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.


Management watch

About a year back, a few months after I had started my current job, I was working late into the evening. I was sitting on the sofa with my laptop when my wife said, “you cannot call yourself senior management if you work like this”.

“What do you mean”, I asked.

“If you are truly senior management, you should not be using your computer after normal work hours. You should be doing everything using your phone. Do you remember, six months into my job at <@#R@#$@@>, I would work late into the night, but only with my phone?”, she countered.

I had to admit this was a good point. More practically, in terms of work stuff, I started thinking about making dashboards and reports more mobile-friendly. I started questioning interactive dashboards – if they are aimed at top management, the latter largely see the stuff on their phones, so interactivity is full of fat fingers.

Of course, the nature of my job means that I can never truly be senior management by this metric – I’m generally  too hands on to be able to work exclusively on my phone. However, that hasn’t stopped me from evangelising this theory of my wife. The theory itself is strong enough.

Recently I’d met a former client. He was using an iPad as a work “laptop”. I told him the theory and that he has truly arrived. He said he had been given a choice of an iPad and a Surface –  basically his company has internalised how senior management ought to be treated.

While I can never be senior management by this metric, I’m in a way trying to leapfrog it. Recently I got myself an Apple Watch. Apart from other things, it gives me notifications for all my messages, and I can reply using the watch as well. And this is where the magic begins.

For starters, Apple offers this standard set of templatised replies you can use. Now, Apple being Apple (and not Google), these replies are not customised to the message that you get. It drives me nuts that there is an “OK” and a “Sure!” and a “No” but no “Yes”. If this template doesn’t work for you, you can actually type a message on the watch itself. My fingers are fat (and I wear my watch on my dominant hand), so this is not so useful for me. However, there is also a voice typing mode, and that is rather good. And that is where things get real.

The other day, I shut work early and went off for a walk (I like doing that). My team had not shut their work though, and they kept bombarding me with messages. And that is when I realised I could actually read their messages and REPLY TO THEM using my watch. Most of the messages were the template monosyllables. Sometimes I spoke into my watch (without breaking my stride), and let Apple’s excellent voice-to-text do the rest.

And so I have this new theory, which is an extension of my wife’s theory. The next level of senior management is to be able to get all your work done simply using your watch – not even needing your phone. Of course, limitations exist – only a few lines of text are shown for each email, and images don’t load, but it is only a matter of time before watches solve for this.

But then, I’ve discovered one massive downside of replying to messages using my watch – the tone. The template monosyllables are all come across as rude (or curt). And the voice-to-text means you don’t really have your filter on while typing, and you end up “writing as you would speak”, and that can’t be great as well.

The other day I was walking from our Michaelpalya office to our Binnamangala office, when I was bombarded with messages from someone. And without breaking my stride I replied to all the messages, speaking into my watch. I “wrote” as I would speak (complete with swearwords), and that turned out to be an incredibly rude set of messages I ended up sending (I apologised later that day when I saw what I’d “written” on my phone later).

So leapfrogging and trying to act too cool can sometimes come at a price.

Compression Stereotypes

One of the most mindblowing things I learnt while I was doing my undergrad in Computer Science and Engineering was Lempel-Ziv-Welch (LZW) compression. It’s one of the standard compression algorithms used everywhere nowadays.

The reason I remember this is twofold – firstly, I remember implementing this as part of an assignment (our CSE program at IITM was full of those), and feeling happy to be coding in C rather than in the dreaded Java (which we had to use for most other assignments).

The other is that this is one of those algorithms that I “internalised” while doing something totally different – in this case I was having coffee/ tea with a classmate in our hostel mess.

I won’t go into the algorithm here. However, the basic concept is that as and when we see a new pattern, we give it a code, and every subsequent occurrence of that pattern is replaced by its corresponding code. And the beauty of it is that you don’t need to ship a separate dictionary -the compressed code itself encapsulates it.

Anyway, in practical terms, the more the same kind of patterns are repeated in the original file, the more the file can be compressed. In some sense, the more the repetition of patterns, the less the overall “information” that the original file can carry – but that discussion is for another day.

