Compensation at the right tail

Yesterday I was reading this article ($) about how Liverpool FC is going about (not) retaining its star forwards Sadio Mane and Mo Salah, who have been key parts of the team that has (almost) “cracked it” in the last 5 seasons.

One of the key ideas in the (paywalled) piece is that Liverpool is more careful about spending on its players than other top contemporary clubs. As Oliver Kay writes:

[…] the Spanish club have the financial strength to operate differently — retaining their superstars well into their 30s and paying them accordingly until they are perceived to have served their purpose, at which point either another A-list star or one of the most coveted youngsters in world football (an Eder Militao, an Eduardo Camavinga, a Vinicius Junior, a Rodrygo and perhaps imminently, an Aurelien Tchouameni) will usually emerge to replace them.

In an ideal world, Liverpool would do something similar with Salah and Mane, just as Manchester City did with Vincent Kompany, Fernandinho, Yaya Toure, David Silva and Sergio Aguero — and as they will surely do with De Bruyne.

But the reality is that the Merseyside club are more restricted. Not dramatically so, but restricted enough for Salah, Mane and their agents to know there is more to be earned elsewhere, and that presents a problem not just when it comes to retaining talent but also when it comes to competing for the signings that might fill the footsteps of today’s heroes.

To go back to fundamentals, earnings in sport follow a power law distribution – a small number of elite players make a large portion of the money. And the deal with the power law is that it is self-similar – you can cut off the distribution at any arbitrary amount, and what remains to the right is still a power law.

So income in football follows a power law. Income in elite football also follows the same power law. The English Premier League is at the far right end of this, but wages there again follow a power law. If you look at really elite players in the league, again it is a (sort of – since number of data points would have become small by now) power law.

What this means is that if you can define “marginal returns to additional skill”, at this far right end of the distribution it can be massive. For example, the article talks about how Salah has been offered a 50% hike (to make him the best paid Liverpool player ever), but that is still short of what some other (perceptibly less skilled) footballers earn.

So how do you go about getting value while operating in this kind of a market? One approach, that Liverpool seems to be playing, is to go Moneyball. “The marginal cost of getting a slightly superior player is massive, so we will operate not so far out at the right tail”, seems to be their strategy.

This means not breaking the bank for any particular player. It means ruthlessly assessing each player’s costs and benefits and acting accordingly (though sometimes it comes across as acting without emotion). For example, James Milner has just got an extension in his contract, but at lower wages to reflect his marginally decreased efficiency as he gets older.

Some of the other elite clubs (Real Madrid, PSG, Manchester City, etc.), on the other hand, believe that the premium for marginal quality is worth it, and so splurge on the elite players (including keeping them till fairly late in their careers even if it costs a lot). The rationale here is that the differences (to the “next level”) might be small, but these differences are sufficient to outperform compared to their peers (for example, Manchester City has won the league by one point over Liverpool twice in the last four seasons).

(Liverpool’s moneyball approach, of course, means that they try to get these “marginal advantages” in other (cheaper) ways, like employing a throw in coach or neuroscience consultants).

This approach is not without risk, of course. At the far right end of the tail, the variance in output can be rather high. Because the marginal cost of small increases in competence is so high, even if a player slightly underperforms, the effective monetary value of this underperformance is massive – you have paid for insanely elite players to win you everything, but they win you nothing.

And the consequences can be disastrous, as FC Barcelona found out last year.

In any case, the story doing the rounds now is that Barcelona want to hire Salah, but given their financial situation, they can’t afford to buy out his contract at Liverpool. So, they are hoping that he will run down his contract and join them on a free transfer next year. Then again, that’s what they had hoped from Gini Wijnaldum two years ago as well. And he’s ended up at PSG, where (to the best of my knowledge) he doesn’t play much.

Structures of professions and returns to experience

I’ve written here a few times about the concept of “returns to experience“. Basically, in some fields such as finance, the “returns to experience” is rather high. Irrespective of what you have studied or where, how long you have continuously been in the industry and what you have been doing has a bigger impact on your performance than your way of thinking or education.

In other domains, returns to experience is far less. After a few years in the profession, you would have learnt all you had to, and working longer in the job will not necessarily make you better at it. And so you see that the average 15 years experience people are not that much better than the average 10 years experience people, and so you see salaries stagnating as careers progress.

