A trip to the supermarket

Normally even I wouldn’t write about a trip to a supermarket, but these aren’t normal times. With the shutdown scheduled to go on for another two weeks, and with some “essential commodities” emptying, I decided to go stock up.

I might just have postponed my trip by a few more days, but then I saw tweets by the top cop of Bangalore saying they’re starting to seize personal vehicles out on the road during the lockdown. I needed to get some heavy stuff (rice, lentils, oils, etc.) so decided to brave it with the car.

Having taken stock of inventory and made a longlist of things we need, I drove out using “back roads” to the very nearby Simpli Namdhari store. While I expected lines at the large-format store, I expected that it would be compensated for by the variety of stuff I could find there.

I got there at 230 only to be told the store was “closed for lunch” and it would reopen at 3. “All counters are open”, the security guard told me. I saw inside that the store was being cleaned. Since it’s a 3 minute drive away, I headed back home and reached there at 3:15.

There was a small line (10-15 people long) when I got there. I must mention I was super impressed by the store at the outset. Lines had been drawn outside to ensure queueing at a safe distance. Deeper in the queue, chairs had been placed (again at a safe distance from each other) to queue in comfort. They were letting in people about 10 at a time, waiting for an equal number to exit the store each time.

It was around 335 by the time I got in (20 minute wait). From the entrance most shelves seemed full.

The thing with Namdhari’s is that they control the supplies of a large number of things they sell (fruits, vegetables, dairy, bread, etc.), and all of them were well stocked. In times like this (I can’t believe I’m using this phrase!), some sort of vertical integration helps, since you can produce the stuff because you know the downstream demand.

(in any case, for things like vegetables and milk, where there is a large gap between “sowing” and “reaping”, production hasn’t fallen at all. It’s a massive supply chain problem and plenty of stuff is getting wasted while people don’t have enough. Stuff like bread is where vertical integration helps)

In any case I took two trips round the supermarket with my trolley, checking items off my checklist as I put items into the trolley (unusual times mean even disorganised people like me make checklists). Again the vertical integration showed.

Stuff that Namdhari’s owns upstream of, like staples and oils, were well stocked. High demand stuff for which Namdhari’s is only a reseller, like Maggi or crisps or biscuits were poorly stocked. Interestingly, “exotic stuff” (like peanut butter or cheeses, around which Namdhari’s has partly built its reputation) was reasonably well stocked, for which I was really thankful (we consume far more of these than the average Indian household).

How much to buy was a dilemma I had in my head through the shopping trip. For one, there was the instinct to hoard, since I was clear I didn’t want another shopping trip like this until the shutdown ends (milk, vegetables and eggs are reasonably easily available close to home, but I wasn’t there for that).

On the other hand, I was “mindful” of “fair usage policy”, to not take more than what I needed, since you didn’t want stockouts if you could help it.

The other thing that shortages do to you is that you buy stuff you don’t normally buy. Like the other day at another shop I’d bought rice bran oil because groundnut oil wasn’t available. While you might buy something as “backup”, you are cognisant that if you get through the lockdown without needing this backup, this backup will never get used.

So even though we’re running short of sambar powder, I ignored it since the only sambar powder on offer looked pretty sad. On the other hand, I bought Haldiram’s Mixture since no “local mixtures” are available nowadays, and mixture is something I love having with my curd rice.

I was a little more “liberal” with stuff that I know won’t go bad such as dry fruits or staples, but then again that’s standard inventory management – you are willing to hold higher inventories of  items with longer shelf life.

I might have taken a bit longer there to make sure I’d got everything on my list, but then my “mask” made out of a hanky and two rubberbands had started to hurt. So, with half my list unfulfilled, I left.

Even at the checkout line, people stood a metre away from each other. You had to bag your own groceries, which isn’t a standard thing in India, but enforced now since you don’t want too many hands touching your stuff.

Oh, and plenty of people had come by car to the store. There were cops around, but they didn’t bother anyone.

Simulating Covid-19 Scenarios

I must warn that this is a super long post. Also I wonder if I should put this on medium in order to get more footage.

Most models of disease spread use what is known as a “SIR” framework. This Numberphile video gives a good primer into this framework.

