Tanzania – initial thoughts

This is our first overseas holiday since august 2019 and it still hasn’t sunk in that we’re not india. It’s been 4-5 hours since we landed at Kilimanjaro international airport, and while thjings have been nice there is very little evidence so far that we are in “forin”.

Vehicles drive on the left side of the road. There are plenty of motorcycles. Trucks are brightly painted. Buses look like those in our city, though a lot of them seem smaller.

The weather is also similar – we’ve swapped 12.8 degree north and 920M above sea level for 3 degree south and 1000M above sea level. It was sunny in the afternoon but there has always been a nice breeze blowing – from the nearby Kilimanjaro!

The place is dry though. there is a lot of dust. And dusty winds. And very little vegetation (outside of our hotel). Our guide, on the way from the airport to the hotel, informed us that rains have been delayed this year and so things have been dry.

So all put together, it’s so far been like being somewhere in india itself, just a part that is drier and dustier than bangalore. The only differences so far have been –

Our guide drove far more carefully than I’ve seen Indian drivers. very measured in overtaking. No honking. Etc.

Looks like liquor licences here are far more liberal than in india. There is some charm sitting at a tiny hotel bar drinking. India’s restricted liquor licenses (Im told there have been no new liquor licenses in Karnataka since 1993 or something) means you need a certain scale to operate a bar. So you have few quaint dribbling places.

But that’s about it. Midway through this blogpost the power supply at the hotel went off. and this post will get published when the power gets restored. And I don’t even know if the hotel here has power backup!

Cross docking in Addis Ababa

I’m writing this from Addis Ababa bole international airport, waiting for my connection to Kilimanjaro. We arrived here some 3 hours back, on a direct flight from bangalore.

The flight was fine, and uneventful. It was possibly half empty, though – the guy in the front seat had all 3 seats to himself and had lay down across them.

Maybe the only issue with the flight was that they gave us “dinner” at the ungodly time of 3am (1230 Eastern Africa time). I know why – airlines prefer to serve as soon as they take off since food is freshest then (rather than reheating at the end of the flight). And if they serve two meals the second one is usually a cold one (sandwiches cakes etc)

The airport here is also uneventful. There are a couple of bars and a few nondescript looking coffee shops. It is linear, with all gates being laid out in a row (reminds me of KL, and very unlike “star shaped airports” such as Barcelona or Delhi).

In any case I’ve been doing the rounds since morning looking for information of my flight gate. The last time I saw it hadn’t yet been published. But there was something very interesting about the flight schedule.

Basically, this airport serves as a cross dock between Africa and the rest of the world, taking advantage of its location in one corner of the continent.

For example, all flights that have either departed in the last hour or due to depart in the next 2 hours are to various destinations in Africa (barring one flight to São Paulo and Buenos Aires).

Kinshasa. Cape Town. Douala. Antananarivo. Entebbe. Accra. Lubumbashi via Lilongwe. Mine to Kilimanjaro (and then onward to Zanzibar). Etc. etc.

No flight that goes north or east, barring one to Djibouti. And no take offs between 6am (when we landed here) till 815 (Cape Town). And until around 8, people kept streaming into the airport (and the lines at the toilets kept getting longer!)

Ethiopian’s schedule at bangalore is also strange. Flights arrive at 8am 3 days of the week and then hang in there idly till 230 am the next morning. Time wise, that’s incredibly low utilisation of a costly asset like an aircraft (that said it’s a Boeing 737Max).

After looking at the airport schedule though it makes more sense to me. Basically in the morning, flights bring in passengers from all over Asia and Europe, and connect them to various places in Africa.

In the evenings, flights stream in from all around Africa and cross dock people to destinations in Europe and Asia. Currently the cross dock is one way – out of Africa in the evenings and into Africa in the mornings.

This means that there are some destinations where, given time of travel, the only way to make this cross dock work is to keep the aircraft idle at the destination. In African destinations for example, I expect shorter turnarounds – this morning I noticed that the first set of departures were to far away locations – Cape Town, Johannesburg, Accra, Harare and then to Lusaka, etc.