While I have spoken about returns to experience, till date, I hadn’t bothered to figure out why returns to experience is a thing in some, and only some, professions. And then I came across this tweetstorm that seeks to explain it.

Now, normally I have a policy of not reading tweetstorms longer than six tweets, but here it was well worth it.

It draws upon a concept called “cognitive flexibility theory”.

Basically, there are two kinds of professions – well-structured and ill-structured. To quickly summarise the tweetstorm, well-structured professions have the same problems again and again, and there are clear patterns. And in these professions, first principles are good to reason out most things, and solve most problems. And so the way you learn it is by learning concepts and theories and solving a few problems.

In ill-structured domains (eg. business or medicine), the concepts are largely the same but the way the concepts manifest in different cases are vastly different. As a consequence, just knowing the theories or fundamentals is not sufficient in being able to understand most cases, each of which is idiosyncratic.

Instead, study in these professions comes from “studying cases”. Business and medicine schools are classic examples of this. The idea with solving lots of cases is NOT that you can see the same patterns in a new case that you see, but that having seen lots of cases, you might be able to reason HOW to approach a new case that comes your way (and the way you approach it is very likely novel).

Picking up from the tweetstorm once again:

 

It is not hard to see that when the problems are ill-structured or “wicked”, the more the cases you have seen in your life, the better placed you are to attack the problem. Naturally, assuming you continue to learn from each incremental case you see, the returns to experience in such professions is high.

In securities trading, for example, the market takes very many forms, and irrespective of what chartists will tell you, patterns seldom repeat. The concepts are the same, however. Hence, you treat each new trade as a “case” and try to learn from it. So returns to experience are high. And so when I tried to reenter the industry after 5 years away, I found it incredibly hard.

Chess, on the other hand, is well-structured. Yes, alpha zero might come and go, but a lot of the general principles simply remain.

Having read this tweetstorm, gobbled a large glass of wine and written this blogpost (so far), I’ve been thinking about my own profession – data science. My sense is that data science is an ill-structured profession where most practitioners pretend it is well-structured. And this is possibly because a significant proportion of practitioners come from academia.

I keep telling people about my first brush with what can now be called data science – I was asked to build a model to forecast demand for air cargo (2006-7). The said demand being both intermittent (one order every few days for a particular flight) and lumpy (a single order could fill up a flight, for example), it was an incredibly wicked problem.

Having had a rather unique career path in this “industry” I have, over the years, been exposed to a large number of unique “cases”. In 2012, I’d set about trying to identify patterns so that I could “productise” some of my work, but the ill-structured nature of problems I was taking up meant this simply wasn’t forthcoming. And I realise (after having read the above-linked tweetstorm) that I continue to learn from cases, and that I’m a much better data scientist than I was a year back, and much much better than I was two years back.

On the other hand, because data science attracts a lot of people from pure science and engineering (classically well-structured fields), you see a lot of people trying to apply overly academic or textbook approaches to problems that they see. As they try to divine problem patterns that don’t really exist, they fail to recognise novel “cases”. And so they don’t really learn from their experience.

Maybe this is why I keep saying that “in data science, years of experience and competence are not correlated”. However, fundamentally, that ought NOT to be the case.

This is also perhaps why a lot of data scientists, irrespective of their years of experience, continue to remain “junior” in their thinking.

PS: The last few paragraphs apply equally well to quantitative finance and economics as well. They are ill-structured professions that some practitioners (thanks to well-structured backgrounds) assume are well-structured.

Management and Verification

For those of you who are new here, my wife and I used to organise “NED Talks” in our home in Bangalore. The first edition happened in 2015 (organised on a whim), and encouraged by its success, we organised 10 more editions until 2019. We have put up snippets of some talks here.

In the second edition of the NED Talks (February 2015), we had a talk by V Vinay (noted computer scientist, former IISc professor, co-inventor of Simputer, co-founder of Strand Life Sciences, Ati Motors, etc. etc.), where he spoke about “computational complexity”.

Now, having studied computer science, “computational complexity” was not a new topic to me, but one thing that Vinay said has stayed with me – it is that verifying an algorithm is far more efficient than actually executing the algorithm.

To take a simple example, factorising a number into prime factors is NP Hard – in other words, it is a really hard problem. However, verifying the prime factorisation of a number is trivial – you can just multiply the factors and see if it gives back the number you started with.