I’ve been thinking of compression in general and LZW compression in particular when I think of stereotyping. The whole idea of stereotyping is that we are fundamentally lazy, and want to “classify” or categorise or pigeon-hole people using the fewest number of bits necessary.

And so, we use lazy heuristics – gender, caste, race, degrees, employers, height, even names, etc. to make our assumptions of what people are going to be like. This is fundamentally lazy, but also effective – in a sense, we have evolved to stereotype people (and objects and animals) because that allows our brain to be efficient; to internalise more data by using fewer bits. And for this precise reason, to some extent, stereotyping is rational.

However, the problem with stereotypes is that they can frequently be wrong. We might see a name and assume something about a person, and they might turn out to be completely different. The rational response to this is not to beat oneself for stereotyping in the first place – it is to update one’s priors with the new information that one has learnt about this person.

So, you might have used a combination of pre-known features of a person to categorise him/her. The moment you realise that this categorisation is wrong, you ought to invest additional bits in your brain to classify this person so that the stereotype doesn’t remain any more.

The more idiosyncratic and interesting you are, the more the number of bits that will be required to describe you. You are very very different from any of the stereotypes that can possibly be used to describe you, and this means people will need to make that effort to try and understand you.

One of the downsides of being idiosyncratic, though, is that most people are lazy and won’t make the effort to use the additional bits required to know you, and so will grossly mischaracterise you using one of the standard stereotypes.

On yet another tangential note, getting to know someone is a Bayesian process. You make your first impressions of them based on whatever you find out about them, and go on building a picture of them incrementally based on the information you find out about them. It is like loading a picture on a website using a bad internet connection – first the picture appears grainy, and then the more idiosyncratic features can be seen.

The problem with refusing to use stereotypes, or demonising stereotypes, is that you fail to use the grainy pictures when that is the best available, and instead infinitely wait to get better pictures. On the other hand, failing to see beyond stereotypes means that you end up using grainy pictures when more clear ones are available.

And both of these approaches is suboptimal.

PS: I’ve sometimes wondered why I find it so hard to remember certain people’s faces. And I realise that it’s usually because they are highly idiosyncratic and not easy to stereotype / compress (both are the same thing). And so it takes more effort to remember them, and if I don’t really need to remember them so much, I just don’t bother.

Go East Policy

When you take time off work, one thing you want to do is to explore the world – go to parts of it that you haven’t been to before.

The original idea for this week was to travel – we wanted to do an impromptu road trip starting the past Sunday, booking only one hotel at a time on each day. As it happened, on Friday, daughter’s school sent an email that offline classes would begin on Monday, so we didn’t travel.

Instead, I decided to do a “staycation” – continue to be off work but be at home and vegetate. However, not going anywhere didn’t seem right. The whole point of taking time off is to go see parts of the world you haven’t seen before. And so I decided to set aside today for this purpose, apart from meeting people. Thanks to the pandemic and the latest round of lockdowns and school closures, I hadn’t seen too many people outside my family since the beginning of January.

And so I set off east, to parts that I hadn’t really seen or explored in a very long time.

  1. Bellandur
    First stop was Bellandur, to meet a friend who I hadn’t seen in over two years, and who’s recently moved back to “Bangalore”. We were to meet at a sort of a mall that’s part of this absolutely massive office complex.

    Despite all the metro construction going on, I got to Bellandur in quick time (the only wait being at Madivala checkpost). However, getting to Bellandur was only half the story. To get to the “bay” (as the mall was called) I had to turn off outer ring road, and into what felt like a strange road, with random barricades and private security personnel every 100 metres. Both sides were office complexes.

    Finally, at the end of the road (2-3 km in), I found the “bay”. It’s a sort of strip mall with a food court, and coffee and tea shops, and even an Apple reseller store. Maybe because most offshored businesses (which largely populate this area) haven’t got back to office yet, the place was largely empty. I had a bit of an embarrassing incident, though, as rather confusing signage meant I had opened the door to the women’s restroom (a janitor stopped me).

    I found the entire area sort of unreal and weird – even if the metro comes to ORR, it is going to be a massive pain to get to these offices and apartment blocks (and “mall”). There is no sense of redundancy in the roads. Security personnel every 100 metres is disconcerting.

