The pros and cons of judging people

It's a bit of a social taboo to be 'judging' others. Yet, all of us do it all the time. In fact, I've noticed that leaders and people in positions of higher responsibility tend to judge people a lot more than the average bloke. What is it about judging people that's so taboo then? And how do 'successful' people use smart judgement to climb up in their careers?

'Judging' someone refers to making often pre-mature stereotyping and application of generalisations in the assessment of a person's character. For instance, branding a person as quiet just because he didnt talk to you much the first time you met him would be 'judging' him since you don't have enough evidence to suggest that you're right. Similarly, thinking that an attractive woman is dumb just because she's attractive would again be judging her. Now, these judgements can be right or wrong obviously but let us assume that more often than not they are right (it would help explain why everyone judges). Among the cases where the judgements are wrong, if they are made by a society at large they can be often self-fulfilling and lead to them eventually becoming correct because of how the judged people react. If black men are considered gangsters in Southern US (used to happen as recently as the 1990s) a number of them end up so, since they are may not be given equal opportunity in other fields to succeed.

So, why do we judge at all? Let me borrow a concept from behavioural finance and talk about heuristics. We use heuristics to make decisions, when we do not have complete information about something. The lesser the information we have the more prone we are to using a heuristic. A heuristic is something like this : You take the most colourful apple thinking it's tasty although you've never tasted it, based on your prior experience of eating bright apples. Heuristics help us because we do not have to 'search' for complete information on things and can make decisions without wasting often unnecessary time in gathering information which may or may not be worth the time spent in acquiring them. Thus, we end up using these heuristics or 'rules-of-thumb' as we call them in layman language. They can be very useful most of the time but can lead to incorrect decisions at times and can also lead to systemic biases which are difficult to eliminate.

Judging a person is the equivalent if using a large number of heuristics to decide on his/her character. It may be right or wrong, but it's often important for us to understand a person's character before dealing with him. Using heuristics will let us break the ice much easier or to take more important decisions such as whether to do business with him. Coming back to the self-fulfilling aspect of judging people- some of these heuristics have become so common that we accept them as fact. For example, someone who is polite is more often than not considered as nice (and enough people abuse this heuristic). Also, a well-dressed person is considered organised by the people he meets even if he is completely disorganised in real life. Judging people helps us take quick decisions which would not otherwise have been possible considering the time and effort required to collect information about all the people we meet.

What's so wrong about judging people then? It can obviously go wrong a few times, but most of the time if you're right then what's the big deal? This has to do with the application of humanity rather than decision making theories. We are offended by the idea that people try and use their personal experiences to define our character, that too in the matter of a few minutes. It is against your idea of yourself being completely unique. There is however, no getting around heuristics. First impression is always the best, and accepting heuristics such as this is part of living as a functional social being,

Cricket strike rates and financial leverage

This is my first piece on cricket and quite possibly the only one for the foreseeable future. It's a game I used to follow a lot as a kid and hence I'm familiar with how the game works, but I'm a noob at the modern day intricacies of it. I'll keep it short, technical and to-the-point. Non followers of cricket/corporate finance may find it difficult to relate to the article

So, I was going through this article the other day about a metric which is supposed to indicate how useful a player is in T20 cricket. Similar to how batting average is an excellent indicator of the performance of a batsman is tests, the metric : Strike-rate+average is used to measure roughly the effectiveness of a player in T20s. My short criticism of this is that while strike-rate is something a player scores over 100 balls and average is the what he scores before getting out, there is a bias in the metric towards players having high strike-rates since on an average, players (batsmen, bowlers and keepers) get out before playing 100 balls. Now, there can be an argument that strike-rates are more important than average in T20s and that the metric somehow accommodates for this increased importance by giving more weight to the strike-rate. However, the likelihood that the weightage provided in this simple metric being correct is very low (although the metric scores very high on simplicity due to the strike-rates and averages being readily available) and I would suggest a calculation of the average balls a player faces before getting out and calculating the actual weight that should be given to the average and strike-rate respectively. But why should strike-rates have a higher weightage in T20s?

Now, for anyone having even the most remote knowledge of cricket would know by intuition that strike-rates are more important in shorter versions of the game than in the longer versions like tests. It's something like this - when there is a smaller risk of the team being bowled out well before the allotted overs (or, time in tests- to avoid draws) the team can afford to lose more wickets sooner and thus play a high risk game which allows for a few wickets to fall. High risk tends to give high returns- players are expected to (and do) score much faster in shorter versions of the game but they might get out quicker. In longer versions, the risk of failure if wickets fall is much higher and so scoring runs is more important than scoring runs fast. To draw an imperfect comparison with the world of Credit Risk and finance, a team getting out well before its allotted quota of overs or time = default (it must be noted that there is no allotted quota of survival for corporations), faster scoring rates= financial/other forms of leverage (let's keep it financial leverage to keep things simple) and different forms of cricket represent different worlds where the risk of default is affected differently by financial leverage (while keeping in mind again that there is no expected time-span for survival of corporations).

So, when a player A scores a 3 ball 12 and a player B scores a 20 ball 30, you can judge which one is better (with all the imperfections of using statistics to model real world decisions) if you go back to the metric and combine the strike-rate and 'average' of A (400,12) with sufficient weightage given to both depending upon which form of cricket we are looking at and compare it with the metric value obtained by using the strike-rate and average of B (150,30). However, some complexities which are very difficult to factor in to the model include (1) The fact that batsmen are often expected to stay at the crease longer and make the innings stable (2) Performances in clutch situations especially while chasing require a higher average than strike-rate and (3) A reliable middle order (higher average) often gives the top order batsman more confidence and might result in a higher strike-rate for them.

Going back to finance terminology and how the financial leverage is impacted when a player scores a 60 ball 80 instead of a 10 ball 30: he is scoring for his team (getting profits for the corporation) at a slightly slower rate (the returns are lower) but resulting in lower financial risk for the team. Until now, we have assumed that it is not possible for a batsman to consistently score at higher speeds without risking dismissal. There can also be individuals who score at very high strike-rates without taking much risk, (I'm slightly deviating from the concept of risk being measured at the team level to go to risk at the individual level)- these are akin to the market beaters of the investing world and manage higher returns without taking much risk. The risk here is slightly different from what we commonly talk about in cricket- it doesn't really matter how 'risky'/aerial the shots of a cricketer are; what matters is the probability of him getting out and subsequently increasing the probability of default of the team. A batsman getting out can be considered as a default in itself, and much simpler to measure than the risk of the team getting all out faster if a particular batsman gets out (conditional probability-> Sachin during the late 90s if out quickly would have resulted in a much higher probability of the team getting all-out than with other Indian batsmen). And so, we go back to the metric which weighs and combines average and strike-rate (somehow), to reward players who score consistently higher without risking getting out themselves. The most obvious flaw with the metric (which exists with plain averages as well) is that some players who get out in the last few overs taking extreme personal risks, but not having a substantial impact on the team getting all-out (defaulting) get punished by the metric, which uses probability of a person getting out instead of a more accurate : increased marginal probability of a team getting all-out due to the player getting out. And, due to all these complexities and more, human judgement is extremely important to compensate for the lack of common sense that statistics have.