## A day at an award function

So I got an award today. It is called “exemplary data scientist”, and was given out by the Analytics India Magazine as part of their MachineCon 2022. I didn’t really do anything to get the award, apart from existing in my current job.

I guess having been out of the corporate world for nearly a decade, I had so far completely missed out on the awards and conferences circuit. I would see old classmates and colleagues put pictures on LinkedIn collecting awards. I wouldn’t know what to make of it when my oldest friend would tell me that whenever he heard “eye of the tiger”, he would mentally prepare to get up and go receive an award (he got so many I think). It was a world alien to me.

Parallelly, I used to crib about how while I’m well networked in India, and especially in Bangalore, my networking within the analytics and data science community is shit. In a way, I was longing for physical events to remedy this, and would lament that the pandemic had killed those.

So I was positively surprised when about a month ago Analytics India Magazine wrote to me saying they wanted to give me this award, and it would be part of this in-person conference. I knew of the magazine, so after asking around a bit on legitimacy of such awards and looking at who had got it the last time round, I happily accepted.

Most of the awardees were people like me – heads of analytics or data science at some company in India. And my hypothesis that my networking in the industry was shit was confirmed when I looked at the list of attendees – of 100 odd people listed on the MachineCon website, I barely knew 5 (of which 2 didn’t turn up at the event today).

Again I might sound like a n00b, but conferences like today are classic two sided markets (read this eminently readable paper on two sided markets and pricing of the same by Jean Tirole of the University of Toulouse). On the one hand are awardees – people like me and 99 others, who are incentivised to attend the event with the carrot of the award. On the other hand are people who want to meet us, who will then pay to attend the event (or sponsor it; the entry fee for paid tickets to the event was a hefty \$399).

It is like “ladies’ night” that pubs have, where on a particular days of the week, women who go to the pub get a free drink. This attracts women, which in turn attracts men who seek to court the women. And what the pub spends in subsidising the women it makes back in terms of greater revenue from the men on the night.

And so it was at today’s conference. I got courted by at least 10 people, trying to sell me cloud services, “AI services on the cloud”, business intelligence tools, “AI powered business intelligence tools”, recruitment services and the like. Before the conference, I had received LinkedIn requests from a few people seeking to sell me stuff at the conference. In the middle of the conference, I got a call from an organiser asking me to step out of the hall so that a sponsor could sell to me.

I held a poker face with stock replies like “I’m not the person who makes this purchasing decision” or “I prefer open source tools” or “we’re building this in house”.

With full benefit of hindsight, Radisson Blu in Marathahalli is a pretty good conference venue. An entire wing of the ground floor of the hotel is dedicated for events, and the AIM guys had taken over the place. While I had not attended any such event earlier, it had all the markings of a well-funded and well-organised event.

As I entered the conference hall, the first thing that struck me was the number of people in suits. Most people were in suits (though few wore ties; And as if the conference expected people to turn up in suits, the goodie bag included a tie, a pair of cufflinks and a pocket square). And I’m just not used to that. Half the days I go to office in shorts. When I feel like wearing something more formal, I wear polo T-shirts with chinos.

My colleagues who went to the NSE last month to ring the bell to take us public all turned up company T-shirts and jeans. And that’s precisely what I wore to the conference today, though I had recently procured a “formal uniform” (polo T-shirt with company logo, rather than my “usual uniform” which is a round neck T-shirt). I was pretty much the only person there in “uniform”. Towards the end of the day, I saw one other guy in his company shirt, but he was wearing a blazer over it!

Pretty soon I met an old acquaintance (who I hadn’t known would be at the conference). He introduced me to a friend, and we went for coffee. I was eating a cookie with the coffee, and had an insight – at conferences, you should eat with your left hand. That way, you don’t touch the food with the same hand you use to touch other people’s hands (surprisingly I couldn’t find sanitiser dispensers at the venue).