The problem with the framework is that it’s too simplistic. It depends primarily on one parameter “R0”, which is the average number of people that each infected patient infects. When R0 is high, each patient infects a number of other people, and the disease spreads fast. With a low R0, the disease spreads slow. It was the SIR model that was used to produce all those “flatten the curve” pictures that we were bombarded with a week or two back.

There is a second parameter as well – the recovery or removal rate. Some diseases are so lethal that they have a high removal rate (eg. Ebola), and this puts a natural limit on how much the disease can spread, since infected people die before they can infect too many people.

In any case, such modelling is great for academic studies, and post-facto analyses where R0 can be estimated. As we are currently in the middle of an epidemic, this kind of simplistic modelling can’t take us far. Nobody has a clue yet on what the R0 for covid-19 is. Nobody knows what proportion of total cases are asymptomatic. Nobody knows the mortality rate.

And things are changing well-at-a-faster-rate. Governments are imposing distancing of various forms. First offices were shut down. Then shops were shut down. Now everything is shut down, and many of us have been asked to step out “only to get necessities”. And in such dynamic and fast-changing environments, a simplistic model such as the SIR can only take us so far, and uncertainty in estimating R0 means it can be pretty much useless as well.

In this context, I thought I’ll simulate a few real-life situations, and try to model the spread of the disease in these situations. This can give us an insight into what kind of services are more dangerous than others, and how we could potentially “get back to life” after going through an initial period of lockdown.

The basic assumption I’ve made is that the longer you spend with an infected person, the greater the chance of getting infected yourself. This is not an unreasonable assumption because the spread happens through activities such as sneezing, touching, inadvertently dropping droplets of your saliva on to the other person, and so on, each of which is more likely the longer the time you spend with someone.

Some basic modelling revealed that this can be modelled as a sort of negative exponential curve that looks like this.

p = 1 - e^{-\lambda T}

T is the number of hours you spend with the other person. \lambda is a parameter of transmission – the higher it is, the more likely the disease with transmit (holding the amount of time spent together constant).

The function looks like this: 

We have no clue what \lambda is, but I’ll make an educated guess based on some limited data I’ve seen. I’ll take a conservative estimate and say that if an uninfected person spends 24 hours with an infected person, the former has a 50% chance of getting the disease from the latter.

This gives the value of \lambda to be 0.02888 per hour. We will now use this to model various scenarios.

  1. Delivery

This is the simplest model I built. There is one shop, and N customers.  Customers come one at a time and spend a fixed amount of time (1 or 2 or 5 minutes) at the shop, which has one shopkeeper. Initially, a proportion p of the population is infected, and we assume that the shopkeeper is uninfected.

And then we model the transmission – based on our \lambda = 0.02888, for a two minute interaction, the probability of transmission is 1 - e^{-\lambda T} = 1 - e^{-\frac{0.02888 * 2}{60}} ~= 0.1%.

In hindsight, I realised that this kind of a set up better describes “delivery” than a shop. With a 0.1% probability the delivery person gets infected from an infected customer during a delivery. With the same probability an infected delivery person infects a customer. The only way the disease can spread through this “shop” is for the shopkeeper / delivery person to be uninfected.

How does it play out? I simulated 10000 paths where one guy delivers to 1000 homes (maybe over the course of a week? that doesn’t matter as long as the overall infected rate in the population otherwise is constant), and spends exactly two minutes at each delivery, which is made to a single person. Let’s take a few cases, with different base cases of incidence of the disease – 0.1%, 0.2%, 0.5%, 1%, 2%, 5%, 10%, 20% and 50%.

The number of NEW people infected in each case is graphed here (we don’t care how many got the disease otherwise. We’re modelling how many got it from our “shop”). The  right side graph excludes the case of zero new infections, just to show you the scale of the problem.

Notice this – even when 50% of the population is infected, as long as the shopkeeper or delivery person is not initially infected, the chances of additional infections through 2-minute delivery are MINUSCULE. A strong case for policy-makers to enable delivery of all kinds, essential or inessential.

2. SHOP

Now, let’s complicate matters a little bit. Instead of a delivery person going to each home, let’s assume a shop. Multiple people can be in the shop at the same time, and there can be more than one shopkeeper.

Let’s use the assumptions of standard queueing theory, and assume that the inter-arrival time for customers is guided by an Exponential distribution, and the time they spend in the shop is also guided by an Exponential distribution.

