Author: SK

Available only on flipkart

This mornings mint has a full page advertisement on the front page announcing the launch of the moto x phone in India. The ad mentions that the phone is available in India exclusively on flipkart the online retailer. The question is if this is a good idea.

While it is true that online retail offers the best costs and prices – thanks largely in part to the massive savings on real estate and inventory costs, I’m not sure if we are still thee at a stage where retail can be online only. In fact people like to touch and feel the stuff that they’re buying. Especially when it comes to big ticket purchases such as a phone. Without giving people the opportunity to do so – shops won’t carry the dummy model unless they’re also selling it, at a good margin – I’m not sure how many will want to make the jump and buy.

On a related note I saw a report last week, again in mint, talking about pushback from offline retailers and malls to the online retail phenomenon. This brings into focus how retail will evolve going forward since people now have a low cost (low inventory, zero real estate) option for making their purchases. We’re already seeing some “progress” in that direction where people go to malls and high streets to browse and get a touch and feel and then buy online where the prices are lower.

This points to one direction in which retail might evolve – soon stores in malls and high streets might be set up with the primary purpose of building the brand and letting customers get a touch and feel. Any sales from these stores for the brands will only be a bonus – the primary purpose being to let people know what is out there and to let them touch and feel and experience it.

If this were tO happen we can expect malls and high streets to move to more brand stores and less multi brand stores – unless the latter can somehow either match the cost and price structure of online or get paid for purely providing the experience to the customers.

Either ways we can expect the overall demand for retail real estate space to come down in the next few years. If there are any malls or retail real estate firms which are listed its time to short them. Or by hedging against them by going long on online retail.

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Getting monkeys off your back

I’m mortally scared every time I make pulav. Now, I’m reputed to be a pretty good pulav maker – at least the wife and the mother-in-law will vouch for this, and it is this reputation that puts pressure on me every time I stand throwing spices into the pressure cooker. “The law of averages will soon catch up with me”, I think, and hope that this is not the time it will catch up.

Normally, if you make pulav seven times, and each time make it better than the previous time, you begin to think you’re becoming an expert in that and you can do no wrong thenceforth. I don’t feel that way. Knowing myself fairly well, I know it’s nigh impossible for me to hit 100% accuracy in pretty much anything that I do – at best I can hit a 90%. That I got a “hit” seven times in a row means that the coin fell on the 90% side seven times, and even assuming a Markovian process (success or failure of this batch of pulav is unrelated to previous performances), it gives me a 10% chance of failure each time I make it!

The thing with making pulav in a pressure cooker is that when it comes out well, it comes out great, but it can go spectacularly wrong. I don’t use formal measures for the amount of rice and water I use – it is all based on rules of thumb (literally – sometimes I stick my thumb into the mixture in the pressure cooker to feel if the amount of water is right). And I know that if I put too much water, it can end up being a soggy mess. At the other end, it can end up not cooking at all, or worse, burning.

So when a couple of months back my pulav went marginally wrong (slightly watery, but not inedible) – it made me feel happy. It made me feel happy that the law of averages had caught up with me, and that it didn’t result in a spectacular failure! Sometimes when you know that you are due for a failure, it can be self-reinforcing and result in spectacular failures. So it helps to take a mild fall once in a while that gives you the assurance that you’re human after all, and doesn’t put undue pressure on you the next time.

So what do you think about your continued successes, in the kitchen, at the workplace, and elsewhere? Does that make you feel better or worse? Does it lead to a sense of hubris, or greater self-doubt? Do leave a comment here and let me know.

Wasps have thin tails, or why cricket prediction algorithms fail..

A couple of months back, i was watching a One Day International match between New Zealand and India. it was during this series that the WASP algorithm for predicting score at the end of the innings (for the team batting first) and chances of victory (for the team batting second) first came in to public prominence. During the games, the scorecard would include the above data, which was derived from the WASP algorithm.

This one game that I was watching (I think it was the fourth match of the series), New Zealand was chasing. They were fifty odd without loss, and WASP showed their chances of winning as somewhere around 60%. Then Jesse Ryder got out. Suddenly, the chances of winning, as shown on screen dropped to the forties! How can the fall of one wicket, and at an early stage in the game, influence a game so much? The problem is with the algorithm.

