Processes, Methodologies, and the Human Brain
Original from 6/24/2010: Gestão 2.0
The human brain is a fantastic machine, and saying that is basically a redundancy of the term. But there are many anecdotes and mysticism when people talk about it.
Everyone has at some point discussed the separation of “Emotion” from “Reasoning.” Since the time of Plato, emotions have been seen as something that gets in the way of logical thinking. Worse: most people believe that, at least in the most important decisions, we’re capable of setting emotions aside. The idea is to think according to classical economics, based on facts, evidence, and cost-benefit.
But in the vast majority of cases, that’s not how we behave. When we go to the supermarket, we rarely stand there doing arithmetic, weighing each product’s ingredients or nutritional value. Usually we look at a product and decide whether to buy it based on how we feel.
Among dozens of brands for the same type of product, we choose based on past experiences, on some memorable event, on memories, and all in fractions of a second. We prefer to buy an “80% light” product over a “20% fat” one, even though both phrases say the same thing.
Antonio Damasio is a well-known neurologist who studies the brain and our behavior. He followed patients who literally lost the ability to have emotions because of brain damage, whether from a tumor or a genetic problem. We might imagine, as the philosopher Plato did, that a person without emotions would make the best decisions all the time, since they wouldn’t be influenced by them.
But without emotions, these people can’t learn. Any trivial decision becomes a cost-benefit analysis. Everyday choices like what clothes to wear, what TV channel to watch, tea or coffee, all the mundane things we decide almost instantly, can take hours before this type of patient reaches a conclusion.
A fact we already know: all emotions, sadness, compassion, joy, depression, pleasure, are chemical reactions in the brain. And we already know how to influence or control many of them.
Drug users know the sensation of pleasure. People who take antidepressants do too. They’re all chemicals that act on the brain and modify our emotions. Schizophrenia and Parkinson’s, on the other hand, are damage to this chemical system.
Another fact is that our brain evolved to learn. We learn through trial and error. We learn by observing and inferring patterns. Emotions strongly influence our decisions, and that’s good.
When we learn some pattern, dopamine is released in the brain and creates a sensation of pleasure. We like to discover the pattern of things and to try to predict future events.
Take an experiment with monkeys: we ring a bell and then give a banana. The monkey learns the pattern “after the bell comes the banana.” You can measure dopamine being released the moment the bell rings, because the monkey starts to anticipate that event.
If we turn on a light, ring the bell, and then give the banana, the monkey learns that the “light” event precedes the bell and then the banana. The pattern can be repeated with several stages, and the monkey learns it. But if we follow the pattern and the banana doesn’t come at the end, the monkey gets sad, because the prediction failed.
We also work this way.
For many simple events, with few variables, this works well. Perhaps that’s why many like routine, where the results are well defined.
Our brain, however, has a flaw: in its eagerness to find patterns, it tries to fit them where they don’t exist. That’s how superstitions are born. Before we understood meteorology, primitive tribes thought “it’s raining” was tied to a dance they had just done, and imagined that repeating the dance would bring the rain back.
I translated on my other blog a Scientific American article showing how we are “mathematically ignorant.” We try to find a pattern for everything. A passage that illustrates our superstitions and explanations about coincidence is this:
It’s always possible to combine random data and find some regularity. A very well-known example is the comparison of coincidences in the lives of Abraham Lincoln and John Kennedy, two presidents with 7 letters in their last names, and elected 100 years apart, 1860 and 1960. Both were assassinated on a Friday in the presence of their wives, Lincoln at the Ford Theater and Kennedy in an automobile made by Ford. Both assassins have 3 names: John Wilkes Booth and Lee Harvey Oswald, with 15 letters in each full name. Oswald shot Kennedy from a warehouse and ran to a theater, and Booth shot Lincoln in a theater and ran to a kind of warehouse. Both successor vice presidents were Southern Democrats and former senators named Johnson (Andrew and Lyndon), with 13 letters in their names and born 100 years apart, 1808 and 1908.
