Reliance Jio Tariffs Seem Stupid

For the longest time I used a post-paid mobile phone. The hassle of recharging regularly, combined with the attractive rates available on post-paid “corporate” plans, meant that right from the time I graduated business school (in 2006) till I moved to England in 2017, I almost wholly used postpaid phones.

And then in England, I got a prepaid sim upon landing, and then soon discovered that it wasn’t more expensive than a postpaid (and there was no paperwork), and I kept the prepaid. Upon returning to India earlier this year, I’ve continued with a prepaid phone, with a Reliance Jio number. A few months back, I took an annual plan with Jio, paying for a year what I used to pay Airtel in less than two months before I moved out of India.

One of the reasons I don’t really mind having a pre-paid now is that it is far less of a hassle than postpaid. I have a 12 month program, for which I paid once, and until next May I don’t need to worry at all. There is one less bill to be paid each month.

And one thing that makes this “hassle-free” is that I don’t need to check my usage at all, either in terms of voice and data. It is a nicely bundled plan, with zero marginal cost for either calling or using data (the latter up to a (very high) limit). When there is a per-call charge, the balance notification at the end of each call places a mental cost (even if it is a low marginal cost), and you sometimes wonder if you need to call at all, or when you need to recharge.

The “current” zero marginal cost plan by Jio (I had a similar plan from EE in the UK) means that there is no such mental cost, and you can treat your prepaid mobile like you used to a postpaid.

Now things are changing. There are regulatory issues in India – on the “inter connection charge”. When a Jio customer calls an Airtel customer, Jio has to pay Airtel 6 paise per minute for Airtel’s service of completing the call on its network. This was earlier 14 paise a minute, which came down to 6 thanks to Jio’s lobbying, and was supposed to go away entirely in 2020.

When the entire market has settled on a zero marginal cost plan, like it is the case in the UK, inter connection charges don’t really matter. In India, however, there is massive asymmetry. People on older plans from Airtel and Vodafone still pay a lot for their calls, so they don’t mind paying a high interconnection charge, and want to receive a high inter-connection charge.

So over the last couple of months you’ve had massive lobbying, and hilarious exchanges like the debate among the major telcos regarding “missed calls” and how long the phone should ring.

Anyway, it appears that the inter connection charges won’t go away next year as planned. Jio is not happy. And in order to show its spite, it has decided to start charging for calling. A marginal charge of 6 paise a minute is going to be applied on Jio customers calling non-Jio phones.

I don’t see how this is going to be good for the Jio customer (I’m protected since I’d bought a long term plan earlier this year). The mental cost of calling comes back. You need to start worrying about what network the person receiving your call uses. You start getting that balance notification at the end of your call. You might need to recharge before your validity is over, creating more mental cost.

In other words, it seems like a rather dumb move by Jio. While it has clearly been taken to show that the operator is pissed off with the competition and the regulators, it is likely to hurt Ji0’s own business and drive its customers to the competition.

There were several smarter ways to handle this. Basically the problem is that Jio’s costs aren’t coming down as expected, so it needs to charge more. And there are several ways of charging more without imposing a mental cost.

One, the price point itself can be increased. Instead of Rs. 150 a month, it can charge Rs. 160. Second, instead of “unlimited free calls”, they can offer “1000 minutes of free calling per month” or something like that, with a different plan offering 2000 minutes of free calling per month. And so on.

But no. Reliance is more interested in making a statement than serving its own customers. And so it comes up with hare-brained schemes like charging per call “outside the network”. It will be interesting to see how their growth goes like over the next few months.

Dunzo and Urbanclap

I realise that Dunzo and Urbanclap (and many other apps) grew in a particular way. Initially they weren’t sure of the exact problem that they were solving, and instead focussed on a particular “problem class”.

And then over time, based on pattern recognition and segmentation/cluster analysis of the kind of problems that people were using these apps to solve, they started providing more targeted solutions that made better business sense.

Dunzo started off as a “we’ll do anything for you” app. People making fun of the company would talk about a Dunzo executive who would come home, collect your bean bag, get the beans refilled and bring it back to you, and only charge for the beans.

I’m pretty sure that there were many other such weird use cases in which people sort of abused Dunzo in its early days. However, most of the users of the app, I’m guessing, used it for sending packages across town, and to fetch stuff for them from shops and restaurants. And now, four years down the line, Dunzo highlights these specific streamlined use cases in the app, and has figured out a good way of charging for each of them.

