Parks and public safety

I spent the last hour and a half working from a park near my house in Barcelona. It helped that I wasn’t using my laptop – I was mostly working with a notebook and pen. The incredible thing was that never once did I feel unsafe working in that park, and it has to do with the park’s design.

I got accosted by a human only once – by this guy asking me if I had a cigarette lighter and who walked away when I said no, and by dogs (of all shapes and sizes) multiple times. Despite the fact that I was in a park, and people don’t go to parks at 10 am on a weekday morning, there was a constant flow of people in front of me. There were, to put it in other words, sufficient “eyes on the street” which contributed to the place’s safety.

I’ve ranted sufficiently on this blog about the design (or lack of it) of Bangalore’s public parks (one with a name sufficiently similar to that of this post). The problem with the parks, in my opinion, is that they are exclusive closed spaces which are hard to access.

The sprawling Krishna Rao Park in the middle of Basavanagudi, for example, has only two or three entrances, and the number of trees in the park means that large parts of it are hardly visible, providing a refuge to unsavoury elements. This phenomenon of few entrances to parks is prevalent in other city parks as well, with the consequence that the BBMP (city administration) closes off the parks during the day when few people want to go in.

The park I was sitting in this morning, on the other hand, had no such safety issues. It helped that there weren’t too many trees (not always a positive thing about parks), which improved visibility, but most importantly, it was open on all sides, providing a nice thoroughfare for people walking across the area. This meant that a large number of people in the vicinity, even if they didn’t want to “go to a park” ended up passing through the park, because of which there was a constant flow of human traffic and “eyes on the park street”, making it a significantly safer space.

There might be (maintenance-related ) reasons for having limited entrances to parks in Bangalore, but the administration should seriously consider opening up parks on all sides and encouraging people to walk through them (after all, walking paths are an important part of Bangalore parks). Maintenance costs might go up, but safety of parks will be enhanced significantly, and it will be possible to keep parks open at all times, which will enhance their utility to the public.

Maybe Krishna Rao park, with roads on all sides and in the middle of Basavanagudi, might serve as a good pilot case for this.

Revenue management at Liverpool Football Club

Liverpool Football Club, of which I’ve been a fan for nearly eleven years now, is in the midst of a storm with fans protesting against high ticket prices. The butt of the fans’ ire has been the new £77 ticket that will be introduced next season. Though there will be few tickets that will be sold at that price, the existence of the price point has been enough to provoke the fans, many of whom walked out in the 77th minute of the home draw against Sunderland last weekend.

For a stadium that routinely sells out its tickets, an increase in ticket prices should be a no-brainer – it is poor revenue management if either people are scrambling for tickets or if there are empty seats. The problem here has been the way the price increase has been handled and communicated to the fans, and also what the club is optimising for.

At the outset, it must be understood that from a pure watching point of view, being in a stadium is inferior to being in front of a television. In the latter case, you not only have the best view of the action at all points in time, but also replays of important events and (occasionally) expert commentary to help you understand the game. From this point of view, the reason people want to watch a game at the ground is for reasons other than just watching – to put it simply, they go for “the experience”.

Now the thing with stadium experience is that it is a function of the other people at the stadium. In other words, it displays network effects – your experience at the stadium is a function of who else is in the stadium along with you.

This can be complex to model – for this could involve modelling every possible interaction between every pair of spectators at the ground. For example, if your sworn nemesis is at the ground a few seats away from you, you are unlikely to enjoy the game much.

However, given the rather large number of spectators, these individual interactions can be ignored, and only aggregate interactions considered. In other words, we can look at the interaction term between each spectator (who wants to watch the game at the ground) and the “rest of the crowd” (we assume idiosyncrasies like your sworn enemy’s presence as getting averaged out).

Now we have different ways in which a particular spectator can influence the rest of the crowd – in the most trivial case, he just quietly takes his seat, watches the game and leaves without uttering a word, in which case he adds zero value. In another case, he could be a hooligan and be a pain to everyone around him, adding negative value. A third spectator could be a possible cheerleader getting people around him to contribute positively, organising Mexican waves and generally keeping everyone entertained. There can be several other such categories.

