Creative Cycles

When you’re doing creative work, your work broadly falls into two phases – the “invention phase” and the “implementation phase”. Both imply what they mean.

There are times when you are tinkering around and experimenting to find something fundamentally new that is cool. And then, once you have made the breakthrough in finding something cool, you need to make it useful. And this can take considerable amount of work, and its own creativity.

So if you are one person doing a “creative job”, your work will alternate in these cycles – where you create and you implement. The cycles are unlikely to be periodic. Some creative solutions are so creative that implementation is a breeze. In most cases, the inspiration is only 1% of the problem – the devil in the details for which you need to perspire.

When you are part of a creative team, this cycle thing can play out in different ways. Some teams form a caste system, where one set of people work purely on the invention phase, while the other works on the implementation phase. This is especially useful when solving highly complex problems, in which case the skills required for the invention and implementation phases are different.

The big cost of having separate teams like his is the cost of communication (AGES back, when GPUs were just becoming a thing, I was part of a committee that was exploring the use of GPUs in our work. One of the findings there was that GPUs can do the work incredibly fast, but the data transfer from GPUs to CPUs was slow, and could be a bottleneck. I assume that problem is solved now). People sometimes grossly underestimate the effort involved in communicating your solution to someone else. Even if you manage to communicate, there can be significant handholding that might be required to get the other team to take forward your invention.

And so this investment in communication cost is worth it if and only if the work is complex enough. Think of large industrial projects – such as the manufacture of the iPhone, for example – they are complex enough that you need several specialist teams to perform the entire creative process. And in the larger scheme of the complexity, the cost of communication across teams is small.

On the other hand, this usage of multiple teams to perform a creative process can be massive overkill for simpler work – there the cost of communication can far overpower the gains in efficiency through specialisation.

Anyway, I’m getting distracted here.

Coming back, the alternative is to have the same people or sub-teams perform the invention and implementation stages of the creative process. Here, I’ve seen things play out in multiple ways.

Some teams are uncorrelated – this means that different members or sub-teams are in different phases of the work. As a consequence, this kind of a team constantly provides creative output. When some of the people are deep in implementation, others are inventing. And the other way round. This means that the team is constantly both coming up with new ideas and delivering stuff.

Other teams can be more correlated – either everyone is working on the same thing, or the whole team moves in sync (invention at some points in time, implementation at others). Here the issue is that there can go long periods of time without the team really producing anything – in the common invention phase, no shit is getting done. In the common implementation phase, there are no new ideas.

This can lead to stagnation in the team, and frustration outside. And so not ideal.

The other related concept is in terms of management. Some managers of creative teams are better off at managing the invention phase. Others are better off at managing the implementation phase. Given that the creative process involves both, for the team to be effective, we need managers who can manage both as well.

And this is easier said than done in a single person, and so you need a management team. And what you find is that you have a “complementary number two” (no pun intended). If you as the team leader is better off at invention, you get a number two who is better at implementation. And the two (or more) of you together manage the process.

I’ve spoken about this before – this can sometimes lead to suboptimal succession. Let’s say the inventive head leaves. The organisation promotes the implementation number two. Now, it is contingent upon this new number one to get a (inventive) number two asap. If that doesn’t happen, invention can cease. The team will carry on for a while implementing the already invented stuff, and then grind to a halt.

Similarly if an implementation head leaves, the inventive number two gets promoted. And unless a new implementation number two is hired, you’ll see lots of proofs of concept and little actual implementation. Again suboptimal.

Status and money

Over the last week or so, I’ve been discussing this post by Robin Hanson with just about anyone. The first paragraph is the one that caught my attention.

Having a romantic partner is useful in many ways. You won’t be as lonely, you can ask them for advice, you can do activities together, and you can share transport and even a household with them. But if you look carefully, you will notice that many people don’t choose such partners mainly for their promise in such roles. They instead seek high status partners, who make them look good by association. Partners who are hot, funny, rich, powerful, etc.

Nevertheless, I urge you to read the whole thing. Hanson goes on to talk about status in several other fields, such as politics or in organisations.

