Luxury and frugal managers

You remember very random things from business school, nearly two decades on. Usually none of this is academic – the lessons are only “internalised”, not “learnt”. A lot of it is from outside the classroom, silly things someone said or did or posted on the internal bulletin board. Most of the stuff you remember are rather arbitrary things that professors said, and made it seem like something profound.

“Management is like making music”, one professor lectured to us in the first week of classes at IIMB, back in 2004. “First you make music with what you have, and when you don’t have that, you make music with what you have left”. It was rather random, but random enough to stick in my head 18 years on.

It has been another disappointing season beginning for Liverpool. I didn’t watch the Crystal Palace game last night, but I clearly remember feeling at multiple points during the draw at Fulham that this was “like 2020-21 all over again”. The sort of mistakes that Virgil Van Dijk made. The length of the injury list. More players (Thiago) going off injured midway through the game. Nat Phillips starting. And add some new issues – like having your shiny new striker getting himself sent off and suspended for 3 games for a stupid show of anger.

I see the list of substitutes.

  • 2
    Joe Gomez (s 63′)
  • 8
    Naby Keita
  • 13
    del Castillo Adrian
  • 14
    Jordan Henderson (s 63′)
  • 21
    Konstantinos Tsimikas (s 63′)
  • 28
    Fabio Carvalho (s 79′)
  • 43
    Stefan Bajcetic
  • 72
    Sepp van den Berg
  • 42
    Bobby Clark

Yes, there are youngsters (unlike 2021-22) but that is fully understandable. What I don’t understand is seeing youngsters I’ve never heard of. Two games in, I’m already getting the feeling that this will be a really hard league campaign.

I wonder if Klopp is more of a “luxury manager” than a “frugal manager”. These are two very different management styles, requiring very different skillsets. The names are fairly descriptive.

Luxury managers need luxury. They need resources for “option value”. In the corporate context, they need large budgets and space and little control over how they operate. And given all of this, a lot of the time, they deliver big. Yes – there are cases where they spectacularly fail (in which case they don’t stay on in their management jobs), but when they do deliver they deliver big.

Frugal managers don’t need any of this luxury. They are experts at making the most of whatever they have been given. In Ramnath’s words, they are adept at “making music with what they have left”. Any kind of luxury, any kind of optionality, seems like a waste to them. Why pay the option premium when you can get the same payoff through a complicated basket of one deltas?

And just like any other dichotomies (think of studs vs fighters, for example), luxury and frugal managers struggle in the opposite settings. Without the luxury, luxury managers are simply out of their depth. They are necessarily wasteful (a bit like Salah) and cannot produce if they are not able to waste some. However, they win big when they do.

Frugal managers are good at eking out solutions in terms of adversity, but abundant resources can overwhelm them. They won’t know what to do with it. More importantly, they are unable to deal with the expectations of delivering big (which come with the luxury) – they have been experts at delivering small against nonexistent expectations.

What about teams though? If you’ve been used to working for a luxury manager, what happens when you get a frugal manager? And the other way round? I don’t have immediate answers for this but I suppose you will struggle as well?

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.

Management Gurus

A few years back, one of the professors from my wife’s business school had come to London, and had given a talk to the alumni of the school. He was a professor of Operations Management (IIRC), and had given a talk about the Toyota Production System or some such.

At the time, my wife was working for Amazon and was completely unimpressed by the lecture. “This guy is 20 years behind”, she claimed, as she gave me a review of the lecture the same evening. The processes the professor had described were apparently extremely primitive compared to what Amazon was following at that time (I believe that).

So this got me thinking about management academia as a profession, and what value they add apart from teaching and preparing MBAs. I’ve sort of worked as one, though my position as Adjunct Professor at IIMB meant that I only taught and didn’t do any research. I did talk to some of the professors there during that time and tried to figure out what they were working on in terms of research.

Putting all this together with material I’ve gathered from Clayton Christensen’s obituaries, I think I’ve recognised a pattern that connects management research – it’s all about looking back at business over the last few years, deciphering patterns about them and then theorising about them.