The talks, as expected, were nothing much to write about. Most were by sponsors selling their wares. The one talk that wasn’t by a sponsor was delivered by a guy who was introduced as “his greatgrandfather did this. His grandfather did that. And now this guy is here to talk about ethics of AI”. Full Challenge Gopalakrishna feels happened (though, unfortunately, the Kannada fellows I’d hung out with earlier that day hadn’t watched the movie).

I was telling some people over lunch (which was pretty good) that talking about ethics in AI at a conference has become like worshipping Ganesha as part of any elaborate pooja. It has become the de riguer thing to do. And so you pay obeisance to the concept and move on.

The awards function had three sections. The first section was for “users of AI” (from what I understood). The second (where I was included) was for “exemplary data scientists”. I don’t know what the third was for (my wife is ill today so I came home early as soon as I’d collected my award), except that it would be given by fast bowler and match referee Javagal Srinath. Most of the people I’d hung out with through the day were in the Srinath section of the awards.

Overall it felt good. The drive to Marathahalli took only 45 minutes each way (I drove). A lot of people had travelled from other cities in India to reach the venue. I met a few new people. My networking in data science and analytics is still not great, but far better than it used to be. I hope to go for more such events (though we need to figure out how to do these events without that talks).

PS: Everyone who got the award in my section was made to line up for a group photo. As we posed with our awards, an organiser said “make sure all of you hold the prizes in a way that the Intel (today’s chief sponsor) logo faces the camera”. “I guess they want Intel outside”, I joked. It seemed to be well received by the people standing around me. I didn’t talk to any of them after that, though.

## Incredible stupidity in taxi marketplaces

So it’s nearly a week since Uber and Ola drivers in Bangalore went on strike, and there’s no sign of it (the strike) ending. The longer the strike goes on for, the more incredibly stupid all parties involve look.

The blame for the strike should first fall on Uber and Ola, who in some hare-brained madness, forgot that running a platform means that both sides of the market are customers and need to be taken care of. They took good care of passengers, providing discounts and growing their market, but rather quickly pulled the plug on drivers, and there is no surprise that drivers are a rather pissed off lot.

The root cause of driver dissatisfaction has been falling bonus payments, and consequently, incomes. This is a result of Uber and Ola providing too great a subsidy during the time they built up the market.

I don’t fault them for providing those bonuses – when you are building a two-sided market, you need to subsidise one side to solve the chicken-and-egg problem. Where I have the problem is with the extent of bonuses, which gave drivers an income far in excess of what they could make in steady state. This meant that as the market approached steady state and incentives were withdrawn, once side of the market started getting pissed off, undermining the market (Disclosure: I’d once proposed to Ola that they hire me to help them with pricing and incentive structuring. the conversation didn’t go too far).

With Uber and Ola having done their stupid things, the next round has gone to the drivers. In a misguided attempt that a long strike will help them get better deals from the platforms, they are prolonging the strike. They’ve even ransacked Uber’s offices, and gone to the government for help.

What they don’t realise is that having invested what they have in their cars to drive on these marketplaces, their success is inextricably tied to the success of the marketplaces. And the more the jeopardise the marketplaces, the less their incomes in future.

A long strike reduces market size on two counts – it gives people time to adjust to the absence of service and get adjusted to alternate arrangements, and it decreases the reliability of the marketplaces in the eyes of the passengers. Thus, the longer and more frequent the strikers by the drivers, the less that passengers will look to use these services in the future.

A strike can work when the striking employees are protected by some form of labour laws, and there is no way ahead for their employers apart from a negotiated settlement. In case of a marketplace, the platform has absolutely no obligation to the drivers, and Uber and Ola can simply do what Uber and Lyft did in Austin, TX – pack up and move on. And if they do that in Bangalore, the drivers with their shiny new cars will be significantly worse off than they were before the strike.

The other act of stupidity on the drivers’ part has been to involve the government, which, as expected, has responded in a nandelliDLi (“where do I keep mine?”) fashion. The recent ban on shared rides (UberPool/OlaShare) came after a regulator read the rulebook after the last strike by the drivers. Given the complex economics of platform markets, any further regulation can only hurt the drivers.

