“While A’s tend to hire A’s, B’s tend to hire not just B’s but C’s and D’s too”From the section “The herd effect” in the book How Google Works by former CEO of Google Eric Schmidt and Jonathan Rosenberg
It is unclear the precise meaning of A, B, C and D, but from the context it can be gathered that it is a categorization of employees where the quality is descending with every letter of the alphabet. Presumably it alludes to the American grading system. This echoes Steve Jobs’ talk about always hiring an A-team and indeed I would think this is more a generic Silicon Valley insight than a Google thing. It seems to indicate that there is a superior class of employees that you need to attract and that the rest is bad that will make your company even worse.
Before we start to evaluate the merits of the statement, we have to check the assumption that employees can be put into squarely delineated quality brackets. First question is how you measure quality of employees. The discrete labeling seems to indicate two important assumptions:
- that this pertains to a person in general, not some particular area of expertise of that person. You are either an A or you are not
- Another assumption is that the predicate is immutable. If you are an A you always were and always will be an A
These assumptions indicate that we are working with the philosophical position of essentialism, the view that an entity has an essence, from which its behavior, appearance or traits can be derived. In psychology this is used to describe how humans have a tendency to conceptualize biological entities and humans according to an immutable essence. Based on this essence it is possible to deduce behavior for other members of the same biological class.
While essentialism may be a common human trait it does not mean it is the best way to conceptualize other humans. The root of racism is also derived from essentialism, and we don’t just blindly accept that as a viable or helpful way of assessing the merits of other people, so why should we accept this piece of Silicon Valley wisdom at face value?
We should not. Because it is wrong. Let us look at the two assumptions again:
The first assumption stipulates a general level of quality for a person but there is no reason to assume that a person can be A level at all traits. If not for anything else, then for the very fact that some traits are mutually exclusive. If we think about it in terms of physical qualities, it makes no sense to talk about A athletes across the board. An A weightlifter will be an F marathon runner and Vice versa. An A level football player may, however, be an A level baseball and basketball player and this is what we often think about, when we call someone a great athlete. There are examples of such great athletes that have competed at the highest level in the NFL, MLB and NBA. But looks are deceiving here. These sports are only superficially very different. They are built around explosive outlets of energy, eye hand coordination with a ball and little stamina. It is less common, if it ever happened, that an elite athlete moved to the NHL even though it is similarly explosive, because you suddenly need another skill, that is, skating. This great athleticism will not either apply to swimming or to bicycling.
You can also counter that in track and field there is nothing but general athletic ability. Look at Carl Lewis who won Olympic gold medals in many different disciplines. Again, looks can be deceiving. He competed and dominated the following disciplines: 100 m, 200 m, 4 x 100 m relay, long jump. These are ultra-explosive and none of them takes him out running further than 200 meters. How would he fare in 400 m, 800 m, pole vaulting, discus or 2000 m? We don’t know since he never competed. My guess is that he wouldn’t be an A athlete in these and probably an F in pole vaulting.
In the tech industry there are similar complications. You cannot be both adventurous and want to try new things and risk adverse making sure that everything works. If you are working on quantum computing, you probably have a pretty high tolerance for failure and appetite for risk. If you are developing new models of airplanes you probably (and hopefully) don’t. The A person in the quantum computing setting may very well turn out to be an F- person in the aviation industry.
Can-do attitude and perfectionism also do not align. The employee who is ready to approach any job with a pragmatic mindset and get things done will succeed in a climate of constant change, such as a startup, where you don’t know what you will do tomorrow or even later today. That person would probably not fare well in a heavily regulated industry like banking. The perfectionist though may thrive in a setting where work needs to be done with acute attention to detail. Switch these two persons around and they will no longer be A’s
The second assumption, that you will remain the same, is similarly ill founded. First of all, human cognitive abilities develop and change over time. In mathematics and physics there is a tendency for people to peak in their twenties. Einstein, Tesla, Newton and Leibniz did their most impressive work before they were 30. Conversely, with age comes greater ability for synthetic thinking: few philosophers or historians peak before they are 40. Similarly, politicians have a tendency be more successful when they are older. It takes time to build up the skill to interact with people to achieve a result. It also takes time to build alliances and network. This is not an immutable trait.