In a sense it reminds me of second and third order levers. Scientific academic research is usually (though not always) cutting edge, with new science being created in the academic laboratories and then engineered in industries which then go on to commercialise this research.

Management research, on the other hand, is flipped. The true cutting edge in management happens at businesses, where the experimentation is relatively easier than experimenting with scientific stuff. Once some experimentation has happened at the business level and successes and failures have been observed, the academics get into action.

They look at the experiments that the industries did, meticulously collect data that documents the success or failure of these experiments (along with the external factors that might have affected the success or lack of it), and then theorise about the costs and benefits of these experiments, and the situations where they work (or not).

Sometimes the academics supplement their data gathering of the experiments and situations with experiments of their own, and some interviews, and then apply their deep academic and theoretical knowledge on top of it to create theories about them. And once the academic theoretical peer review process has taken place, the idea can get better traction in parts of the industry that have not already figured it out.

The competitive advantage that management academics have is that they sit an arm’s length away from the industries that they study, and they are able to gather data from large numbers of companies in order to build their theories. They may not be the originators of the ideas but their value addition in terms of synthesising ideas generated elsewhere is significant.

Slavedriver sandwich

Something that happened at home earlier today reminded me of my very first full-time job, which I had ended up literally running away from barely two months after I’d started. I like to call this the “slavedriver sandwich”.

The basic problem is this – you need to get someone you normally have no influence over to do something for you, and this something is contrary to what this person needs to do. You somehow need to convince this person to do this – effectively, you need to “slave-drive” her so that what you want done is done.

The problem is that you aren’t even sure that you want this thing to be done. The only reason you are slavedriving the person you’re slavedriving is because someone else (let’s call this person “the boss”) is slavedriving you, and trying to make you get this person to do this.

The boss is very clear on what she wants done, and how she wants it done, but for reasons of her own choosing, doesn’t want to get it done directly. She wants you to do it. And you aren’t convinced that what she needs to be done is the right thing to be done – you agree with the basic principles but think there’s a better way to do it than slavedriving the person you normally have no control over.

Like I remember this time from 2006 when the then boss wanted some data, and I had to convince this client to give us the data. It seemed tractable that the data would be available in a day, and in CSV format. But the boss wanted it the same day, and in Excel format (yeah, I worked for people who considered conversion from CSV to Excel nontrivial). And so I was slavedriven, so that I could slave drive this client, and get the data to the boss in time (never mind that it was I who would ultimately use the data, and I actually preferred CSV!).

In other words, then and now, I was stuck in a “slavedriver sandwich”. Someone slavedriving you to slavedrive someone, and you are wondering what role you have to do in the whole business in the first place. And then you decide that you have nothing to do there, and you should just eliminate the middleman, which is yourself.

In that sense, the problem of 2006 was easy – eliminating the middleman simply meant resigning my job. The current circumstances (which I can’t particularly describe here) doesn’t allow for so elegant a solution! So it goes.

The Ramayana and the Mahabharata principles

An army of monkeys can’t win you a complex war like the Mahabharata. For that you need a clever charioteer.

A business development meeting didn’t go well. The potential client indicated his preference for a different kind of organisation to solve his problem. I was about to say “why would you go for an army of monkeys to solve this problem when you can.. ” but I couldn’t think of a clever end to the sentence. So I ended up not saying it.

Later on I was thinking of the line and good ways to end it. The mind went back to Hindu mythology. The Ramayana war was won with an army of monkeys, of course. The Mahabharata war was won with the support of a clever and skilled consultant (Krishna didn’t actually fight the war, did he?). “Why would you go for an army of monkeys to solve this problem when you can hire a studmax charioteer”, I phrased. Still doesn’t have that ring. But it’s a useful concept anyway.

Extending the analogy, the Ramayana was was different from the Mahabharata war. In the former, the enemy was a ten-headed demon who had abducted the hero’s wife. Despite what alternate retellings say, it was all mostly black and white. A simple war made complex with the special prowess of the enemy (ten heads, special weaponry, etc.). The army of monkeys proved decisive, and the war was won.