It’s similar with Urbanclap. While I didn’t use them in the early days, I used their competitor HouseJoy. I used the app to request for “a plumber”. A plumber duly arrived and did all sorts of odd jobs in our apartment building, some of which were dangerous. And then at the end we paid him in cash, and he told us that “if someone from the app calls, tell them you paid me only 200 rupees” (we had paid him 2000).

Soon, after being a marketplace for all sorts of odd jobs, Urbanclap and its ilk noticed patterns and started specific services. So last week we got someone from Urbanclap to “repair our water heater” (this had a fixed fee on the app). It is another set of such specific services that UrbanClap offers.

I may not have said much new in this post, but it’s basically a crystallisation of some of my thoughts of late – sometimes it’s okay to not have a particularly precise business plan as long as you know what problem class you’re tackling. If you manage to get funded and are willing to burn money, you can learn the best set of problems from the market (within your identified class).

It’s an expensive process for sure, since until you figure this out you’ll be spending a lot of time and money doing random shit, but if you and your investors are willing to bear this kind of expense, it might be worth it.

The worst thing that can happen to you, though, is that after you’ve burnt your company’s money in learning about the market’s precise problem statement, another well-capitalised firm moves faster than you to address this specific market. The question is how well you can put to use your learnings from the early period for later on.

Instagram targeting

Instagram is really good at what I call “one dimensional psychographic targeting”.

Essentially, based on the photos and videos (more likely hashtags) that you see, spend time on, like and comment, the platform figures out some of your interests and targets at you advertisements of products that serve these interests. And instagram manages to combine this with demographic information (where you live, etc.) to target advertisements better at you.

For example, of late I’ve been looking at a lot of weightlifting stuff on Instagram – I follow most of the coaches at my gym, and a few other handles that post fitness stuff. I’ve even posted a video of myself deadlifting.

As a result, Instagram has been following me with advertisements related to fitness, and the combination with demographics means I’m being served stuff I can get in Bangalore. For example, last two days I’ve been seeing ads of my own gym (!!). There are ads for whey proteins and healthy foods of all kinds as well.

This targeting is not perfect – for the last few months, ever since I returned to India, I’ve been bombarded on Instagram with advertisements asking me to emigrate to Canada (I don’t know what makes it think I want to move abroad again given I’ve just moved back home). The seemingly un-targeted mattress advertisements are everywhere. The shirt advertisements as well (though recently I uploaded a picture of my wardrobe on Instagram).

Nevertheless, this is a massive step up from what marketers were able to do a generation ago, where they could at best target based on a demographic. Marketers might have created elaborate psychographic or behavioural profiles of their target audiences, but when it came to advertising, the media available (newspaper, television and outdoors) meant that they had to collapse it into a demographic profile.

Instagram is not perfect, though. To the best of my knowledge, it can only target me on one “psychographic dimension” (“interested in weight lifting”, “interested in coloured chinos”, “likes Bangalore”) along with a multitude of demographic dimensions (I’m sure it’s figured out my gender, age group and maybe even caste, even if it exists in some vector somewhere and no human knows these classifications).

However, when you have created elaborate psychographic profiles, collapsing them into one dimension is still a simplification process. And so you get a reasonable degree of error in targeting. So I’m wondering what can be done that can enable advertisers to target me with more specific products that I might be interested in.

Finally, really how much are the likes of Charles Tyrwhitt, and some mattress brand whose name I don’t recall, willing to pay for their campaigns, given that their untargeted campaigns have beaten the highly targeted campaigns of the fitness guys and coffee companies to reach my eyeballs?

Margaret Atwood doesn’t escape my fate

My book released exactly two years ago (if you haven’t read it yet, you can buy it here). Rather, it was supposed to release two years ago, on 6th of September 2017. As it happened, people who had pre-ordered the book got deliveries a few days early. Amazon had messed up with the release date.

I remember getting in touch with Amazon Customer Care. They didn’t seem to care. I spoke to friends and relatives who worked there, and they suggested a “Jeff B escalation” (an email sent to Jeff Bezos – apparently he reads them). There was no response to that either. And so my book came out in a trickle, being sent to people as they ordered them, rather than with a bang.