All in all, the drivers’ stupidity can be traced back to not understanding platform markets, and protesting the way protests used to be done in highly unionised industries. Drivers, whose main skill is in driving cars, cannot be faulted so much for not understanding platform markets. Uber and Ola, on the other hand, have no such excuse!

## Pipes, Platforms, the Internet and Zero Rating

My friend Sangeet Paul Chaudary, who runs Platform Thinking Labs, likes to describe the world in terms of “pipes” and “platforms”. One of the themes of his work is that we are moving away from a situation of “dumb pipes”, which simply connect things without intelligence, to that of “smart platforms”. Read the entire Wired piece (liked above) to appreciate it fully.

So I was reading this excellent paper on Two-Sided Markets by Jean-Charles Rochet and Jean Tirole (both associated with the Toulouse School of Economics) earlier today, and I found their definition of two-sided markets (the same as platform business) striking. This is something I’d struggled with in the past (I admit to saying things like “every market is two-sided. There’s a buyer and a seller”), especially given the buzzword status accorded to the phrase, but it is unlikely I’ll struggle again. The paper says:

A necessary condition for a market to be two-sided is that the Coase theorem does not apply to the relation between the two sides of the markets: The gain from trade between the two parties generated by the interaction depends only on the total charge levied by the platform, and so in a Coase (1960) world the price structure is neutral.

This is an absolutely brilliant way to define two-sided markets. The paper elaborates:

Definition 1: Consider a platform charging per-interaction charges $a^B$ and $a^S$ to the buyer and seller sides. The market for interactions between the two sides is one-sided if the volume V of transactions realized on the platform depends only on the aggregate price level

$a=a^B +a^S$

i.e., is insensitive to reallocations of this total price a between the buyer and the seller. If by contrast V varies with $a^B$ while a is kept constant, the market is said to be two-sided.

So for a market to be two-sided, i.e. for it to be intermediated by an “intelligent platform” rather than a “dumb pipe”, the volume of transactions should depend not only on the sum of prices paid by the buyer and seller, but on each price independently.

The “traditional” neutral internet, by this definition, is a platform. The amount of content I consume on Youtube, for example, is a function of my internet plan – the agreement between my internet service provider and me on how much I get charged as a function of what I consume. It doesn’t depend on the total cost of transmitting that content from Youtube to me. In other words, I don’t care what Youtube pays its internet service provider for the content it streams. Transaction costs (large number of small transactions) also mean that it is not practically possible for Youtube to subsidise my use of their service in this model.

Note that if buyers and sellers on a platform can make deals “on the side”, it ceases to be a platform, for now only the total price charged to the two matters (side deals can take care of any “adjustments”). The reason this can’t take place for a Youtube like scenario is that you have a large number of small transactions, accounting for which imposes massive transaction costs.

The example that Rochet and Tirole take while explaining this concept in their paper is very interesting (note that the paper was written in 2004):

…As the variable charge for outgoing traffic increases, websites would like to pass this cost increase through to the users who request content downloads…

..an increase in their cost of Internet traffic could induce websites that post content for the convenience of other users or that are cash-strapped, to not produce or else reduce the amount of content posted on the web, as they are unable to pass the cost increase onto the other side.

Note how nicely this argument mirrors what Indian telecom companies are saying on the Zero Rating issue. That a general increase in cost of internet access for consumers can result in small “poor” consumers to not consume on the internet at all, as they are unable to pass on the cost to the other side!

Fascinating stuff!

## Market-making in on-demand markets

I’ve written a post on LinkedIn about the need for market-making in on-demand markets. I argue that for a market to be on-demand for one side, you require the other side to be able to provide liquidity. This liquidity comes at a cost and the side needs to get compensated for it. Driver incentive schemes at Ola/Uber and two-part electricity tariffs are examples of such incentives.