Another more mundane concern in Silicon Valley is burn out. Even the best, or maybe in particular the best, programmers sometimes burn out, and are not able to write any good code anymore. Others just do not stay on top of development. They may have been the smartest assembly coders in the room but just never jumped on this newfangled thing called C++. They would hardly be considered A’s today. On the other hand, some people continue learning and may not have started out on the right path but changed to become better. Steve Jobs himself started out in liberal arts and learned tech skills only later. He would probably never have been hired out of college by Google.
Consequently, what we can deduce is that quality is always domain specific. There are no A people per se. They are always high quality with regard to a particular area of specialization.
We can also see that quality is not immutable. Even the best people turn bad for one reason or another and even bad people can become good. People change both according to a biological and cognitive development and due to personal circumstances.
It is consequently dangerous to assume that A’s will magically beget A’s in a continuous stream of awesomeness. A’s burnout and A’s sometime don’t adapt. They degrade. Following the advice could therefore lead to a false sense of confidence. Classifying people as A’s can also be dangerous if you put them too far out of their area of expertise. Many companies have seen how the brilliant engineer turns out to be a subpar manager. Engineering’s attention to detail and focus on there always being a right and a wrong is perhaps not always conducive to employee empathy and development. This line of thinking also creates missed opportunities. If a person has historically been given the C stamp and that is all we look at then how will we ever know that this person developed into an A?
A further point concerns that of generalizability. It is fine for Google to hire only A’s but most companies are not in a privileged situation that Google is and cannot attract any of the best. We have to remember that Google and the top Silicon Valley companies are in a unique position where they earn so much money that they can offer whatever compensation. They have also made a name for themselves with prospective employees. That means that their problem is one of filtering. Everybody wants to work for Google, their problem is to find the best. 99,99% of other companies in the world do not have that problem when it comes to recruiting. Rather ordinary companies’ problem is one of attraction. For example, one of the thousands of auto-parts suppliers will not be known to most potential applicants. Therefore, they have to attract not filter employees. If they can even get somebody qualified, they would be happy. Talking to them about hiring only A’s is close to an insult. They would never be able to because they don’t have infinite pockets, Michelin chefs in their cafeterias and 20% time for the employee to work on what he or she thinks is fun. The vast majority of the world’s companies fall into this category of unknown companies, with limited budgets and a regular workplace with a kitchenette and a water cooler.
The last point is more subjective. The sentence seems to echo privilege and entitlement. Who are these A’s? They are the best people from the elite universities in the US: Stanford, MIT, Columbia. They were able to become perceived as A’s because they got into those universities. Some do get there due to hard work and scholarships. Most don’t. They get there through their parents’ wealth. Google doesn’t go to a Southern community college or African universities to look for A people. They go looking where the managers went themselves.
As can be seen from the above, not only is the sentence wrong and unhelpful, it may be dangerous to follow even for Google. For the vast majority of companies, it will be completely irrelevant if not downright insulting and it tacitly expounds an air of privilege and entitlement that they overtly claim to be fighting.
Consequently, I would like to turn the sentence on its head. Since most employees are not A’s according to the measurement scale of Silicon Valley, we need to think of how we make the most of the B’s and C’s and D’s. This is the real problem for the world (not for Google and Silicon Valley). How do we get the best performance out of the people who prioritize being with their kids or family, the people who prefer hanging out with friends or playing tennis to working 80 hours on the latest feature that may be gone next month? These people would never be perceived as A’s that will invent the next big thing. But most companies don’t need that. They need happy reliable people that do a job within a limited scope well enough. How do we find the person with the right skills for a particular job? They need people with new skills but can’t hire them, so how do we train and create the environment for ordinary people to perform new functions? And last of all how do we turn the story to redeem the dignity of the people in the tech industry who go to work to do a solid job 9 to 5 without any fanfare?
These are the real problems that we need to be focusing on in order to take advantage of technology in the future and create a better world with more productive and happier employees.