I’m possibly feeling a sense of schadenfreude that it’s not just first-time authors like me who got screwed over like this by Amazon in terms of early release of the book. I am in illustrious company – Canadian author Margaret Atwood suffered the same fate this week.

Amazon, the biggest book vendor in the United States, recently started shipping preorders of Margaret Atwood’s book Testaments. The problem, notably, is that Atwood’s book is not supposed to launch until Tuesday, September 10. Amazon is violating the embargo that all sellers of the book have agreed to. And its indie bookselling rivals are pissed.

In my case, Amazon had exclusive sales on the book – thanks to using a small first-time publisher, we didn’t have the network to go wider and get the book into more stores. In that sense, apart from me, there was possibly nobody pissed off at the early release of the book.

Then again, this early release of pre-ordered books was an endemic problem to Amazon, and a high-profile leak such as this one was bound to happen some time or the other. Hopefully this will lead to the retailer to put enough measures in place to prevent this kind of thing from happening again (mainstream publishers have strong relationships with bookshops, so they are likely to put pressure on Amazon).

In any case, I’m glad to have such good company!

PS: If you haven’t listened to Atwood’s conversation with Tyler Cowen, you should do so soon. It’s fantastic (and I say this as someone who hasn’t read any of her works)

Amazon and Sony Liv

Amazon is pretty bad at design of products they’re not pioneers in. They’ve built a great shopping engine (25 years ago) and a great cloud service (15 years ago), but these were both things they were pioneers in.

Amazon being Amazon, however, they have a compulsive need to be in pretty much every industry, and so they’ve launched clones of lots of other businesses. However, their product design in these is far from optimal, and the user experience is generally very underwhelming.

Prime Video has a worse user experience than Netflix. The search function is much worse. The machine learning (for recommendations) isn’t great. The X-ray is good, but overall I don’t have as pleasant a time watching Prime as I do with Netflix.

However, the degree to which Prime Video is worse than Netflix is far far smaller than the degree to which Amazon Music is worse than Spotify. The only thing going for Amazon Music (which I only use because it comes free with my prime delivery membership in India) is that they have inventory.

Spotify in India has been unable to secure rights to a lot of classic rock and metal bands, such as Iron Maiden and Black Sabbath and Led Zeppelin and Dream Theater. And these form a heavy part of my routine listening. And so I’m forced to use Amazon Music (Apple Music has these bands as well, but I have to pay extra for that).

The product (Amazon Music) is atrocious. The learning is next to nothing. After five months of using the service to exclusively listen to Classic Rock and Heavy Metal, and zero Indian music, the home page still recommends to me Bollywood, Punjabi and Tamil stuff! History is not properly maintained. Getting to the album or playlist (the less said about playlists on Amazon, the better) I want takes way too much more effort than it does on Spotify.

In other words, the only thing that keeps Amazon going in businesses they’re not pioneers in is inventory – Prime Video works because it has movies and shows other streaming services don’t have. Amazon Music is used because it has music that Spotify doesn’t.

I figured it is a similar case with Sony Liv, Sony’s streaming service in India. They sit on a bunch of lucrative monopolies, such as rights to broadcasting Test cricket in a lot of countries (all three Test series being played right now are on Sony, for example), Champions League football and so on. Beyond that it’s an atrocity to watch them.

I remember missing a goal in the Liverpool-Porto Champions League quarterfinal because of a temporary power cut. There was no way in the broadcast to go back and see the goal. If I by mistake pause for a couple of seconds, I’m forever behind “live” (unless I refresh). Yesterday during the classic Ashes Test, the app simply gave up when I tried to load the game.

The product is atrocious (actually more atrocious than Amazon Music), but people are forced to use it only because they have a monopoly on content. And in that way, it is similar to Amazon, which can get away with atrocious products only because they have the inventory!

I’m glad the Premier League is on Hotstar, which is mostly a pleasure to watch! (actually back in the day when I had cable TV, the star sports bouquet had significantly superior production values to the sony-zee-ten bouquet)

The Indian Second Wave

Most obituaries will describe the just-deceased VG Siddhartha as a businessman, a “coffee tycoon” and as the son-in-law of a prominent politician. However, the way I see it, he was no less than a cultural icon, and with one business, dramatically changed Indian culture in two ways.

