I would add that the "Sales vs engineering and sales winning" would be a very relevant warning also:
> [sales] signed up a large number of smaller businesses on the platform. [...] However, integrating these smaller businesses was challenging thanks to several customizations needed for each new customer.
The ratio of revenue per each small customer vs the total cost of integration (and very likely on-going maintenance) was probably at least an amber flag somewhere for those who had visibility of it.
But maybe there was on-going hope that they would be able to sign up a big customer and integrate them before they ran out of money?
> The ratio of revenue per each small customer vs the total cost of integration (and very likely on-going maintenance) was probably at least an amber flag somewhere for those who had visibility of it.
At the last company I worked at (won't call them a startup, just a 10-year old small business that somehow kept raising funding but has never made a profit) I was astonished to learn from a new CPO that in our tenth year we didn't know if we were making money from a customer.
We had no idea how individual customers used the application, which was very data intensive, or what that was costing us. The information was there, but no-one ever looked. Every sale was considered a success, even if it turned out to cost us 3x in data costs and customer support. Often customer support alone would make a sale into a loss.
We spent a relatively large portion of our revenue running very expensive servers to respond instantly to searches that no-one ever performed. I created detailed monitoring to show this. I talked about them to everyone, including Product and the CEO. No-one disputed those facts. But instead we had several people essentially dedicated to downsizing application servers and deleting unused S3 buckets, trimming three zeros a month when we could have trimmed five.
I have learned not to assume that warnings are visible, that people pay attention to them if they are visible, or that anyone cares.
They're still circling the drain, still raising money (somehow!) and I doubt anything's changed.
We also had multiple contractors working full-time for months on a CI project that was projected before it began to save us at most a few thousand dollars a year. In the end they half-delivered a poorly-built system everyone hated, and I forced the abandonment of the project and we went back to the old system.
It was the pet project of another team-lead, that no-one else wanted. Group decision making is bizarre.
> We had no idea how individual customers used the application, which was very data intensive, or what that was costing us.
Cost can be a difficult problem to solve! I've been working on a project for about six months trying to identify just how much it costs to deliver a unit of the thing we sell. There's just so much variability, one customer might have widgets that are 40kb in size and rarely ever run widget analytics workloads, while another customer has 40mb widgets and can't stop looking at them.
I feel for the whole "how do customers use the application" thing too. Product analytics at most places seems to be a concern long after features are developed.
"So how many customers have been using that feature we spent two years and $20MM developing?"
"Good question."
"Soooo, mywittyname, can you figure out how many people at companies with over 200 seats look at dog pictures after opening an email with a 'C' in the title?"
I think what saved us was the unlimited license we had negotiated for the database server we were using (which wasn’t bad technology), expired and then the company was going to charge us through the nose for any new servers.
That triggered a rearchitecture of our system, into micro services that made sense for the kinds of queries, volume, and load we were dealing with. We did have a lot of data, but many of the queries could be satisfied by a key value store, for example, which didn’t require the same amount of hardware resources.
The original project did lead us to products our customers wanted to buy. Then we just had to change the architecture to fit those actual products.
Management probably really screwed this up if they were really only making $600k/yr.
Places I've worked yearly contracts for B2B have been in the $100k-$5M/yr range.
The customers paying $100k/yr barely get any integrations and feature changes... they go for the ride. The customers paying $1M+/yr get features on the double.
If Fast was doing integrations and customization for customers that were paying $1000 or less a year something was very very wrong.
At some point managers often fear the "red flag" of "we have a giant team with no work/customers". Hence, they will often push for dubious consulting(ish) work to at least ensure everyone remains busy.
Unfortunately this can lead to the outcome that the company just loses more money.
I went to a state school in a country where the only way in to university is by taking a test (this was in the early 00's), so I went to one of these cram schools after I finished high school. The cram school was focused on students of lower income families who would otherwise not have the means to attend a more prestigious one, and I remember in the inauguration ceremony for my year's class, one of their former students was invited to give a speech.
Her story was that after four years trying to get into medical school (i.e. four years attending the same cram school), she was given a tuition scholarship to a more prestigious cram school for her fifth year, and then she finally passed the test.
The thing is, this wasn't even an elite school -- it was just the only federal (state-funded) medical school in our state. The fact that the students' only way in was by taking the exam -- extracurriculars were not taken into account there also -- only made it even more of an _achievement_ for you to actually get in, especially if you were not from an upper middle class family.
IMHO the solution is probably to de-emphasize the metric. Class bottlenecks are probably bad. They’ll always happen, but it shouldn’t be the only route to a good life.
I don't know how famous/big they are, but I have already heard about it from more than one person, which makes me think that they are gaining traction.
I think there's a high chance that they are all linked. That perhaps the founders of each great religion were all "teachers at the same school", but that the teachings they brought to humanity were given according to humanity's state of evolution, similar to how students have to go through different grades. Each teacher would then teach only what that grade is ready to learn, though they have all the knowledge.
I believe the focus of what's being said is that people who claim to work these insane hours, _and_ manage to keep all other plates in their personal lives spinning, usually do not spend that much time doing productive work.
That is not to say that there are others who can do many actual productive hours. But usually, at least in my personal experience, when one does that they are sacrificing other aspects of their personal life in the hopes that when they achieve their goals they can then deal with everything else.
In my experience, things don't really work out all that well. Ideally one should find balance in the now.
It kind of depends what the work is and if it's tiring. Take someone like Warren Buffett - he's reading and thinking pretty much all working hours but it's what he likes to do and not especially tiring. Seems to work quite well in that case. The only real downside seems to have been his family complaining they didn't see enough of him.
AFAIK, there are two different types of cassava: the one we eat, and the one that's poisonous (which I think they called mandioca braba) and is only used to make farinha.
It is likely though that, if GDPR proves effective, other countries will soon follow suit and implement a similar set of data protection regulations.
Perhaps by then companies around the world will be forced into paying more attention to these matters, and a system of reward for white hats may become the norm.
My comment is merely anecdotal, I guess, but I believe if I were part of this study my data point would have been considered a 'statistical anomaly'.
I am a career changer who moved from admin roles to software development. This part of my life started in 2014, when I decided to make the change. My first instinct was to get a degree, since I had never got one before, so I started an evening presential course with a local university.
During the course, I often noticed that I wasn't taking much in from the lectures, so I'd come in on weekends and do my study then. I'd still attend classes, as I was always afraid I'd miss something important for the exams, but this turned out to be rarely the case. In my last year, I was already so frustrated with spending 3 hours in class each night after a day at my full time job, that I decided to completely skip my lectures altogether. Surprisingly, these were the modules where I had the best performance.
There's a lot of correlation here, but in my case I'd say that what motivated me were not the classes themselves, but the deadlines. I tried online at-your-own-pace classes before in my previous career (accounting), and they did not work at all. It was very hard to keep myself motivated. Again, the correlation here does not necessarily indicate causality -- it could be argued that the lack of motivation came from the fact that I didn't like the subject. But I still believe that what works best for my case is to have a deadline, and learning resources other than presential lectures.
TL;DR: career changer who tried learn-at-your-own-pace resources for previous career path and wasn't successful. Then tried presential lectures + self study for CS career, was moderately successful. Best results were obtained with self study + externally imposed deadlines.
> [sales] signed up a large number of smaller businesses on the platform. [...] However, integrating these smaller businesses was challenging thanks to several customizations needed for each new customer.
The ratio of revenue per each small customer vs the total cost of integration (and very likely on-going maintenance) was probably at least an amber flag somewhere for those who had visibility of it.
But maybe there was on-going hope that they would be able to sign up a big customer and integrate them before they ran out of money?