The question is what the stadium is aiming to optimise for – the trivial case would be to optimise for revenue from a particular game, but that might come at the cost of stadium “atmosphere”. Stadium atmosphere is important not only to galvanise the team but also to enthuse spectators and get them to want to come for the next game, too. These two objectives (revenue and atmosphere) are never perfectly correlated (in fact their correlation might be negative), and the challenge for the club is to price in a way that the chosen linear combination of these objectives is maximised.

Fundamental principles of pricing in two-sided markets (here it’s a multisided market) say that the price to be charged to a participant should be a negative function of the value he adds to the rest of the event (to the “rest of the crowd” in this case).

A spectator who adds value to the crowd by this metric should be given a discount, while one who subtracts value (by either being a hooligan or a prude) should be charged a premium. The challenge here is that it may not be possible to discriminate at the spectator level – other proxies might have to be used for price discrimination.

One way to do this could be to model the value added by a spectator class as a function of the historic revenues from that class – with some clever modelling it might be possible to come up with credible values for this one, and then taking this value into account while adjusting the prices.

Coming back to Liverpool, the problem seems to be that the ticket price increase (no doubt given by an intention to further maximise revenue takings) has badly hit fans who were otherwise adding positive value to the stadium atmosphere. With such fans potentially getting priced out (in favour of fans who are willing to pay more, but not necessarily adding as much value to the ground), they are trying to send a message to the club that their value (toward the stadium atmosphere) is being underestimated, and thus they need greater discounts. The stadium walkouts are a vehicle to get across this point.

Maximising for per-game revenue need not be sustainable in the long term – an element of “atmosphere” has to be added, too. It seems like the current worthies at Liverpool Football Club have failed to take this into account, resulting in the current unsavoury negotiations.

Now that I’ve moved to Barcelona, Liverpool FC need not look too far – I’ve done a fair bit of work on pricing and revenue management, and on two-sided markets, and can help them understand and analyse the kind of value added by different kinds of spectators, and how this can translate to actual revenues and atmosphere. So go ahead and hire me!

Family enterprise startups

Recently, Ambiga Dhiraj, co-founder of MuSigma, was appointed CEO of the company, replacing her other co-founder (and husband) Dhiraj Rajaram. There was a lot of chatter about the “first woman CEO of Indian unicorn”.

I didn’t see it that way. The way, I saw it, MuSigma was like a family enterprise, and so it was no big deal that one of the woman founders had become CEO. A couple of tweets went out:

People didn’t take my tweets too kindly. One guy quickly pointed out that she had had a pivotal role in building the company, and so she was more like Hillary Clinton than like Rabri Devi.

Another guy (a MuSigma employee) said that she’s gotten there on merit and not on account of her relationship.

While it might be the case that she got there on her own merit (I don’t know her at all, so can’t comment), the fact that she’s become CEO of a company she founded with her husband means that people will judge her on her relationships rather than purely on merit.

I wonder if this is a good reason to not start a company with a close relative.

On another note, I’d think twice (or maybe three times) before working for a company whose top management is closely related to each other – it will create a kind of glass ceiling and also a highly correlated top management meaning others will find it that much harder to create impact.

Counter staffing and service levels

I’m writing this from the international section of the Bangalore International Airport, as I wait to board my flight to Barcelona. It was a plan I’d made in October 2014 to “hibernate” for a few months in Barcelona during my wife’s last term of classes there, and this is the execution of the same plan.

There was a fairly long line at the passport control counters this morning, and it took me perhaps twenty minutes to cross it. When I joined the line, there were about 10 passport officers to say goodbye to Indian passport, so the line moved fairly quickly.

Presently, officers started getting up one by one, and going to one side to drink tea. I initially thought it was a tea break, but the officers drinking tea soon disappeared, leaving just four counters in operation, implying that the line moved much slowly thereafter. Some people were pissed off, but I soon got out.

It is not an uncommon occurrence to suddenly see a section of “servers” being closed. For example, you might go to the supermarket on a weekday afternoon to expect quick checkouts, but you might notice that only a fraction of the checkout counters are operational, leading to lines as long as on a weekend evening.

From the system of servers’ point of view, this is quite rational. While some customers might expect some kind of a moral obligation from the system of servers to keep all servers operational, the system of servers has no obligation to do so. All they have an obligation towards is in maintaining a certain service level.

So coming back to passport control at the Bangalore airport, maybe they have a service level of “an average of 30 minutes of waiting time for passengers”, and knowing that the number of international flights in late morning is lower than early morning, they know that the new demand can be met with a smaller number of servers.