I don’t expect this to last long though. In a few years (maybe already delayed by the pandemic) I expect ethiopian to double its flight capacity across all existing destinations. Then, it can operate both into Africa and out of Africa cross docks twice in a day. And won’t need to waste precious flight depreciation time at faraway airports such as bangalore.

PS: so far I haven’t seen a single flight from any other airline apart from Ethiopian at the airport here.

Missionaries and Mercenaries

When a company gets founded, it does so by a bunch of “missionaries”. Founders seldom are in it solely for the money (though that is obviously one big reason they are there). They found companies because they are “missionary” about the purpose that the company wants to achieve (it doesn’t matter what this mission is – it varies from company to company).

As they start building the company, they look for more missionaries to help them to do it. Rather, among early employees, there is a self selection that happens – only people who are passionate about the mission (or maybe passionate about the founders) survive, and those in it for other purposes just move on.

And this way, the company gets built, and grows. However, there comes a point when this strategy becomes unsustainable. A largish company needs a whole different set of skills from what made the company large in the first place. And some of these skills are specialist enough that it is not going to be easy to attract employees who are both good at this specialisation and passionate enough about the company’s mission.

These people look at their jobs as just that – jobs. They are good at what they do and capable of taking the company forward. However, they don’t share the “mission”, and this means to attract them, you need to be able to serve their “needs”.

For starters, they demand to be paid more. Then, they need the recognition that the job is just a job for them – they need their holidays and “benefits” and “work life balance” and decent working hours and all that. These are things people who are missionary about the business don’t necessarily need – the purpose of the mission means that they are able to “adjust”.

The choice to move from a missionary organisation to a more “mercenary” organisation (not just talking of money here, but also other benefits and perks) needs to be a conscious one from the point of view of the company. At some point, the company needs to recognise that it cannot run on missionary fuel alone and make changes (in structure and function and what not) to accommodate mercenaries and let them grow the business.

The choice of this timing is something a lot of companies don’t get right. Some do it too late – they try to run on missionary fuel for way longer than it is sustainable, and then find it impossible to change culture. This leads to a revolving door of mercenaries and the company unable to leverage their talents.

Others – such as Twitter – do it way too early. One thing that seems to be clear (to me) from the recent wave of layoffs at the company, and also having broadly followed the company for a long time (I’ve had a twitter account since 2008), is that the company “went professional” too early.

There was a revolving door of founders in the initial days, until Jack Dorsey came back to run the company (apart from running Square) for a few years. This revolving door meant that the company, from its early days, was forced to rely on professional management – mercenaries in other words. Over a period of time, this resulted in massive bloat. The company struggled along until Elon Musk came in with an outlandish bid and bought it outright.

From the commentary that I see on twitter now, what Musk seems to be doing is to take the company back to “missionaries”. Take his recent letter for example. He is demanding that staff “work long hours at high intensity“. A bunch have resigned in protest (in addition to last week’s layoffs).

The objective of all these exercises – abrasive management style, laying off half the people first, and then putting onerous work conditions on the rest – is to simply weed out all the mercenaries. The only people who will agree to “work long hours at high intensity” will be “missionaries” – people who are passionate about growing the company and will do what it takes to get there.

Musk’s bet, in my opinion (and based on what I’ve read elsewhere), is that the company was massively overstaffed in the first place, and that there is a sufficient quorum of missionaries who will stay on and take the company forward. The reason he is doing all this in public (using his public twitter account to give instructions to his employees, for example) is the hope that these actions might attract potential missionaries from outside to beef up the staff.

I have no clue if this will succeed. At the heart of it, a 16 year old company wanting to run on missionaries only doesn’t make sense. However, given that the company had been listing (no pun intended), this might be necessary for a temporary reboot.

However, one thing I know is that this needs to be an “impulse” (in the physics sense of the term). A short and powerful jab to move the company forward. At an old company like this, running on missionaries can’t be sustainable. So they better fix the company soon and then move it on a more sustainable mercenary path.

Heads of departments

Recently I was talking to someone about someone else. “He got an offer to join XXXXXX as CTO”, the guy I was talking to told me, “but I told him not to take it. Problem with CTO role is that you just stop learning and growing. Better to join a bigger place as a VP”.