But if we compare other relevant attributes, we fail to find coincidences. Lincoln and Kennedy were born and died on different dates (day and month) and in different states, and none of the dates are 100 years apart. Their ages were different, as were their wives’ names. Of course, if any of these had matched, they would be on the list of “mysterious” coincidences. For any person with a life reasonably full of events, it’s possible to find coincidences between them. Two people meeting at a party often find shocking coincidences between them, but what they are – birthdays, hometowns, etc. – aren’t predicted in advance.
The real world is full of randomness, and it isn’t hard to find patterns in it. Actually it’s very easy. Complex situations have many random aspects, more than we imagine. And our brain hasn’t evolved enough to feel comfortable in a totally random world.
An example is successful people. Imagine a mega-investor like Warren Buffett. Books upon books get printed, with analyses, biographies, and theories, trying to explain the process that takes an ordinary person to earning billions on the stock exchange. Just as speculation: what if Warren Buffett is nothing more, nothing less, than a statistical accident?
Nassim Taleb explains this in a Malcolm Gladwell article:
Suppose that there were ten thousand investment managers out there — which is not an outlandish number — and that every year, entirely by chance, half of them made money and half of them lost money. And suppose that every year the losers were tossed out, and the game replayed with those who remained. At the end of five years, there would be three hundred and thirteen people who had made money in every one of those years, and after ten years there would be nine people who had made money every single year in a row — all out of pure luck. And who’s to say Buffett isn’t one of those nine?
Our brain takes pleasure in looking for patterns in everything, especially in success stories. We want to find the recipe, the magic formula. Sometimes we get that feeling of “what does he have that I don’t?”
Sometimes two people are technically equally capable, but one gets rich and the other doesn’t. The difference can simply be randomness. “But that isn’t fair!” you complain. The world wasn’t made to be fair. Justice is a human concept, and reality has no sense of morality: it simply “is.”
Science, fortunately, has a procedure to avoid this trap of the brain: the scientific method. Everything can start with one of these misfirings, thinking it found a pattern and generating a theory. Now that theory has to be put to the test.
For it to become a good theory, we need not only to try to prove it but, mainly, to try to disprove it. And even if we don’t find a way to disprove the hypothesis, that doesn’t make it a “Law.” Science is very careful with the claims it makes.
Even if a theory works well a thousand times, a single failure is enough for it to be rejected. It’s thanks to this way of thinking that we have solid and reliable foundations in science, free of superstition and mysticism.
Processes, Methodologies, and Superstitions
I gave that whole explanation to get to the main topic of this blog: project and people management. Anyone following my posts noticed that at no point do I preach a methodology, a process, a cookbook recipe. Things like “how to make correct estimates” or “how to predict the success of a project.”
If you’re well informed, you know there’s a whole market of individuals and companies that try exactly this: to sell you processes and methodologies. Whether traditional Software Engineering, PMI, or the so-called “Agile methodologies.”
First I need to leave a warning: all these methodologies were thought up with the best of intentions. The idea was to share the factors that led a certain project to success.
My explanation is more or less this: the leaders of these projects, or rather, their brains, tirelessly start looking for patterns. Maybe it’s the post-it on the wall. Maybe the kind of document used. Maybe the way people sit at the table.
All of this forms a set of “pseudo-truths” that the brain understands as the “lights” and “bells” that lead to the “banana.” These leaders apply the recipe to other projects and, as Nassim Taleb explained, succeed consecutively.
Eureka! It seems we found the formula for turning iron into gold! Quickly these pseudo-truths get formatted as methodologies, canned, packaged, and sold.
But think for a moment: what if all these methodologies are exactly like the rain dance? As I said, it’s very easy to find patterns in randomness.
When we start discussing minutiae, what level of detail to make an estimate at, what metrics to use, what mechanisms for team communication, I can’t help thinking of primitive tribes discussing “What feathers should we wear? What colors on our face? Should we take long or short steps in the dance?”