The problem here is with the way that this gets implemented, which might piss off people – when half the servers summarily disappear, and waiting period suddenly goes up, people are bound to get pissed off. A superior strategy would be to do it in phases – giving a reasonable gap between each server going off. That smoothens the supply and waiting time, and people are far less likely to notice.

As the old Mirinda Lime advertisement went (#youremember), zor ka jhatka dheere se lage.

Bias in price signals from ask only markets

Yesterday I listened to this superb podcast where Russ Roberts of the Hoover Institution interviews Josh Luber who runs Campless, a secondary market for sneakers (listen to the podcast, it isn’t as bizarre as it sounds). The podcast is full of insights on markets and “thickness” and liquidity and signalling and secondary markets and so on.

To me, one of the most interesting takeaways of the podcast was the concept that the price information in “ask only markets” is positively biased. Let me explain.

A financial market is symmetric in that it has both bids (offers to buy stock) and asks (offers to sell). When there is a seller who is willing to sell the stock at a bid amount, he gets matched to the corresponding bid and the two trade. Similarly, if a buyer is willing to buy at ask, the ask gets “taken out”.

The “order book” at any time thus contains of both bids and asks – which have been unmatched thus far, and looking at the order book gives you an idea of what the “fair price” for the stock is.

However, not all markets are symmetric this way. In fact, most markets are asymmetric in that they only contain asks – offers to sell. Think of your neighbourhood shop – the shopkeeper is set up to only sell goods, at a price he determines (his “ask”). When a buyer comes along who is willing to pay the ask price of a good, a transaction happens and the good disappears.

Most online auction markets (such as eBay or OLX) also function the same way – they are ask only. People post on these platforms only when they have something to sell, accompanied by the ask price. Once a buyer who is willing to pay that price is found, the item disappears and the transaction is concluded.

What makes things complicated with platforms such as OLX or eBay (or Josh Luber’s Campless) is that most sellers are “retail”, who don’t have a clear idea of what price to ask for their wares. And this introduces an interesting bias.

Low (and more reasonable) asks are much more likely to find a match than higher asks. Thus, the former remain in the market for much shorter amount of time than the latter.

So if you were to poll the market at periodic intervals looking at the “best price” for a particular product, you are likely to end up with an overestimate because the unreasonable asks (which don’t get taken out that easily) are much more likely to occur in your sample than more reasonable asks. This problem can get compounded by prospective sellers who decide their ask by polling the market at regular intervals for the “best price” and use that as a benchmark.

Absolutely fascinating stuff that you don’t normally think about. Go ahead and listen to the full podcast!

PS: Wondering how it would be if OLX/eBay were to be symmetric markets, where bids can also be placed. Like “I want a Samsun 26 inch flatscreen LCD TV for Rs. 10000”. There is a marketplace for B&Bs (not Airbnb) which functions this way. Would be interesting to study for sure!

Gandhi

I was playing table tennis in my hostel at IIT with a friend who came from North India. At some point during a rally, the ball hit the edge of the table on his side, and moved far away, giving me the point. I apologised (when you normally do when you win a point by fluke), and said “Gandhi”. He didn’t understand what that meant.

It was then that I realised that using the word “Gandhi” as a euphemism for “fluke” is mostly a Bangalore thing. Back when I played table tennis during my school days, a let was called “Gandhi”, as was a ball hitting the edge of the table. It was the same case with comparable sports such as badminton or tennis or even volleyball. A basket that went in by fluke in basketball was also “Gandhi”.

Now, it might be hard for people to reconcile flukes with MK Gandhi, who was assassinated sixty eight years ago. Some people might also find it repugnant – that the great Mahatma’s name might be used to describe flukes. Looking at it as a fluke, however, is a shallow interpretation.

While it is hard to compare Gandhi (the person) with flukes, it is not hard at all to look at him as a figure of benevolence. He was known for his non-violent methods, and for turning the proverbial “other cheek”. He pioneered the use of non-cooperation as a method of protest (which has unfortunately far outlived its utility) and showed that you could win by being extremely nice. This was channelled in a movie a decade ago which spoke about “Gandhigiri” as a strategy for world domination.

So when the table tennis ball hits the edge of the table and flies off, invoking Gandhi’s name is a sign of benevolence by the person who has lost the point, who implicitly says “you, bugger, didn’t deserve to win this point. But I’ll be benevolent like Gandhi and allow you to take it”. It is similar in other sporting contexts, such as a let or a freak basket.

