Basketball and playing to your strengths

Earlier this week the wife went to play basketball with some classmates in Barcelona. As she was on her way back home, we were talking about the game and I inevitably referred to my own style of playing (it’s a theme now – she says something about school, and I start off my own story with “back when I was in B-school…”). I was telling her about how I never really got good at laying up or dribbling, and I built my game around a careful avoidance of those themes.

She snapped that I was “one of those guys” who doesn’t bother learning certain kind of stuff because I’m good at other kind of stuff, so I assume that I don’t need to learn new stuff. What she said took me back to this piece in Scientific American which talks about two kinds of learning – which the piece calls as “fixed mindset” and “growth mindset”. The piece goes on to say that kids who are usually praised for results or intelligence end up developing “fixed mindsets” and that for such kids, learning stops at some stage. Those praised for effort and process on the other hand, the piece says, continue to learn and their learning is everlasting.

When I read the piece I completely identified with the fixed mindset. I sailed through most of school without putting in much effort, but when the learning curve got steep (like in Class XI physics, or at IIT) I simply gave up and started working around concepts that I found hard to learn. I didn’t do badly then, but it started affecting me when I started working. And over the last three years I’ve institutionalised playing to my strengths, while making an effort to simultaneously learn.

Coming back to basketball, the wife talked that day about how my view of the game was wrong and compared my views to those of people who would ask her “so how many points did you score” after a game – which she said was extremely pointless.

Anyway I had a chance to put that to test this morning when I played basketball (after a gap of close to 9 years) with Rohin, Vivaan and Issac (links not available to latter two). It was a chance occurrence – I stumbled upon Rohin’s tweet calling for people to play basketball with him and I responded. And it was a wonderful morning today, as I played the game after nine years.

Two pertinent observations – firstly I haven’t regressed too much. I missed shots much more frequently than I normally do, but got better as the game wore on. The second and more important pertinent observation – I still play in a fashion similar to how I played back in 1997.

So despite having gone for formal training in basketball for a brief period when I was in class 1 (or 2), I’ve never been good at dribbling. I’ve never learnt to put a good lay up . And I’ve never been a quick runner. And right from the beginning rather than working on these weaknesses, I simply played to my strengths and improving my play in those – I can shoot reasonably well (though I didn’t do so today), my above-average height (by Indian standards) means I can pick rebounds well, I have developed a good sense of positioning to compensate for my lack of speed, which also means I can defend fairly well, and so forth. And I make up for lack of dribbling and layups by relying on quick short passing. And all this put together has made me a reasonable player at casual level, and I had a satisfactory game this morning too.

In short, the way I’ve developed my basketball is by just ignoring what I suck at but focussing on getting better at my strengths. While this means that I rarely put myself outside of my comfort zone, it also means that I become an overall better (though incomplete) player given the amount of effort I put in. I remember times when I would play alone in the half-court behind my hostel at IIT. When you play basketball alone, you have two choices – do layups and shoot. To become a complete player I should’ve practised the former. I chose the latter!

So coming back to the Scientific American piece, while I agree that a fixed mindset can stop growth at some point in time, it is possible to grow around it as long as you recognise your limitations and simply focus on your strengths. And with the coming up of the on-demand economy (which I’m in a weird way part of), division of labour can be such that you can possibly get away doing only those things that you are good at! At least that’s the hope for people like me who’ve grown up with a fixed mindset.

And finally, I realise I’m unfit. Despite going to the gym fairly regularly, the game of basketball this morning showed me up as being severely unfit. Despite being the youngest guy on the court ( I think, but am not sure), it was I who was calling the time outs this morning, and it was I who was panting the most. It’s not good. Basically the kind of fitness you need to play sports such as basketball (lots of short sprints) is very different from what you build by doing “normal gym activities”. To put it another way, squatting 150 lb is no indication of whether you’re capable of playing half-court basketball for 30 minutes!

