More issues with Slack

A long time back I’d written about how Slack in some ways was like the old DBabble messaging and discussion group platform, except for one small difference – Slack didn’t have threaded conversations which meant that it was only possible to hold one thread of thought in a channel, significantly limiting discussion.

Since then, Slack has introduced threaded conversations, but done it in an atrocious manner. The same linear feed in each channel remains, but there’s now a way to reply to specific messages. However, even in this little implementation Slack has done worse than even WhatsApp – by default, unless you check one little checkbox, your reply will only be sent to the person who originally posted the message, and doesn’t really post the message on the group.

And if you click the checkbox, the message is displayed in the feed, but in a rather ungainly manner. And threads are only one level deep (this was one reason I used to prefer LiveJournal over blogspot back in the day – comments could be nested in the former, allowing for significantly superior discussions).

Anyway, the point of this post is not about threads. It’s about another bug/feature of Slack which makes it an extremely difficult tool to use, especially for people like me.

The problem is slack is that it nudges you towards sending shorter messages rather than longer messages. In fact, there’s no facility at all to send a long well-constructed argument unless you keep holding on to Shift+Enter everytime you need a new line. There is a “insert text snippet” feature, but that lacks richness of any kind – like bullet points, for example.

What this does is to force you to use Slack for quick messages only, or only share summaries. It’s possible that this is a design feature, intended to capture the lack of attention span of the “twitter generation”, but it makes it an incredibly hard platform to use to have real discussions.

And when Slack is the primary mode of communication in your company (some organisations have effectively done away with email for internal communications, preferring to put everything on Slack), there is no way at all to communicate nuance.

PS: It’s possible that the metric for someone at Slack is “number of messages sent”. And nudging users towards writing shorter messages can mean more messages are sent!

PS2: DBabble allowed for plenty of nuance, with plenty of space to write your messages and arguments.

 

The problem with Slack, and why it’s inferior to DBabble

When two of the organisations I’m associated with introduced me to the chatting app Slack, it reminded me of the chatting app DBabble (known to us in IIMB as BRacket) that was popular back when I was in college.

There were two primary reasons because of which Slack reminded me of DBabble. The first was the presence of forums/groups. There was a “General” that everyone in the organisation was part of, and then were other groups that you could choose to join and be a conversation in. The second was that you could not only converse on the fora, but also send personal messages to each other – something DBabble also enabled.

There are several reasons why Slack is superior to DBabble. Most importantly, you can tag people in your messages on forums and they get notified, so that they can respond – this is a critical feature for using it for work purposes.

Secondly, Slack integrates well with other tools that people use for work – such as email and a lot of development tools, for example (which one of the organisations I’m associated with uses heavily, but I’ve never got into that loop). Slack also has a very nice search feature that allows you to pull up discussions based on keywords, etc.

What Slack sorely lacks, which makes me miss DBabble like crazy, however, is threaded conversations. The conversation structure in each channel in Slack is linear – which means you can effectively have only one thread of conversation at a time.

When you have a large number of people on the channel, however, people might initiate several different threads of conversation. As things are, however, a Darwinian process means that all but one of them get unceremoniously cut out, and we end up having only one conversation.

It is also a function of whether Slack is used for synchronous or asynchronous messaging (former implies everyone replies immediately, latter means conversations can take their own time and there’s no urgency to participate immediately, like email, for example). My understanding is that the way it’s built, it can be used in both ways. My attempts to use it as an asynchronous messenger, however, have failed because some of the conversations I’ve tried to initiate have gotten buried above other conversations others on the channel have tried to start.

The problem with Slack is that it assumes that each forum will have only one active conversation at a time. Instead, if (like DBabble) it allows us to have different conversation threads, things can become a lot more efficient.

One of the nice features of forums on DBabble was that everytime you went to the forum, it would show you all the active threads by showing them in bold. DBabble allowed infinite levels of threading, and only messages that were unread (irrespective of which branch of which thread they were in) would be in bold, meaning you could follow all threads of conversation (this also proved problematic for some as we developed an OCD to “unbold” – read every single message on every forum we were part of).

Imagine how powerful threaded conversations can be at the corporate level especially when you can tag people in them – so you go to a forum, and can see all open discussions and see where your attention has been called, and contribute. Threading also means that you can carry out several different personal (1-to-1) conversations at a time without losing track of any.

