Tag: groupthink

Axes of diversity

Companies and educational institutions, especially those that have a global footprint and a reputation to protect, make a big deal about diversity policies. It is almost impossible to sit through a recruitment or admissions talk by one such entity without a mention to their diversity policies, which they are proud of.

And they have good reasons to have a diverse workforce. It has been shown, for example, that diversity leads to better decision-making and overall better performance. Having a diverse workforce brings together people with different backgrounds, and since backgrounds influence opinion, a more diverse team is more likely to have more diversity of opinion which results in better decision making. And so forth.

The problem, however, is that it is not easy to simultaneously achieve diversity on all possible axes. Let’s say that we have defined a number of axes, and are looking to recruit an incoming MBA class. If we want diversity on each of these axes, selection of each candidate is going to rule out a large number of other candidates and we will need a really large pool to choose from. In other words, it is akin to the eight queens problem (where you have to place eight queens on a chessboard such that no two of them are on the same row, column or diagonal). For those of you not familiar with chess, think of it like a Sudoku puzzle.

Since the pool of candidates large enough to achieve diversity on all axes is simply not feasible, firms and schools choose to prioritise certain axes over others, and seek to achieve diversity in these chosen axes. And since they can arbitrarily choose axes that they can prioritise, the incentive is to pick out those axes where diversity is most visible.

And so when you go to a global organisation or school that preaches diversity, you will notice that they indeed have a very diverse workforce/student body in terms of gender, race, and nationality, which are fairly visible dimensions. Beyond this, the choice of dimensions to impose diversity on is a matter of discretion. So you have organisations which seek diversity in sexual orientation. Others seek diversity in age profile. Yet others in educational backgrounds. And so forth.

The result of prioritising more “visible” dimensions to ensure diversity is that organisations end up becoming horribly similar in the “sacrificed dimensions”. Check out this excerpt from Peter Thiel’s Zero to One, for example, on the founding members of paypal:

The early PayPal team worked well together because we were all the same kind of nerd. We all loved science fiction: Cryptonomicon was required reading, and we preferred the capitalist Star Wars to the communist Star Trek

Now, remember that this was a fairly diverse team when it came to ethnicity, nationality and sexuality. But in a less visible dimension, the team was not diverse at all. And Thiel mentions it in his book as if it’s a good thing that they all thought so similarly.

On a similar note, I once worked for an organisation that made great shakes of its diversity policy, and the organisation was pretty diverse in terms pretty much every visible axis of diversity. And the seminars (some compulsory) they organised helped me significantly broaden my outlook on issues such as race or sexual orientation. But when it came to work, the (fairly large) team was horribly similar. Quoting from an earlier blogpost (a bit ranty, I admit):

First, a large number of guys building models come from similar backgrounds, so they think similarly. Because so many people think similarly, the rest train themselves to think similarly (or else get nudged out, by whatever means). So you have massive organizations full of massively talented brilliant minds which all think similarly! Who is to ask the uncomfortable questions?

So essentially because you had a large organisation of people from basically similar educational backgrounds (masters and PhDs in similar subjects), their way of thinking became dominant, and others were forced to conform, leading to groupthink, which might have potentially led to mishaps (but didn’t, at least not in my time).

And what of the Ivy League schools that again pride themselves on (visible forms of) diversity? Here is an excerpt from William Deresiewicz’s excellent 2008 essay:

Elite schools pride themselves on their diversity, but that diversity is almost entirely a matter of ethnicity and race. With respect to class, these schools are largely—indeed increasingly—homogeneous. Visit any elite campus in our great nation and you can thrill to the heartwarming spectacle of the children of white businesspeople and professionals studying and playing alongside the children of black, Asian, and Latino businesspeople and professionals. At the same time, because these schools tend to cultivate liberal attitudes, they leave their students in the paradoxical position of wanting to advocate on behalf of the working class while being unable to hold a simple conversation with anyone in it.

So the next time you want to make your organisation diverse, think of which axes you want diversity on. If you are public-minded and want to brag about your diversity, the obvious way to go would be to be diverse on visible axes, but that leaves other issues. On the other hand you could put together a team of people that look the same but think different!

It’s entirely up to you!

 

The Quants

Since investment bank bashing seems to be in fashion nowadays, let me add my two naya paise to the fire. I exited a large investment bank in September 2011, after having worked for a little over two years there. I used to work as a quant, spending most of my time building pricing and execution models. I was a bit of an anomaly there, since I had an MBA degree. What was also unusual was that I had previously spent time as a salesperson in an investment bank . Most other people in the quant organization came from a heavily technical background, with the most popular degrees being PhDs in Physics and Maths, and had no experience or interest in the business side of things at the bank.