  2. Windmills
    Next on the agenda was  Windmills Craftworks in Whitefield, where I was meeting someone for lunch. It was going to be my first time there, so I simply followed Google Maps.

    I was pleasantly surprised that this drive took only 25 minutes, again because most offshored staff have not returned to office. I was also pleasantly surprised to see a reasonably wide road that connects somewhere in the middle of nowhere in outer ring road to Graphite India.

    The location of the brewery is a bit strange – being located in a middle floor of a commercial building! The person I was meeting is a Whitefield local, and the thing that invariably happens in a microbrewery happens – he ran into others he knew. The food was good. I didn’t have much of the beer (since I was driving), but the IPA sampler was good as well.

    The valet was strange. When I got off the car, I was asked for my phone number and name, and got an SMS. When I was done, I simply clicked a link sent in the same SMS – by the time I came down, the car had arrived.

    On another note, I was thinking of all the places that were collecting my number – the valet, the restaurant above, some random shop I’d been to yesterday, etc. I was wondering what can be done with all this data. At one level, it scared me. At another, I thought it would be exciting to work with all this data and see what can be done with it!

  3. Sheraton Whitefield
    I was meeting someone at the coffee shop here. Being tucked away inside Prestige Shantiniketan, the hotel was a bit hard to find, and given that offices in the area have not yet been staffed, the hotel was empty.

    The hotel seemed nice enough and the coffee was good. And there was very little traffic in the usually rather busy road in front of it. I don’t expect this to last once people are back in their offices.


The way back was largely uneventful. Again I trusted Google, which took me on yet another random road to get from whitefield back to ORR. This was narrower and involved going through some rural areas.

Apart from some sections where the metro was being constructed, the drive back through ORR into Koramangala (I was meeting yet another friend after getting back to town) was quick and peaceful. And I noticed that the one-way systems in Hosur Road and Sarjapur Road have been reversed yet again. If there is a road (or pair of roads) deserving to be a “Tughlaq” in Bangalore, it’s this system. I’ve lost count of the number of times they’ve made these roads one-way and two-way (going back to at least 2004).

So the “exploring new areas” part of my week-long vacation is done. I want to step up on meeting people, but I’ll possibly do it on “home ground” in the days to come.

PS: The general convention I’ve settled on in life is that when one person travels to meet the other, the latter pays for the food / drink / coffee. As it happens, EVERYONE I met today offered to pay, and I simply let them without once insisting that I take the bill or we split it.

Impossible careers

A month ago, I had this idea that rather than squatting and deadlifting super heavy, I should learn “olympic lifts” (snatch, clean and jerk). I’d even made up my mind that I’ll ask one of the coaches at my gym to offer personal training during the summer so I can learn it.

And then, randomly, 2-3 weeks back, I decided to do some new exercises, and decided to do snatch grip overhead squat (something you need to do while you’re doing an olympic snatch). And that’s when I realised I would struggle.

I’ve mentioned here a couple of times that I have incredibly long arms. What I had not realised is that I have long enough, and a torso short enough, that it is physically impossible for me to snatch with a barbell.


So in the snatch, you need to use a wide grip and bring up the barbell, and at the same time thrust your hips forward to make sure the hips hit the barbell. The momentum of you having sharply pulled the barbell off the floor, and the hips hitting it, means that the barbell will go upwards, and you squat down and catch it overhead.

The key is that your waist needs to precisely hit the barbell when you thrust your hips forward. If the bar makes contact higher, your stomach can’t convey the same momentum that the waist can. And if the bar makes contact lower, well, let’s not get into below-the-belt stuff here.

And so your snatch grip on the barbell is determined by the width you hold it at so that the bar is exactly at your waist. You see professional weightlifters, and they usually hold the barbell well inside the ends (apparently short arms are a huge advantage in professional weight lifting). Most people in my gym also hold their snatch grip well inside the ends of the bar. Just that I can’t.

I got this photo taken at the gym today to demonstrate this:

Me trying to hold a snatch grip.