The discussion meandered for a couple of minutes when I added “I feel the same way about being head of analytics”. I didn’t mention it then (maybe it didn’t flash), but this was one of the reasons why I lobbied for (and got) taking on the head of data science role as well.

I sometimes feel lonely in my job. It is not something anyone in my company can do anything about. The loneliness is external – I sometimes find that I don’t have too many “peers” (across companies). Yes, I know a handful of heads of analytics / data science across companies, but it is just that – a handful. And I can’t claim to empathise with all of them (and I’m sure the feeling is mutual).

Irrespective of the career path you have chosen, there comes a point in your career where your role suddenly becomes “illiquid”. Within your company, you are the only person doing the sort of job that you are doing. Across companies, again, there are few people who do stuff similar to what you do.

The kind of problems they solve might be different. Different companies are structured differently. The same role name might mean very different things in very different places. The challenges you have to face daily to do your job may be different. And more importantly, you might simply be interested in doing different things.

And the danger that you can get into when you get into this kind of a role is that you “stop growing”. Unless you get sufficient “push from below” (team members who are smarter than you, and who are better than you on some dimensions), there is no natural way for you to learn more about the kind of problems you are solving (or the techniques). You find that your current level is more than sufficient to be comfortable in your job. And you “put peace”.

And then one day you find ten years have got behind youNo one told you when to run, you missed the starting gun

(I want you to now imagine the gong sound at the beginning of “Time” playing in your ears at this point in the blogpost)

One thing I tell pretty much everyone I meet is that my networking within my own industry (analytics and data science) is shit. And this is something I need to improve upon. Apart from the “push from below” (which I get), the only way to continue to grow in my job is to network with peers and learn from them.

The other thing is to read. Over the weekend I snatched the new iPad (which my daughter had been using; now she has got my wife’s old Macbook Air) and put all my favourite apps on it. I feel like I’m back in 2007 again, subscribing to random blogs (just that most of them are on substack now, rather than on Blogspot or Livejournal or WordPress), in the hope that I will learn. Let me see where this takes me.

And maybe some people decide that all this pain is simply not worth it, and choose to grow by simply becoming more managerial, and “building an empire”.

CGM Notes

At about 5:30 pm last Wednesday, I chanced upon a box of Sandesh crumbs lying in the office. A colleague had brought the sweets to share the previous day, and people had devoured it; but left aside the crumbs. I picked up the box and proceeded to demolish it as I reviewed a teammate’s work.

Soon the box was in the dustbin. I chanced upon a cookie box that another colleague had got. And started to demolish the cookies. This was highly atypical behaviour for me, since I’m trying to follow a low-carb diet. At the moment, I assumed it was because I was stressed that day.

Presently, I took out my phone to log this “meal” in the Ultrahuman app. There the reason for my binge was clearly visible – my blood sugar had gone down to 68 mg / dL, pretty much my lowest low in the 2 weeks I wore the last sensor.

This, I realised, was a consequence of the day’s lunch, at Sodabottleopenerwala. Maybe it was the batter (or more likely, the sauce) of the fried chicken wings. Or the batter of the onion pakoda. Something I had eaten that afternoon had spiked my blood sugar high enough to trigger a massive insulin response. And that insulin, having acted upon my lunch, had acted upon the rest of the sugars in my blood. Sending it really low. To a point where I was gorging on whatever sweets I could find.

About a year (or maybe two?) back, I had read Jason Fung’s The Obesity Code, which had talked about insulin being the hormone responsible for weight gain. High levels of insulin in the blood means you feel hungrier and you gorge more, or something like that the argument went. The answer was to not keep triggering insulin release in the blood – for that would make the body “insulin resistant” (so you need more insulin than usual to take care of a particular amount of blood sugar). Which can lead to Type 2 diabetes, high triglycerides, weight gain, etc.

And so Fung’s recommendations (paraphrasing – you should see my full blogpost based on the book ) included fasting, and eating fewer carbs. Here I was, two years later, finding evidence of the concepts in my CGM data.