In 1996, Siddhartha started India’s first cyber cafe, which was one of the few cyber cafes that was actually a cafe. A coffee wholesale exporter, he got into the retail business with the first outlet of Cafe Coffee Day (CCD) on Bangalore’s busy Brigade Road. For fees, you could sit there to browse the internet while sipping on espresso and cappuccino, drinks hitherto unknown to Bangalore’s (already established) coffee culture.

Soon enough he was to exit the cyber side of the business, as his retail chain’s expansion focussed on coffee, and dedicated “cyber cafes” (they were still called that) that enabled people to browse the internet for a fee mushroomed across the country. Nevertheless, we should give him credit for giving birth to an idea that enabled the first generation of Indians to truly access the internet before broadband became a thing.

The first time I interacted with his business was in 1998, when I visited the aforementioned Brigade Road CCD. For a conservative 15-year-old from South Bangalore, it was a bit of a sticker shock, with espresso priced at Rs. 10 and cappuccino at Rs. 20. There were iced drinks on the menu as well, but they were more expensive.

I don’t think I quite liked the espresso (we all ordered that that day, given the prices), but it was a new experience of consuming coffee. As I grew up and came into more money I would patronise CCD much more often.

There was an outlet on the IIMB campus, and that became the default location for any campus “treats”. I clearly remember the cold drinks – tropical iceberg and cold sparkle – being priced at Rs. 32 back in 2004. Prices went up over time but these drinks remain my favourite cold drinks at CCD to this day.

Over the last 10 years, CCD has mostly served as a meeting room for me. When I moved into my current house 5 years ago, I used a CCD that was 300 metres away to entertain any visitors (this outlet closed recently, but a flyer in today’s newspaper informs me that an “experience centre” is coming up closer by).

Whenever I have had to meet someone and we’ve had to find a place to meet, by default we have looked for CCD outlets. And we continue to do so – while Starbucks and the artisanal “Aussie-style” coffee shops (such as Third Wave or Blue Tokai) might be preferable, CCD’s sheer density has meant that it is India’s default meeting room.

Sometimes we under-appreciate the impact that CCD has had in Indian culture. It was perhaps the first large chain of “neutral venues”, where people could meet and hang out for a long time without being pestered by the waiters. I mentioned that I have been using the chain as a meeting room for a few years now. While that might be its primary use, you also find college kids who have saved up a bit on their pocket money hanging out there. My first date with my wife also took place partly at a CCD.

And then there are the loos. CCD has also completely altered the face of highways in India by offering clean loos at its outlets, making it far easier for women to travel.

The chain may not be doing that well – it seems like its financial troubles led to Siddhartha killing himself. However, given that it is a publicly traded company, we can trust the market to resolve its issues so that it continues.

And even if it fails and has to shut shop in due course, what CCD has done is to show that there is a viable market in India for a coffee shop that sells decent (but not great) coffee, where people can sit around and linger and do their business, whatever that may be.

In that way, Siddhartha’s legacy will endure.

 

Gamification and finite and infinite games

Ok here I’m integrating a few concepts that I learnt via Venkatesh Guru Rao. The first is that of Finite and Infinite games, a classic if hard to read book written by philosopher James Carse (which I initially discovered thanks to his Breaking Smart Season 1 compilation). The second is of “playflow”, which again I discovered through a recent edition of his newsletter.

A lot of companies try to “gamify” the experiences for their employees in order to make work more fun, and to possibly make them more efficient.

For example, sales organisations offer complicated incentives (one of my historically favourite work assignments has been to help a large client optimise these incentives). These incentives are offered at multiple “slabs”, and used to drive multiple objectives (customer acquisition, retention, cross-sell, etc.). And by offering employees incentives for achieving some combination of these objectives, the experience is being “gamified”. It’s like the employee is gaining points by achieving each of these objectives, and the points together lead to some “reward”.

This is just one example. There are several other ways in which organisations try to gamify the experience for their employees. All of them involve some sort of award of “points” for things that people do, and then a combination of points leading to some “reward”.

The problem with gamification is that the games organisations design are usually finite games. “Sell 10 more widgets in the next month”. “Limit your emails to a maximum of 200 words in the next fifteen days”. “Visit at least one client each day”. And so on.