Last year, during the IPL, i tried running this graphic that I called the “Tug-of-War”, that was to depict how the game swung between the two teams. Taking the analogy forward, if you were to imagine the game of cricket as a game of Tug-of-War, the graph plotted the position of the middle of the rope as a function of time. Here is a sample graphic from last year:

baseplot

 

This shows how the game between the Pune Warriors and Sun Risers “moved”. The upper end of the graph represents the Sun Risers’ “line” and the lower end the line of the Pune Warriors. So we can see from this graph that for the first half of the Sun Risers innings (they batted first), the Sun Risers were marginally ahead. Then Pune pulled it back in the second half, and then somewhere midway through the Pune Innings, the SunRisers pulled it back again, and eventually won the game.

At least that’s the intention with which I started putting out this graphic. In practice, you can see that there is a problem. Check out the graph somewhere around the 8th over of the Pune innings. This was when Marlon Samuels got out. How can one event change the course of the game so dramatically? It was similar to the movement in the WASP when Ryder got out in the recent NZ-India match.

So what is the problem here? Based on the WASP algorithm that the designers have kindly published, and the algorithm I used for last year’s IPL (which was Monte Carlo-based), the one thing common is that both algorithms are Markovian (I know mine is, and from what WASP has put out, I’m guessing theirs is, too). To explain in English, what our algorithms assume is that what happens in the next ball doesn’t depend on what has happened so far. The odds of different events on the next ball (dot, six, single, out, etc.) are independent of how the previous balls have shaped up – this is the assumption that our algorithms use. And since that doesn’t accurately represent what happens in a cricket match, we end up with “thin tails”.

Recently, to evaluate IPL matches, with a view of evaluating players ahead of the auction, I reverse engineered the WASP algorithm, and decided to see what it says about the score at the end of an ODI innings. Note that my version is team agnostic, and assumes that every ball is bowled by “the average bowler” to “the average batsman”. The distribution of team score at the end of the first innings, as calculated by my algorithm, can be seen in the blue line in the graph below. The red line shows the actual distribution of score at the end of an ODI innings in the last 5 years (same data that’s been used to construct the model).

wasptails

Note how the blue curve has a much higher peak, and tails off very quickly on either side. In other words, a lot of “mass” is situated within a small range of scores, and this leads to the bizarre situations as you can see in the first graph, and what I saw in the New Zealand India game.

The problem with a dynamic programming based approach, such as WASP, is that you need to make a Markovian assumption, and that assumption results in thin tails. And when you are trying to predict the probability of victory, and are using a curve such as the blue one above as your expected distribution of score at the end of the innings, events such as a six or a wicket can drastically alter your calculated odds.

To improve the cricket prediction system, what we need is an algorithm that can replicate the “fat tails” that the actual distribution of cricket scores shows. My current Monte Carlo based algorithm doesn’t cut it. Neither does the WASP.

The pressure of chasing a target in One Day Internationals

I was looking at the average runs scored per over in One Day Internationals from 2009 onwards (data from cricsheet ). The data is presented in the graph below. What is striking is the difference in runs scored per over between the team batting first and second.

innruns

 

 

The  blue line shows the runs per over for the team batting first, and the red line for the team batting second. These figures are averaged over all ODIs from 2009 till the end of the recent Asia Cup. What you will notice is that the way you score runs in the first and second innings is different.

For the first part of the innings, till almost over 35, the team batting second scores much faster than the team batting first. Then somewhere around over 40, the two lines cross, And then the blue line pulls away from the red one – and really fast.

In the last over of the innings, for example, the team batting first is expected to score ten runs, while the team batting second is expected to score only eight and a half. In the forty fifth over, the team batting first scores seven runs on an average, while the chasing team only scores six!

The difference in scoring patterns is striking, and the only possible explanation is the pressure of chasing! When you have a target in mind, and you are chasing, you are unable to bat as freely as you do when you are setting a target. Consequently, you are not able to score as many runs!

The next question is if there is a variation across teams. Given below is the same graph as above, but plotted by batting team.

innrunbyteam

 

 

The graphs are smaller, so the gaps aren’t too visible, but if you look for a gap between the blue and red lines by team, you will find that the biggest gaps are for India, New Zealand and Australia! Sri Lanka and Pakistan seem to bat similarly, however, irrespective of whether they are setting a target or chasing!

 

 

Levels of polymorphism

Different languages have different levels of polymorphism, and it is a function of the environment in which the language developed. I discovered this last night when someone wrote on twitter that there is no word in Tamil for snow:

That got me thinking as to whether Kannada has a word for snow. Thinking of words for all the super-rain things in Kannada, I figured that “hima” is the word for fog, and “manju” means mist. But there is no word for snow in Kannada!

