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 really believe that, at least in the most important decisions, we’re capable of setting emotions aside and thinking according to classical economic thinking: based on facts, evidence, and cost-benefit.
But the truth is that in the vast majority of cases, that’s not how we behave. In a daily situation, when we go to the supermarket, we rarely stand there doing arithmetic, considering each product’s ingredients, nutritional value. Usually we look at a product and decide whether to buy it or not based on how we feel. Among dozens of different brands for the same type of product, we choose based on past experiences, on some memorable event, on memories, and so on, all in fractions of a second. We prefer to buy a “80% light” product rather than 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 studied patients who literally lost the ability to have emotions because of brain damage, whether from a tumor or genetic problem. We might think, as the great philosopher Plato did, that a person without emotions would be able to make the best decisions all the time, since they wouldn’t be influenced by them.
But what happens is that without emotions, these people can’t learn. Any trivial decision becomes a cost-benefit analysis. Everyday decisions like what clothes to wear, what TV channel to watch, have tea or coffee — all the mundane things we decide almost instantly — this type of patient can take hours to reach a conclusion.
A fact we already know is that all emotions — sadness, compassion, joy, depression, pleasure, etc. — are chemical reactions in the brain, all of them. We even know how to influence or control many of these emotions. Drug users know the sensation of pleasure. People who take antidepressants too. 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 was made — or better said, evolved — to learn. We learn through trial and error. We learn by observing and inferring patterns. Emotions strongly influence our decisions. And that isn’t bad. When we learn some pattern, dopamine is released in the brain, creating a sensation of pleasure. We like to discover the pattern of things, to try to predict future events.
In an experiment with monkeys, where we ring a bell and then give a banana, the monkey learns the pattern “after the bell comes the banana.” It learns this, and we can measure dopamine being released when the bell is rung, because the monkey learns 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. This can be repeated with several stages, and the monkey learns the pattern. But if we follow the pattern and the banana doesn’t come at the end, the monkey effectively gets sad, because the prediction didn’t work.
We also work this way.
For many simple events, with few variables, this will work 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, the brain will try to fit patterns where they don’t exist. That’s how superstitions are born. Before we understood meteorology, primitive tribes thought that the fact “it’s raining” was related to a dance they had just done. So they imagined that repeating the dance would make it rain again.
I translated on my other blog a Scientific American article demonstrating 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 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. It isn’t hard to find patterns in it. Actually it’s very easy. In the real world, complex situations have many random aspects. The real world is much more random than we imagine. And our brain hasn’t evolved enough to feel really comfortable in a totally random world.
An example is successful people. Imagine a mega-investor like Warren Buffett. Books upon books are printed, with analyses, biographies, theories, trying to explain the process that takes an ordinary person to earning billions on the stock exchange. What if, by speculation, Warren Buffett is nothing more, nothing less, than a statistical accident?
Nassim Taleb explains this in a Malcolm Gladwell article:
Suppose there are 10,000 investment managers out there, which is not such an unrealistic number, and that each year half of them, entirely by chance, made money, and the other half lost money, also entirely by chance. And suppose that every year those who lost money leave the market, and the game is repeated every year with those who remained. At the end of 5 years, there would still be 330 people who made money consecutively every year. And after 10 years there would still be 9 people who made money every year, consecutively, entirely by chance, by pure luck of randomness. And who’s to say Buffett isn’t one of those 9?
Our brain, however, takes pleasure in trying to find patterns in everything. Especially in success cases. We want to find the recipe, the magic formula. Sometimes we get that feeling of “what do they have that I don’t?” And sometimes two people are technically equally capable, but one is richer and the other isn’t. The difference can simply be randomness. “But that isn’t fair!” you might complain, but the world wasn’t made to be fair. Justice is a human concept. Reality has no sense of human morality — it simply “is.”
Science, fortunately, has the right procedure to avoid this trap of our brain: the scientific method. Everything can start precisely with one of these brain misfirings, thinking it found a pattern, generating a theory. Now that theory has to be tested. For it to become a good theory we need not just to try to prove it but, mainly, to try to disprove it. Even if we don’t find a way to disprove the hypothesis, that doesn’t mean it can be considered a “Law.” Science is very careful with the claims it makes. Even if a certain theory has worked well a thousand times, a single case of failure is enough for that theory to be rejected. It’s thanks to this way of thinking that we have very solid and reliable foundations in science. Free of superstitions and mysticism.