Broadly paraphrasing (you should still read the whole thing), he says that people want to be associated with people with high status, or people who add status to them. So politicians who can project higher status will get elected. Organisations will appoint people who can further increase the status of the organisation.

I was thinking about this today from the point of view of last night’s post, where I had compared my life in my (current) full time job to that of a consultant, which I had been for nine years prior.

Sometimes it is common for us to comment, or gossip, that someone  got hired purely on the strength of their reputation, and that their abilities are not extraordinary. Sometimes, reputations can be self-fulfilling – if you can somehow get the reputation of being good at something, more people will start with the Bayesian prior that you’re good at that, and as long as you don’t suck at that thing, the prior will continue to hold. And so more people will think you’re good at it, and so on.

So when I think of my own career, basically I realise the way to go is to get into a position that my sheer presence adds status to the organisation I’m associated with. That way, they will be more forgiving of the work that I do (or don’t do). At the same time, from my own perspective, the organisation also needs to (at least marginally) add to my status – at some level I may not want to join a club that wants me as a member.

I remember back in the day when I was consulting – one of my clients, during the negotiations prior to the engagement, had wanted me to put on LinkedIn that I was working for them. Now when I think of it from the point of view of Hanson’s post, this was the client leveraging my then reputation in data to further their own status.

This is what I need to bring to my employers as well (I have no clue if I do already with my current ones – though I’m not so popular within my (data science) domain in india). The target, if I were to think of it, is to get into that self-fulfilling space when it comes to status – that people want me just because I’m me and bring along a certain (positive) status.

Now that I’ve identified the target, I need to figure out how to get there. I know in his famous podcast, Naval said that we should optimise for wealth (a positive sum game) rather than for status (a zero sum game). But Hanson’s post, and my analysis of it, suggests that status can also lead to wealth. I need to figure out the tradeoff now!

Why social media went woke

When Elon Musk took over twitter recently, one of the “drain the swamp” things he did was to get rid of the platform’s overt bias towards political correctness and “wokeness”. Out went most of the “trust and safety” team. In came Donald Trump (though he hasn’t tweeted since) and the guy who stupidly got himself arrested in Romania.

As some people in my office have never tired of saying, Musk let go of 70% of the company, and the app still largely runs fine (apart from some weird bugs that creep in once in a while). One part of twitter that is NOT running fine, though, is advertising – you might be able to guess that from the quality of ads you are getting served on your timeline nowadays. There are two theories behind this – one is that Musk got rid of most of the ad sales team, and the other is that advertisers don’t want to advertise on twitter given it is more prone to free speech now.

The latter was a bit of a surprising theory to me, since my assumption had always been that what advertisers largely care for is audiences, and relevance of the audiences to their products; and as long as the audiences were there, the advertisers would come.

However, something I heard on a podcast this morning on my way to work made me question this assumption. Listen to this (the link is from the approximate point I want you to listen):

So in this conversation, Jeff Green talks about “brand safety” in the context of advertising. What he effectively says is that advertisers are finicky about what kind of content their ads come next to. He says “right now I would say the value of user generated content has actually gone down dramatically because of brand safety”.

Back in IIMB, there were a couple of fellows who formed a quiz team called “Mary Magdalenes: The Reformed Prostitutes”. During our annual fest Unmaad, they conducted a quiz, which (I think) was sponsored by IBM. I I remember right, the title slide of the quiz said “Unmaad Open Quiz, brought to you by Mary Magdalenes: The Reformed Prostitutes”, with the logo of IBM (or whoever the sponsor was) somewhere on the slide.

The sponsors did not take to it too kindly – I was doing a quiz the following day and the sponsorship coordinators demanded to inspect my deck so that there were no such potentially embarrassing juxtapositions.

As it happens, one, or maybe both, of Mary Magdalenes: The Reformed Prostitutes, went into a career in marketing. However, contrary to the image you get by looking at advertising “creatives”, advertisers are fundamentally boring people. They are insanely risk averse, and very very loathe to bring even the slightest hint of controversy to their brands.