Running an organisation, however, is an infinite game. At the basic level, the objective of an organisation is to remain a going concern, and keep on running. Growth and dividends and shareholder returns are secondary to that – if the organisation is not a going concern, none of that matters.

And there is the contradiction – the organisation is fundamentally playing an infinite game. The employees, thanks to the gamified experience, are playing finite games. And they aren’t always compatible.

Of course, there are situations where finite games can be designed in a way that their objectives align with the objectives of the overarching infinite game. This, however, is not always possible. Hence, gamification is not always a good strategy for organisations.

Organisations have figured out the solution to this, of course. There is a simple way to make employees play the same infinite game as the organisation – by offering employees equity in the company. Except that employees have the option of converting that to a finite game by selling the said equity.

Whoever said incentive alignment is an easy task..

 

Housewife Careers

This is something I’ve been wanting to write about for a very long time, but have kept putting it off. The ultimate trigger for writing this is this article about women with children in Amazon asking for backup child care at work. Since this hits rather close home, this is a good enough trigger to write.

Quoting the article:

“Everyone wants to act really tough and pretend they don’t have human needs,” says Kristi Coulter, who worked in various roles at Amazon for almost 12 years and observed that many senior executives had stay-at-home wives.

(emphasis mine)

While this might be true of Amazon (though not necessarily for other large tech companies), it is true for other careers as well. The nature of the job means that it is impossible to function if you even have partial child-care responsibilities. And that implies that the only way you can do this job is if you have a spouse whose full time job is bringing up the kids.

Without loss of generality (considering that in most cases it’s the women who give up their careers for child-rearing), we can call these jobs “housewife jobs”.

Housewife jobs are jobs where you can do a good job if an only if you have a spouse who spends all her time taking care of the kids. 

The main feature (I would say it is a bug, but whatever) of such a job is usually long work hours that require you to “overlap both ways” – both leave home early in the morning and return late every night, implying that even if you have to drop your kid to day care, it is your spouse who has to do so. And as I’ve found from personal experience, it is simply not possible to work profitably when you have both child-dropping and child-picking-up duties on a single day (unless you have zero commute, like I’ve had for the last eight months).

Housewife jobs also involve lots of travel. Whether it is overnight or not doesn’t matter, since you are likely to be away early mornings and late evenings at least, and this means (once again) that the spouse has to pick up the slack.

Housewife jobs also involve a lot of pressure, which means that even when you are done with work and want to relax with the kids, you are unable to take your mind off work. So it turns out to be rather unprofitable time with the kids – so you might as well spend that working. Which again means the spouse picks up the slack.

Sometimes a job may not be inherently stressful or require long hours, but might be housewife because the company is led by a bunch of people with housewives (the article linked above claims this about Amazon). What this means is that when there is a sufficient number of (mostly) men in senior management who have housewives taking care of kids, their way of working percolates through the culture of the organisation.

These organisations are more likely to demand “facetime” (not the Apple variety). They are more likely to value input more than output (thus privileging fighter work?). And soon people without housewives get crowded out of such organisations, making it even more housewife organisations.

Finally, you may argue that I’ve used UK-style nurseries as the dominant child care mechanism in my post (these usually run 8-6), and that it might be possible to hedge the situations completely with 24/7 nannies or Singapore-style “helpers”. Now, even with full time child care, there are some emergencies that occur from time to time which require the presence of at least one parent. And it can’t be the same parent providing that presence all the time. So if one of the parents is in a “housewife job”, things don’t really work out.

I guess it is not hard to work out a list of jobs or sectors which are inherently “housewife”. Look at where people quit once they have kids. Look at where people quit once they get married. Look at jobs that are staffed by rolling legions of fresh graduates (if you don’t have a kid, you don’t need a housewife).

The scary realisation I’m coming to is that most jobs are housewife jobs, and it is really not easy being a DI(>=1)K household.

Tigers and Bullwhips

Over three years ago, well before our daughter was born, my wife’s cousin had told us that she likes to watch her daughter’s TV shows because they contained “morals”, which were often useful to her at work. While we never took to the “moral” TV show she mentioned (Daniel Tiger – it is bloody boring), I have begun to notice that there are important management lessons in other popular children’s stories.

So I hereby begin this blog series on what I call the “Kiddie MBA” – basically business lessons from kids’s stories. And we will start with that all-time classic, The Tiger Who Came To Tea, by Judith Kerr. 