I have worn a CGM a couple of times before. Those were primarily to figure out my body’s response to different kinds of foods, and find out what I should eat to maintain a healthy blood sugar level. The insights had been fairly clear. However, since it had been ten months since I last wore a CGM, I had forgotten some of the insights. I was “cheating” (eating what I wasn’t supposed to eat) too much. And my blood sugar had started going up to scary levels.

The objective of this round of the CGM was to find out “high ROI foods”. Foods that gave me a lot of “satisfaction” while not triggering much of a blood glucose response. The specific hypothesis I was trying to test was that sweets and traditional south indian lunch trigger my blood sugar in the same manner, so I might as well have dessert instead of traditional south indian lunches!

Two weeks of this CGM and I rejected this hypothesis. I had sweets enough number of times (kalakand, sandesh, corner house cake fudge, etc) to notice that the glucose response was not scary at all. The problem, each time, however, occurred later – maybe the “density of sugars” in the sweets triggered off too much of an insulin response, leading to a glucose crash (and low glucose levels at the end of it).

Traditional south indian lunch (I would start with the vegetables before I moved on to rice with sambar and then rice with curd) was something I tested multiple times. And it’s not funny how much the response varied – a couple of times, my blood glucose went up very high (160 etc.). A couple of times there was a minimal impact on my blood glucose. It was all over the place. That said, given the ease of preparation, it is something I’m not cutting out.

What I’m cutting out is pretty much anything that involves “pulverised grains”. Those just don’t work for me. Two times I had dosa – once it sent my blood sugar beyond 200, once beyond 180. One idli with vade sent my blood sugar from 80 to 140 (on the other hand, khara bath (uppit) with vaDe only sent it to 120). Paneer paratha (on the streets of Gurgaon) sent my sugar up to 200.

That some flours work for me I had established in previous iterations wearing the CGM – rice rotti hadn’t worked, jowar rotti hadn’t worked, ragi mudde had been especially bad. But that dose and idli and paratha also don’t work for me was an interesting observation this time. I guess I’ll be eating much less of these.

What did work for me was what has sort of become my usual meals when going out of late – avoiding carbs. One Wednesday, I got my team to order me an entire Paneer Butter Masala for lunch (Gurgaon again). Minimal change in glucose levels. That Friday, I had butter chicken (only; no bread or rice with it). Minimal change yet again! Omelettes simply don’t register on my blood sugar levels (even with generous amounts of cheese).

To summarise,

  • Sweets may not send my sugar very high, but in due course they send it very low (due to high insulin response). The only time this crash doesn’t happen is if I’ve had the sweets at the end of a meal. Basically, avoid.
  • Any kinds of pulverised grains (dosa, idli, rotti, paratha) is not good for me. Avoid again
  • The same food can have very different response at different times. This could be due to the pre-existing levels of insulin in the body. So any data analysis (I plan to do it) needs to be done very carefully
  • On a couple of occasions I found artificial sweeteners (like those in my whey protein) causing a glucose crash – maybe they get the body to release insulin despite not having sugars. Avoid again.
  • Again last week I met a friend for dinner and we had humongous amounts of seafood. I didn’t eat carbs with it. Minimal spike.
  • Some foods cause an immediate spike. Some cause a delayed spike. Some cause a crash.
  • Crashes in glucose levels (usually 1-2 hours after a massively insulin-triggering meal) were massively correlated with me feeling low and jittery and unable to focus. It didn’t matter how recently I had taken the last dose of my ADHD medication – glucose crash meant I was unable to focus.
  • Milk is not as good for me as I thought. It does produce a spike (and crash), especially when I’m drinking on an empty stomach
  • Speaking of drinking, minimal impact from alcohols such as whiskey or wine. I didn’t test beer (I know it’s not good)
  • Biryani (Nagarjuna) wasn’t so bad – again it was important I ate very little rice and lots of chicken (ordered sides)
  • Just omelette is great. Omelette with a slice of toast not so.

All these notes are for myself. Any benefit you get from this is only a bonus.