The Ambareesh Principle and First Come First Served Nature of Calendars

The story goes (this is third hand information, so take it with adequate amount of salt) that a few years ago a bunch of people went to actor (and now Minister) MH Ambareesh’s house asking him to be a chief guest at a function they were going to organise three months hence. Ambareesh, it is said, gave them a funny look, saying it was impossible for him to commit to something so far away. He asked them to get back to him ten days before the event.

Based on this (possibly apocryphal) story, I christen this the “Ambareesh Principle” – when someone invites you for an event or meeting that is way too far away for you to plan, you refuse to commit and ask them to come back to you a reasonable number of days before the event. (Perhaps Ambareesh might not like his name being attached to this principle, but since he is a public figure, I’m entitled to use his name).

The problem with calendars (of the variety we use on our computers, like iCal or Outlook) is that they operate on a “First Come First Served” basis. The way calendars are designed, you need to decide whether you are going to attend an event or not in an “online” fashion – without knowing what other event might come up at the same time. This can at times lead to suboptimal decisions, and unsavoury cancellations, for you have to go back on your commitments when something more interesting comes along.

Because of the FCFS nature of our calendars, you have people (the usually busy types – CEOs and suchtypes) who have their calendars blocked for ages together, and in order to get an appointment with them, you have to take one a long time in the future. And with such appointments you never know if you might get pre-empted by something else “more pressing” that might come along in the meantime. Leading to lower efficiency all round.

The question is if we can redesign the calendar, and the “blocking time” system in order to make it more efficient, and make it compatible with the “Ambareesh principle”. Is there a way that we can respond to far-flung meeting requests with “too far to take appointments. Ping me <= X days in advance”, or set some kind of a auto reply to our calendar systems to send the above message for meeting requests sent too early?

And what is going to happen when CEOs and other such “important people” decide to implement such a scheme where they don’t take meeting requests more than N days in advance? Maybe we should get Ambareesh to answer! :)

Why the proposed Ola-TaxiForSure merger is bad news

While a merger intuitively makes economic sense, it’s not good for the customers. The industry is consolidating way too fast, and hopefully new challengers will arise soon

Today’s Economic Times reports that Ola Cabs is in the process of buying out competitor TaxiForSure. As a regular user of such services, I’m not happy, and I think this is a bad move. I must mention upfront, though, that I don’t use either of these two services much. I’ve never used TaxiForSure (mostly because I never find a cab using its service), and have used Ola sparingly (it’s my second choice after Uber, so use it only when Uber is not available).

Now, intuitively, consolidation in a platform industry is a good thing. This means that more customers and more drivers are on the same platform, and that implies that the possibility of finding a real-time match between a customer who wants a ride and a driver who wants to offer one is enhanced. The two-sided network effects that are inherent in markets like this imply super-linear returns to scale, and so such models work only at scale. This is perhaps the reason as to why this sector has drawn such massive investments.

While it is true that consolidation will mean lower matching cost for both customers and drivers, my view on this is that it’s happening too soon. The on-demand taxi market in India is still very young (it effectively took off less than a year back when Uber made its entry here. Prior to that, TaxiForSure was not “on demand” and Ola was too niche), and is still going through the process of experimentation that a young industry should.

For starters, the licensing norms for this industry are not clear (and it is unlikely they will be for a long time, considering how disruptive this industry is). Secondly, pricing models are still fluid and firms are experimenting significantly with them. As a corollary to that, driver incentive schemes (especially to prevent them from “multihoming”) are also  rather fluid. The process of finding a match (the process a customer and a driver have to go through in order to “match” with each other), is also being experimented with, though the deal indicates that the verdict on this is clear. Essentially there are too many things in the industry that are still fluid.

The problem with consolidation at a time when paradigms and procedures are still fluid is that current paradigms (which may not be optimal) will get “frozen”, and customers (and drivers) will have to live with the inefficiencies and suboptimalities that are part of the current paradigms. It looks as if after this consolidation the industry will settle into a comfortable duopoly, and comfortable duopolies are never great for innovation and for finding more optimal solutions.