So, this is why social media goes woke. They don’t care about “misinformation” and “fake news” and porn and slander for the sake of you or me – as long as we are visiting their sites and looking at the ads there, they are happy. The reason they clamp down on free speech in the name of “trust and safety” is for the sake of the (normally rather boring) advertisers, who want certainty on the sort of content next to which their ads are shown.

And so, driven by risk-averse advertisers, social media platforms censor free speech and “go woke”, much to the chagrin of people like Musk and me.

Recently I read this fantastic essay by Robin Hanson on why most people are boring. Only a very long quote will do justice, but that too partially. You should read the whole essay.

If we act interesting, passionate, and opinionated in public, we are likely to seem to claim high status for ourselves, and to touch on sacred subjects, either by word or deed. And this makes us quite vulnerable to accusations of arrogance and violating the sacred. Because: a) the sacred is full of contradictions, so that saying truths clearly does not protect you, b) observers feel free to use complex codings to attribute to you intentions that you did not literally say (or have), and c) observers are much more willing to accept unfair and unproven accusations if they are seen as “punching up” at presumed dominant or evil races, genders, ages, professions, or political factions.

The degree of this danger is made clear, I think by the reaction of the “gods” among us. The public tone of huge powerful firms and other orgs is consistently “officious”, i.e., mild boring supplication.

Mild boring supplication is all okay. Just that they impose upon you and me with their ad dollars, meaning that places where their ad dollars go also tend to mild boring supplication. And thus for us, it is death by a thousand bores.

Discoverability and chaos

Last weekend (4-5 Feb) I visited Blossom Book House on Church Street (the “second branch” (above Cafe Matteo), to be precise). I bought a total of six books that day, of which four I was explicitly looking for (including two of Tufte’s books). So only two books were “discovered” in the hour or so I spent there.

This weekend (11-12 Feb) I walked a little further down Church Street (both times I had parked on Brigade Road), and with wife and daughter in tow, to Bookworm. The main reason for going to Bookworm this weekend is that daughter, based on a limited data points she has about both shops, declared that “Bookworm has a much better collection of Geronimo Stilton books, so I want to go there”.

This time there were no books I had intended to buy, but I still came back with half a dozen books for myself – all “discovered”. Daughter got a half dozen of Geronimos. I might have spent more time there and got more books for myself, except that the daughter had finished her binge in 10 minutes and was now desperate to go home and read; and the wife got bored after some 10-20 minutes of browsing and finding one book. “This place is too chaotic”, she said.

To be fair, I’ve been to Blossom many many more times than I’ve been to Bookworm (visits to the latter are still in single digits for me). Having been there so many times, the Blossom layout is incredibly familiar to me. I know  that I start with the section right in front of the billing counter that has the bestsellers. Then straight down to the publisher-wise shelves. And so on and so forth.

My pattern of browsing at Blossom has got so ritualised that I know that there are specific sections of the store where I can discover new books (being a big user of a Kindle, I don’t really fancy very old books now). And so if I discover something there, great, else my browsing very quickly comes to a halt.

At Bookworm, though, I haven’t yet figured out the patterns in terms of how they place their books. Yes, I agree with my wife that it is “more random”, but in terms of discoverability, this increased randomness is a feature for me, not a bug! Not knowing what books to expect where, I’m frequently pleasantly surprised. And that leads to more purchases.

That said, the chaos means that if I go to the bookstore with a list of things to buy, the likelihood of finding them will be very very low (that said, both shops have incredibly helpful shopkeepers who will find you any book that you want and which is in stock at the store).

Now I’m thinking about this in the context of e-commerce. If randomness is what drives discoverability, maybe one bug of e-commerce is that it is too organised. You search for something specific, and you get that. You search for something vague, and the cost of going through all the results to find something you like is very high.

As for my books, my first task is to finish most of the books I got these weekends. And I’ll continue to play it random, and patronise both these shops.

Decision making and explainability

This is NOT a post about AI. It is, instead, about real intelligence.

My hypothesis is – the more you need to explain your decisions to people, the worse your decision-making gets.

Basically, instinct gets thrown out of the window.