Signalling, anti-signalling and dress codes

A few months back, I read Rob Henderson‘s seminal work on signalling and anti-signalling. To use a online community term, I’ve been “unable to unsee”. Wherever I see, I see signalling, and anti-signalling. Recently, I thought that some things work as signals to one community but anti-signals to others. And so on.

I was reminded of this a couple of weekends back when we were shopping at FabIndia. Having picked up a tablecloth and other “house things”, my wife asked if I wanted to check out some shirts. “No, I have 3 FabIndia shirts in the washing pile”, I countered. “I like them but maintenance is too hard, so not buying”.

The issue with FabIndia shirts is  that they leech colour, so you cannot put them in the washing machine (especially not with other clothes). Sometimes you might get lucky to get a quorum of indigos (and maybe jeans) to put in the machine at a time, but if you want to wear your FabIndia clothes regularly you have no option but to wash them by hand. Or have them someone wash them for you.

That gave rise to the thought that FabIndia shirts can possibly send out a strong signal that you are well to do, since you have domestic help – since these shirts need to be hand washed and then pressed before wearing (the logistics of giving clothes for pressing near my house aren’t efficient, and if I’ve to do it consistently, I need help with that. I end up wearing Tshirts that don’t need much ironing instead).

On the other hand, the black T-shirts (I have several in various styles, with and without my company logo) I wear usually are very low maintenance. Plonk them into the washing machine with everything else. No need of any ironing. I don’t need no help to wear such clothes.

And then I started thinking back to the day when I would wear formal shirts regularly. Those can go into the washing machine (though you are careful on what you put in with them), but the problem is that they need proper ironing. You either spend 20 minutes per shirt, or figure out dynamics of giving them out for ironing regularly (if you’re lucky enough to have an iron guy close to your house) – which involves transaction costs. So again wearing well cleaned and ironed formals sends out a signal that you are well to do.

I think it was Rob Henderson again (not sure) who once wrote that the “casualisation” of office dress codes has done a disservice to people from lower class backgrounds. The argument here is that when there is a clear dress code (suits, say), everyone knows what to wear, and while you can still signal with labels and cufflinks and the cut of your suit, it is hard to go wrong.

In the absence of formal dress codes, however, people from lower class are at a loss on what to wear (since they don’t know what the inherent signals of different clothes are), and the class and status markers might be more stark.

My counterargument is that the effort to maintain the sort of clothes most dress codes demand is significant, and imposing such codes puts an unnecessary burden on those who are unable to afford the time or money for it. The lack of a dress code might make things ambiguous, but in most places, the Nash equilibrium is most people wearing easy-to-maintain clothes (relative to the image they want to portray), and less time and money going in conformity.

As it happened, I didn’t buy anything at FabIndia that day. I came home and looked in the washing bin, and found a quorum of indigo shirts (and threw in my 3-month old jeans) to fill the washing machine. My wife requested our domestic helper to hand-wash the brown FabIndia shirts. While watching the T20 world cup, I ironed the lot. I’m wearing one of them today, as I write this.

They look nice (though some might think they’re funny – that’s an anti-signal I’m sending out). They’re comfortable. But they require too much maintenance. Tomorrow I’m likely to be in a plain black t-shirt again.

George Mallory and Metrics

It is not really known if George Mallory actually summited the Everest in 1924 – he died on that climb, and his body was only found in 1999 or so. It wasn’t his first attempt at scaling the Everest, and at 37, some people thought he was too old to do so.

There is this popular story about Mallory that after one of his earlier attempts at scaling the Everest, someone asked him why he wanted to climb the peak. “Because it’s there”, he replied.

George Mallory (extreme left) and companions

In the sense of adventure sport, that’s a noble intention to have. That you want to do something just because it is possible to do it is awesome, and can inspire others. However, one problem with taking quotes from something like adventure sport, and then translating it to business (it’s rather common to get sportspeople to give “inspirational lectures” to business people) is that the entire context gets lost, and the concept loses relevance.

Take Mallory’s “because it’s there” for example. And think about it in the context of corporate metrics. “Because it’s there” is possibly the worst reason to have a metric in place (or should we say “because it can be measured?”). In fact, if you think about it, a lot of metrics exist simply because it is possible to measure them. And usually, unless there is some strong context to it, the metric itself is meaningless.