But the main question never comes up: is the rain dance the thing that actually makes it rain? Or, in our case, is the methodology the thing that actually takes the project to success?
And the scientific method? The problem is that a “project” is a very complex situation. Even the smallest projects are complex, in the sense that they have more variables than it’s possible to measure.
One way to test a theory is to run a double-blind experiment, like drug labs do: one group receives the real medication and another receives a placebo, without knowing. If both have approximately the same result, the drug doesn’t work.
But a methodology is more complicated than a drug. Even if we create two isolated and identical work environments, put two groups of “approximately” similar people in each, start at the same time and with the same requirements, one side with methodology “A” and the other with “B,” we still have no way to compare the results.
That’s because methodologies involve the micro-decisions and capabilities of each person, and “approximately similar” is very different from “equal.” It’s impossible to duplicate the same group of people in each environment.
We would first have to successfully clone the people. Then, with exactly identical groups, we could run a double-blind experiment. But that’s impossible.
The conclusion is that proving a methodology of this type as “correct” is impossible, just as it’s hard to disprove it. So it’s useless to try to claim they work or not. Of course they influence, and separately, each technique can be tested more carefully. But I don’t think it’s possible to scientifically claim that they work.
“But I tested methodology X on my project and it worked!”
Excellent, good for you. But for every project that succeeded with a certain methodology, you can find a case where it went wrong.
And the individuals and consultancies that sell these methodologies are clever: if the project worked, it was thanks to the methodology; if it went wrong, it’s because the people didn’t follow the methodology as they should have. The methodology is never at fault. It’s excellent rhetoric for building a sales argument.
And since people aren’t used to evaluating things rationally, and as I explained, most of the time they don’t reason at all, we’re left with lots of consultants making a lot of money without having to commit to results.
That matters because many people believe that, with the help of the fashionable methodology, simply applying it to a team of nothing but inexperienced people will make a good result appear, as if what mattered were the process and not the people. The opposite happens.
Most of the time these methodologies don’t describe the exact qualifications each member needs to have, because it’s impossible to list them all. At most they offer vague descriptions of “roles,” which generate more discussion than answers. A project with a chance of succeeding starts with at least some very experienced people, capable of guiding the rest of the team.
Anyway, my recommendation: study the so-called “methodologies,” because, as I said, some techniques there have value. But understand that none of them represents the truth.
And there’s no point in adding two half-methodologies together thinking it makes them “more complete.” Projects are executed by people, human behavior is hard to predict, and the real world is full of unpredictable variables, forming a complex system with a lot of randomness involved.
Start by accepting that the world is random and beyond your control. In complex situations it’s better to err sooner than later, because errors bring information that helps refine the next decisions.
Accept that predicting the future in a complex system is impossible, and adapt: some things will go as planned and others will need to change. Maybe some unforeseen feature will need to be built, and the deadline will have to stretch. Maybe some planned feature wasn’t so necessary after all and can be dropped. That’s how you deal with a complex and unpredictable environment: adapting.
Biology explains it: all living beings on the planet are the result of a constant sequence of trial and error. Nature isn’t “perfect,” in the sense that there is no creator, no intelligent design, no grand plan, no destiny. Every living being came from a very bad biological draft that, little by little, via natural selection, discarded what didn’t work and favored what did.
We humans carry biological leftovers, like the appendix. We are a product in constant evolution, and for plenty of things the current stage is “good enough.” In terms of a project, that’s exactly the point where it can be launched: when it’s “good enough,” still with rough edges to fix, but working overall.
Trial and error. Adaptation. Evolution. That’s how you manage anything.
If you want a more detailed view on this topic, I recommend starting with the following books:
- How We Decide by Jonah Lehrer
- Descartes’ Error by Antonio Damasio
- Predictably Irrational by Dan Ariely
- Fooled by Randomness by Nassim Taleb
- The Lucifer Effect by Philip Zimbardo