I was thinking about this paradigm the ohter day when I was thinking about professional managers – several times in life I have wondered “how can this person manage this function when he/she has no experience in that function?”. Maybe it is because I had been subjected to two semesters of workshop in the beginning of my engineering, but I have intuitively assumed that you can only manage stuff that you have personally done – especially if it is a non-trivial / specialist role.

But then – if you think about it, at some level, management is basically about “verification”. To see whether you have done your work properly, I don’t need to precisely know how you have done it. All I need to know is whether you have done bullshit – which means, I don’t need to “replicate your algorithm”. I only need to “verify your algorithm”, which computer science tells us can be an order of magnitude simpler than actually building the algorithm.

The corollary of this is that if you have managed X, you need not be good at X, or actually even have done X. All it shows is that you know how to manage X, which can be an order of magnitude simple than actually doing X.

This also (rather belatedly) explains why I have largely been wary of hiring “pure managers” for my team. Unless they have been hands on at their work, I start wondering if they actually know how to do it, or only know how to manage it (and I’m rather hands on, and only hire hands on people).

And yet another corollary is that if you have spent too long just managing teams, you might have gotten so used to just verifying algorithms that you can’t write algorithms any more.

And yet another before I finish – computer science has a lot of lessons to offer life.

 

Accelerated Cookie Licking

For a few months now, I’ve been reading Hardcore Software, a “sub stack book” that’s being written by Steven Sinofsky, about his time at Microsoft. In one of the “episodes” (the book is literally being written in public chapter by chapter, the same way I would go if I were to write another book), he introduces this spectacular concept called “cookie licking“:

Microsoft developed a vocabulary that to this day dominates discussions between alumni. Cookie licking is when one group would lay claim to innovate in an area by simply pre-emptively announcing (via slides in some deck at some meeting) ownership of an initiative.

Cookie licking is one of those concepts where once you’ve seen it you “can’t unsee”. Now that I’m aware of the concept, I keep finding it all over the place. And thinking about it, it is literally all over the place.

And it can happen in many ways. One way is how it happened at Microsoft – where multiple teams might have “been eligible” to work on a particular project, and one team tries to grab the project by “licking the cookie”. It is a pretty common corporate tactic. “Oh, why do you want to work on it when the XXXX team is already working on it?”.

Then, I also see it happening in the startup space. You go to a potential customer or mentor or investor with a certain idea. And then they tell you “why do you want to work on it when XXXX is already doing it?” (usually XXXX is a larger or better known company, but not always). And many a time you fall for the bait, assume that the cookie has been “jooThaafied”, and try to do something else. In a large number of cases, though, the licker of the cookie would have done nothing to consume it apart from the act of licking itself.

I don’t know how exactly to describe cookie licking from a game theoretic perspective, but I can imagine concepts such as “cheap talk”, “game of chicken”, “option value” and “bluffing” coming into play there. The question is if you will fold or call (yay, I made a poker analogy) when you are shown this licked cookie.

And while I was talking about this wonderful concept with someone earlier this evening, I realised that there also exists this concept that I will call “accelerated cookie licking”. Here, you not only lick the proverbial cookie, but also get paid for doing so.

For this, you need to have an independently built reputation (either a successful corporate career, or an exit from an earlier startup, or having been a VC, or some such). And thanks to this reputation built elsewhere, all you need to do is to say that you are licking the cookie, and people will come forward to pay you to do so.

And once you have licked the cookie and raised money for your company, you have an automatic moat – anyone else who wants to eat the same cookie will be told by any potential investors “why do you want to get into this when <this hifunda person with an independently built reputation> is already doing it, and is so well capitalised? Do you really want to take him on?”.

Thinking about it, in poker terms, this is equivalent to bluffing with a really large raise. Even if the opponent knows you are bluffing, it takes a lot for them to be able to call your bluff. And so it is with “accelerated cookie licking”.

Shopping for girls

Maybe this can be my “international women’s day” post.

We went shopping yesterday, after a very long time. We had to shop for all three of us (wife, daughter and I). And we went to a few large stores in Mantri Mall and ended up shopping in the men’s section, women’s section, girls’ section and boys’ section.

You read that right. We shopped in the boys’ section. And no, we didn’t buy anything for gifting. The reason we shopped in the boys’ section was to buy our daughter nice clothes.