For example, let’s say we can measure N features of a particular entity (take N = 4, and the features as length, breadth, height and weight, for example). There will be N! was in which these metrics can be combined, and if you take all possible arithmetic operations, the number of metrics you can produce from these basic N metrics is insane. And you can keep taking differences and products and ratios ad infinitum, so with a small number of measurements, the number of metrics you can produce is infinite (both literally and figuratively). And most of them don’t make sense.

That doesn’t normally dissuade our corporate “measurer”. That something can be measured, that “it’s there”, is sometimes enough reason to measure something. And soon enough, before you know it, Goodhart’s Law would have taken over, and that metric would have become a target for some poor manager somewhere (and of course, soon ceases to be a metric itself). And circular logic starts from there.

That something can be measured, even if it can be measured highly accurately, doesn’t make it a good metric.

So what do we do about it? If you are in a job that requires you to construct or design or make metrics, how can you avoid the “George Mallory trap”?

Long back when I used to take lectures on logical fallacies, I would have this bit on not mistaking correlation for causation. “Abandon your numbers and look for logic”, I would say. “See if the pattern you are looking at makes intuitive sense”.

I guess it is the same for metrics. It is all well to describe a metric using arithmetic. However, can you simply explain it in natural language, and can the listener easily understand what you are saying? And more importantly, does that make intuitive sense?

It might be fashionable nowadays to come up with complicated metrics (I do that all the time), in the hope that it will offer incremental benefit over something simpler, but more often than not the difficulty in understanding it makes the additional benefit moot. It is like machine learning, actually, where sometimes adding features can improve the apparent accuracy of the model, while you’re making it worse by overfitting.

So, remember that lessons from adventure sport don’t translate well to business. “Because it’s there” / “because it can be measured” is absolutely NO REASON to define a metric.

Speed, Accuracy and Shannon’s Channel Coding Theorem

I was probably the CAT topper in my year (2004) (they don’t give out ranks, only percentiles (to two digits of precision), so this is a stochastic measure). I was also perhaps the only (or one of the very few) person to get into IIMs that year despite getting 20 questions wrong.

It had just happened that I had attempted far more questions than most other people. And so even though my accuracy was rather poor, my speed more than made up for it, and I ended up doing rather well.

I remember this time during my CAT prep, where the guy who was leading my CAT factory once suggested that I was making too many errors so I should possibly slow down and make fewer mistakes. I did that in a few mock exams. I ended up attempting far fewer questions. My accuracy (measured as % of answers I got wrong) didn’t change by much. So it was an easy decision to forget above accuracy and focus on speed and that served me well.

However, what serves you well in an entrance exam need not necessarily serve you well in life. An exam is, by definition, an artificial space. It is usually bounded by certain norms (of the format). And so, you can make blanket decisions such as “let me just go for speed”, and you can get away with it. In a way, an exam is a predictable space. It is a caricature of the world. So your learnings from there don’t extend to life.

In real life, you can’t “get away with 20 wrong answers”. If you have done something wrong, you are (most likely) expected to correct it. Which means, in real life, if you are inaccurate in your work, you will end up making further iterations.

Observing myself, and people around me (literally and figuratively at work), I sometimes wonder if there is a sort of efficient frontier in terms of speed and accuracy. For a given level of speed and accuracy, can we determine an “ideal gradient” – on which way a person needs to move in order to make the maximum impact?

Once in a while, I take book recommendations from academics, and end up reading (rather, trying to read) academic books. Recently, someone had recommended a book that combined information theory and machine learning, and I started reading it. Needless to say, within half a chapter, I was lost, and I had abandoned the book. Yet, the little I read performed the useful purpose of reminding me of Shannon’s channel coding theorem.

Paraphrasing, what it states is that irrespective of how noisy a channel is, using the right kind of encoding and redundancy, we will be able to predictably send across information at a certain maximum speed. The noisier the channel, the more the redundancy we will need, and the lower the speed of transmission.