I tucked in my shirt to show where my waist is. Notice that I’m holding the bar in the widest possible position. Yet I’m unable to get the bar to my waist. So with my body proportions, if I were to try and snatch, I would be putting myself in grave danger.

The reason I’ve told such a long story here is to illustrate that your choice of profession or game or sport highly depends on who you are. If, for whatever reason, I’d decided when I was young that weightlifting is cool and I want to specialise in that, I would have NEVER made it.

A lot of times, we make the mistake of going for “cool stuff” (or worse, forcing our kids to do something that we think is cool), without realising if we are cut out to do the cool stuff -whether we will like it, enjoy it and be good at it. And sometimes, driven by “inspirational stories”, we push ourselves too hard to get the cool job or college admission or whatever, without realising we may not have the aptitude for it at all.

Now that I tried to find my snatch grip, I know better than to take personal training for snatching. Yes, I should still be able to clean – though every time I’ve tried to learn, I’ve found it to involve too much coordination between my limbs (just like swimming, something else I’ve never managed to learn though my long arms should make me good at it).

I guess I should just stick to my strengths, and just deadlift and chill.

Why WFH is unsustainable

A couple of weekends back I decided to re-read Yuval Noah Harari’s Sapiens. Rather than digging into my kindle for the regular version (which I’d read in 2015), I decided to read the graphic novel instead.

I’d purchased a copy of it a few months back, and a month ago, my daughter had finished reading it (it was only after she finished reading that I realised the extent of the sex and violence in the book. anyways).

Since I was re-reading, there was nothing particularly new. It was just a refresher of everything I’d read and enjoyed back in 2015. And one of the things I read was something highly pertinent to what I’d been thinking about the preceding Friday – on gossip.

One of the key points that Harari makes in Sapiens is that what makes us sapiens sapiens is our ability to gossip. Many other animals communicate, but most of their communication is “necessary”. “Oh look, there’s a lion”, or “there is a dead elephant near the lake” types.

Homo sapiens is unique in that most of our conversation is, fundamentally speaking, rather unnecessary stuff. It is basically “gossip”. That we gossip, however, means that we evolved to have a far richer vocabulary. We communicate and bond a lot more. And we are able to create “shared fictions” that means it is far easier for us to cooperate with strangers. And that lets us do more. Then again – it all started with gossip.

This, I realised, is why I find working from home rather isolating. It’s been over a year since I got back to full time employment. There have been two waves of covid-19 after that. This has meant I’ve hardly been to office in this time. Yes, there have been spells when I’ve travelled, or spent a week at office, but they have been few and far in between.

Apart from collaboration with my team, work has been fine. However, what I realise I miss is the general “bonding” that you would come to expect when you work for a company. The problem is with remote work.

While chat (we use Google Chat; other companies use Slack or DBabble of Microsoft Teams or Discord) is good enough for most “quick communication”, the big problem is that everything you say is necessarily in writing. Yes, you can delete or modify, some messengers have disappearing messages and all that.

Yet, because you need to put everything in writing, you say less than you otherwise would. Most importantly, you think twice before you gossip. It takes a long time for pairs of people to build sufficient mutual trust to be able to gossip (and when I think of it, most of this kind of trust has developed through offline interactions). Even if I trust you, I’ll think maybe one and a half times before putting gossip in writing.

So prolonged period of remote work means work gets robbed of the core human element – gossip. And extending what Harari says in sapiens, when you gossip less, you believe in fewer shared fictions (though by definition all of you in your company believe in the fiction of the limited liability corporation). And you cooperate less.

I can’t wait to get back to office (planning in 2 weeks or so), and (hopefully) start gossiping again. It won’t be easy since so far I’ve largely been remote. However, if we can get a sustained period of office work going, we should be able to gossip and bond and be a little more human.

Returns to experience and business school career choices

Go to any elite business school, especially one where the average years of pre-MBA industry experience is low, and ask students what they want to do. Most first year students will tell you that they either want to do “marketing” or “investment banking”. Second year students will still say this, but some will also say “consulting”.

With the benefit of a lot of hindsight (it’s nearly 16 years since I graduated from business school), there is definite merit in these being primary career choices for business school students – rather than other seemingly equally valid careers such as B2B sales, or product management, or not-for-profits, or data analytics, or logistics.