Last week, union minister Smriti Irani made this statement somewhere:

The problem is that even if we as parents want to be progressive and want to bring up our daughter without creating gender biases, the world conspires to reinforce gender biases into her. We find that visiting relatives and friends gift her Barbie dolls. There is “pattern recognition” from things she sees around her (last year she shocked us by saying that it was OK for a boy to hit others but not for a girl). Boys her age are not beyond making sexist comments.

But the biggest reinforcer of childhood gender norms, we’ve seen, are clothes shops, and this is a thing we’ve seen both in the UK and in India.

For some reason, clothes manufacturers have collectively decided that the only thing little girls want to wear is bling – every shirt, and skirt, and pair of shorts, and shoes, inevitably have some frills or some bling attached to them. Beyond a point, as we are shopping, it becomes unbearable to even consider such clothes. And we naturally gravitate towards the boys’ section.

Where, for whatever reason, the selection is far more palatable. No-frill (pun intended) T-shirts and comfortable trousers are conspicuous by their abundance. The design on the printed T-shirts are far better (like last year we got her a T-shirt with the nine (clearly a pre-2005 design) planets on it, which she loves wearing). Shoes are comfortable and you can actually run in them.

At pretty much any given point of time in her entire lifetime, the daughter has owned at least half a dozen pieces of clothing that have been shopped from boys’ sections of clothes shops.

There are limitations, of course – that women’s shirts have buttons on the left means that it is easy to identify “cross-dressing” when it comes to polos and button-down shirts. A lot of boys’ clothes are franchise driven, and not the sort of franchises that my wife or I would endorse (there is an overabundance of Disney stuff, such as Marvel, and not enough heavy metal).

And we were worried that once the daughter learnt to read, she would herself start objecting to wearing clothes bought from boys’ section – thankfully, until now at least, that fear hasn’t borne out. She happily selected clothes from boys’ sections yesterday, and even bought a cute T-shirt that said “King of … “.

I really don’t know when children’s clothes designers and merchandisers realise that girls want nice clothes as well – and not just frills and bling. Until then, as long as the daughter approves that is, we’ll be shopping in the boys’ section.

Jio, Amazon and Information Content

A long long time ago I had installed the Jio Cinema app on my Fire TV Stick. I had perhaps watched two movies on that, and then completely forgotten about it. This evening, I had to look for a movie to watch my the wife, and having exhausted most of the “compatible content” (stuff we can watch together on Netflix) and been exhausted by the user experience on Prime Video, I decided to give this app a try.

I ended up selecting a movie, which I later found out has a 4.5 IMDB rating and doesn’t even have a Wikepedia page. Needless to say, we abandoned the movie midway. That’s when the wife went in to put the daughter to bed and my fun began.

So Jio Cinema follows what I call the “Amazon paradigm for product management”. Since Amazon tries to sell every product (or service) as if it is a physical book, it has one single mantra for product management. “Improve selection and they will come”.

The user experience doesn’t matter. How easy the product is to use, and how pleasing it looks on the eye, and whether it has occasional bugs, is all secondary. All that matters is selection. Given that the company built its business on the back of selling “long tail” books, this is not so surprising, except that it doesn’t necessarily work in other categories.

I’ve written about Amazon’s ineptitude in product management before, in the context of that atrocity of an app called Sony Liv. The funny thing is that the Jio Cinema app (on Fire TV Stick) looks and feels pretty much exactly like Sony Liv. Maybe there is an open source shitty fire TV app that these guys have based themselves on?

In any case, I started browsing the Jio Cinema app, and I found something called “movies in 15 minutes“. Initially I thought it was a parody. The first few movies I noticed there were things I had never heard of. “This is perhaps for bad movies”, I reasoned. I kept scrolling, and more recognisable names popped up.

I decided to watch Deewana, which was released just before the start of my optimal age of movie appreciation, and which, for some reason, we didn’t get home a video cassette of.

It’s basically a collage of scenes from the movie. It’s like someone has put together a “highlights package”, taking all the important scenes and then putting them together.

And for a movie like Deewana it works. The 15 minute version had all the necessary plot elements to fully follow the movie. It is a great movie, for 15 minutes. Maybe at 30 minutes as well it might be a great movie. However, I can’t imagine having watched it in the full version.

That was two hours back. I’ve since gone crazy watching 15 minute versions of many other movies (mostly from the 70s and 80s, though they have movies as recent as Jab We Met). It’s been fantastic.