In my opinion (and in the opinions of several others, I’m sure), this is a rather profound observation, and has significant impact on various aspects of life. In fact, I’m prone to abusing it in inexact manners (no wonder I never tried to become an academic).

So while thinking of the tradeoff between speed and accuracy, I started thinking of the channel coding theorem. You can think of a person’s work (or “working mind”) as a communication channel. The speed is the raw speed of transmission. The accuracy (rather, the lack of it) is a measure of noise in the channel.

So the less accurate someone is, the more the redundancy they require in communication (or in work). For example, if you are especially prone to mistakes (like I am sometimes), you might need to redo your work (or at least a part of it) several times. If you are the more accurate types, you need to redo less often.

And different people have different speed-accuracy trade-offs.

I don’t have a perfect way to quantify this, but maybe we can think of “true speed of work” by dividing the actual speed in which someone does a piece of work by the number of iterations they need to get it right.  OK it is not so straightforward (there might be other ways to build redundancy – like getting two independent people to do the same thing and then tally the numbers), but I suppose you get the drift.

The interesting thing here is that the speed and accuracy is not only depend on the person but the nature of work itself. For me, a piece of work that on average takes 1 hour has a different speed-accuracy tradeoff compared to a piece of work that on average takes a day (usually, the more complicated and involved a piece of analysis, the more the error rate for me).

In any case, the point to be noted is that the speed-accuracy tradeoff is different for different people, and in different contexts. For some people, in some contexts, there is no point at all in expecting highly accurate work – you know they will make mistakes anyways, so you might as well get the work done quickly (to allow for more time to iterate).

And in a way, figuring out speed-accuracy tradeoffs of the people who work for you is an important step in getting the best out of them.

 

Financial ratio metrics

It’s funny how random things stick in your head a couple of decades later. I don’t even remember which class in IIMB this was. It surely wasn’t an accounting or a finance class. But it was one in which we learnt about some financial ratios.

I don’t even remember what exactly we had learnt that day (possibly return on invested capital?). I think it was three different financial metrics that can be read off a financial statement, and which then telescope very nicely together to give a fourth metric. I’ve forgotten the details, but I remember the basic concepts.

A decade ago, I used to lecture frequently on how NOT to do data analytics. I had this standard lecture that I called “smelling bullshit” that dealt with common statistical fallacies. Things like correlation-causation, or reasoning with small samples, or selection bias. Or stocks and flows.

One set of slides in that lecture was about not comparing stocks and flows. Most people don’t internalise it. It even seems like you cannot get a job as a journalist if you understand the distinction between stocks and flows. Every other week you see comparisons of someone’s net worth to some country’s GDP, for example. Journalists make a living out of this.

In any case, whenever I would come to these slides, there would always be someone in the audience with a training in finance who would ask “but what about financial ratios? Don’t we constantly divide stocks and flows there?”

And then I would go off into how we would divide a stock by a flow (typically) in finance, but we never compared a stock to a flow. For example, you can think of working capital as a ratio – you take the total receivables on the balance sheet and divide it by the sales in a given period from the income statement, to get “days of working capital”. Note that you are only dividing, not comparing the sales to the receivables. And then you take this ratio (which has dimension “days”) and then compare it across companies or across regions to do your financial analysis.

If you look at financial ratios, a lot of them have dimensions, though sometimes you don’t really notice it (I sometimes say “dimensional analysis is among the most powerful tools in data science”). Asset turnover, for example, is sales in a period divided by assets and has the dimension of inverse time. Inventory (total inventory on BS divided by sales in a period) has a dimension of time. Likewise working capital. Profit margins, however, are dimensionless.

In any case, the other day at work I was trying to come up with a ratio for something. I kept doing gymnastics with numbers on an excel sheet, but without luck. And I had given up.

Nowadays I have started taking afternoon walks at office (whenever I go there), just after I eat lunch (I carry a box of lunch which I eat at my desk, and then go for a walk). And on today’s walk (or was it Tuesday’s?) I realised the shortcomings in my attempts to come up with a metric for whatever I was trying to measure.

I was basically trying too hard to come up with a dimensionless metric and kept coming up with some nonsense or the other. Somewhere during my walk, I thought of finance, and financial metrics. Light bulb lit up.