It has to do with reversibility, and “one-way doors”.

Different professions have different levels of “returns to experience”. In some professions, all that mattters is the total amount of contiguous experience you’ve had in that particular profession.

I figured this out the hard way, for example, in my brief flirtation with getting back to becoming a banking quant in 2017. I had left the profession (banking quant) in late 2011, to become an independent consultant. A series of financial services projects later, I wondered if I could get back to what I was doing earlier. Except that they wouldn’t have me back – all they cared about was that I had “been out of the industry for 5 years”, and what experience I got in those 5 years didn’t really matter.

In other words, investment banking is a “high returns to experience” industry, where your experience within the industry is highly valued, but anything outside is completely disregarded.

Marketing (though not “digital marketing”) is also similarly – your experience outside the field is not valued at all. So even if you look to get into consumer goods marketing at a later point of time in your career, you will most likely have to start right at the bottom, at an entry level position. All your years of experience doing something else are of no use here.

You notice a pattern (despite the small number of data points I’ve offered)? Popular out-of-business-school careers are professions with a high “perceived returns to experience”. The reason why so many business school students want to do marketing or investment banking is because they are irreversible choices. You either get in from school, or get in later on but start at the bottom anyway. So you might as well get in straight from school.

Technology and data and product management and B2B sales and corporate strategy and logistics and general management are all rather more forgiving – a large number of employers offering these jobs give adequate weightage to experience outside of the field as well. Which means it is easier to switch into these professions at a later point of time in one’s career.

Putting it another way, starting your career in a hard-to-enter (or “enter-at-bottom”) field is a risk-averse way of building your career. If you don’t like it, you can always move to a more welcoming career path. Start in a more welcoming place, and you’ll find it harder to move to a less welcoming career.

So that explains marketing and investment banking, but what about strategy consulting? Surely, strategy consulting should value diverse experience, for that will make you a better consultant? The difference here is between strategy consulting and “brand name strategy consulting”. If you work for a “brand name strategy consultant”, you’re not only offering your own advice – you are also offering advice on behalf of that firm.

This means, in order to do so, you need adequate training in the ways of the firm. And so there will always be (less than 100% of course) a discount on the rest of your experience – in order to learn the ways nad means of the firm that you are going to represent, you will need to start at a more junior level than your experience dictates. So once again you might as well get in right upfront, straight out of school.

So the next time a business school student tells you she wants to do marketing or investment banking or strategy consulting, don’t berate her for “being too cliched and not open minded enough”. She is just being rational, and playing the optionality in the way it should be.

Random Friday night thoughts about myself

I’m flamboyant. That’s who I am. That’s my style. There’s no two ways about it. I can’t be conservative or risk-averse. That’s not who i am.

And because being flamboyant is who I am, I necessarily take risk in everything I do. This means that occasionally the risks don’t pay off – if they pay off all the time they’re not a risk.

In the past I’ve taken the wrong kind of lessons from risks not paying off. That I should not have taken those risks. That I should have taken more calculated risks. That I should have hedged better.

Irrespective of how calculated your risks are, they will not pay off some of the time. The calculation is basically to put a better handle on this probability, and the impact of the risk not paying off. Hedging achieves the same thing.

For example, my motorcycle trip to Rajasthan in 2012 was a calculated risk, hedged by full body riding gear. I had a pretty bad accident – the motorcycle was travelling at 85 kmph when I hit a cow and got thrown off the bike, but the gear meant I escaped with just a hairline fracture in my last metacarpal – I rode on and finished the trip.

Back to real life – what happened was that between approx 2006-09 a number of risks didn’t pay off. Nowadays I like to think of it as a coincidence. Or maybe it was a “hot hand” of the wrong kind – after the initial set of failed risks, I became less confident and less calculating about my risks, and more of them did not pay off.

This is my view now, of course, looking back. Back then I thought I was finished. I started beating myself for every single (what turned out to be, in hindsight) bad decision. And that made me take worse decisions.