However, I have one crib. This has to do with information content. Essentially, the premise behind “movies in 15 minutes” is that the information content in these movies is so little that the whole thing can be compressed into 15 minutes.  The problem is that not every movie has the same amount of information.

15 minutes was perfect for Deewana. It was also appropriate for Kasam Paida Karne Waali Ki, which I watched only because it gets referenced in Gangs of Wasseypur. Between these two, I “watched” Namak Halaal, and I didn’t understand the head or tail of it. I had to go to Wikepedia to understand the plot.

Essentially the plot of Namak Halaal is complex enough, I imagine, that compressing it into 15 minutes is impossible without significant information loss. And the loss of information was so much that I couldn’t understand the summary at all. Maybe I’ll watch the movie in full some day.

I’m writing this blogpost after watching the 15 minute version of Don. I guess whoever made the summary realised that the movie is so complex that it can’t really be compressed into 15 minutes – and so they have added a voiceover to narrate the key elements.

In any case, I’m feeling super thrilled. I normally don’t watch movies because the bit rate in most movies is too low. Compression means that I can happily watch the movies without ever getting bored.

I wish they made these 15 minute versions of all movies. Jio, all (your Amazon-style product maangement) is forgiven.

Now on to Amar Akbar Anthony.

Signalling quality on Instagram ads

I have mentioned multiple times here before that I love Instagram advertising. I love that whatever Instagram learns from my likes (and not likes) on the platform, and through the various pixels that Facebook leaves all over the interwebs, gets used in showing me highly relevant advertising.

Rather, ever since I started using Instagram, I loved the advertising for its visual quality (that made it hard to distinguish if it was an advertisement or native content), and as things have gotten more relevant over time, I’ve started clicking through. And as I’ve started clicking occasionally, the advertising has become more relevant.

I’m sure some silicon valley marketer has some imagery about flywheels. I’m reminded of that hamster spinning this wheel when I’d gone to this animal farm near Bangalore last year.

In any case, I read this article about “the hard thing about easy things“. The basic theory, if I understand it right, is that by commoditising all the tools of production when it comes to direct to consumer selling, the business of direct to consumer selling has gotten that much harder.

The article goes on to say that unless the brand has a competitive advantage in manufacturing (or sourcing by any other means), it is pretty much impossible to make money off direct to consumer products – you struggle to repel the attack of the clones, and you have to spend increasing amounts of money on online marketing (through Google and Facebook).

While this makes sense (or not?) from an investment and entrepreneurship perspective, it got me wondering – as a consumer, how can I distinguish the quality direct to consumer products from those that have somehow simply managed to get into my feed?

Some advertising is like a peacock’s tail – it doesn’t signal any direct value about the brand being advertised. However, it signals that if the brand can afford to spend such huge amounts of money on this form of advertising, it ought to be a brand with sufficient spare cash flow that it is a good brand.

For example, when Vivo got title sponsorship of the IPL, it not only created awareness (which possibly existed thanks to its retail stores and advertising on Amazon) but also signalled that it is a “good brand” since it had bought prime advertising real estate.

Similarly, when a brand advertises on the SuperBowl, the actual dollars per eyeball may not make sense. However, when you add in the signalling value of having been there on SuperBowl (“if a brand can afford to advertise on SuperbOwl, it ought to be a good brand”), it starts making sense.

This works with a lot of mass media advertising. Front page of Times of India is premium because of peacock’s tail. Advertising in the IPL for the same reason. Perhaps similar with hoardings on the way out of airports. And booking prime time slots on popular television shows.

The problem with online advertising is that it is so targeted (and algorithmic) that this signalling effect goes away. Your instagram feed is like the Times of India where every page is similar to every other page.

From that perspective, it is hard to determine whether an advertisement represents a quality product when it appears on your Instagram timeline.

I bought Vahdam tea after someone recommended it to me on Twitter. I bought Paul and Mike’s chocolates after a friend wrote her appreciation for it on Instagram. When I started buying Blue Tokai coffee, I needed good coffee powder and was in the mood for exploration, but was helped by multiple friends and acquaintances vouching for it .

Marketing solely using digital means runs into this problem of not having the signalling effect. And that means you need to invest in “social” also, however you can imagine that to be. Then again, people have started seeing through “influencers”, like how they started seeing through “endorsements” a generation ago.

Unbundling news and advertising

I’ve written earlier about how once news media became dependent on subscriptions, it started becoming partisan. Thinking about it, it is not particularly correct.