At the time when customers are in the shop, any infected customer (or shopkeeper) inside can infect any other customer or shopkeeper. So if you spend 2 minutes in a shop where there is 1 infected person, our calculation above tells us that you have a 0.1% chance of being infected yourself. If there are 10 infected people in the shop and you spend 2 minutes there, this is akin to spending 20 minutes with one infected person, and you have a 1% chance of getting infected.

Let’s consider two or three scenarios here. First is the “normal” case where one customer arrives every 5 minutes, and each customer spends 10 minutes in the shop (note that the shop can “serve” multiple customers simultaneously, so the queue doesn’t blow up here). Again let’s take a total of 1000 customers (assume a 24/7 open shop), and one shopkeeper.

 

Notice that there is significant transmission of infection here, even though we started with 5% of the population being infected. On average, another 3% of the population gets infected! Open supermarkets with usual crowd can result in significant transmission.

Does keeping the shop open with some sort of social distancing (let’s see only one-fourth as many people arrive) work? So people arrive with an average gap of 20 minutes, and still spend 10 minutes in the shop. There are still 10 shopkeepers. What does it look like when we start with 5% of the people being infected?

The graph is pretty much identical so I’m not bothering to put that here!

3. Office

This scenario simulates for N people who are working together for a certain number of hours. We assume that exactly one person is infected at the beginning of the meeting. We also assume that once a person is infected, she can start infecting others in the very next minute (with our transmission probability).

How does the infection grow in this case? This is an easier simulation than the earlier one so we can run 10000 Monte Carlo paths. Let’s say we have a “meeting” with 40 people (could just be 40 people working in a small room) which lasts 4 hours. If we start with one infected person, this is how the number of infected grows over the 4 hours.

 

 

 

The spread is massive! When you have a large bunch of people in a small closed space over a significant period of time, the infection spreads rapidly among them. Even if you take a 10 person meeting over an hour, one infected person at the start can result in an average of 0.3 other people being infected by the end of the meeting.

10 persons meeting over 8 hours (a small office) with one initially infected means 3.5 others (on average) being infected by the end of the day.

Offices are dangerous places for the infection to spread. Even after the lockdown is lifted, some sort of work from home regulations need to be in place until the infection has been fully brought under control.

4. Conferences

This is another form of “meeting”, except that at each point in time, people don’t engage with the whole room, but only a handful of others. These groups form at random, changing every minute, and infection can spread only within a particular group.

Let’s take a 100 person conference with 1 initially infected person. Let’s assume it lasts 8 hours. Depending upon how many people come together at a time, the spread of the infection rapidly changes, as can be seen in the graph below.

If people talk two at a time, there’s a 63% probability that the infection doesn’t spread at all. If they talk 5 at a time, this probability is cut by half. And if people congregate 10 at a time, there’s only a 11% chance that by the end of the day the infection HASN’T propagated!

One takeaway from this is that even once offices start functioning, they need to impose social distancing measures (until the virus has been completely wiped out). All large-ish meetings by video conference. A certain proportion of workers working from home by rotation.

And I wonder what will happen to the conferences.

I’ve put my (unedited) code here. Feel free to use and play around.

Finally, you might wonder why I’ve made so many Monte Carlo Simulations. Well, as the great Matt Levine had himself said, that’s my secret sauce!

 

Using ADHD to combat anxiety, anger and everything else

Sometimes I find that documenting thoughts can really help for later on in life when you’ve forgotten certain workflows. As you are well aware, I document pretty much everything here. However, some things sometimes get left out, and the problem with not documenting those things is that you end up forgetting what you had made.

In some way, it’s like the Guy Pearce character in Memento – who has extreme memory loss to the extent that he needs to take polaroid photos and make tattoos on his body as notes for himself. It’s not that bad for me, but I find that when I don’t document stuff adequately, I tend to forget thoughts. And even when I forget thoughts and ideas (that happens all the time), having documented them somewhere means that I stumble upon it sometime (yes, I randomly read my old blog posts from time to time), and that surely helps.

For example, I know that when I go through a prolonged period of depression (most recently happened last December), reading the first chapter of Jordan Peterson’s 12 Rules For Life helps.