Most of you who have worked in a company would have seen a few attempts at least of the company trying to be “more data driven”. Instead of making decisions on executives’ whims and will, they decide to set up a process with objective criteria. The decision is evaluated on each of these criteria and weights drawn up (if the weights are not known and you have a large number of known past decisions, this is just logistic regression). And then a sumproduct is computed, based on which the decision is made.

Now, I might be biased by the samples of this I’ve seen in real life (both in companies I’ve worked for and where I’ve been a consultant), but this kind of decision making usually results in the most atrocious decisions. And it is not even a problem with the criteria that are chosen or the weights each is assigned (so optimising this will get you nowhere). The problem is with the process.

As much as we would like to believe that the world is objective (and we are objective), we as humans are inherently instinctive and intuitive individuals (noticed that anupraas alankaar?). If we weren’t we wouldn’t have evolved as much as we have, since a very large part of the decisions we need to make need to be made quickly (running from a lion when you see one, for example, or braking when the car in front of you also brakes suddenly).

Quick decisions can never be made based on first principles – to be good at that, you need to have internalised the domain and the heuristics sufficiently, so that you know what to do.

I have this theory on why I didn’t do well in traditional strategy consulting (it was the first career I explored, and I left my job in three months) – it demanded way too much structure, and I had faked my way in. For all the interview cases, I would intuitively come up with a solution and then retrofit a “framework”. N-1 of the companies I applied to had possibly seen through this. One didn’t and took me in, and I left very soon.

What I’m trying to say is – when you try to explain your decisions, you are trying to be analytical about something you have instinctively come to the conclusion about, and with the analysis being “a way to convince the other person that I didn’t use my intuition”.

So when a bunch of people come up with their own retrofits on how they make the decision, the “process” that you come up with is basically a bunch of junk. And when you try to follow the process the next time, you end up with a random result.

The other issue with explaining decisions is that you try to come up with explanations that sound plausible and inoffensive. For example, you might interview someone (in person) and decide you don’t want to work with them because they have bad breath (perfectly valid, in my opinion, if you need to work closely with them – no pun intended). However, if you have to document your reason for rejection, this sounds too rude. So you say something rubbish like “he is overqualified for the role”.

At other times, you clearly don’t like the person you have spoken to but are unable to put your rejection reason in a polite manner, so you just reverse your decision and fail to reject the person. If everyone else also thinks the same as you (didn’t like but couldn’t find a polite enough reason to give, so failed to reject), through the “Monte Carlo process”, this person you clearly didn’t like ends up getting hired.

Yet another time, you might decide to write an algorithm for your decision (ok I promised to not talk about AI here, but anyways). You look at all the past decisions everyone has made in this context (and the reasons for those), and based on that, you build an algorithm. But then, if all these decisions have been made intuitively and the people’s documented decisions only retrofits, you are basing your algorithm on rubbish data. And you will end up with a rubbish algorithm (or a “data driven process”).

Actually – this even applies to artificial intelligence, but that is for another day.


The Twelfth Camel

In a way, this post should write itself. For those of you with context, the title should be self explanatory. And you need not read further.

For the rest I’ll write a rather small essay.

The story is of the old Arab who died leaving his eldest son half his wealth, the second a fourth of his wealth and the youngest one sixth. The wealth in question turned out to be 11 camels.

With 11 being a prime number, how could this will be executed without any of the camels being executed? An ingenious neighbour came in and lent his camel. Now there were twelve. The three sons respectively received 6 (\frac{12}{2}), , 3 (\frac{12}{4}) and 2 (\frac{12}{6}) camels respectively. One camel was left over – the neighbour’s, who took it back.

This is mathematically inaccurate, since the sons received fractions of their father’s wealth slightly different from what he had intended. However, in general in life, this parable of the twelfth camel offers a useful metaphor.

In engineering, this is rather common – you have systems such as a choke, for example, to enable systems to get started from a “cold start process”. The choke comes in only at the time of startup – once the thing has started, it plays no role.

However, it has its role in normal life and business as well. For example, after a bad breakup, you might rebound to a “stop gap partner”. You know that this is not going to be a long term relationship, but this partner helps you tide over the shock of the bad breakup, and by the time this relationship (inevitably) breaks up, it has achieved its purpose of getting you back on track. And you get on with life, finding more long term partners.