You might wonder what PhDs in Physics and Maths do at investment banks. I used to wonder the same before I joined. Yes, there are some tough mathematical puzzles to be solved in the course of devising pricing and execution algorithms (part of the work that us quants did), which probably kept them interested. However, the one activity for which these pure science PhDs were prized for, and which they spent most of their time doing, was C++ coding. Yeah, you read that right. These guys could write mean algorithms – I don’t know if even Computer Science graduates (and there were plenty of those) could write as clean (and quick) C++ code as these guys.

While most banks stress heavily on diversity, and makes considerable efforts (in the form of recruitment, affiliation groups, etc.)  to ensure a diverse workplace, it is not enough to prevent a large portion of quants coming from a similar kind of background. And when you put large numbers of Physics and Math PhDs together, it is inevitable that there is some degree of groupthink. You have the mavericks like me who like to model things differently, but if everyone else in your organization thinks one way, who do you go to in order to push your idea? You stop dropping your own ideas and start thinking like everyone else does. And you become yet another cog in the big quant wheel.

The biggest problem with hardcore Math people working on trading strategies is that they do not seek to solve a business problem through their work – they seek to solve a math problem, which they will strive to do as elegantly and correctly as it is possible. It doesn’t matter to the quants if the assumption of asset prices being lognormal is widely off the mark. In fact, they don’t care how the models behave. All they care about is about their formulae and results being correct – GIVEN the model of the market. I remember once spending a significant amount of time (maybe a couple of weeks) looking for bugs in my pricing logic because prices from two methods didn’t match up to the required precision of twelve decimal places (or was it fourteen? I’ve forgotten). And this after making the not-very-accurate assumption that asset prices are log normal. The proverb that says, “measure with a micrometer, mark with a chalk, cut with an axe”, is quite apt to describe the priorities of most quants.

Before I joined the firm, I used to wonder how bankers can be so stupid to make the kind of obvious silly errors (like assuming that housing prices cannot go down) that led to the global financial crisis of 2008. Two years at the firm, however, made me realize why these things happen. In fact, the bigger surprise, after the two years there, was about why such gross mistakes don’t occur more regularly. I think I’ve already talked about the culprits earlier in the post, but I should repeat myself.

First, a large number of guys building models come from similar backgrounds, so they think similarly. Because so many people think similarly, the rest train themselves to think similarly (or else get nudged out, by whatever means). So you have massive organizations full of massively talented brilliant minds which all think similarly! Who is to ask the uncomfortable questions? Next, who has time to ask the uncomfortable questions? Every one, from Partner downwards, has significant amount of “day to day work” to take care of every day. Bankers are driven hard (in that sense, and in that they are mostly brilliant, they do deserve the money they make), and everyone has a full plate (if you don’t it is an indication that you may not have a plate any more). There is little scope for strategic thinking. Again, remember that in an organization full of people who think similarly, people who have got promoted and made it to the top are likely to be those that think best along that particular axis. While it is the top management of the firm that is supposed to be responsible for the “big” strategic decisions, the kind of attention to details (which Math/Physics PhDs are rich in) that takes them to the top doesn’t leave them enough bandwidth for such thinking.

And so shit happens. Anyone who had the ability to think differently has either been “converted” to the conventional way of thinking, or is playing around with big bucks at some tiny hedge fund somewhere – because he found that it wasn’t possible to grow significantly in a place where most people think different to the way he thinks, and no one has the patience for his thinking.

This is the real failure in investment banking (markets) culture that has led to innumerable crises. The screwing over of clients and loss of “culture” in terms of ethics is a problem that has existed for a long time, and nothing new, contrary to what Greg Smith (formerly of Goldman Sachs) has written. The real failure of banking culture is this promotion of one-dimensional in-line-with-the-party thought, and the curbs against thinking and acting contrary to popular (in the firm) wisdom. It is this failure of culture that has led to the large negative shocks to the economy in the years gone by, and it is these shocks that have led common people to lose money rather than one off acts by banks where they don’t necessarily act in the interest of clients. And irrespective of how many Business Standards Committees and Risk Committees banks constitute, it is unlikely that this risk is going to go away any time soon. And I can’t think of a regulatory cure against this.