If we think of the traditional (physical) newspaper, it was seldom given away for free (when I lived in London I would pick up free copies of the Evening Standard on days when I needed to line my compost bin). Traditional newspapers relied (and still do) on a combination of subscription and advertising for their revenues.

In that sense, what the New York Times does now (read this nice interview with its outgoing CEO) is basically a digital transformation of what it has been doing for over a hundred years – make money off a combination of subscription and advertising.

So if the business model was the same, why did the online New York Times differ from its previous avatar and become politically partisan? Because the nature of advertising changed.

Nowadays I have this favourite theory that everything is a bundle (maybe I should write my next book about this?).

You can consider this post to belong to this meme.

The traditional newspaper, if you think about it, was a collection of news and advertisements all bundled together. While you could choose what part of the paper you wanted to consume, when you went to a page you would inevitably scan all the headlines. And whether you liked them or not, you would actually eyeball all the advertisements.

The important thing to note is that the paper was a physical product and what advertisement the reader was shown did not depend on that person at all. Whether you were a raving communist or a slaveholder, you would be shown the same set of advertisements.

This meant that physical newspaper advertisements were (and still are) dominated by mass products that were aimed at everyone. And since these advertisements were usually paid for based on an estimate (sometimes highly inaccurate) of how many people saw them, the newspapers wanted to maximise the eyeballs. This meant not taking any extreme political stances, and keeping all parts of the political spectrum onside.

What changed with the move to digital was that this bundle containing the news and the advertisements broke down.

With advertising being sold through data-driven ad exchanges, it was now possible to show different advertisements to different people. And with advertisements now dependent on your search and browsing history (apart from your political preferences), it was effectively personalised. The New York Times did not need to directly sell advertising any more. All they needed to do was to sign a contract with Google or Facebook or both. Job done.

Digital advertising doesn’t make sense for mass brands. Rather, it is highly likely that the availability of data will mean that they will frequently get outbid by highly targeted brands. So whether mass brands wanted to advertise in the New York Times became a less important decision. The paper had no compulsion to be politically neutral any more.

And once their early set of subscribers showed a marked preference for one kind of politics, it made sense to them to go after the subscription dollars of this audience rather than the already uncertain dollars of potential subscribers that preferred another kind of politics. And then there as a self-reinforcement cycle.

Media can crib as much as they want about the likes of Google and Facebook taking away their money. They can lobby, like they have done in Australia, to “levy a google tax“. People can crib about media having become biased.

However, we need to remember that all this mess started with the unmaking of a bundle – once news and advertising had been separated, there was no turning back.

Amazon and brand-building

Sometimes shopping on Amazon feels like shopping in Burma Bazaar or National Market or any of those (literally) underground “shopping malls” where you get cheap imported stuff of uncertain quality. This is especially true when shopping for things like children’s toys and some electronics, where you don’t have too many established brands.

The only times I feel completely comfortable shopping on Amazon is when I’m buying known brands – like last month when I bought a LG monitor or Logitech keyboard and mouse. LG and Logitech have built their brands sufficiently outside of the Amazon ecosystem that I trust their quality even while buying on Amazon.

This is not the case when it comes to other categories, though. One day I was browsing for toys on Amazon and was simply unable to decide what to buy – it all looked so “cheap”. Finally, my wife noticed one brand of which we already had a toy (that we liked), and we ended up buying that (that was a sound decision). Once again, we had used our knowledge of brands that had build their brands outside of Amazon to make our decision.

The thing with Amazon is that it is an “everything store” – one store to serve all markets. That’s not how offline markets work. In offline markets, stores fairly easily differentiate themselves based on the markets that they serve – by their locations, by their price points, by the overall “look and feel” and so on. That way, when you go to a store that you know serves your segment, you can be confident that what the store sells you is what you’re looking for.

This is not the case with Amazon. Since one store serves all, it is very difficult to know upon seeing a product whether it is “made for you”. Well, Amazon has information about your previous purchases on the platform, which should give them a good idea of the “segment” you belong to, but I guess making money from advertisers on the platform trumps making your choice easier?

From this perspective, if you are a hitherto unknown brand trying to sell on Amazon, it makes sense for you to build your brand elsewhere. Here, we run into the “double cost problem” (that I had used to describe long ago why Grofers is not a sustainable business). Essentially, building a brand is expensive and once you’ve spend your dollars on (let’s say) the Facebook ecosystem to build your brand, does it make sense to also pay Amazon to push up your product when it comes to search?

