This is an image from Stockholm, Sweden on September 3, 1967. That was the day when Sweden changed from driving on the left side of the road to the right side.
Naturally, there was chaos.
A few posts back, I wrote about change, and why it sucks. No matter how necessary or beneficial a change may be, it is natural human tendency to resist it. We hate the transition associated with change. Going from a current status quo to a new status quo is always accompanied by Chaos and then persistence to implement it. Chaos scares us – partly because it is uncomfortable; partly because we think of Chaos as the actual change and run back to the safety of our old status quo.
Change is hard. It’s difficult. It sucks!
Well, it’s not really that hard. It’s hard because of how we deal with the change.
We hate change. We detest it. We resist it. We procrastinate. We put it off. We do whatever we can to avoid it. We make a herculean effort to avoid the potentially small effort required to make the change.
That is how we are hardwired. If our current state has some sort of equilibrium, a sense of sanity and acceptance of where we are, we would resist change. Even a change that is for better.
It is not because we do not like to make things better. We all like to be richer, happier and more satisfied.
It’s the process of change that we hate.
The more I learn about child development, the more fascinated I get at the similarity of the fundamentals between adult professional growth and child development.
Consider the following advice from Baby Center on helping your child develop fast:
It’s important not to frustrate your child with toys and activities that are way beyond his abilities, but a little struggling goes a long way toward learning new skills.
When an activity doesn’t come easily to your baby, he has to figure out a new way to accomplish the task. That type of problem solving is the stuff better brains are made of. If he’s attempting to open a box, for example, resist the urge to do it for him. Let him try first. If he continues to struggle, show him how it’s done, but then give him back a closed box so he can try again on his own.
Setting a goal or target, which is not unrealistic but certainly a stretch, and letting the child figure out how to get there, is the primary premise of learning. I wrote an earlier blog post about the Creative Stretch as well.
This child development model is similar to how the knowledge professionals should be groomed, matured and trained. Give a challenging goal and let them figure it out themselves.
While watching a cricket match over the weekend, the commentators were lamenting why a particular player was not selected for the encounter. They argued that he had been performing well, is an important member of the team and had no injuries. They conjectured and speculated. There did not seem to be any apparent reason not to pick him for the match. Suddenly, the captain and coach looked dumb.
Every day, we come across decisions around us that apparently do not make sense. A logical analysis of the known facts and visible indicators reveal them as imprudent and silly. There is a giant corporate’s surprise decision to acquire a startup; another is firing an apparently well-performing CEO; another decides to ban work from home; there is a surprise decision to bypass someone for a promotion (he had already planned the party); a product is retired that seemed to just start making money; or a player not picked up to play when that was all that made sense.
These executives making all these big decisions – they are all morons! Who put them in there in the first place?
On August 23rd, 1973 two machine-gun carrying criminals entered a bank in Stockholm, Sweden. Blasting their guns, one prison escapee named Jan-Erik Olsson announced to the terrified bank employees “The party has just begun!” The two bank robbers held four hostages, three women and one man, for the next 131 hours. The hostages were strapped with dynamite and held in a bank vault until finally rescued on August 28th.
After their rescue, the hostages exhibited a shocking attitude considering they were threatened, abused, and feared for their lives for over five days. In their media interviews, it was clear that they supported their captors and actually feared law enforcement personnel who came to their rescue. The hostages had begun to feel the captors were actually protecting them from the police. One woman later became engaged to one of the criminals and another developed a legal defense fund to aid in their criminal defense fees. Clearly, the hostages had “bonded” emotionally with their captors.
— Dr Joseph Carver, “Love and Stockholm Syndrome: The Mystery of Loving an Abuser”
This emotional attachment and protective behavior of an abused or captive person towards his captor, abuser or tormentor is known as “Stockholm Syndrome” and is coined after the 1973 Stockholm robbery incident. Though seemingly illogical and unnatural, this syndrome is common among hostages and those who are victims of abuse in a relationship. They exhibit behaviors that are protective and empathetic to those causing harm to them and ensuring to maintain the situation where they keep getting abused.
If you have been following me even casually, you would know of my obsession with understanding and applying models. Accurate modeling helps in efficient understanding of the situation, stops us from reinventing the wheel, reuse solutions that have worked before and ensures that we do not leave out anything in our analysis.
Mathematics has not been my forte but that will not prevent me from foraying into it.
Let’s start with a Normal (Bell) distribution – a model that explains many common phenomenon. For example, distribution of marks in a typical university course and distribution of heights, weights or IQs of people in a community. It helps in finding the mean (most commonly occurring value), variance and standard deviation of other data around it. We can extract useful results and make accurate predictions.
The normal distribution focuses on the average – and how everything relates to the average or the most common. You can identify common clusters and predominant patterns. You can see the outliers at the fringes of the bell, but they are really just at the peripheries. They are not the focus of the model. There is a reason why it is called a ‘normal’ distribution.
A more interesting model is the Power Law. It is typically used to model a relationship where the frequency of occurrence of a quantity varies as a power of some attribute of that quantity. It’s a skewed relationship where for a small set of values, the frequency of occurrence of the quantity is disproportionately different from that of others. A good example is the distribution of wealth in a society. There is a certain number of people – probably less than 2% of the population – who are disproportionately wealthier than the rest. The rest are relatively of similar wealth relative to that elite set. The distribution looks like this:
I try not to get very techie in my posts, keeping my Computer Science background in the hood. The intent is to talk about management issues that transcend a specific domain.
But sometimes the temptation to get out of the hood gets … well – too tempting. Specially, when you can use a good analogy to explain something important. For example, how can the compiler tool help us model where we go wrong in managing people.
A compiler is a key ingredient of the life of a software developer. It translates the code that software programmers write into a language that the computer understands. When you see a programmer furiously typing away on his screen telling you he is writing code (to make the world a better place), in reality what he is writing is really for himself, his team and manager only. He is writing down what he thinks the software should do in a prescribed format and structure – it’s just standard English with a very strict grammar. However, the computer that needs to make that software available to the world, lives in its own complex world with its own language and rules. There is a need to translate what the programmer writes into a language that the computer understands. That is what a compiler does. When asked by the programmer, it takes all the fancy writings by the programmer and creates the instructions that the computer can work with. It’s like hiring a language interpreter when you visit the Amazon tribes. The fancy English you speak is unfathomable to the half-clad and crocodile hunting tribesman. The language interpreter acts like a compiler, taking what you say and other data like your facial expressions and body language, and translates into what the tribesman can understand. Hopefully, you and the tribesman can eat the crocodile together rather than they together having you for dinner.
Well, the idea is not to teach you about compilers but why it is relevant to our topic – why smart people fail miserably when they move from a technical role to one involving dealing with people.