A year of medication (2012), which included the aforementioned motorcycle trip, a new career and a lot of time off, helped me get rid of some of these logical fallacies. I started accepting that risks sometimes don’t pay off. And the solution to that is NOT to take less risk.

However, that thought (that every single risk thay didn’t pay off was a bad decision on my past) has been permanently seeded in my brain – whether I like it or not (I don’t like it). And so whenever something goes bad – basically a risk I consciously took not paying off – I instinctively look for a bad decision that I personally made to lay the blame on. And that, putting it simply, never makes me happy. And this is something I need to overcome.

As I said at the beginning of the post, cutting risk simply isn’t my style. And as I internalise that this is how I inherently am, I need to accept that some of my decisions will inherently turn out to have bad outcomes. And in a way, that is part of my strategy.

This blogpost is essentially a note to myself – to document this realisation on my risk profile and to make sure that I have something to refer to the next time a risky decision I take doesn’t pay off (well that happens every single day – this is for the big ones).

The next time I shoot off my mouth without thinking it’s part of my strategy.

The next time I resist the urge to contain myself and blurt out what I’m thinking it’s part of my strategy.

The next time I unwittingly harm myself because of a bad decision I make it’s just part of my strategy.

To close – there was a time when Inzamam-ul-Haq took someone’s advice and lost weight and found that he just couldn’t bat. In a weird way his belly was positively correlated with his batting. Similarly the odd bad decision I take is positively correlated with how I operate naturally.

And I need to learn to live with it.

Legacy Metrics

Yesterday (or was it the day before? I’ve lost track of time with full time WFH now) the Times of India Bangalore edition had two headlines.

One was the Karnataka education minister BC Nagesh talking about deciding on school closures on a taluk (sub-district) wise basis. “We don’t want to take a decision for the whole state. However, in taluks where test positivity is more than 5%, we will shut schools”, he said.

That was on page one.

And then somewhere inside the newspaper, there was another article. The Indian Council for Medical Research has recommended that “only symptomatic patients should be tested for Covid-19”. However, for whatever reason, Karnataka had decided to not go by this recommendation, and instead decided to ramp up testing.

These two articles are correlated, though the paper didn’t say they were.

I should remind you of one tweet, that I elaborated about a few days back:


The reason why Karnataka has decided to ramp up testing despite advisory to the contrary is that changing policy at this point in time will mess with metrics. Yes, I stand by my tweet that test positivity ratio is a shit metric. However, with the government having accepted over the last two years that it is a good metric, it has become “conventional wisdom”. Everyone uses it because everyone else uses it. 

And so you have policies on school shutdowns and other restrictive measures being dictated by this metric – because everyone else uses the same metric, using this “cannot be wrong”. It’s like the old adage that “nobody got fired for hiring IBM”.

ICMR’s message to cut testing of asymptomatic individuals is a laudable one – given that an overwhelming number of people infected by the incumbent Omicron variant of covid-19 have no symptoms at all. The reason it has not been accepted is that it will mess with the well-accepted metric.

If you stop testing asymptomatic people, the total number of tests will drop sharply. The people who are ill will get themselves tested anyways, and so the numerator (number of positive reports) won’t drop. This means that the ratio will suddenly jump up.

And that needs new measures – while 5% is some sort of a “critical number” now (like it is with p-values), the “critical number” will be something else. Moreover, if only symptomatic people are to be tested, the number of tests a day will vary even more – and so the positivity ratio may not be as stable as it is now.

All kinds of currently carefully curated metrics will get messed up. And that is a big problem for everyone who uses these metrics. And so there will be pushback.

Over a period of time, I expect the government and its departments to come up alternate metrics (like how banks have now come up with an alternative to LIBOR), after which the policy to cut testing for asymptomatic people will get implemented. Until then, we should bow to the “legacy metric”.

And if you didn’t figure out already, legacy metrics are everywhere. You might be the cleverest data scientist going around and you might come up with what you think might be a totally stellar metric. However, irrespective of how stellar it is, that people have to change their way of thinking and their process to process it means that it won’t get much acceptance.

The strategy I’ve come to is to either change the metric slowly, in stages (change it little by little), or to publish the new metric along with the old one. Depending on how clever the new metric is, one of the metrics will die away.