It’s interesting that after DBabble (which also died after a later edition gave the option of “chat mode” which did away with threaded conversations) there has been no decent chat app that has come up that allows threaded conversations. Apart from possible bandwidth issues (which can happen when each message is suffixed with the full thread below it), I don’t see any reason this can’t be implemented!

I want my BRacket (DBabble) back. But then, chat has powerful network effects and there’s no use of me wanting a particular technology if sufficient number of other people don’t!

Airline delays in India

So DNA put out a news report proclaiming “Air India, IndiGo flyers worst hit by flight delays in January: DGCA“. The way the headline has been written, it appears as if Air India and Indigo are equally bad in terms of delayed flights. And an innumerate reader or journalist would actually believe that number, since the article states that 96,000 people were inconvenienced by Air India’s delays, and 75,000 odd by Indigo’s delays – both are of the same order of magnitude.

However, by comparing raw numbers thus, an important point that this news report misses out is that Indigo flies twice as many passengers as Air India. For the same period as the above data (January 2015), DGCA data (it’s all in this one big clunky PDF) shows that while about 11.65 lakh passengers flew Air India, about 22.76 lakh passengers flew Indigo – almost twice the number. So on a percentage basis, Indigo is only half as bad as Air India.

airlinedelays

The graph above shows the number of passengers delayed as a proportion of the number of passengers flown, and this indicates that Indigo is in clear second place as an offender (joined by tiny AirAsia). Yet, to bracket it with Air India (by not taking proportions) indicates sheer innumeracy on the part of the journalist (unnamed in the article)!

I’m not surprised by the numbers, though. The thing with Indigo (and AirAsia) is that the business model depends upon quick turnaround of planes, and thus there is little slack between flights. In winters, morning flights (especially from North India) get delayed because of fog and the lack of slack means the delays cascade leading to massive delays. Hence there is good reason to not fly Indigo in winter (and for Indigo to build slack into its winter schedules). Interestingly, the passenger load factor (number of passengers carried as a function of capacity) for Indigo is 85%, which is interestingly lower than Jet Airways (a so-called “full service carrier”)’ s 87%. And newly launched full service Vistara operated at only 45% in January!

We are in for interesting times in the Indian aviation industry.

The Impact of Wall Street on Grad School

I don’t need to be an insider to tell you that Wall Street employs lots of PhDs. PhDs of various denominations, but mostly those with backgrounds in Math, Physics and Engineering are employed by various Wall Street firms by the thousand. I don’t think too many of them exactly work on the kind of stuff that they were doing in grad school, but certain general skills that they pick up and hone through their multiple years in grad school are found extremely useful by banks.

So while scores of older scientists and economists and policymakers lament the “loss” of so many bright minds to science, has anyone at all considered the reverse possibility? Of the impact that Wall Street has had on grad schools in the US?

One thing you need to face is that there are not a lot of academic jobs going around. The number of people finishing with PhDs each year is far more than the number of academic jobs that open up each year. I’m mostly talking about “assistant professor” kind of jobs here, and assuming that becoming a post-doc just delays your entry into the job market rather than removing you from the market altogether.

In certain fields such as engineering, there are plenty of jobs in the industry for PhDs who don’t get academic jobs, for whatever reason. Given this, it is “cheaper” to do a PhD in these subjects, since it is very likely that you will end up with a “good job”. Hence, there is more incentive to do a PhD in subjects like this, and universities usually never have a problem in finding suitable candidates for their PhD programs. However, there is no such cushion in the pure sciences (math/physics). There are few “industry employers” who take on the slack after all the academic positions have been filled up. And that is where Wall Street steps in.

The presence of Wall street jobs offers a good backstop to potential Math and Physics PhD candidates. If they aren’t able to do the research that they so cherish, they needn’t despair since there exists a career path which will enable them to make lots of money. And knowing the existence of this career option means more people will be willing to take the risk of doing a PhD in these subjects (since the worst case isn’t so bad now). Which in turn enhances the candidate pool available to grad schools.

