Such things in-fact happened to me (even tho I'm a bit younger than Mayer & my career started a few years later than hers), human memory is really unreliable & a lot of times you remember your feelings & translate those to facts upon recollection even when that wasn't quite the case.
I was at Netscape and was actually in meetings that marca, and others were not in, and it's funny to hear what they say happened, when they weren't in the room, nor were they consulted. Even the people at the top can be guilty of speculation.
If both companies’ data needs to be combined an analyzed, they usually bring in an outside deals consulting firm. Those teams tend to be very small due to the sensitive nature of the discussions involved — usually 2 or 3 people (backed by a large shared support staff and tooling) over the course of a few weeks.
Often the data used is a combination of proprietary data from both companies, commercially sourced data or proprietary data platforms built by the consulting companies. Deals are a big, sensitive, relationship-driven business.
It's often one guy with a spreadsheet, and 1-2 people to review the spreadsheet and a few business people to validate assumptions. The modeling is easy, getting the assumptions right is hard.
To be honest, if you're skilled very simple models that you can do in your head or in a few minutes usually give you a perfectly good answer. The more complex exhaustive models are usually there to make sure you didn't overlook something or 20 small inputs all cross multiplied to throw your answer off.
Getting the answer exactly right also doesn't matter, if you make $90m in profit off a deal or $100m your going to do it. What you are most concerned about is making sure that you don't lose money and what factors would push you to do that.AOL had ad inventory and Google had to get enough eye balls?
See also the Yahoo/Bing deal which didn't work out as well. Microsoft didn't end up actually hitting the targets, and convinced Yahoo to take less; and Yahoo also didn't reduce employee count anywhere near plan on searchy/advertising stuff, so they missed targets on revenue and cost and user experience.
"I think this is a common thing that very analytical people trip themselves up with. They look at things as if there’s a right answer and a wrong answer when, the truth is, there’s often just good choices, and maybe a great choice in there."
The above paragraph is rational, and yet people who consider themselves hyper rational often ignore the truth of this. And the irony is that some of them do this for an emotional reason: they want the security that comes from believing that there is an absolute right answer. They are irrationally rational.
Here's a simple counterexample to what I understand your theorem to say: consider an infinite search space: 𝕽∞ and a utility function: 1-|x|. There's a single global optimum at (0, ...), and the gradient of the utility function would find it quickly.
There's no such thing.
I understand the point you're making, but these gross assumptions aren't how the world works. Reminds me of econ models with ridiculous assumptions that don't pan out when reality is a constraint.
It is also a very good example of exactly what the previous post refers to: overthinking stuff.
Well done.
Now granted there are time to hunker down and commit but sometimes all that data doesn't really tell you anything and you're still facing an unknown no matter how much work you do, and it might be worth thinking about it after taking a few steps down that road / experience. It's not uncommon to come across a variable(s) that plays a far stronger role than any other, only AFTER you tried doing something.
For hyper analytical folks the data on hand is the hammer for every nail it seems sometimes.
Hard data also suggest how often the allegedly rational result suddenly became wrong. The rational conclusion here should be to decrease hubris then, shouldn't it? Nope...
And this is already a stereotype for softies...
This absolutely drives me crazy in design/engineering decisions. Very commonly there are a lot of good solutions and one great one, and the good ones are good enough. Yet all the brilliant intellectuals want to find the VERY BEST METHOD EVER instead of just getting stuff done.
For many mathematical, CS problems, it _does_ help to think very hard to find the very best solution to the problem, sometimes irrationally hard. I do agree that we operate in a real world, and the facts of running a business mean that you can't be spending all your time trying to figure out the best.
However, it was only by thinking very, very deeply about these problems have many of the technological improvements been possible. MapReduce, AI, ML, Cloud Computing... all started as ideas in companies where people dedicate quite a bit of thought into how to solve some basic problems.
I'll be honest: I am glad that I can reap the fruits of the labor of all these smart people, that they have enabled me to change the way computing is done, to make it easier for anyone to get started and to generate value very quickly, using the building blocks which they created after thinking about and working about this for so long.
Mayer: "I had a long analytical evening with a friend of mine where we looked at all the job offers I had received. We created a giant matrix with one row per job offer and one column per value. We compared everything from the basics like cash and stock to where I'd be living, happiness factor, and trajectory factor—all of these different elements. And so we went to work analyzing this problem."
Sandberg: "After a while I had a few offers and I had to make a decision, so what did I do? I am MBA trained, so I made a spreadsheet. I listed my jobs in the columns and my criteria in the rows, and compared the companies and the missions and the roles."
It's a fun bit of trivia that Sandberg put the criteria in the rows, which enables sorting the criteria - a nice way to see the upsides and downsides of each choice.
I think this is a luxury problem. How many people have competing job offers that are even close to each other in attractiveness?
I think about this quote a lot. It's so easy to get trapped in analysis paralysis which is really just procrastinating a decision. Like most things, there is a balance. Notice he says 'good' plan, not any plan.
The very term "overthinking" implies that there's a right amount of thinking for any decision, so your real problem is working out how much thinking to do.
It's how leaders need to operate to survive if they want to avoid micromanaging, honestly.
One could argue this article looks at a restricted range where the log behaves more lineary, but if we're going to apply mathematical modeling to our life choices, ... :-)
Somewhat ironically being irrational can actually be a good way to make unknown, but largely equal, decisions. Because at least you picked something with conviction, rather than having analyzed the situation incorrectly.
Of course for a lot of us good choices aren't the problem so much as the downside. I remember someone made a calculator online for how many time one would most likely see their parents before they died.
I am confused. Is she talking about foundation CS courses like OS & database systems OR AI courses?