The basic premise of this story that remains a classic fifty years after being published is what operations managers call the “bullwhip effect“. Sometimes a business, possibly in trading, can be subject to a sudden demand, which the business will not be able to fulfil given its current inventories.

As a result of this sudden one-time spurt in demand, the business increases its future forecasts of demand, and starts keeping more inventory. This business’s supplier sees this increased demand and increases its own forecasts upward, and increases its own inventory. Thus, this one-time demand “shock” percolates up the supply chain, giving the illusion of higher demand and with each layer in the chain keeping higher and higher inventory.

And then one day the retailer will realise that this demand shock is not replicable and moves forecasts downwards, and this triggers a downward edge in the forecasts up the value chain, and demand at the source comes crashing down.

Being a children’s book, The Tiger Who Came To Tea eschews the complexity of the supply chain and instead keeps the story at one level – at the level of the household of the protagonist Sophie (not to be confused with Sophie the Giraffe).

The premise of the story is the demand shock for supplies in Sophie’s home – a tiger comes home for tea and eats up everything that’s at home, drinks up all that’s there to be drunk (including “all the water in the tap”) and leaves, leaving nothing for Sophie and her family.

Assuming that the tiger will return the next day, Sophie’s family stocks up heavily, including “lots of tiger food”. And the tiger never arrives.

My guess is that the rest of the supply chain is left as an exercise to the reader – how the retailer who sold Sophie the tiger food will react to the suddenly higher demand for food (and for tiger food), how this retailer’s supplier will react, whether the tiger visits some other household for tea the next day (making this demand “regular” at the retailer’s level), and so forth.

Perhaps this is what makes this such as great book, and an all-time classic!

Just Plot It

One of my favourite work stories is from this job I did a long time ago. The task given to me was demand forecasting, and the variable I needed to forecast was so “micro” (this intersection that intersection the other) that forecasting was an absolute nightmare.

A side effect of this has been that I find it impossible to believe that it’s possible to forecast anything at all. Several (reasonably successful) forecasting assignments later, I still dread it when the client tells me that the project in question involves forecasting.

Another side effect is that the utter failure of standard textbook methods in that monster forecasting exercise all those years ago means that I find it impossible to believe that textbook methods work with “real life data”. Textbooks and college assignments are filled with problems that when “twisted” in a particular way easily unravel, like a well-tied tie knot. Industry data and problems are never as clean, and elegance doesn’t always work.

Anyway, coming back to the problem at hand, I had struggled for several months with this monster forecasting problem. Most of this time, I had been using one programming language that everyone else in the company used. The code was simultaneously being applied to lots of different sub-problems, so through the months of struggle I had never bothered to really “look at” the data.

I must have told this story before, when I spoke about why “data scientists” should learn MS Excel. For what I did next was to load the data onto a spreadsheet and start looking at it. And “looking at it” involved graphing it. And the solution, or the lack of it, lay right before my eyes. The data was so damn random that it was a wonder that anything had been forecast at all.

It was also a wonder that the people who had built the larger model (into which my forecasting piece was to plug in) had assumed that this data would be forecast-able at all (I mentioned this to the people who had built the model, and we’ll leave that story for another occasion).

In any case, looking at the data, by putting it in a visualisation, completely changed my perspective on how the problem needed to be tackled. And this has been a learning I haven’t let go of since – the first thing I do when presented with data is to graph it out, and visually inspect it. Any statistics (and any forecasting for sure) comes after that.

Yet, I find that a lot of people simply fail to appreciate the benefits of graphing. That it is not intuitive to do with most programming languages doesn’t help. Incredibly, even Python, a favoured tool of a lot of “data scientists”, doesn’t make graphing easy. Last year when I was forced to use it, I found that it was virtually impossible to create a PDF with lots of graphs – something that I do as a matter of routine when working on R (I subsequently figured out a (rather inelegant) hack the next time I was forced to use Python).

Maybe when you work on data that doesn’t have meaningful variables – such as images, for example – graphing doesn’t help (since a variable on its own has little information). But when the data remotely has some meaning – sales or production or clicks or words, graphing can be of immense help, and can give you massive insight on how to develop your model!

So go ahead, and plot it. And I won’t mind if you fail to thank me later!