Processes, Methodologies, and Superstitions
I gave that whole explanation to get to the main topic in the case of this blog: project and people management. If you’re following my posts so far, you noticed that at no point do I try to preach any methodology, any process, any procedure, any cookbook recipe. Things like “how to make correct estimates,” “how to predict the success of a project,” and things of that kind.
If you’re well informed, you should also know that there’s a whole market of individuals and companies that try precisely this: to sell you processes and methodologies. Whether traditional Software Engineering, PMI, or even the so-called “Agile methodologies.”
Before I do this I need to leave a warning: all these methodologies were initially thought of with the best of intentions. The idea was to share the factors that led a certain project to success. But my explanation is more or less like this: the leaders of these projects, or rather, their brains, tirelessly begin trying to find patterns. Maybe it’s the post-it on the wall. Maybe it’s the kind of document used. Maybe it’s the way people sit at the table. All of this forms a set of “pseudo-truths” that our brain understands are the “lights” and “bells” that lead to the “banana.” These leaders apply it to other projects, and just as Nassim Taleb explained, they consecutively succeed.
Eureka! It seems we found the formula for turning iron into gold! Quickly these pseudo-truths are formatted in the form of methodologies, canned, packaged, and sold.
But think for a moment: what if all these methodologies are exactly like the rain dance? As I said before, it’s very easy to find patterns in randomness. When we start discussing minutiae, like what level of detail should we make an estimate at? What metrics should we use? What team communication mechanisms? I can’t help thinking of primitive tribes discussing things like “What feathers should we wear? What colors should we use on our face? Should we take long or short steps in the dance?”
But the main question isn’t raised: 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 there are more variables than it’s possible to measure. One of the ways to test a theory is to do a double-blind experiment, like drug labs do: one group of people receives the actual medication, and another group receives a placebo without knowing. If both groups have approximately the same result, it means the drug doesn’t work.
But a methodology is more complicated than a drug. Even if we manage to create two isolated and identical physical work environments, put two groups of “approximately” similar people in each, start at exactly the same time, with the same requirements, on one side with methodology “A” and on the other with methodology “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 of the environments. We would first have to successfully clone the people. Then, with exactly identical groups, we could do a double-blind experiment. But that’s impossible.
The conclusion is that it’s impossible to prove a methodology of this type as “correct,” just as it’s hard to disprove it. So it’s useless to try to claim that they work or not. Of course they influence, and separately, each of the techniques 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 was successful with a certain methodology, we can also find a case where it went wrong. But the individuals and consultancies that sell these methodologies are clever: if a project worked, it was thanks to the methodology. Now, if a project went wrong, it’s because the people didn’t follow the methodology as they should have. So the methodology is never at fault! It’s excellent rhetoric to form a sales argument. And if people aren’t used to evaluating things rationally — and as I explained above, they usually don’t reason at all — we’ll have lots of consultants making a lot of money without having to commit to results.
That’s important because many believe that, with the help of the fashionable methodology, simply applying it to a team that only has inexperienced people will make a good result appear, because what matters isn’t the people but the process. And it’s exactly the opposite: most of the time these methodologies don’t describe what the exact qualifications each member needs to have. Because it’s impossible to list them all. At most there are vague descriptions of “roles” that generate more discussions than answers to the question. A project with chances of being successful starts with at least some very experienced people who will know how to conduct the rest of the team.
Finally, my recommendation is: study the so-called “methodologies” — as I said before, they really do have some techniques that have value. But understand that none of them represents the truth. And there’s no point in trying to add two half-methodologies together because that won’t make them “more complete.” Understand that projects are executed by people, human behavior is hard to predict, and the real-world environment 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 it’s impossible to predict what will happen in the future in a complex system — instead, adapt: accept that some things will go as planned but that some things will necessarily need to change. Perhaps some unforeseen functionality will need to be done — in that case maybe the deadline will need to be stretched. Perhaps some planned functionality wasn’t really so necessary deep down and can be discarded. That’s how we deal with a complex and unpredictable environment: adapting.
Biology explains: 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 have biological leftovers (like the appendix, for example). We are a product in constant evolution. For many, the current stage is “good enough.” In terms of projects, that’s exactly the point where it can be launched, when it’s “good enough,” that is, still has rough edges to fix but overall works.
Trial and error. Adaptation. Evolution. That’s how you manage anything.
If you want a more detailed view on this topic, I recommend starting by reading 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