So even if you were to believe that complex derivatives are financial “weapons of mass destruction”, there is reason for them to exist, to encourage the financial sector to pick up PhDs. For if PhDs were kept out of these jobs, it is real academic research in “real subjects” such as the pure sciences that will suffer. By picking up PhDs in large numbers, the financial sector is making its own little contribution to research in pure sciences.

Arranged Scissors 7: Foreign boys

This post has been in the pipeline for a long time now, but a recent article in the Wall Street Journal documenting the diffficulties faced by NRI men in finding brides has finally resulting in my writing this.

For a long time, the grooms that came highest in the pecking order in the arranged marriage market were the NRIs, as most women aspired to migrate to America. In communities where dowry is practised, these guys used to get the maximum dowry; where dowry isn’t practised, the more beautiful and smart women would be the prize for being an NRI. Actually, one can make a weak case that since most of the good-looking women migrated abroad one generation ago, a lot of their daughters who would have otherwise been prize catches in the arranged marriage market here have now grown up as ABCDs, leaving the local (indian) markets poorer.

The three-way ticket protocol for bridehunting by NRI grooms has been well documented (I would especially recommend this article by noted AI stud and ASU prof Subbarao Kambhampati). I think I might have written about this in my blog some time back, though I wouldn’t have used this name for the protocol. The protocol goes something like this:

  • Boy lands in india on a two or three week trip (this is getting shorter nowadays)
  • On the way home from the airport his father hands him a sheaf of CVs and photos. By the time they reach home, a shortlist has been made.
  • Boy rushes off into the kitchen to eat the long-awaited home food, while his father quickly calls up the parents of all shortlisted girls and arranges for “bride-seeing sessions” (i’ll put a separate post on that) with each of the shortlists in their respective houses. Boy’s father needs to make sure to allow for some slack so as to account for traffic jams
  • Bride-seeing ceremonies happen wrt all the shortlists
  • End of the day boy and parents sit down with a list of all girls, and objectively note down each of their strong and weak points. Appropriate weights are given for each point, and an objective sumproduct (nowadays this is done on excel I think) reveals the winner.
  • In the classic version of the protocol, wedding would happen a week later in the US and the couple would go to Madras the following day with marriage album in order to apply for the wife’s H4. Boy would return to the US and girl would hopefully follow him a few months later
  • In the modern version, where you have cheap tools to keep in touch across continents, the first trip for the boy ends with engagement (usually held less than a week after he landed in india). He goes back to India six months later for the wedding. In some cases, the engagement is followed by a discreet registration of marriage in court, so that the girl can have her visa ready by the time she gets married formally.

In fact, I sometimes get the feeling that the speed with which NRIs want to process their “scissors” is what has led to the common minimum programme model. Given the absolute lack of time in order to make a decision, they would look for checklists. “good looking enough”. “smart enough”. “dowry enough”. etc. Now, the girls that they would usually end up getting were “premium”, because of which what these girls did would be “aspirational” to the rest of the girls. (waves hand furiously). And thus, the entire market tilted in favour of the common minimum programme.

I know of a NRI boy who got ditched by his fiancee a week before they were supposed to get married (it was the usual protocol; he had come to india six months back; seen this girl; got engaged and flown back to return just in time for the wedding). Now all arrangements had been made and he had also spent thousands of dollars for the India trip, so it would have been suboptimal for him to have gone back emptyhanded. So what does he do? Within the course of the one week between the ditching and the original date of his wedding, he does another round of scouting, finds another girl, and gets married to her at the same time and place as he was supposed to originally get married!

In another case, I know of the cycle time being as short as four days. Basically two days between the bride-seeing ceremony, and the first wedding ritual. And some other cases have had the two parties agreeing to get married to each other by just looking at each other’s photos. Bizarre is an understatement.

So  I suppose I’ve spent most of this post talking around the mechanics of the NRI marriage, and making a few random pertinent observations about them. Next, I want to talk about segmentation in the arranged marriage market (which I had briefly touched upon in this post), which I think vaguely ties in to this NRI concept. I hope to write that sometime this weekend.

Arranged Scissors 1 – The Common Minimum Programme

Arranged Scissors 2

Arranged Scissors 3 – Due Diligence

Arranged Scissors 4 – Dear Cesare

Arranged Scissors 5 – Finding the Right Exchange

Arranged Scissors 6: Due Diligence Networks