Then, when the company is in deep trouble, you have specialists who come in to take over with the explicit goal of cleaning things up and getting the company ready for new ownership. For exanple, John Ray III has recently taken over as CEO of FTX. His previous notable appointment was as CEO of Enron, soon after that scandal had broken. He will not stay for a long term – he will just clean things up and move on.

And sometimes the role of the twelfth camel is rather more specific. Apart from “generic cleaning”, the temporary presence of the twelfth camel can be used to get rid of people who had earlier been hard to get rid of.

In sum, the key thing about the twelfth camel theory is that the neighbour knew all along that he was going to get back his camel. In other words, it is a deliberate temporary measure intended to achieve a certain set of specific outcomes. And the camel itself may not know that it is being “lent”!

Key Person Risk and Creative Professions

I’m coming to the conclusion that creative professions inevitably come with a “key person risk”. And this is due to the way teams in such professions are usually built.

I’ll start with a tweet that I put out today.

(I had NOT planned this post at the time when I put out this tweet)

I’ll not go into defining creative professions here, but I will leave it to say that you typically know it when you see one.

The thing with teams in such professions is that people who are good and creative are highly unlikely to get along with each other. Going into the animal kingdom for an analogy, we can think of dividing everyone in any such professions into “alphas” and “betas”. Alphas are the massively creative people who usually rise to lead their teams. Betas are the rest.

And given that any kind of creativity is due to some amount of lateral thinking, people good at creative professions are likely to hallucinate a bit (hallucination is basically lateral thinking taken to an extreme). And stretching it a bit more, you can say that people who are good at creative tasks are usually mad in one way or another.

As I had written briefly this morning, it is not usual for mad people (especially of a similar nature of madness) to get along with each other. So if you have a creative alpha leading the team, it is highly unlikely that he/she will have similar alphas in the next line of leadership. It is more likely that the next line of leadership will have people who are good complements to the alpha leader.

For example, in the ongoing World Cup, I’ve seen several tactical videos that have all said one thing – that Rodrigo De Paul’s primary role in the Argentinian team is to “cover for Messi”. Messi doesn’t track back, but De Paul will do the defending for him. Messi largely switches off, but De Paul is industrious enough to cover for Messi. When Messi goes forward, De Paul goes back. When Messi drops deep, De Paul makes a forward run.

This is the most typical creative partnership that you can get – one very obviously alpha creative supported by one or more steady performers who enable the creative person to do the creative work.

The question is – what happens when the creative head (the alpha) leaves? And the answer to this are going to be different in elite sport and the corporate world (and I’m mostly talking about the latter in this post).

In elite sport, when Messi retires (which he is likely to do after tomorrow’s final, irrespective of the result), it is virtually inconceivable that Argentina will ask De Paul to play in his position. Instead, they will look into others who are already playing in a sort of Messi role, maybe (or likely) at an inferior level and bring them up. De Paul will continue to play his role of central midfielder and continue to support whoever comes into Messi’s role.

In corporate setups, though, when one employee leaves, the obvious thing to do is to promote that person’s second in command. Sometimes there might be a battle for succession among various seconds in command, and the losers also leave the company. For most teams, where seconds in command are usually similar in style to the leader, this kind of succession planning works.

For creative teams, however, this usually leads to a disaster. More often than not, the second in command’s skills will be very different from that of the leader. If the leader had been an alpha creative (that’s the case we’re largely discussing here), the second in command is more likely to be a steady “water carrier” (a pejorative term used to describe France’s current coach Didier Deschamps).

And if this “water carrier” (no offence meant to anyone by this, but it is a convenient description) stays in the job for a long time, it is likely that the creative team will stop being creative. The thing that made it creative in the first place was the alpha’s leadership (this is especially true of small teams), and unless the new boss has recognised this and brings in a new set of alphas (or identifies potential alphas in the org and quickly promotes them), the team will start specialising in what was the new boss’s specialisation – which is to hold things steady and do all the right things and cover for someone who doesn’t exist any more.