Anyway, this is one thing I’ve followed from time to time since 2013, but have never really documented it. As long-time readers of my blog might know, I was under medication for both anxiety-depression and ADHD for the large part of 2012. I discontinued most of it in early 2013, but have occasionally gone back to taking ADHD medication (it’s a pain to get that medication – being highly controlled, you need doctor’s prescription in triplicate, etc. to get it. In the UK, the entire process through the NHS took a year and a quarter!).

Part of the reason why I’d been able to discontinue the medication was the realisation that it was in some way my ADHD that had contributed to anxiety and depression (making lots of small mistakes -> some of these mistakes proving costly -> fretting endlessly about these -> random pattern recognition based on small samples).

The other reason I was able to step down on all the medications was that I could actually “use my ADHD” to combat anxiety. The thing with ADHD is that while you can sometimes be incredibly distracted and unable to focus, you are also able to go into “hyperfocus” when you are doing something you are interested in. This thing you are hyperfocussed on could be work, or watching certain kinds of TV, or even getting lost in old cricket scorecards (or reading my own old blogposts!).

So the method I developed to combat times when I was anxious about something was to find something quickly that I could get hyperfocussed about (there are plenty of those) and use that to fully distract myself from whatever my thought process was at the time. Having ADHD also means you  can let go of whatever thoughts you have in your head rather easily. And so once you’re done with your hypefocussed task, you don’t usually return to the earlier state of high anxiety, and you can get on to normal life.

It’s a simple enough process, but ADHD also means that you very often forget simple solutions you’ve found to problems earlier, and keep reinventing the wheel. And hence the need for this documentation.

Recently I discovered that this method works for other forms of mental instability as well. For example, the common advice given to deal with anger is to “walk away from the scene” or “take a break”. This has largely worked really badly for me. I get angry. I walk away. Obsess over what just happened. Come back angrier.

But I have a secret weapon to deal with this – ADHD! Just walking away doesn’t help. I just end up hyperfocussing on what just happened. Instead the trick is to find something I can get absorbed in. A rabbit hole I can get into and get out of without remembering what had happened just before I got in. And there’s no way the anger can survive this kind of an experience.

The only problem is that when you’re angry with something, and that’s resulted in a “live fight”, walking away to do something totally unrelated can get the counterparty even angrier. I didn’t say I have solutions for all the problems in the world, did I?

Hanging out on Hangouts

The covid-19 crisis has fundamentally changed the way we work, and I thikn some things we are not going to get back. For the foreseeable future, at least, even after official lockdowns have been lifted, people will be hesitant to meet each other.

This means that meetings that used to earlier happen in person are now going to happen on video calls. People will say that video calls can never replace the face-to-face meetings, and that they are suboptimal, especially for things like sales, account management, relationship management, etc.

The main reason why face-to-face interactions are generally superior to voice or video calls is that the latter is considered transactional. Let’s say I decide to meet you for some work-related thing. We meet in one of our offices, or a coffee  shop, or a bar, and indulge in pleasantaries. We talk about the traffic, about coffee, about food, do some random gossip, discuss common connects, and basically just hang out with each other for a while before we get down to work.

While these pleasantaries and “hanging out” can be considered to be a sort of transaction cost, it is important that we do it, since it helps in building relationships and getting more comfortable with each other. And once you’ve gotten comfortable with someone you are likely (at the margin) to do more business with them, and have a more fruitful relationship.

This kind of pleasantaries is not common on a phone call (or a video call). Usually phone calls have more well defined start and end boundaries than in-person meetings. It is rather common for people to just get started off on the topic of discussion rather than getting to know one another, cracking jokes, discussing the weather and all that.

If we need video and phone calls to become more effective in the coming months (at least as long as people aren’t stepping out), it is imperative that we learn to “hang out on hangouts”. We need to spend some time in the beginning of meetings with random discussions and gossip. We need to be less transactional. This transaction cost is small compared to the benefit of effectively replicating in-person meetings.

However, hanging out on hangouts doesn’t come easily to us – it’s not “natural”. The way to get around it is through practice.

On Sunday night, on a whim, I got onto a group video call with a bunch of college friends. Midway through the call I wondered what we were doing. Most of the discussion was pointless. But it gave us an opportunity to “hang out” with each other in a way we hadn’t for a long time (because we live in different places).

Overall, it was super fun, and since then I’ve been messaging different groups of friends saying we should do group video chats. Hopefully some of those will fructify. Along with the immediate fun to be had, they will also help me prepare better for “hanging out” at the beginning of my work meetings.