I put up the question on twitter, and the answers again were variations of the list I’ve put up earlier – some suggested “hima”, others “hani” (means “drops”, as in “raindrops”). One suggested “tushaara” for snow, but it’s not a commonly used word, so while it might be valid, I was looking for more commonly used words.

It then dawned on me that like the Tamil country, “solid rain” (apart from hailstones – which has its own Kannada word Anekal – translates to “elephant stone”) is not all that common in the Kannada country too. Yes, the Kannada country is cooler than Tamil country, and “solid rain” does happen, but it doesn’t happen on a regular enough basis for each type to have a word of its own. So, while I might think that “hima” is fog (since that’s the context in which it’s used in Bangalore), it also stands for “snow”! It’s all solid rain, and since it’s not all that common, you can have one word that describes it all! Interestingly, I can’t think of a Kannada word for “ice” also (again I haven’t learnt Kannada formally, though I speak the language at home. So what i know is the everyday spoken language)!

On a different note, in Japanese, the same word “Ao” is used to describe both blue and green! I’m again not sure if this because Japanese people are blue-green colour-blind, but the level of polymorphism in colour is interesting. At the other end of the scale, Italian has at least three words to describe different shades of blue (my knowledge of Italy, and Italian, I must mention, is mostly from football).

First, you have “celesti” or sky blue, as in the Biancocelesti of Lazio:

Then you have the blue of the sea or “azzure”, as in Inter Milan’s Nerazzuri. 

And finally, the word “Blu” is used for dark blue, as in Genoa’s Rossoblu. 

As if all this was not enough, they have Viola for purple!

It is interesting how different languages use different levels of polymorphism for different things!

Countercyclical business

I realize being a freelance management consultant is countercyclical business. For two years in succession, I’ve had a light March – both years I’ve ended up finishing projects in Jan/Feb. With March being the end of the Indian financial year, most companies are loathe to commit additional spending in March, and it is a bad time to start new projects!

This is counter-cyclical because most other businesses end up having a bumper March, since they have end-of-year targets, and with a short sales cycle, they push their salespersons hard to achieve this target in March!

Extension of nightlife in Bangalore

Finally the Government of Karnataka has bitten the bullet and announced that restaurants will be allowed to open till 1 am every night, and bars will be allowed to open until 1 am on Fridays and Saturdays. The catch, however, is that this is just a pilot move, and the government will take a decision on making this extension permanent based on feedback from various stakeholders after the pilot period.

The problems with having a three-month pilot period are several. For starters, the Bangalore city police is already over-stressed, and in three months (with only a pilot scheme) it is impossible to recruit and train more policemen who will be required to maintain law and order at the late hours. The result of this will be that the existing policemen will get over-stressed, with extended working hours, which cannot be good for policing in general. And as my colleague Saurabh points out, the police might vote to not extend the deadline beyond the pilot period.

The next problem is with the businesses themselves. A number of restaurants, I’m given to understand, were not in favour of the extension of deadline since they did not think the extended hours of working would be adequately compensated in terms of revenues. Take for example a typical “Family restaurant” (like Shanti Sagar). If most of the restaurant’s regular clientile is families, they are unlikely to provide any incremental business in the extended hours, and thus it doesn’t make sense for such restaurants to be open late in the night.

One constituency that should normally welcome later opening hours are the offshored IT and BPO workers, a large number of whom reside in Bangalore. However, in response to the early shutdown of the city, IT and BPO firms have adapted over the years, and arranged for in-house food and transport for their employees. While life should become theoretically easier for these workers with the extended hours (giving them wider choice for food and transport), three months, and that too a pilot scheme, is not enough for them to change their behaviour. So it is unlikely that these people will take advantage of extended opening hours.

Then, to be open for two additional hours in the night, bars and restaurants will need to make further investments in terms of personnel. However, if the extension in deadline is only for three months, there is no way any bar can realistically invest in the necessary personnel and infrastructure to be open in the late hours. This is likely to further mute the response to the pilot.

