How to play in the NBA or why no one is truly happy working in technology II


How to play in the NBA or why no one is truly happy working in technology II

After the unexpected repercussion of the notes of the last weeks, I have seen a huge increase in some numbers of my LinkedIn (specifically, the number of people who DO NOT agree to contact me). However, I insist on telling you the parallels that I discovered between the factors that explain the success in the world of technology and in the NBA.

In the same way that height is an enabler in basketball (it decisively increases the probability of playing, but has no correlation with subsequent success), “knowing how to program” is the technological enabler. With an excess global demand for programmers of at least 500,000 professionals, any programmer of a reasonable technical level resembles a 2.20 meter player.

Coaches look at each other and say “Let’s try it. How bad can it be? And the programmer, with the assurance of someone who only has success as a destination, winks at them smugly and proceeds to delete a table in production.

What makes a superstar?

Before analyzing the sea of statistics of the NBA, I tried to foresee from my indisputable ignorance, what factors would end up explaining the success of its players. My theory was aimed, mainly, at the ability to shoot.

If someone was capable of doing it a very high percentage of the time, he had to be a very valuable player at least in attack. I also imagined that defensive aspects, such as blocking or stealing, must have an influence. I tell you, then, the results. NO player in the Top 50 in NBA history has achieved a 60% shooting from the field.

The first in the ranking to do it is someone named Clint Capela who is in 345th place. The top five Michael Jordan, Lebron James or Kobe Bryant, for example, did not score half the times they shot at the basket. But there are HUNDREDS of NBA players who had or are more than 70% effective on their shots. Only none of them are in the top 1000 of the all-time best rankings.

There are a dozen finds like this, but let me jump straight to the conclusion. What makes a basketball superstar are two things … the first is THE QUADRUPLE CONSISTENCY. That is: be consistent in your abilities, in different circumstances, in your professional choices and in time. Consistent in their abilities means that while they may not necessarily be the best at anything, they are very good at everything. Only two players (Wilt Chamberlain and Shaquille O’Neal) do not follow this rule.

The rest, tends to be above average in all dimensions (steals, blocks, effectiveness of free throws, effectiveness of field shots, effectiveness of three-point shots, assists, rebounds, etc.) when compared to players in their position. . Consistent in different circumstances means that their level does not drop more than expected in difficult matches.

Their “numbers” are similar in season games and in play offs (many even improve in play offs, although rivals are statistically superior to those in the regular season) Consistent in their career choices means they tend to stay on the same team for long periods, or forever. Consistent over time implies that “their numbers” have low variance throughout their career. And what does “voluntary leadership” mean?

That they choose to actively participate in the game, that they take the difficult shots, that they score the best rival player, that they understand that success depends on them.

In a phrase that can also be a recipe: For someone to be an NBA star, they must play for a long time being reliable in their contribution, which must be above average in most of the dimensions of the game … and assuming the responsibility to lead by example!

Most programmers feel that getting a job is easy, but moving up in a company is difficult. And they feel it because it is, in fact, it is reality. The first is the most obvious. With a deficit of more than 500 thousand professionals worldwide, getting a job in technology is relatively easy (at least for those with a medium level of technical knowledge).

A friend of mine who, in addition to being a great guy is an extraordinary software developer, says that: “LinkedIn today is a backwards Tinder: Pretty girls write to us nerds and we ignore them.” Every year the “excess demand” is amplified, more positions are vacant, and more companies delay their growth due to lack of equipment.

But here is the genesis of the difficulty to grow in a company. The demand for CTOs, CTOs or leaders grows less than the demand for programmers (at a rate between 40% and 84% lower, depending on the position and the market).

As a simple and perfectly representative example, @ n5 had a CTO and 10 employees in 2018. Today it has almost 200 employees, but the CTO is still one.

This generates two consequences:

  1. Getting a job is easier… but once you have it there are a lot more people competing for the top positions.
  2. And perhaps more important: having landed an easy job sends completely distorted signals to candidates.

I like to use this example, which is from real life. Four fellow girls in psychology majors have boyfriends who study systems, economics, and law (2). For one of those magical things of fate, they get along, and they better.

They start to see each other very frequently and after a while they are an inseparable group. When they are in the middle of their career, the kid who studies systems begin to receive constant job offers. They propose to work for hours, remote, pay for courses, anything to attract him.

None of the other seven ever receives a spontaneous job offer. In the year in which they all finish studying, the systems department has already gone through three companies, and has permanent offers. He is the only one who lives alone and has a car.

The rest send HUNDREDS of resumes, talk to contacts, sign up (and do not call them) in summer internships, take postgraduate courses and very gradually end up getting jobs that are demanding a lot and are paid little.

I was lucky to see the evolution of that group, and the individual dynamics of each one. Whatever the labor or economic differences might have been at age 20, they had dissipated or reversed at age 35.

My hypothesis, which I do not have enough data to prove, is that the other seven had been required in all their professional dimensions at the beginning of their career. Therefore, they had learned to improve continuously, to work as a team, to relate appropriately with their bosses, to prioritize tasks, to serve their clients well. In short, to work in an environment where there are 10 people for 9 vacancies and mistakes are expensive.

The systems man had not received any of those signals, because he worked in an environment where there were 9 people for 10 vacancies. Where mistakes cost nothing, because the boss pretended not to see them, so as not to be left with 8 people and 10 vacancies. But that quantitatively favorable scenario for the programmer disappears as one moves up the professional ladder.

In the middle management there are already as many positions as there are professionals, and at the top, the disproportion is the highest in history. Thousands aspire to be CTO of a Big Tech. The vast majority were not trained to do so.

I close with a series of practical tips that can help any young technology professional grow in their career. They all stem from the basketball analogy and the opinion of some of the best CTOs and CEOs I know.

  1. Consistency in your abilities: Not to be below average in anything. Technical knowledge, teamwork, adherence to methodologies, documentation, attention to detail, early detection of risks. Focus on improving the worst of the weaknesses rather than increasing the greatest of the strengths.
  2. Consistency in different circumstances: The best way to show that one “is there for more” is to do extraordinarily well the tasks that theoretically remain small (see note of the drummer cat! N5 |ómo ascender en la empresa una fotocopia a la vez, o la leyenda del gato baterista (
  3. Consistency over time: Messi played 5 years (3 at the highest level) before winning his first Golden Ball. Trust is built on reputation, and reputation on patience, adding value over long periods and in changing circumstances.
  4. Consistency in decisions: A CV that shows 5 companies in 4 years is a red flag that no one misses. No efficient company offers training or gives greater responsibilities to someone who is going to last 8 months in your company.
  5. Be a volunteer protagonist: Understand that you don’t just have to do what they asked you, but what needs to be done. Offer to solve a problem, propose solutions, acknowledge mistakes, understand that your work is a reflection of your reputation.

I kept something for the end, because I did not find any statistics that can measure or prove it, but it is a rule to which I do not find exceptions. Basketball and tech superstars have one more thing in common.

They are not “consistent” or “voluntary protagonists” because they think they should. They are because they can’t help it. Because they are happy doing it. Because they simply love to play the game … that they chose to play.

Until next time!

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