Over the weekend, I wrote this on twitter:


Surprisingly (at the time of writing this at least), I haven’t got that much abuse for this tweet, considering how “test positivity” has been held as the gold standard in terms of tracking the pandemic by governments and commentators.

The reason why I say this is a “shit metric” is simple – it doesn’t give that much information. Let’s think about it.

For a (ratio) metric to make sense, both the numerator and the denominator need to be clearly defined, and there needs to be clear information content in the ratio. In this particular case, both the numerator and the denominator are clear – latter is the number of people who got Covid tests taken, and the former is the number of these people who returned a positive test.

So far so good. Apart from being an objective measure, test positivity ratio is  also a “ratio”, and thus normalised (unlike absolute number of positive tests).

So why do I say it doesn’t give much information? Because of the information content.

The problem with test positivity ratio is the composition of the denominator (now we’re getting into complicated territory). Essentially, there are many reasons why people get tested for Covid-19. The most obvious reason to get tested is that you are ill. Then, you might get tested when a family member is ill. You might get tested because your employer mandates random tests. You might get tested because you have to travel somewhere and the airline requires it. And so on and so forth.

Now, for each of these reasons for getting tested, we can define a sort of “prior probability of testing positive” (based on historical averages, etc). And the positivity ratio needs to be seen in relation to this prior probability. For example, in “peaceful times” (eg. Bangalore between August and November 2021), a large proportion of the tests would be “random” – people travelling or employer-mandated. And this would necessarily mean a low test positivity.

The other extreme is when the disease is spreading rapidly – few people are travelling or going physically to work. Most of the people who get tested are getting tested because they are ill. And so the test positivity ratio will be rather high.

Basically – rather than the ratio telling you how bad the covid situation is in a region, it is influenced by how bad the covid situation is. You can think of it as some sort of a Schrödinger-ian measurement.

That wasn’t an offhand comment. Because government policy is an important input into test positivity ratio. For example, take “contact tracing”, where contacts of people who have tested positive are hunted down and also tested. The prior probability of a contact of a covid patient testing positive is far higher than the prior probability of a random person testing positive.

And so, as and when the government steps up contact tracing (as it does in the early days of each new wave), test positivity ratio goes up, as more “high prior probability” people get tested. Similarly, whether other states require a negative test to travel affects positivity ratio – the more the likelihood that you need a test to travel, the more likely that “low prior probability” people will take the test, and the lower the ratio will be. Or when governments decide to “randomly test” people (puling them off the streets of whatever), the ratio will come down.

In other words – the ratio can be easily gamed by governments, apart from just being influenced by government policy.

So what do we do now? How do we know whether the Covid-19 situation is serious enough to merit clamping down on people’s liberties? If test positivity ratio is a “shit metric” what can be a better one?

In this particular case (writing this on 3rd Jan 2022), absolute number of positive cases is as bad a metric as test positivity – over the last 3 months, the number of tests conducted in Bangalore has been rather steady. Moreover, the theory so far has been that Omicron is far less deadly than earlier versions of Covid-19, and the vaccination rate is rather high in Bangalore.

While defining metrics, sometimes it is useful to go back to first principles, and think about why we need the metric in the first place and what we are trying to optimise. In this particular case, we are trying to see when it makes sense to cut down economic activity to prevent the spread of the disease.

And why do we need lockdowns? To prevent hospitals from getting overwhelmed. You might remember the chaos of April-May 2021, when it was near impossible to get a hospital bed in Bangalore (even crematoriums had long queues). This is a situation we need to avoid – and the only one that merits lockdowns.

One simple measure we can use is to see how many hospital beds are actually full with covid patients, and if that might become a problem soon. Basically – if you can measure something “close to the problem”, measure it and use that as the metric. Rather than using proxies such as test positivity.

Because test positivity depends on too many factors, including government action. Because we are dealing with a new variant here, which is supposedly less severe. Because most of us have been vaccinated now, our response to getting the disease will be different. The change in situation means the old metrics don’t work.

It’s interesting that the Mumbai municipal corporation has started including bed availability in its daily reports.