An excerpt:

In a platform business (or “two sided market”, or a market where the owner of the marketplace is not a participant), however, the owner of the market cannot provide liquidity himself since he is not a participant. Thus, in order to maintain it “on demand”, he should be able to incentivise a set of participants who are willing to provide liquidity in the market. And in return for such liquidity provided, these providers need to be paid a fee in exchange for the liquidity thus provided.

## Fragility of two-sided markets

Two-sided markets are inherently fragile for participation of each side depends on a certain degree of confidence in participation on the other side. Thus, small negative shocks can lead to quick downward spirals.

Following the ill-advised ban on Uber and other taxi aggregators in four Indian states (Delhi, Karnataka, Andhra Pradesh, Telangana), business for drivers who ply their services via such apps has dropped significantly. While on first inspection you might expect it to go to zero (given their services have been banned), the fact that enforcement is tough (there is nothing to identify a cab as “belonging to Uber”) means that apart from Delhi (where Uber has pulled its services) these cabs continue to ply.

In the days after the ban, various news reports have interviewed drivers who ply for Uber who complain about drastically reduced services. While numbers vary from report to report, the general sense is that so far the number of trips per driver per day has fallen by half. And I expect this to fall further unless drastic steps are taken – such as issuance of new regulations or removal of the ban.

In a “normal” market (where the owner of the market is also a participant), when demand for a particular good drops, price is expected to fall and availability is expected to increase. If demand for a particular item that you have in stock drops, you need to take steps to get rid of the excess inventory that you have. You are most likely to indulge in discounting or other such promotional activities, in order to make it more attractive for the buyers to buy, and thus take the inventory off your shelves.

In a “two-sided market” (one where the owner of the market is not a participant), however, things work differently. It is a popular saying that in such markets “demand creates its own supply”. A corollary to that is that “lack of demand creates lack of supply”. Let us take the case of Uber itself. Over the last few days, irrespective of whether the ban on the service is official or not, legal or not, the number of people who have been requesting for the service has dropped.

Now, if you are a driver using the app, you realise that your potential revenues and profits from continuing to use the app are not as high as they used to be. Thus, if there are other avenues for you to make money, you are now more likely to take those avenues rather than logging on to Uber (since the “hurdle rate” for such a switch is now lower thanks to lower Uber revenues). As many of you take the same route, the availability of cabs on Uber also drops – something that I’ve seen anecdotally over the last few days. And when availability of Uber cabs drops beyond a point, I start questioning my trust in the service – a week ago I would be confident that I would be able to hail an Uber from anywhere in Bangalore with very high confidence; that confidence has now dropped. And when my trust in the service drops, I start using it less, and when many of us do that, drivers see less demand and more of them pull away from the market. And this results in a vicious cycle.

Notice that things would work very differently had Uber been a “traditional” taxi service which owned its cabs and employed its drivers. In that case, falling demand would have been met with a response that would have made it easier for customers to buy – price cuts, perks, etc.

The point is that platforms or two-sided markets are inherently fragile, and highly dependent on confident in the system. I leave my car at home only if I have enough trust in the taxi platforms that I’ll be able to get a cab when I need one. A driver will forsake other trips and switch on his Uber app only if he is confident that he can get enough rides through the app.

The same network effects that can lead to a rapid ramp-up in two-sided markets can also lead to its downfall. All it takes is a small trigger that leads to loss of confidence in the service from one side. Unless that loss of confidence is quickly addressed, the “positive feedback” from it can quickly escalate and the market grinds to a halt!

Another good example of lack of confidence killing two-sided markets is in the market for CDOs and associated derivatives in 2007-08. There were standardised pricing models for such products and a vibrant market existed (between sophisticated financial institutions) in 2007. When house prices started coming down, some people started expressing doubts in such models. Soon, this led to massive loss of trust in the pricing models that underpinned such markets and people stopped trading. This meant companies were unable to mark their securities to market or rationalise their portfolios, and this led to the full-blown 2008 financial crisis!

So when you build a platform, you need to make sure that both sides of the market retain confidence in your platform. For in the platforms business loss of confidence can lead to a much quicker fall than in “traditional” markets. This dependence on confidence thus makes such markets fragile.