Apart from the network effects, the reasons for the merger are clear, though – in the mad funding cycle unleashed by investors into this industry, TaxiForSure was a clear loser and was finding itself unable to compete against the larger better-funded rivals. Thus, it was a rational decision for the company to get acquired at this point in time. From Ola’s point of view, too, it is rational to do the deal, for it would give them substantial inorganic growth and undisputed number one position in the industry. For customers and drivers, though, now faced with lower choice, it is not a great deal.

This consolidation doesn’t mean the end, though. The strength of a robust industry is one where weak firms go out of business and new firms spring up in their place in their attempt to make a profit. That three has become two doesn’t mean that it should remain at two. There is room in the short term for a number three and even possibly a number four, as the Indian taxi aggregation industry tries to find its most efficient level.

I would posit that the most likely candidates to emerge as new challengers are companies such as Meru or EasyCabs, which are already in the cab provider business but only need to tweak their model to include an on-demand component. A wholly new venture to take up the place that is being vacated by TaxiForSure, however, cannot be ruled out. The only problem is that most major venture capitalists are in on either Uber or Ola, so it’s going to be a challenge for the new challenger to raise finances.

\begin{shameless plug}
I’m game for such a venture, and come on board to provide services in pricing, revenue management, availability management and driver incentive optimisation. :)
\end{shameless plug}

 

The end of experience

While it might have turned out that the stories about TCS laying of tens of thousands of IT workers in India are simply not true, the fact remains that the Indian IT sector is bloated around the middle. There are way too many employees in the middle management level who have few skills apart from project management, and who are essentially dispensable to their employers. The question is what the change is at the industry level that is putting to peril careers of so many people in their 40s.

Back in my parents’ generation, you could choose two paths, especially in a government job. If you were ambitious, you could choose to be an officer, for which you had to write (and pass) exams and be prepared to work demanding hours (unlike what people usually expect from a “government job”). In return you got advancement in your career, get promoted and get a chance to be part of your company’s top management.

Of course given pyramidal structures of organisations things wouldn’t have worked out so well for everyone had everyone chosen to go along this path (growth would’ve been painfully slow) so there was a parallel track – you could choose to not become an officer. While this meant that beyond a point you would stop getting promoted, you continued to get paid quite well (my parents’ “senior assistant” friends made almost as much as my officer parents did), and you retire with a comfortable pension. It worked well for everyone. Or so it seemed.

As Deepak Shenoy explains so well in this excellent post (same link as above), back in the days when IT exporters made big margins, they could afford to pay their employees well. And they gave them fat raises every year irrespective of their performance. Employees went to middle management. They stopped coding. And the only skills they developed was “project management”, and perhaps people management. And they continued to get fat raises each year. Until margins started thinning down.

Now, as Deepak explains, IT exporters are facing diminishing margins, and they need to cut cost. When you are cutting costs, the first person on the block is one that is drawing a fat salary for not doing too much. And in the Indian IT sector, it’s these mid-level project management guys, who don’t code, are not key to management and have no specific skills. And so, sooner or later, as margins thin out, their jobs are going to be in trouble.

The problem with this particular cohort of workers is that they haven’t developed enough skills as they have gone along, and the skills that they have are easily replaceable with someone much younger (and thus drawing a much lower salary). In something as generic as project management, you are not going to lose too much by replacing a project manager with 15 years experience with one with 10 years experience, especially if the one with 10 years experience will get paid much lower than the other guy.

From a company’s perspective, it should not matter how long a particular employee has been there in its compensation decision. So if an employee with 10 years’ experience is offering the same value as one with 15 years’ experience, they ought to be paid similar salaries. Except that given the massive raises in salaries back in good times and the power of compound interest, the employee with 15 years’ experience is getting paid much more than the one with 10 years’ experience. And that is what makes him dispensable.

The big lesson from this story is that you should continue developing and never “settle”. With 15 years’ experience, you get paid more than someone with 10 years’ experience, but you should also demonstrate sufficient skill sets that show you as being significantly superior to the other guy. Experience, to put it in one way, is a proxy for measuring how much you’ve learned in your job, and if you stop learning there is no point in attributing value to that part of your experience where you’ve not learnt much!