I think you should do them, too.

Why Border Control Is Necessary

India is shutting down its domestic flights today in order to stop the spread of Covid-19. This comes a day after shutting down the national railways and most inter-city buses. States and districts have imposed border controls to control the movement of people across borders.

The immediate reaction to this would be that this is a regressive step. After a few decades of higher integration (national and international) this drawing of borders at minute levels might seem retrogade. Moreover, the right of a citizen to move anywhere in India is a fundamental right, and so this closing of borders might seem like a violation of fundamental rights as well.

However, the nature of the Covid-19 bug is that such measures are not only permissible but also necessary. The evidence so far is that it has a high rate of transmission between people who meet each other – far higher than for any other flu. The mortality rate due to the illness the bug causes is also low enough that each sick person has the opportunity to infect a large number of others before recovery or death (compared to this, diseases such as Ebola had a much higher death rate, which limited its transmission).

So far no cure for Covid-19 has been found. Instead, the most optimal strategy has been found to prevent infected people from meeting uninfected people. And since it is hard to know who is infected yet (since it takes time for symptoms to develop), the strategy is to prevent people from meeting each other. In fact, places like Wuhan, where the disease originated, managed to stem the disease by completely shutting down the city (it’s about the size of Bangalore).

In this context, open borders (at whatever level) can present a huge threat to Covid-19 containment. You might manage to completely stem the spread of the disease in a particular region, only to see it reappear with a vengeance thanks to a handful of people who came in (Singapore and HongKong have witnessed exactly this).

For this reason, the first step for a region to try and get free of the virus is to “stop importing” it. The second step is to shut down the region itself so that the already infected don’t meet the uninfected and transmit the disease to them.

Also, a complete shutdown can be harmful to the economy, which has already taken a massive battering from the disease. So for this reason, the shutdown is best done at as small a level as possible, so that the overall disruption is minimised. Also different regions might need different levels of shutdown in order to contain the disease. For all these reasons, the handling of the virus is best done at as local a level as possible. City/town better than district better than state better than country.

And once the spread of the disease has been stopped in a region, we should be careful that we don’t import it after that, else all the good work gets undone. For this reason, the border controls need to remain for a while longer until transmission has stopped in neighbouring (and other) regions.

It’s a rather complex process, but the main points to be noted are that the containment has to happen at a local level, and once it has been contained, we need to be careful to not import it. And for both these to happen, it is necessary that borders be shut down.

The Prom

The other day, the wife and I were discussing about growing up, and about school crushes, and how relationships worked in school. It was a fascinating discussion, and it has already led to an excellent newsletter episode by her. Here is the key point of our discussion, as she wrote in her newsletter:

There are rumours that some boys have a crush on a couple of girls. You think that it’s a pandemic like the COVID-19, and it’s going to get us all, except it doesn’t. This unfortunately follows a power law, only a couple of boys and girls will be affected by the “crush”, the rest of us just have to be affected by the lack of – crushes, bosoms and baritones. Now, the problem with middle/ high school is that it operates on mob mentality – everyone is only allowed to have a crush on the crushable.

And then later on in the piece, she talks about proms.

You are most likely to fall in love organically and benefit from it early on in life. So, wasting these precious years of socialising is a sin.

So, when I think about it, “prom” is a great concept. It gives everyone a shot at gaining some experience. You’re better off going to prom at 16 rather than at 26.

This got me thinking about proms. I had no clue of the concept of a “prom” while growing up, and only came to know of it through some chick flicks I watched when I was in my late teens. However, I ended up writing about proms in my book (while describing Hall’s Marriage Theorem – yes, you can find Graph Theory concepts in a book on market design), and the more I think about it, the more I think it is a great concept.

The thing with proms is that it forces a matching. One on one. One boy gets one girl and vice versa (I really don’t know how schools that don’t have a balanced sex ratio handle it). And that is very different from how the crush network operates in middle and high school.

As Pinky described in her post, crushes in middle and high school follow a power law, because there is strong mob mentality that operates in early puberty. Before “benefits” get discovered, one of the main reasons for having a boyfriend/girlfriend is the social validation that comes along with it, and such validation is positive if and only if your peer group “approves” of your partner.