The Mahabharata war was, on the other hand, much more complex. Even mainstream retellings talk about the “shades of grey” in the war, and both sides had their share of pluses and minuses. The enemy here was a bunch of cousins, who had snatched away the protagonists’ kingdom. Special weaponry existed on both sides. Sheer brute force, however, wouldn’t do. The Mahabharata war couldn’t be won with an army of monkeys. Its complexity meant it needed was skilled strategic guidance, and a bit of cunning, which is what Krishna provided when he was hired by Arjuna ostensibly as a charioteer. Krishna’s entire army (highly trained and skilled, but footsoldiers mostly) fought on opposite side, but couldn’t influence the outcome.

So when the problem at hand is simple, and the only complexity is in size or volume or complexity of the enemy, you will do well to hire an army of monkeys. They’ll work best for you there. But when faced with a complex situation and complexity that goes well beyond the enemy’s prowess, you need a charioteer. So make the choice based on the kind of problem you are facing.

 

Reforming Air India (yet again!!)

Being a PSU, Air India faces a unique set of constraints. In order to maximize its performance, the airline should take the most optimal decisions that satisfy these constraints. 

On Monday I had to go to Mumbai on some work and I flew Air India. Normally I prefer to fly either Jet or Indigo, but given the short notice at which I had to plan my trip, and the fare difference between Air India and the other two (leaving aside some airline I don’t trust), I decided to go for the national carrier. Overall it wasn’t an unpleasant experience – my onward flight was late by ten minutes or so, while my return flight was on time. There was plenty of leg space, the food was good and online check in was hassle free. Yet, it looked like there was plenty of scope for improvement.

Now for a digression. The difference between club football and international football is that in the latter you cannot buy players (not strictly true – Spain got Brazilian born Diego Costa to play for them on account of 1. his Spanish passport, 2. that he had never played for his native Brazil, but this is an extreme assumption). To use a cliched term, in international football you need to play the hand that you’re dealt. Thus, the job of a manager of an international football team is to organize his team’s strategy and tactics according to the personnel available to him, rather than the other way round. For example, Dutch manager Louis van Gaal is known to favour a possession based passing game. However, given the set of Dutch players available to him, he has set them out as a counterattacking side.

Given the lack of degrees of freedom in running PSUs, it can be argued that running a PSU is closer to managing a national football team than it is to managing a club team. Government ownership and consequent pay structures, combined with the lack of a good lateral entry system to the Indian public sector, mean that it is hard for a PSU to “buy” personnel like private companies can. On the other hand, sacking PSU employees is a politically charged activity, and not easy to administer, so it is hard to get rid of deadwood also.

The traditional argument is that given these restrictions that PSUs face, it is impossible for them to perform at the same level as comparable private sector units. While this argument is well taken, what we need to be careful is to not let this mask any degree of poor performance by a PSU. The question, instead, that we need to ask is if the PSU is actually making best use of the “hand it has been dealt”. What we need to check is if the PSU is optimizing correct given the resources and constraints at hand.

Coming back to Air India, one of the stated causes of its poor performance is that it is overstaffed – it far exceeds its global peers in terms of the number of employees per aircraft (normally assumed to be a good metric of staff size). This was fully visible at the boarding gate on Monday, for there were four personnel with the task of barcode scanning the boarding passes. Most other airlines have two staff doing this. A clear case of overstaffing. While it may not be under the management’s control to downsize (see constraints listed above), what irked me was that they were not being put to best use.

Just to take a simple example, if you have twice the number of required staff at the boarding counter, all you need to do is to put in an additional barcode scanner and run two boarding lines instead of one – which results in doubling the pace at which the plane is boarded. This doubling of boarding pace means planes can have a much faster turnaround time at each airport – which means the number of flights that Air India can run given its stock of aircraft can increase significantly!

To take another example, Air India probably has the best leg space in the economy class among all Indian carriers – this is probably driven by the fact that a large number of government officers and ministers travel mostly by Air India, and holy cows mean that they are forced to travel  “cattle class”, the airline offers some comfort. Now, while this means each plane has one or two rows of seats less than that of other carriers, it constitutes a massive marketing opportunity for the airline! Given the leg space and comfort and meals (!!), Air India can very well position itself as a premium carrier and try to charge a premium on tickets!