I am reminded of the story of Henry IV who stood barefoot in the snow for three days. And through the grace of God not getting frost bite. We have come so far when we no longer believe you need God for acts like this.
[0] https://www.businessinsider.com.au/marissa-mayer-who-just-ba...
This is such an odd post. Who expects someone working 140 hour weeks to do all of their own house work? Sure, they're working 20 hours a day but they ordered chinese takeout and drop off their laundry!
Then, you link to child care as an example of "her domestic work"? Who complains about someone leaving their kid in daycare?
Someone asked a technical question, and you managed to turn the topic into accusations against Marissa Mayer (and ones that at least invoke sexism).
There's a time and a place for criticism, but it's not every time someone asks a question about her.
HER domestic work? There is absolutely no reason why she should or would mention this other than your sexist expectations.
Do you expect male CEOs to mention they pay someone to do their laundry and are abdicating their "domestic responsibilities"? Seriously?!
As I understand it, foundational CS classes are not a requirement for that degree. Although I do know people who majored in Symbolic Systems and completed such courses in undergrad, I assume they were electives rather than requirements.
In Masters she got to cover those off. I think her majoring in Symbolic Systems not CS meant she missed out on compilers, DBs, etc..
A university here has a cognitive science degree. Many people doing it and then a masters in CS to get at least a bit more practical with all the AI stuff they learned.
Yeah... I did both a Bachelor's and Master's degree in CS, and I've never written a complete working compiler, OS or database - I've written and tested "toy" versions of such, but that claim seems to be a bit hyperbolic. Maybe she did do all of those things, but none of those were coursework.
Hope that helps.
Sort of in a slump and I don't have anything smart to say but this made me feel a little better. I feel like I have far more ability than my company utilizes but I cannot quit because I need this job. I don't have the balls to start a company because I don't have a great idea. I just write code. So I will wait. Something will give eventually.
> And one of the reasons I was a good product manager was because I had been an engineer.
Marissa Mayer was an accomplished engineer and then a senior executive at Google through its transition from startup to behemoth, then took on the impossible task of rescuing Yahoo when no comparably experienced man wanted to step up to the plate, and facilitated a solid outcome for shareholders [1].
Reasonable people can debate the merits of her performance and impact at both companies, but these kinds of one-line dismissals of her entire career from armchair quarterbacks are disgraceful.
[1] https://www.businessinsider.com/yahoo-market-cap-over-time-2...
She was a product manager not an engineer. Her greatest accomplishment according to her was keeping the home page simple by only including the search bar. She also made the right decision to invest heavily in google maps.
You also left out the part where she slept with the founder during her time at Google, which undoubtedly gave her a leg up for promotions.
> then took on the impossible task of rescuing Yahoo when no comparably experienced man wanted to step up to the plate
She took it because she struck a sweat deal with board. In exchange for forgoing her google shares, she was able to reap 300 million in 4 years despite having an abysmal performance. Give any experience man that type of deal and I assure you there will be many that step up.
I'm reminded of the chimps who outperformed the stock markets: https://www.ft.com/content/abd15744-9793-11e2-b7ef-00144feab... of course replacing the cocaine bill with grapes dramatically lowers your running costs.
In regards to Marissa, I personally believe that the Glass Cliff is real. It's inspiring that she was integral in creating one of the most valuable company in the valley. Likewise, I find it impressive that she was able to climb the political ladder of a generally sexist industry.
HN demonstrably shows the same attitude towards male leaders as well. Elon Musk is the poster child of this.
This has nothing to do with the gender of the leader, but rather an aversion to self-promotion, hyping, or any other exaggeration of the self or one's accomplishments.
The glass cliff didn't make her buy Tumblr for 1.1 billion dollars only for it to be essentially worthless a few years later.
I also think people are a bit harsh on what situation Yahoo was in. They were still profitable, had a ton of users, and plenty of cash in the bank. Sure, it was being left behind but there was plenty of juice there to do something to become relevant again. In the five years she was CEO there's not really anything you can point to as a success. It raises the question of how important she was to the string of successful products that she headed at Google.
Then again, HN seems to discuss her less than Marissa Mayer. Why is that? She's far more successful. When I think great women leaders in tech, she's the first I think of. Anti-hardware bias maybe? Or maybe it's a valley bias. After all, she came out of MIT rather than Stanford and lives in Austin rather than San Francisco. I don't know, what do you think?
I wasn't there. I don't know the inside story. I'm not going to take sides. But neither am I going to assume that she has poor business skills just because she headed up a shutdown effort.
In contrast to my hypothesis: If you like her, feel free to share your thoughts or prove me wrong. What is special about her?
Of course she chose the rocketship in 1999 while the rest of us fumbled around in the dot com bust. She always had the knack of picking the right place to be at the right time, and the talent (or ability to bs) that she could get noticed when she needed to.
The yahoo thing was the worst misstep I've seen her take, but she got paid $200 million to take the risk, and I'm working for peanuts. So who is the smart one?
Edited to add: There is exactly zero chance she remembers me. But everyone I hung around remembers her. She has a very strange ability to be remembered.
Lest we forget Elizabeth Holmes, Elon Musk, Steve Jobs and for those old enough to remember Bill Gates in the 90s.
If you're lucky you die before you start making terrible decisions. A quote from Napoleon that he supposedly said while in exile "Had I been hit by a canon ball on my entry into Moscow I would have been remembered as the greatest statesman and general the world had ever seen".
But it would be the opposite for Bill Gates wouldn't it?
Running companies and being featured in Vogue? Iconic.
Marissa is a fake computer scientist. There are real female computer scientists out there, and very good ones at that.