It seems like brands are now choosing one way or the other. Mass market brands (it appears) are sticking to the Amazon ecosystem. Some premium brands are using Instagram to acquire customers, and then using the Shopify-Razorpay-Delhivery ecosystem to deliver. Some other premium brands are using a combination of Instagram and Amazon, but only using the latter as a fulfilment mechanism – not spending money to advertise there.

In any case, it seems to me that building brands on Amazon is not a viable business. Now I’m reminded of my other old post where I talk about how platforms are useful only if they aggregate unreliable supply. And this is a path that Amazon seems to have firmly taken.

And the moment you focus on branding, you are trying to send out the message that you are not “unreliable supply”. And this means that getting mixed up with other unreliable suppliers is not good for your business. Which is why you find that the direct to consumer brands that advertise on Instagram (have I told you I love instagram ads?) usually stay away from Amazon.

(you might think I’m going round and round in circles in this post. This is because it’s been about a month since I thought of writing this but only got down to it today. It’s also funny that I’m writing  this less than an hour after talking to someone who builds her brand on Instagram and then sells through Amazon (and offline shops) ).

PS: I got reminded of when I initially thought of this post. I bought a yoga mat from Amazon a couple of months ago. Quality turned out to be pathetic. And there was no way for me to know that when I was buying.

TV Bundling

This is yet another blogpost to expand on a tweet I wrote yesterday.

Just to remind you, Suprio Guha Thakurta (former Chief Strategy Officer at The Economist) and I have started The Paper, a 4-days a week newsletter that goes in (some) depth into one business story from India each day. We rely purely on “secondary reporting” (collating from news items), to which we add our own commentary.

Subscribe here.

Last week we wrote about a new TRAI order about bundling of TV channels. Essentially the telecom (and broadcast) regulator in India has gone to great lengths to ensure that TV channels don’t get bundled in a way that makes it difficult for the customer to choose.

While the effect of this bundling order might be uncertain, one question needs to be asked to TRAI – why are they only concerned about bundling at one level (across channels) and not at the television channel level itself?

After all, television channels are also bundles.

For a fixed fee a month (and a willingness to see a certain proportion of paid content), subscription to a television channel gives you the opportunity to watch any of the programming that the channel offers. Let’s take a sports channel, for example (IMHO, live sports is the only reason you need cable TV. Everything else can be streamed).

Let’s say there is one Sony channel that offers live coverage of UEFA Champions League, NBA and cricket played in England (I know all these are part of the Sony bouquet, though I don’t know if they are regularly broadcast on the same or different channels here. Let’s assume there is one channel that shows all three).

Assume that I’m only interested in the football, but not in either NBA or cricket played in England. In order to watch my football, I’m forced to buy subscription to the entire TV channel (and thus pay for the cricket and basketball as well). Why am I being forced to do this?

Take any channel, and the outcome is going to be similar. You will subscribe to the channel only because you want to watch a few programs, but you are forced to pay for everything. Is this fair?

Let’s move beyond televisions. Consider the Times of India. I’m mainly interested in the local news and the bridge column (OK, my daughter has taken a liking for the cartoon page as well). Still I need to pay for the whole paper. Is that fair?

Essentially, bundling exists everywhere. And it is going to be incredibly hard to regulate it away. TRAI wants to reduce one kind of bundling (across channels), but its regulation seems  blind to in-channel bundling. Essentially it is impossible to regulate against in-channel bundling as well.

And in any case, there are clear benefits to customers from bundling, the most important of which is the elimination of “mental cost”. If some day I suddenly want to watch NBA, it’s already there on the Sony channel I’ve paid for, and I don’t need to rush that moment to try and buy subscription.

Yes, pay per view exists in certain markets, and it can be profitably offered for certain kinds of premium events whose viewership is so uncorrelated with viewership of other events that bundling is nigh impossible.

Also, isn’t your spouse or partner also a bundle? To quote Esther Perel:

Today, we turn to one person to provide what an entire village once did: a sense of grounding, meaning, and continuity. At the same time, we expect our committed relationships to be romantic as well as emotionally and sexually fulfilling. Is it any wonder that so many relationships crumble under the weight of it all?

I leave you with her TED TAlk.