The invocation of Gandhi’s name as a sign of benevolence is common in other fields as well. In 1991, my cousin had to miss her second standard annual exams as she had to fly to Bangalore on account of the death of the grandfather we shared. Her school, in an act of benevolence, promoted her anyway, an act that was described by other relatives in Bangalore as “Gandhi pass”.

If there is a Gandhi pass, there is a Gandhi class also (again I was surprised to know it’s not a thing in North India). Another of Gandhi’s defining characteristics was the simplicity of his life. Though he could afford to travel better, he would always travel third class, which had the cheapest ticket. As a consequence, the cheapest ticket came to be known as the “Gandhi class”.

The term (Gandhi class) is now most commonly used in the context of cinemas, referring to the front few rows for which tickets are the cheapest. Even though multiplexes have larger blocks nowadays, which means front row tickets are no cheaper than those a few rows behind, the nomenclature sticks. If you are unlucky enough to only get a seat in the first couple of rows, you proudly say you are in “Gandhi class”.

That his name has come to be associated with so many everyday occurrences, mostly in irreverence, illustrates the impact Gandhi has had. Some people might outrage (as the fashion is nowadays) about the irreverence, and “reduction” of Gandhi to these concepts.

I’m still surprised, though, that things like “Gandhi class”, “Gandhi pass” and “Gandhi” as a euphemism for fluke weren’t that prevalent in North India fifteen years ago.

Continuous and barrier regulation

One of the most important pieces of financial regulation in the US and Europe following the 2008 financial crisis is the designation of certain large institutions as “systemically important”, or in other words “too big to fail”. Institutions thus designated have greater regulatory and capital requirements, thus rendering them at a disadvantage compared to smaller competitors.

This is by design – one of the intentions of the “SiFi” (systemically important financial regulations) is to provide incentives to companies to become smaller so that the systemic risk is reduced. American insurer Metlife, for example, decided to hive off certain divisions so that it’s not a SiFi any more.

AIG, another major American insurer (which had to be bailed out during the 2008 financial crisis), is under pressure from its activist investors led by Carl Icahn to similarly break up so that it can avoid being a SiFi. The FT reports that there were celebrations in Italy when insurer Generali managed to get itself off the global SiFi list. Based on all this, the SiFi regulation seems to be working in spirit.

The problem, however, is with the method in which companies are designated SiFis, or rather, with that SiFi is a binary definition. A company is either a SiFi or it isn’t –  there is no continuum. This can lead to perverse incentives for companies to escape the SiFi tag, which might undermine the regulation.

Let’s say that the minimum market capitalisation for a company to be defined a SiFi is $10 billion (pulling this number out of thin air, and assuming that market cap is the only consideration for an entity to be classified as a SiFi). Does this mean that a company that is worth $10 Bn is “systemically important” but one that is worth $9.9 Bn is not? This might lead to regulatory arbitrage that might lead to a revision of the benchmark, but it still remains a binary thing.

A better method for regulation would be for the definition of SiFi to be continuous, or fuzzy, so that as the company’s size increases, its “SiFiness” also increases proportionally, and the amount of additional regulations it has to face goes up “continuously” rather than being hit by a “barrier”. This way, the chances of regulatory arbitrage remain small, and the regulation will indeed serve its purpose.

SiFi is just one example – there are several other cases which are much better served by regulating companies (or individuals) as a continuum and not classifying them into discrete buckets. When you regulate companies as parts of discrete buckets, there is always the temptation to change just enough to move from one bucket to the other, and that might result in gaming. Continuous regulation, on the other hand, leaves no room for such marginal gaming – marginal changes aer only giong to have a marginal impact.

Perhaps for something like SiFi, where the requirements of being a SiFi are binary (compliance, etc.) there may not be a choice but to keep the definition discrete (if there are 10 different compliance measures, they can kick in at 10 different points, to simulate a continuous definition).

However, when the classification results in monetary benefits or costs (let’s say something like SiFis paying additional regulatory costs) it can be managed via non-linear funding. Let’s say that you pay 10% fees (for whatever) in category A and 12% in category B (which you get to once you cross a benchmark). A simply way to regulate would be to have the fees as a superlinear function of your market cap (if that’s what the benchmark is based on).