Google has strong data that it does predict job performance, better than GPA, college degree and so on. What are your aggregate data showing that Google is wrong on this?
Does it? Because their strong data haven't helped them not screw up their messenger space. Or to have a fast email web client. Indeed, they seem to be going backwards on that chart.
They flopped on wave and Google plus, hard. Those are the kinds of mistakes that kill most companies. Even Google glass still somewhat rankles and has left me with no confidence in any of their consumer things.
And I say this as a happy Google fi user. In that I'm not convinced any alternative is worth moving to. Still can't fathom why Android is wasting fully half of my storage for "system".
I'm not claiming they are crap. But I do have a hard time making all the things they do that are beyond the industry. Other than spend a ton of money.
> their strong data haven't helped them not screw up their messenger space. Or to have a fast email web client.
That second example seems to invalidate your whole point, doesn't it? Yeah, they've had flops, but gmail has been an outrageous success, to the extent that more than a decade after launch it completely dominates internet email. I mean, yeah, I'm sure it could be faster (not a user, which makes me painfully aware of how rare my condition is!). But clearly they're doing this product "right" for any reasonable definition you want to use.
Gmail, the client, has gotten noticeably worse as the years have gone on, sadly. It is laughable how long I have to wait for the page to come up just so I can start drafting an email to my wife.
I don’t think those products failed due to poor engineering, google just hasn’t been great at social (if you don’t count YouTube). Other companies which use the same interview techniques are winning in those exact product spaces.
But, then what are they succeeding at? If engineering hasn't helped them not kill most of their products, what is it helping do?
And again, it is more than just social. ChomeOS? Even still a thing? How is android wear doing nowadays?
Again, I'm not claiming they are bad at engineering. I honestly don't feel qualified to judge. But I don't know that they are qualified to judge success of new hire, either. Their main success seems to be to simply suffocate the talent pipelines of the industry by hiring the top talent first. But not by actually using it.
> "If engineering hasn't helped them not kill most of their products, what is it helping do?"
Engineering does not set direction, they just build what they're told to. There are entire product management, market research, and similar teams that help senior management decide what to build. This is the case at most large software companies.
Yes, direction can be set independent of engineering. But a string of failures, at best, shows a string of misused engineering resources. Which just leads back to my challenge of why do they think they know what a successfull candidate is?
I'm questioning if they really know what good engineering is. I'm not saying they are bad at it. Those are two different claims
That they are the default entry to the web is their main asset. Agreed. Their search is good enough, and they are good at monetizing the top boxes of their search results. Really good.
That said, most of their engineering hires are not working on that. And they have a string of unfocused attempts at entering markets that smacks of not having a good sense of how to use engineering in a field. Basically, of they can't recreate the field, they give up. Rather quickly. That isn't engineering. That is just brash spending of money.
Why not both? It was a poor usage of engineering effort to try and recreate a field, instead of leveraging some assets and building on what they actually had.
It isn't like reader died alone. They had buzz going, which did a decent job of linking reader and Gmail. That is solid engineering. Instead, they have constantly tried to recreate Gmail to kill it. Wave? Plus? Inbox? I'm sure there are others.
Not defending Google, but this is dangerous myopia:
> Those are the kinds of mistakes that kill most companies.
All companies make big mistakes and burn lots of money on failed projects. The difference between a medium-sized company and a huge company is that a huge one can absorb the cost of failure, shrug and carry on. Medium-sized one will indeed die.
The difference between a large company and a huge company is that while both can survive the cost of a failed megaproject, for a large company the failure is probably enough to warrant a rethink and change in strategy. A huge company knows (from their aggregate financial metrics, of course) that what they are doing is right and proper, and will take the failure as just one more datapoint.
The moral is that there is no moral. (Or if we're talking business, morals.) Wild success begets arrogance, which begets organisational cargo-culting.
I'm not sure what the debate is. I'm all for changing strategies. My claim is that they don't have data on success from engineering. As evidenced by every pivot they have done being driven as much from marketing as technical.
Chrome, as an example, had a ton of marketing push behind it. Still some solid engineering, but not really any better than Firefox. Wasn't really any better than edge, but ms decided to drop the push for their own tech.
So, my question is what engineering successes do they have to back up their data on what will succeed?
I think you could pull in some of the ml work they are doing. Not sure how much data they actually have there, though.
My understanding is that they stopped asking brain teasers because they found no correlation with job performance. Which is good because for awhile it seemed like other companies were cargo culting questions like “why are manhole covers round”
What is "job performance"? I assume job performance in this case means getting promotions or good reviews. How well correlated are promotions to actual ability? In my experience they are mostly just political.
Google's 2013 study called Project Oxygen says different, "The seven top characteristics of success at Google are all soft skills: being a good coach; communicating and listening well; possessing insights into others (including others different values and points of view); having empathy toward and being supportive of one’s colleagues; being a good critical thinker and problem solver; and being able to make connections across complex ideas."
