, by far. Why fly-ball hitters?

Since one of ten fly balls is a home run, fly-ball hitters hit more home runs: an important factor in winning games. Fly-ball hitters also avoid ground-ball double plays, a rally killer if ever there as one. They are particularly effective against ground-ball pitches because they tend to swing underneath the ball, taking way the advantage of those pitchers. In fact, the A’s fly-ball hitters batted an all-star caliber .302 against ground-ball pitchers in 2013 on their way to their second consecutive division title despite having the fourth-lowest payroll in major-league baseball.

Unfortunately, the new rules had a short-lived effectiveness: In 2014 the A’s fell to 2nd place and have been struggling the last two seasons. Two Cinderella stories is a great achievement, but it’s hard to maintain that edge. 

This wonderful demonstration of the Red Queen Effect in sports can be described as an “arms race.’” As everyone tries to get ahead, a strange equilibrium is created by the simultaneous continual improvement, and those with more limited resources must work even harder as the pack moves ahead one at a time.

Even though they have adapted and created some wonderful “Simple Rules” in the past, the A’s (and all of their competitors) must stay in the race in order to return to the top: No “rule” will allow them to rest on their laurels. Second Level Thinking and a little real world experience shows this to be true: Those that prosper consistently will think deeply, reevaluate, adapt, and continually evolve. That is the nature of a competitive world. 

The Peter Principle

Laurence J. Peter and James Hull defined The Peter Principle: “In a hierarchically structured administration, people tend to be promoted up to their level of incompetence.”

I think that’s fairly well understood, but what does it look like if we frame it in an evolutionary perspective?

The evolutionary generalization of the principle is less pessimistic in its implications, since evolution lacks the bureaucratic inertia that pushes and maintains people in an unfit position. But what will certainly remain is that systems confronted by evolutionary problems will quickly tackle the easy ones, but tend to get stuck in the difficult ones. The better (more fit, smarter, more competent, more adaptive) a system is, the more quickly it will solve all the easy problems, but the more difficult the problem will be it finally gets stuck in. Getting stuck here does not mean “being unfit”, it just means having reached the limit of one’s competence, and thus having great difficulty advancing further. This explains why even the most complex and adaptive species (such as ourselves, humans) are always still “struggling for survival” in their niches as energetically as are the most primitive organisms such as bacteria. If ever a species would get control over all its evolutionary problems, then the “Red Queen Principle” would make sure that new, more complex problems would arise, so that the species would continue to balance on the border of its domain of incompetence. In conclusion, the generalized Peter principle states that in evolution systems tend to develop up to the limit of their adaptive competence.

The Red Queen Effect: Avoid Running Faster and Faster Only to Stay in the Same Place

The Red Queen Effect

Charles Lutwidge Dodgson (1832-1898), better known by his pseudonym Lewis Carroll, was not only an author but a keen observer of human nature. His most famous works are Alice’s Adventures in Wonderland and its sequel Through the Looking Glasswhich have become timeless classics.

“Bees have to move very fast to stay still.”

— David Foster Wallace

In Through the Looking Glass, Alice, a young girl, gets schooled by the Red Queen in an important life lesson that many of us fail to heed. Alice finds herself running faster and faster but saying in the same place.

Alice never could quite make out, in thinking it over afterwards, how it was that they began: all she remembers is, that they were running hand in hand, and the Queen went so fast that it was all she could do to keep up with her: and still the Queen kept crying ‘Faster! Faster!’ but Alice felt she could not go faster, though she had not breath left to say so.

The most curious part of the thing was, that the trees and the other things round them never changed their places at all: however fast they went, they never seemed to pass anything. ‘I wonder if all the things move along with us?’ thought poor puzzled Alice. And the Queen seemed to guess her thoughts, for she cried, ‘Faster! Don’t try to talk!’

Eventually, the Queen stops running and props Alice up against a tree, telling her to rest.

Alice looked round her in great surprise. ‘Why, I do believe we’ve been under this tree the whole time! Everything’s just as it was!’

‘Of course it is,’ said the Queen, ‘what would you have it?’

‘Well, in our country,’ said Alice, still panting a little, ‘you’d generally get to somewhere else — if you ran very fast for a long time, as we’ve been doing.’

‘A slow sort of country!’ said the Queen. ‘Now, here, you see, it takes all the running you can do, to keep in the same place.

If you want to get somewhere else, you must run at least twice as fast as that!’

“It is not the strongest of the species that survives,
nor the most intelligent,
but the one most responsive to change.”

— Charles Darwin

Smarter, Not Harde

The Red Queen Effect means we can’t be complacent or we’ll fall behind. To survive another day we have to run very fast and hard, we need to co-evolve with the systems we interact with.

If all animals evolved at the same rate, there would be no change in the relative interactions between species. However, not all animals evolve at the same rate. As Darwin observed, some are more “responsive to change” than others. Species that are more responsive to change can gain a relative advantage over the ones they compete with and increase the odds of survival. In the short run, these small gains don’t make much of a difference, but as generations pass the advantage can compound. A compounding advantage… that sounds nice.

Everyone from Entrepreneurs and Fortune 500 CEOs to best-selling authors and middle managers is embedded is in their own Red Queen. Rather than run harder, wouldn’t it be nice to run smarter?

Here are just three of the ways we try to avoid the Red Queen.