So teams in creative professions have a key man risk in that if a particularly successful alpha leaves, the team as it remains is likely to stagnate and stop being creative. The only potential solutions I can think of are:

  • Bring in a new creative from outside to lead the team. The second in command remains just that
  • Coach the second in command to identify diverse (and creative alpha) talents within the team and recognise that there are alphas and betas. And the second in command basically leads the team but not the creative work
  • Organise the team more as a sports team where each person has a specific role. So if the attacking midfielder leaves, replace with a new attacking midfielder (or promote a junior attacking midfielder into a senior attacking midfielder). Don’t ask your defensive midfielders to suddenly become an attacking midfielder
  • Put pressure from above for alphas to have a sufficient number of other alphas as the next line of command. Retaining this team is easier said than done, and without betas the team can collapse.

Of course, if you look at all this from the perspective of the beta, there is an obvious question mark about career prospects. Unless you suddenly change your style (easier said than done), you will never be the alpha, and this puts in place a sort of glass ceiling for your career.

More on CRM

On Friday afternoon, I got a call on my phone. It was  “+91 9818… ” number, and my first instinct was it was someone at work (my company is headquartered in Gurgaon), and I mentally prepared a “don’t you know I’m on vacation? can you call me on Monday instead” as I picked the call.

It turned out to be Baninder Singh, founder of Savorworks Coffee. I had placed an order on his website on Thursday, and I half expected him to tell me that some of the things I had ordered were out of stock.

“Karthik, for your order of the Pi?anas, you have asked for an Aeropress grind. Are you sure of this? I’m asking you because you usually order whole beans”, Baninder said. This was a remarkably pertinent observation, and an appropriate question from a seller. I confirmed to him that this was indeed deliberate (this smaller package is to take to office along with my Aeropress Go), and thanked him for asking. He went on to point out that one of the other coffees I had ordered had very limited stocks, and I should consider stocking up on it.

Some people might find this creepy (that the seller knows exactly what you order, and notices changes in your order), but from a more conventional retail perspective, this is brilliant. It is great that the seller has accurate information on your profile, and is able to detect any anomalies and alert you before something goes wrong.

Now, Savorworks is a small business (a Delhi based independent roastery), and having ordered from them at least a dozen times, I guess I’m one of their more regular customers. So it’s easy for them to keep track and take care of me.

It is similar with small “mom-and-pop” stores. Limited and high-repeat clientele means it’s easy for them to keep track of them and look after them. The challenge, though, is how do you scale it? Now, I’m by no means the only person thinking about this problem. Thousands of business people and data scientists and retailers and technology people and what not have pondered this question for over a decade now. Yet, what you find is that at scale you are simply unable to provide the sort of service you can at small scale.

In theory it should be possible for an AI to profile customers based on their purchases, adds to carts, etc. and then provide them customised experiences. I’m sure tonnes of companies are already trying to do this. However, based on my experience I don’t think anyone is doing this well.

I might sound like a broken record here, but my sense is that this is because the people who are building the algos are not the ones who are thinking of solving the business problems. The algos exist. In theory, if I look at stuff like stable diffusion or Chat GPT (both of which I’ve been playing around with extensively in the last 2 days), algorithms for stuff like customer profiling shouldn’t be THAT hard. The issue, I suspect, is that people have not been asking the right questions of the algos.

On one hand, you could have business people looking at patterns they have divined themselves and then giving precise instructions to the data scientists on how to detect them – and the detection of these patterns would have been hard coded. On the other, the data scientists would have had a free hand and would have done some unsupervised stuff without much business context. And both approaches lead to easily predictable algos that aren’t particularly intelligent.

Now I’m thinking of this as a “dollar bill on the road” kind of a problem. My instinct tells me that “solution exists”, but my other instinct tells that “if a solution existed someone would have found it given how many companies are working on this kind of thing for so long”.

The other issue with such algos it that the deeper you get in prediction the harder it is. At the cohort (of hundreds of users) level, it should not be hard to profile. However, at the personal user level (at which the results of the algos are seen by customers) it is much harder to get right. So maybe there are good solutions but we haven’t yet seen it.

Maybe at some point in the near future, I’ll take another stab at solving this kind of problem. Until then, you have human intelligence and random algos.


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.