On an absolute basis, the recommendations above may not be optimal – it might be well possible to make more money by sacking boarding gate employees than by cutting boarding time, or it may make more business sense to add an extra row of seats than try to enhance legspace. However, given the constraints the carrier faces, these are possibly the “second best decisions” that the carrier can take. And by not taking these decisions, the carrier is not making as much money as it can make!

Should you have an analytics team?

In an earlier post, I had talked about the importance of business people knowing numbers and numbers people knowing business, and had put in a small advertisement for my consulting services by mentioning that I know both business and numbers and work at their cusp. In this post, I take that further and analyze if it makes sense to have a dedicated analytics team.

Following the data boom, most companies have decided (rightly) that they need to do something to take advantage of all the data that they have and have created dedicated analytics teams. These teams, normally staffed with people from a quantitative or statistical background, with perhaps a few MBAs, is in charge of taking care of all the data the company has along with doing some rudimentary analysis. The question is if having such dedicated teams is effective or if it is better to have numbers-enabled people across the firm.

Having an analytics team makes sense from the point of view of economies of scale. People who are conversant with numbers are hard to come by, and when you find some, it makes sense to put them together and get them to work exclusively on numerical problems. That also ensures collaboration and knowledge sharing and that can have positive externalities.

Then, there is the data aspect. Anyone doing business analytics within a firm needs access to data from all over the firm, and if the firm doesn’t have a centralized data warehouse which houses all its data, one task of each analytics person would be to get together the data that they need for their analysis. Here again, the economies of scale of having an integrated analytics team work. The job of putting together data from multiple parts of the firm is not solved multiple times, and thus the analysts can spend more time on analyzing rather than collecting data.

So far so good. However, writing a while back I had explained that investment banks’ policies of having exclusive quant teams have doomed them to long-term failure. My contention there (including an insider view) was that an exclusive quant team whose only job is to model and which doesn’t have a view of the market can quickly get insular, and can lead to groupthink. People are more likely to solve for problems as defined by their models rather than problems posed by the market. This, I had mentioned can soon lead to a disconnect between the bank’s models and the markets, and ultimately lead to trading losses.

Extending that argument, it works the same way with non-banking firms as well. When you put together a group of numbers people and call them the analytics group, and only give them the job of building models rather than looking at actual business issues, they are likely to get similarly insular and opaque. While initially they might do well, soon they start getting disconnected from the actual business the firm is doing, and soon fall in love with their models. Soon, like the quants at big investment banks, they too will start solving for their models rather than for the actual business, and that prevents the rest of the firm from getting the best out of them.

Then there is the jargon. You say “I fitted a multinomial logistic regression and it gave me a p-value of 0.05 so this model is correct”, the business manager without much clue of numbers can be bulldozed into submission. By talking a language which most of the firm understands you are obscuring yourself, which leads to two responses from the rest. Either they deem the analytics team to be incapable (since they fail to talk the language of business, in which case the purpose of existence of the analytics team may be lost), or they assume the analytics team to be fundamentally superior (thanks to the obscurity in the language), in which case there is the risk of incorrect and possibly inappropriate models being adopted.

I can think of several solutions for this – but irrespective of what solution you ultimately adopt –  whether you go completely centralized or completely distributed or a hybrid like above – the key step in getting the best out of your analytics is to have your senior and senior-middle management team conversant with numbers. By that I don’t mean that they all go for a course in statistics. What I mean is that your middle and senior management should know how to solve problems using numbers. When they see data, they should have the ability to ask the right kind of questions. Irrespective of how the analytics team is placed, as long as you ask them the right kind of questions, you are likely to benefit from their work (assuming basic levels of competence of course). This way, they can remain conversant with the analytics people, and a middle ground can be established so that insights from numbers can actually flow into business.

So here is the plug for this post – shortly I’ll be launching short (1-day) workshops for middle and senior level managers in analytics. Keep watching this space :)