  1. We invest significantly in new product development and content. Our courses, evolve quickly incorporating student-tested concepts that work and reducing the importance of the ones that don’t. Another example, our learning community, adds real-world value to people who make decisions by discussing time-tested principles. This is not a popular path as it’s incredibly expensive in time and money. Standing still, however, is more expensive. We’re not in the business of Edutainment but rather providing better outcomes. If we fail to keep getting better, we won’t exist.
  2. We try to spend our limited mental resources working on things that won’t change next week. We call these mental models and the ones we want to focus on are the ones that stand the test of time.
  3. We recognize how the world works and not how we want it to work. When the world isn’t working the way we’d like it to, it’s easy to say the world is wrong and sit back to see what happens. You know what happens right? You fall behind and it’s even harder to catch up. It’s like you’re on a plane. When you’re flying into the wind you have to work very hard. When you’re flying with the wind at your back, you need to expend less energy and you get there earlier. Recognizing reality and adapting your behavior creates a tailwind.

More Examples of the Red Queen Effect

In Deep Simplicity, John Gribbon describes the red queen principle with frogs.

There are lots of ways in which the frogs, who want to eat flies, and the flies, who want to avoid being eaten, interact. Frogs might evolve longer tongues, for fly-catching purposes; flies might evolve faster flight, to escape. Flies might evolve an unpleasant taste, or even excrete poisons that damage the frogs, and so on. We’ll pick one possibility. If a frog has a particularly sticky tongue, it will find it easier to catch flies. But if flies have particularly slippery bodies, they will find it easier to escape, even if the tongue touches them. Imagine a stable situation in which a certain number of frogs live on a pond and eat a certain proportion of the flies around them each year.

Because of a mutation a frog developes an extra sticky tongue. It will do well, compared with other frogs, and genes for extra sticky tongues will spread through the frog population. At first, a larger proportion of flies gets eaten. But the ones who don’t get eaten will be the more slippery ones, so genes for extra slipperiness will spread through the fly population. After a while, there will be the same number of frogs on the pond as before, and the same proportion of flies will be eaten each year. It looks as if nothing has changed – but the frogs have got stickier tongues, and the flies have got more slippery bodies.

Drugs and disease also represent an “arms-race.”

Siddhartha Mukherjee, in his Pulitzer-prize winning book The Emperor of All Maladies describes this in the context of drugs and cancer.

In August 2000, Jerry Mayfield, a forty-one-year-old Louisiana policeman diagnosed with CML, began treatment with Gleevec. Mayfield’s cancer responded briskly at first. The fraction of leukemic cells in his bone marrow dropped over six months. His blood count normalized and his symptoms improved; he felt rejuvenated—“like a new man [on] a wonderful drug.” But the response was short-lived. In the winter of 2003, Mayfield’s CML stopped responding. Moshe Talpaz, the oncologist treating Mayfield in Houston, increased the dose of Gleevec, then increased it again, hoping to outpace the leukemia. But by October of that year, there was no response. Leukemia cells had fully recolonized his bone marrow and blood and invaded his spleen. Mayfield’s cancer had become resistant to targeted therapy…

… Even targeted therapy, then, was a cat-and-mouse game. One could direct endless arrows at the Achilles’ heel of cancer, but the disease might simply shift its foot, switching one vulnerability for another. We were locked in a perpetual battle with a volatile combatant. When CML cells kicked Gleevec away, only a different molecular variant would drive them down, and when they outgrew that drug, then we would need the next-generation drug. If the vigilance was dropped, even for a moment, then the weight of the battle would shift. In Lewis Carroll’s Through the Looking-Glass, the Red Queen tells Alice that the world keeps shifting so quickly under her feet that she has to keep running just to keep her position. This is our predicament with cancer: we are forced to keep running merely to keep still.

This doesn’t only happen in nature, there are many business examples as well. 

In describing the capital investment needed to maintain a relative placement in the textile industry, Warren Buffett writes:

Over the years, we had the option of making large capital expenditures in the textile operation that would have allowed us to somewhat reduce variable costs. Each proposal to do so looked like an immediate winner. Measured by standard return-on-investment tests, in fact, these proposals usually promised greater economic benefits than would have resulted from comparable expenditures in our highly-profitable candy and newspaper businesses.

But the promised benefits from these textile investments were illusory. Many of our competitors, both domestic and foreign, were stepping up to the same kind of expenditures and, once enough companies did so, their reduced costs became the baseline for reduced prices industrywide. Viewed individually, each company’s capital investment decision appeared cost-effective and rational; viewed collectively, the decisions neutralized each other and were irrational (just as happens when each person watching a parade decides he can see a little better if he stands on tiptoes). After each round of investment, all the players had more money in the game and returns remained anemic.

In other words, more and more money is needed just to maintain your relative position in the industry and stay in the game. This situation plays out over and over again and brings with it many ripple effects. For example, the company distracted by maintaining a relative position in a poor industry places resources in a position almost assured to get a poor return on capital.

Inflation also causes a Red Queen Effect, here’s Buffett Again:

Unfortunately, earnings reported in corporate financial statements are no longer the dominant variable that determines whether there are any real earnings for you, the owner. For only gains in purchasing power represent real earnings on investment. If you (a) forego ten hamburgers to purchase an investment; (b) receive dividends which, after tax, buy two hamburgers; and (c) receive, upon sale of your holdings, after-tax proceeds that will buy eight hamburgers, then (d) you have had no real income from your investment, no matter how much it appreciated in dollars. You may feel richer, but you won’t eat richer.

High rates of inflation create a tax on capital that makes much corporate investment unwise—at least if measured by the criterion of a positive real investment return to owners. This “hurdle rate” the return on equity that must be achieved by a corporation in order to produce any real return for its individual owners—has increased dramatically in recent years. The average tax-paying investor is now running up a down escalator whose pace has accelerated to the point where his upward progress is nil.

The Red Queen is part of the Farnam Street latticework of mental models.

– The excellent Sanjay Bakshi
Through the Looking Glass