So this leads to a “rich get richer” kind of situation. Everyone wants to hit on the hottest boys and girls, with the result that a small minority are overwhelmed with attention, while the large majority remains partnerless. And they continue to be partnerless this way, friendzoning large sets of their classmates at an age that is possibly most suited for finding a long-term gene-propagating partner. 

In most Indian schools, the crush graph in high school looks like this. The boys and girls towards the bottom are the “long tail” – they are not cool to hit on, so nobody hits on them. In other words, they are unloved in High School. Notice that it’s a fairly long tail.

Also notice that most of the arrows point upwards (I’ve drawn the graph so the most sought-after people are on top). Because nothing prevents “one way crushes”, everyone just tries “as high as they can” to find a partner. And most of these don’t work out. And most people remain unloved.

So what does a prom do? Firstly, everyone wants to go to the prom, and to go to a prom, you need a date. Which means that everyone here in this long tail needs a partner as well. In the original setup, when crushes were based on mob-mentality, there was no concept of seeking “undervalued assets” (people nobody else is hitting on). Now, when everyone needs a unique partner, there is value to be found in undervalued assets.

Basically a prom, by providing immediate rewards for finding a partner (soon enough, the kids will discover other “benefits” as well), moves the schoolkids from a “crush network” to a “partner network”, which better represents real-world romantic networks.

Many people may not be able to pair with their first choice (notice in the above network that even the most sought after people may not necessarily match with their favourites), but everyone will get a partner. The Gale Shapley (or should I say Shapely Gal?) algorithm will ensure a stable matching.

Moreover, it doesn’t help your cause in getting a preferred (if not most preferred) partner for the prom if you make your attempt just before the prom. You need to have put in efforts before. This means that in anticipation of the prom, “pair bonding” can happen much earlier. Which means that schoolkids are able to get trained in finding a partner for themselves much earlier than they do now.

That will make it less likely that they’ll bug their parents a decade (or two) later to find them a partner.

Footage

So after a fifteen year gap, I was in the Times of India yesterday, writing about the joys of working from home (I’d shared the clipping yesterday, sharing it again). The interesting thing is that this piece got me the kind of attention that I very rarely got with my six  years with the HT Media family (Mint and Hindustan Times).

The main reason, I guess, that this got far more footage, was that it came in a newspaper with a really high circulation. ToI is by far the number one English newspaper in India. While HT may be number two, we don’t even know how much of a number two it is, since it seemingly didn’t participate in the last Indian Readership Survey.

Moreover, ToI is read widely by people in my network. While the same might be true of Mint (at least until its distribution in Bangalore went kaput), it was surely not the case with HT. I didn’t know anyone who read the paper, and since my articles mostly never appeared online, they seemed to go into a black hole.

Another reason why my article got noticed so widely was the positioning in the paper – it was part of ToI’s massively extended “page one” (it came on the back of the front page, which was full of advertisements). So anyone who picked up the paper would have seen this in the first “real page of news” (though this page was filled with analysis of working from home).

On top of all this, I think my mugshot accompanying the article made a lot of difference. While the title of the article itself might have been missed by a few, my photo popping out of there (it helps I have the same photo on my Twitter, Facebook, LinkedIn and WhatsApp – thanks Anuroop) ensured that anyone who paid remote attention to my face would end up reading the article, and that helped me get further reach among my existing network.

ToI is going to pay me a nominal amount for this article, far less than what Mint or HT used to pay me per piece (then again, this one is completely non-technical), but I don’t seem to mind it at all. That it’s given me much more reach among my network means that I’m satisfied with ToI’s nominal payment.

Thinking about it, if we think of newspapers as three-sided markets connecting writers, readers and advertisers, it is possible that others who write for ToI do so for below market prices as well, for it has an incredibly large reach among “people like us”. And that sets the size-related network effects (“flywheel” as silicon valley types like to call it) in action among the writer side as well -you don’t write for money along, and if it can be sort of guaranteed that a larger number of people will read what you write, you will be willing to take lower payment.

In any case, this ToI thingy was a one-off (the last time I’d written for them was way back in 2005, when I was a student – it’s incredible I’ve given this post the same title as that one. I guess I haven’t grown up). But I may not mind doing more of such stuff for them. The more obscure the paper, though, the higher I’ll be inclined to charge! Oh, and henceforth, I’ll insist my mugshot goes with everything I write, even if that lowers my monetary fees.