Selection bias and recommendation systems

Yesterday I was watching a video on youtube, and at the end of it it recommended another (the “top recommendation” at that point in time). This video floored me – it was a superb rendition of Endaro Mahaanubhaavulu by Mandolin U Shrinivas. Listen and enjoy as you read the rest of the post.

I was immediately bowled over by youtube’s recommendation system. I had searched for both Shrinivas and Endaro … in the not-so-distant past so Youtube had put two and two together and served me up an awesome rendition! I was so happy that I went to town twitter about it.

It was then that I realised that this was the firs time ever that I had noticed the top recommendation of Youtube. In other words, every time I use youtube, it recommends a video to me, but I seldom notice it. And I seldom notice it for a reason – they’re usually irrelevant and crap. The one time I like the video it throws up, though, I feel really happy and go gaga over the algorithm!

In other words, there’s a bias which I don’t know what its exactly called – the bias that when event happens in a certain direction, you tend to notice it and give credit where you think it’s due. And when it doesn’t happen that way, you simply ignore it!

In terms of larger implications, this is similar to how legends such as “lucky shirts” are born. When something spectacular happens, you notice everything that is associated with that spectacular event and give credit where you think it’s due (lucky shirt, lucky pen, etc.). But when things don’t go your way you think it’s despite the lucky shirt, not because the shirt has become unlucky.

It’s the same thing with belief in “god”. When you pray and something good happens to you after that, you believe that your prayers have been answered. However, when you pray and something good doesn’t happen, you ignore the fact that you prayed.

Coming back to recommendation systems such as Youtube’s, the problem is that it is impossible for a recommendation system to get recommendations right all the time. There will be times when you get it wrong. In fact, going by my personal experience with Youtube, Amazon, etc. most of the time you will get your recommendation wrong.

The key to building a recommendation system, thus, is to build it such that you maximise the chances of getting it right. Going one step further I can say that you should maximise the chances of getting it spectacularly right, in which case the customer will notice and give you credit for understanding her. Getting it “partly right” most of the time is not enough to catch the customer’s attention.

Putting marketing jargon on it, what you should focus on is delighting the customer some of the time rather than keeping her merely happy most of the time!

Teaching at IIMB: Mid-term review

IIMB has a strange policy. They are not allowed to have classes tomorrow on account of it being a national holiday so they shifted tomorrow’s concept to today, indicating a complete lack of appreciation of the concept of the long weekend. Anyway, since I didn’t have any other plans for the day or the weekend I decided to not request for a slot change and went anyways. This was my eleventh class out of twenty.

I expected the attendance to be rather thin today, but the class surprised me with more than three-fourths of the registered students turning up (on par with most sessions so far). And despite the class being at 8 am in the morning, none of them slept (at least I didn’t notice anyone sleeping). That is again on par with the course so far – more than halfway though the course and I’m yet to catch a single person sleeping in class! Maybe I should take some credit for that.

The class before today’s was about ten days back (long gap due to mid-term exams), and that day I had a minor scare. I had formulated a case that involved solving the Newsboy Problem (now politically corrected to “Newsvendor model“) as a sub-step in the solution to the case. Having worked out the sketches of the case solution the previous night I went to sleep hoping to work out the full case before I went to class. And my brain froze.

So it was 6:30 on the morning of an 8am class and I wasn’t getting the head or tail of the newsboy problem despite having known it fairly well. Decided to have cereal at home rather than go to SN to give myself more time to read up and understand the model. And my brain refused to open up. Yet I made my way to class, hoping I could “wing it”.

I didn’t have to, for the class exceeded expectations and solved the case for me. One guy popped up with “newsvendor model”. Another guy said that we could consider a certain thing as a “spot price”, thus eliminating the need to make any assumptions on costs. Then we started working out the model on Excel (remember that this is a “spreadsheet modelling” course). And the time came to implement the newsvendor model. And my brain froze in anticipation. “How do we do this?”, I asked, trying to not give away my brain freeze.