Finally, it needs to be noted that there are strong network effects involved in maintaining a night life. The streets of a city will be safe late at night only if they are busy. The streets of residential areas are unlikely to be busy at that hour (in fact, they are empty as early as 9:30 pm in some areas), but what we need for successful night life is a cluster of bars, restaurants, theaters and other “happening” places in small geographical areas that ensure large human traffic in those areas, which makes them safe. You wouldn’t, for example, feel safe traveling back on entirely empty streets from the pub to your home. What this implies is the need for organic growth of night-life. Abruptly shifting the deadline, and that too on a temporary basis, is unlikely to have an impact.

It appears that the three-month pilot for extension of deadlines is a policy that is designed to fail. Three months is too short a time for any of the stakeholders to make any realistic investments or behavioural changes, and given the network effects involved, it is unlikely that we are going to have a critical mass of establishments and people who will take advantage of the extended deadline for the policy change to be made permanent.

Expect the extension in deadline to be rolled back as soon as the three months of pilot are over.

Privacy and network effects

It is intuitive that some people are more concerned about their privacy than others. These people usually connect to the internet via a VPN (to prevent snooping), do not use popular applications because they rank marginally lower on privacy (not using Facebook, for example), and are strict about using only those apps on their phones that don’t ask for too much privacy-revealing information.

The vast  majority, however, is not particularly concerned about privacy – as long as a reasonable amount of privacy exists, and their basic transactions are safe, they are happy to use any service that is of value to them.

Now, with the purchase of WhatsApp by Facebook, the former (more concerned about privacy) brand of people are concerned that WhatsApp, which famously refused to collect user data, did not store messages and did not show advertisements, is now going to move to the “dark side”. Facebook, in the opinion of some of these people, is notorious for its constant changing of privacy terms (making it harder for you to truly secure your data there), and they suspect that WhatsApp will go the same way sooner rather than later. And they have begun their search to move away from WhatsApp to an alternate messenger service.

The problem, however, is that WhatsApp is a network effect based service. A messenger service is of no use to you if your friends don’t use it. Blackberry messenger, for example, was limited in its growth because only users with blackberries used it (before they belatedly released an android app). With people moving away from Blackberries (in favour of iOS and Android), BBM essentially died.

I see posts on my facebook and twitter timelines asking people to move to this messenger service called Telegraph, which is supposedly superior to Facebook in its privacy settings. i also see posts that show that Telegraph is not all that better, and you are better off sticking to WhatsApp. Based on these posts, it seems likely that some people might want to move away from WhatsApp.  The question is if network effects will allow them to do so.

Email is not a network effect based service. I can use my GMail to email anyone with a valid email address, irrespective of who their provider is. This allows for people with more esoteric preferences to choose an email provider of their choice without compromising on connectivity. The problem is the same doesn’t apply to messenger service – which are app-locked. You can use WhatsApp to only message friends who also have WhatsApp. Thus, the success (or lack of it) of messenger services will be primarily driven by network effects.

For whatever reasons, WhatsApp has got a significant market share in messenger applications, and going by network effects, their fast pace of growth is expected to continue. The problem for people concerned about privacy is that it is useless for them to move to a different service, because their less privacy conscious friends are unlikely to make the move along with them. Unless they want to stop using messenger services altogether, they are going to be locked in to WhatsApp thanks to network effects!

There is one upside to this for those of us who are normally not so worried about privacy. That these privacy conscious people are locked in to WhatsApp (thanks to network effects) implies that there will always be this section of WhatsApp users who are conscious about privacy, and vocal about it. Their activism is going to put pressure on the company to not dilute its privacy standards. And this is going to benefit all users of the service!

Bonuses and federalism

I spent a couple of years working for an investment bank, and the way they would distribute (the rather hefty) bonuses in the organization was rather interesting. Each manager in the firm would receive two sums – the first was his own bonus, and the second was the bonus to be distributed among all his subordinates. If any of the said subordinates were managers themselves, they would similarly receive two sums – separately for themselves and for their subordinates.

This is pertinent in relation to the devolution of power between the states and the third level of government. Even though district, taluk and city governments have been empowered by the 73rd and 74th amendments, they don’t have much real power because their finances are controlled by their respective state governments. In banking terms, this is like giving a manager one pot, and asking him to divide it between himself and his subordinates. The incentive is obviously to distribute the minimum amount possible to keep the subordinates happy. And this is exactly what is happening to federalism in India today.

What we need is a strict rule-based formula of distribution of central government revenues between the central governments, states and the next level (rule can be made based on populations, etc.). What we also need is a requirement for states to enact similar rules to divide revenue between states, districts and sub-districts in a rule-based manner. Until this happens, true federalism will remain a pipe dream.