 

The future of work, and cities

Ok this is the sort of speculative predictive post that I don’t usually indulge in. However, I think my blog is at the right level of obscurity that makes it conducive for making speculative predictions. It is not popular enough that enough people will remember this prediction in case this doesn’t come through. And it’s not that obscure as well – in case it does come through, I can claim credit.

So my claim is that companies whose work doesn’t involve physically making stuff haven’t explored the possibilities of remote work enough before the current (covid-19) crisis hit. With the gatherings of large people, especially in air-conditioned spaces being strongly discouraged, companies that hadn’t given remote working enough thought are being forced to consider the opportunity now.

My prediction is that once the crisis over and things go back to “normal”, there will be converts. Organisations and teams and individuals who had never before thought that working from home would have taken enough of a liking to the concept to give it a better try. Companies will become more open to remote working, having seen the benefits (or lack of costs) of it in the period of the crisis. People will commute less. They will travel less (at least for work purposes). This is going to have a major impact on the economy, and on cities.

I’m still not done with cities.

For most of history, there has always been a sort of natural upper limit to urbanisation, in the form of disease. Before germ theory became a thing, and vaccinations and cures came about for a lot of common illnesses, it was routine for epidemics to rage through cities from time to time, thus decimating their population. As a consequence, people didn’t live in cities if they could help it.

Over the last hundred years or so (after the “Spanish” flu of 1918), medicine has made sufficient progress that we haven’t seen such disease or epidemics (maybe until now). And so the network effect of cities has far outweighed the problem of living in close proximity to lots of other people.

Especially in the last 30 years or so, as “knowledge work” has formed a larger part of the economies, a disproportionate part of the economic growth (and population growth) has been in large cities. Across the world – Mumbai, Bangalore, London, the Bay Area – a large part of the growth has come in large urban agglomerations.

One impact of this has been a rapid rise in property prices in such cities – it is in the same period that these cities have become virtually unaffordable for the young to buy houses in. The existing large size and rapid growth contribute to this.

Now that we have a scary epidemic around us, which is likely to spread far more in dense urban agglomerations, I imagine people at the margin to reconsider their decisions to live in large cities. If they can help it, they might try to move to smaller towns or suburbs. And the rise of remote work will aid this – if you hardly go to office and it doesn’t really matter where you live, do you want to live in a crowded city with a high chance of being hit by a stray virus?

This won’t be a drastic movement, but I see a marginal redistribution of population in the next decade away from the largest cities, and in favour of smaller towns and cities.It won’t be large, but significant enough to have an impact on property prices. The bull run we’ve seen in property prices, especially in large and fast-growing cities, is likely to see some corrections. Property holders in smaller cities that aren’t too unpleasant to live in can expect some appreciation.

Oh, and speaking of remote work, I have an article in today’s Times Of India about the joys of working from home. It’s not yet available online, so I’ve attached a clipping.

How Mani Ratnam Ruined A Generation Of Indian Men

If you fall in love, you might be falling in love with a terrorist. In the arranged marriage market, you’ll find a hot girl who asks if you’re a virgin

I had recently written about how the ages are 13 to 16 are “peak movie appreciation age”, and about how I got influenced by several movies in that period in life. One of them was Mani Ratnam’s Dil Se (1998).

Of course, the most influential thing about this movie was the idea of dancing on top of a moving vehicle. I clearly remember our school picnic (on October 31st 1998), when responding to a challenge, a friend and I (later joined by another friend) clambered on top of the picnic bus and started dancing. I got a 2 litre bottle of Pepsi (presented by the friend who joined us later) for my efforts, which was duly shared between the rest of my class.

Dancing on top of a bus was fun, though it could get dangerous if the bus moved well-at-a -faster rate (I don’t think too many people copied that). The more dangerous thing about Dil Se was about the sort of ideas about arranged marriage that it presented.

Dil Se happened to be Preity Zinta’s debut movie (she was earlier mainly known for this Cadbury’s Perk ad) (it wasn’t technically her debut but I think it got released before the other movie she had shot).

