Tag: option value

Ranji Reform

Perhaps the best thing that the BCCI has done in recent times is to hike the match fees given to players in First Class and List A matches. If i’m not wrong, first class players now get Rs. 2 lakh per game as match fees, and 1 lakh for List A games. Thus, if a player is a regular in his state team, he is assured of at least Rs. 15 lakh per annum, thus ensuring he can remain professional and not have to do a “day job”.

This is excellent in terms of option value for high school students who are good at cricket who are undecided if they should concentrate on their cricket career or if they should go to college and concentrate on studies. And this in turn leads to better quality of cricketers in the pool available for first class games.

For a fringe player, selection to the national team is a lottery. It is also a big step up from the Ranji game. And when you are an under 19 cricketer (unless you are Tendulkar of course; let’s talk about normal people here) there is little that indicates if you are going to be an international regular. However, your performances in school/college level and age group tournaments are an extremely good indicator of how well you are likely to do on the domestic circuit.

Now, the income that the domestic circuit offers means that it might be more profitable for you to concentrate on cricket and try and make it big, rather than giving up cricket and going to college. Even if you fail to make it big, you won’t end up doing too badly in life. So if you think you have a good chance of making the state team, you would rather go for it than playing safe and going to college.

And this means that several players who would have otherwise left the game (in the absence of reasonable income from playing domestic cricket) are available in the pool which makes it more competitive and raises the overall quality of cricket in the country, and consequently that of the national team.

At least the BCCI gets some things right.

It’s about getting the Cos Theta right

Earlier today I was talking to Baada and to Aadisht (independently) about jobs, and fit, and utilization of various skills and option value of skills not utilized etc. So it is like this – you possess a variety of skills, and the job that you are going to do will not involve a large number of these. For the skills that you have that match the job’s requirements, you get paid in full. For the rest of the skills you possess, you only get paid the “option value” – i.e. your employer has the option to utilize these skills of yours and need not actually utilize them.

Hence in order to maximize your productivity and your pay, you need to maximize the cos theta.

Assume your skill set to be a vector in a N-dimensioanl hyperspace where N is the universe of orthogonal skills that people might possess. Now there are jobs which require a certain combination of skill sets, and can thus be seen as a vector. So it’s about maximizing the cos theta between your vector and your job’s vector.

So it’s something like this – you take your skills vector and project it on to the job requirement vector – your total skills will get multiplied now by the value of cos theta, where theta is the angle in the hyperspace between your skills vector and the job vector. For the projection of your skills on the requirement, you get paid in full. For the skills that you have that are orthogonal to the requirement, you get paid only in option value.

One option is to of course build skill set, and keep learning new tricks, and maybe even invent new skills. However, that is not a short-term plan. In the short to medium term, however, you need to maximize the cos theta in order to maximize the returns that your job provides. But as Baada put it, “But there is slisha too much information asymmetry to ensure that cos theta is maximised.”

There are two difficult steps, actually. First, you need to know your vector properly – most people don’t. Even if you assume that you can do a lot of “Ramnath” stuff and get to know yourself, there still lies the challenge of knowing the job’s vector. And the job’s requirement vector is typically more fluid than your skills vector. Hence you actually need to estimate the expected value of the job’s requirement vector before you take up the job.

The same applies when you are hiring. It is actually easier here since the variation in the hiree’s vector will not be as high as the variation in the job profile requirement vector, and you have a pretty good idea of the latter so it is easy to estimate the “projection”.

This perhaps explains why specialists have it easy. Typically, they have a major component of their skills vector along the axis of a fairly well-defined job profile (which is their specialization). And thus, since theta tends to 0, cos theta tends to 1, and they pretty much get full value for their skills.

At the other extreme, polymaths will find it tough to maximize their returns to skills out of a single job, since it is unlikely that there is any job that comes close to their skills vector. So whichever job they do, the small value of the resulting cos theta will cancel out the large magnitude of the skills vector. So for a polymath to maximize his/her skills, it is necessary to do more than one “job”. Unless he/she can define a job for himsel/herself which lies reasonably close to his/her skills vector.

(there is a small inaccuracy in this post. i’ve talked about the angle between two vectors, and taking the cosine of that. however, i’m not sure how it plays out in hyperspaces with a large number of dimensions. let us assume that it’s vaguely similar. people with more math fundaes on this please to be cantributing)