My mistake had been that I had been trying to come up with something dimensionless. The moment I realised that this metric needs to involve both stocks and flows, I had it. To be honest, I haven’t yet come up with the perfect metric (this is for those colleagues who are reading this and wondering what new metric I’ve come up with), but I’m on my way there.

Since both a stock and a flow need to be measured, the metric is going to be a ratio of both. And it is necessarily going to have dimensions (most likely either time or inverse time).

And if I think about it (again I won’t be able to give specific examples), a lot of metrics in life will follow this pattern – where you take a stock and a flow and divide one by the other. Not just in finance, not just in logistics, not just in data science,  it is useful to think of metrics that have dimensions, and express them using those dimensions.

Some product manager (I have a lot of friends in that profession) once told me that a major job of being a product manager is to define metrics. Now I’ll say that dimensional analysis is the most fundamental tool for a product manager.

Stereotypes, K-Dramas and ADHD

My wife is currently watching a K-drama which she said I might like, because the leading female character in that is autistic. “You have ADHD, and you might be on the spectrum, so you can at least half watch with me”, she said.

Given that it is in a language that I don’t know, I can’t really “half watch”, but I’ve sat through an aggregate of about ten-fifteen minutes of the show in the last 2-3 days.

My first impression of the show and the character was “gosh she’s such a stereotype”. They showed her in court or something (the character is a lawyer), and she takes something someone says extremely literally. And then there was something else that seemed rather stereotypical and then I almost wrote off the show.

And then they showed one scene, which is also possibly stereotypical (I don’t know) but which I massively massively empathised with, and then my view of the show turned, and at this point in time I’m “half watching” the show (to the best extent you can when you need subtitles) as I write this.

I might have written about this before – back in 2013, after about six months of taking methylphenidate for my ADHD, I had started to believe that it was crimping my creativity. What I thought had defined me until then, which is also something you see a lot on this blog, is connecting very random and seemingly unconnected things.

In fact, I considered that to be one of my superpowers – to see connections that a lot of other people can’t. After a few days of not taking the medication (when I saw myself making those connections again), I decided to get off them. I didn’t get back on till 2020 (as things stand I take them).

Anyway, back to the show, the protagonist is shown having a vision of a whale, and that vision reminds her of something else, and she keeps connecting one thing to another (I was really empathising with her in this snippet), and gets a massive insight that solves the case that she is on. My view of the show turned.

A few pertinent observations before I continue:

  • One of the speakers at one of the early episodes of NED Talks made a point about how some of have possibly evolved to have what are now considered as “disorders”. “Hunting and gathering are team activities, and you need different skills for it. Not everyone needs to run after the prey. The autistic person in the tribe will be able to detect where the prey is and the rest can hunt it”.

    So we have evolved to be different like this. Putting together genetics and game theory, it is a “mixed strategy”.

  • The downside of being able to connect seemingly unconnected things is that you tend to hallucinate. I’ve written about this, in a completely different context.
  • Another downside of seeing visions and connecting unconnected things to find a solution to the problem that you’re working on is that it makes it incredibly difficult to communicate your solution. Having seen it in a “vision”, it is less explainable. You cannot “show steps”. Then again I don’t think this trait is specific to people with ADHD or on the autism spectrum – I know one person (very well) who doesn’t have ADHD by any stretch of imagination, but has a worse problem than me in showing steps
  • I have always been happy that I didn’t study law because it’s “too fighter” and “involves too much mugging”. But then the protagonist in this show shows remarkable attention to detail on things that she can hyperfocus on (and which her visions of whales can lead to). I’ve also read about how Michael Burry found holes in CDOs (back in 2008 during the global financial crisis) because he was able to hyperfocus on some details because he has Aspergers (now classified under the autism spectrum in general)

Anyway as I was writing this, I half watched parts of the second episode. In this again, the protagonist had another vision of the whales, which led to something else and an insight that led her to win her case. Now it appears stereotyping again, after I saw the same setup in two different episodes – it seems like the standard format the show has set up on.

I don’t know if I’ll half watch any more.