Ten years back, when I was in the arranged marriage market, I wrote this series of blog posts called “Arranged Scissors“. One of them was a hypothetical letter I’d written to a prospective father-in-law (I don’t think I’ve got my actual father-in-law to read it). That included:

During the interview, I’m going to ask your daughter if she is a virgin. If you think she is the type that will be scandalized at such questions, you need not shortlist me.

I must admit that wasn’t an original. It was inspired by this movie released more than ten years before I wrote that.

Preity Zinta plays the role of this Mallu girl whom the protagonist (played by Shah Rukh Khan) meets in the arranged marriage market. They break out to a side room in the house for a chat. The first thing she asks him is if he is a virgin (that also happened to be Zinta’s first line on-screen, helping her set herself an image of a no-nonsense actress).

It fit into the story, so it was all fine. But for a generation of teenage boys watching Dil Se in 1998, it gave the perfectly wrong idea of what arranged marriage was like. It was almost like how Mani Ratnam was telling us that “if you fall in love, you might be falling in love with a terrorist. In the arranged marriage market, you’ll find a hot girl who asks if you’re a virgin”.

And some of us influential boys bought it. It didn’t help matters that just three years later, in Dil Chahta Hai, the Saif Ali Khan character finds that he can find himself a good match in the arranged marriage market (that occurred after my optimal age of movie appreciation, but Preity Zinta in Dil Se had influenced me enough that I bought the tripe anyway).

Many years later, many of us came into the arranged marriage market looking for Preity Zintas and Sonali Kulkarnis, only to find that it was an admission of failure, where you could at best look for a “common minimum program”, and which was overall a dehumanising experience (I’m glad I met my wife when I did, and she bailed me out of the market).

Now, we look back and curse the filmmakers. All because we happened to watch these movies at our most optimal movie appreciation age.

Range of possibilities

After I wrote about “love and arranged jobs” last week, an old friend got back saying he quite appreciates the concept and he’s seen it in his career as well. He’s fundamentally a researcher, with a PhD, who then made a transition to corporate jobs.

He told me that back in his research days, he had many “love work relationships”, where he would come across and meet people, and they would “flirt” (in a professional sense), and that could lead to a wide range of outcomes. Sometimes they would just have discussions without anything professional coming out of it, sometimes it would result in a paper, sometimes in a longer collaboration, and so on.

Now that he is in the corporate world, he told me that it is mostly “arranged jobs” for him now, and that meeting people for this is much less enjoyable in that sense.

The one phrase that he used in our conversation stuck with me, and has made it to the title of this post. He said that “love jobs” work when people meet with a “range of possibilities” in mind.

And that is precisely how it works in terms of romantic relationships as well. When you go out on a date, you are open to exploring a range of possibilities. It could just be an evening out. It could be a one-night stand. It could result in friendship, with or without benefits. There could be a long-term relationship that is possible. Gene propagation is yet another possible result. There is a rather wide range of possibilities and that is what I suppose makes dating fun (I suppose because I’ve hardly dated. I randomly one day met my wife after three years of blog-commenting, orkutting and GTalking, and we ended up hitting the highest part of the range).

Arranged marriages are not like that – you go into the “date” with a binary possibility in mind – you either settle into a long-term gene-propagating relationship with this person or you wish you never encounter them in life again. There is simply no range, or room for any range.

Job interviews in an arranged sense are like that. You either get the job or you don’t – there is one midpoint, though, where things don’t temporarily work out but you keep open the possibility of working together at a later date. This, however, is an incredibly rare occurrence – the outcome is usually binary.

It’s possible I’m even thinking about this “love jobs” scenario because I’ve been consulting for the last 8 odd years now. In all this time I’ve met several people, and the great part of this has been that the first meeting usually happens without any expectations – both parties are open to a range of possibilities.

Some people I’ve met have tried to hire me (for a job). Some have become friends. Some have given me gigs, some several. Some have first given me gigs and then become friends. Others have asked me to write recommendation letters. Yet others have become partners. And so on.

And this has sort of “spoilt” me into believing that a job can be found through this kind of a “love process” where a range of possibilities is open upon the first meeting itself. And when people try to propose the arranged route (“once we start this process we expect to hire you in a week”) I’ve chickened out.

Thinking about it, that’s how a lot of hiring works. Except maybe for the handful of employers which are infamous for long interview processes (I love those proceses, btw), I guess most of the “industry” is all about arranged jobs.

And maybe that’s why so few people “love” their jobs!