“We calculate the critical ratio”, came the chorus (sometimes I dispense with the politeness and order of people raising their hands and speaking in order). “And what is that here?”, I asked. “B6/(B5+B6)” came back the chorus. And then when I asked them how to impute the ordering level based on this, the chorus had figured out the exact way in which we should use NormInv to determine this. The troubling bit of the newsvendor problem having been thus solved, I took control and went forward with the rest of the case. And my respect for the class went up significantly that day.

Later in the day I was relating the incident to the wife, who I might have mentioned is an MBA student at IESE Business School in Barcelona. “Oh my god, your class is so quant”, she exclaimed. This is a topic for another day but perhaps due to the nature of the admissions procedure, students at IIMs are definitely much much more quantitatively oriented than students at B-schools elsewhere. Yet, IIMs don’t seem to be doing much in terms of harnessing this quant potential which should be giving their students a global competitive advantage.

And coming back to my class, they’ll be sitting for placements starting the 9th of February. If my class is a representative sample (it is most likely not, since I’m teaching an elective and these people expressed interest in learning what I’m teaching, so there is a definite bias), this seems like a great batch at IIMB. So I encourage you to go and recruit!

 

Aggregate quality of life

I was going through some discussions on the “Bangalore – Photos from a Bygone Era” (membership required to view) group on Facebook. From some of the discussions, it is evident that people are nostalgic about the quality of life in Bangalore in “those bygone days” compared to now (irrespective of your definition of bygone).

For example, someone was marvelling about how empty the HAL airport used to be in those days, until it became intolerably crowded in the late 1990s necessitating the construction of the new airport in Devanahalli. Someone else, perhaps in the same thread, wondered about how one could make a dash from HAL airport to Commercial street and back in 30 minutes “back in those days”. Outside of the group, I remember Vijay Mallya mention in an interview a couple of years back about how when he was young he could drive from his home in the middle of town to HAL airport in 15 minutes, and it’s not possible any more.

Reading such reports, you start thinking that life back in those days was truly superior to life today.

While narratives like the above might indeed make you believe that life in a “bygone era” was significantly superior, what that doesn’t take into account is that life was possibly superior for only certain people back then – airports were empty because tickets were prohibitively expensive and the monopolist Indian Airlines ran few flights out of Bangalore. Traffic was smooth because there were few cars, so if you were lucky to have one you could zip around the city. However, if you were not as lucky, and one of the many who didn’t have access to a personal vehicle, things could be really bad for you, for you had to either walk, or wait endlessly for a perpetually crowded bus!

One of the ostensible purposes of the socialist model followed by India in the early decades after independence was to limit inequality. Yet, the shortages that the system led to led to widening inequality rather than suppressing it. By conventional metrics of inequality – such as the Gini coefficient, it might be that wealth/income inequality in India today is significantly higher than in the decades immediately after independence.

However, if you were to take into account consumption and access to living a certain way, inequality today is far lower than it was in those socialist years. In the 1970s you could get an asset only if you knew someone that mattered (my father waited four years (1976-80) before he was “allotted” his scooter. His first telephone connection took six years (1989-95) to arrive), and this only served to exacerbate the inequality between those that had access to the “system” and those that didn’t. Today on the other hand you are able to purchase any asset on demand as long as you can afford it! And so a lot more people can afford a “reasonable” quality of life that was beyond them (or their ancestors) back in those days!

What we need is a redefinition of the concept of inequality from a strictly monetary one to one based on consumption and access to certain goods and services. While wealth inequality is indeed a problem (because of lower marginal utility of money the super-rich don’t spend as much as the less rich), what matters more is inequality in terms of quality of life. And this is something standard measures such as the Gini coefficient cannot measure.

I tried getting some students work on a “quality of life index” to show the improvements in quality of life (as explained above) since the “bygone era”. Perhaps I didn’t communicate it well enough, but they just stuck to standard definitions like per capita income, education, life expectancy, etc. What I want to build is an index that captures and tracks “true inequality”.