As someone who works in IT (or on the fringes of it, at least), a job at Google is seen as the Holy Grail of positions: if it’s not going to be a job for life, it’ll at least set you up for itâ€”after all, who wouldn’t want to hire Google alumni, right? And the benefits? Let’s not even start.
But is the reality a bit more, well, real?
According to this Google Group thread set up by the company’s HR department to discover why ex-employees left, the answer is a resounding Yes: their gripes are the same as those of any other employee in a sizeable organisation.
Those of us who failed to thrive at Google are faced with some pretty serious questions about ourselves. [â€¦] Google is supposed to be some kind of Nirvana, so if you can’t be happy there how will you ever be happy? It’s supposed to be the ultimate font of technical resources, so if you can’t be productive there how will you ever be productive?
After visiting both the Microsoft and Google campuses to discuss Stack Overflow (Google Tech Talk: Learning from StackOverflow.com), Joel Spolsky discusses the similarities and differences between the two corporationsÂ and his ownÂ small company.
What I’ll probably remember most about the trip is what I learned about company culture and how it’s affected by scale. Giant corporations such as Google and Microsoft are like cities full of relatively anonymous people: You don’t actually expect to see anyone you know as you walk around. Going to lunch on either campus is like going to the cafeteria at a huge university. The other 2,000 students seem nice, but you don’t know most of them well enough to sit with them. Meanwhile, a typical lunchtime at my company is like Thanksgiving dinner: There’s a big meal you get to share with a bunch of people you know and like.
I particularly liked Spolsky’s reaction to his discovery that while Microsoft’s campus-wide Wi-Fi network is closed-access and requires registration, Google’s was free and open: “I had to wonder: What might we be doing at our company that is similarly a waste of time?”.
It made me think: What might I be doing that is similarly a waste of time?
Mark Hurst, author of Bit Literacy and host of the Gel conference, takes a look at Microsoft’s Bing and discusses the problem with Microsoft’s current strategy and ways they can improve.
Customers online don’t respond to a brand marketed to them, they respond to the experience they have. If they can accomplish their goal quickly and easily, they return to the site, and tell their friends. It’s that simple. And if one site already provides a good experience, then there’s no need to consider switching to some other site, no matter what the company brags about itself in its ads.
In the context of what’s being discussed (Microsoft’s recent advertising) I couldn’t agree more with the above sentiments (out of context, however, I feel it’s not entirely accurate).
Hal Varian is the Chief Economist at Google, engaged primarily in the design of the company’s ‘advertising auctions’; the auctions that happen every time a search takes place in order to determine the advertising that appears on the results page.
After introducing us to this concept, Steven Levy looks at Google’s “across-the-board emphasis on engineering, mathematical formulas, and data-mining” and how these ‘Google-style auctions’ are applicable to all sorts of applications.
You can argue about [AdWords’] fairness, but arbitrary it ain’t. To figure out the quality score, Google needs to estimate in advance how many users will click on an ad. That’s very tricky, especially since we’re talking about billions of auctions. But since the ad model depends on predicting clickthroughs as perfectly as possible, the company must quantify and analyze every twist and turn of the data. Susan Wojcicki, who oversees Google’s advertising, refers to it as “the physics of clicks.”
[â€¦] “Google needs mathematical types that have a rich tool set for looking for signals in noise,” says statistician Daryl Pregibon, who joined Google in 2003 after 23 years as a top scientist at Bell Labs and AT&T Labs. “The rough rule of thumb is one statistician for every 100 computer scientists.”
Keywords and click rates are their bread and butter. “We are trying to understand the mechanisms behind the metrics,” says Qing Wu, one of Varian’s minions. His specialty is forecasting, so now he predicts patterns of queries based on the season, the climate, international holidays, even the time of day. “We have temperature data, weather data, and queries data, so we can do correlation and statistical modeling,” Wu says. The results all feed into Google’s backend system, helping advertisers devise more-efficient campaigns.
In an article profiling Google’s Marissa Meyer (employee number 20), there’s this quote on Meyer’s views with regard to hiring practices:Â
One candidate got a C in macroeconomics. “That’s troubling to me,” Ms. Mayer says. “Good students are good at all things.”
Another candidate looked promising with a quarterly rating from a supervisor of 3.5, out of 4, which meant she had exceeded her manager’s expectations. Ms. Mayer is suspicious, however, because her rating hasn’t changed in several quarters.
However serial entrepreneur Steve Blank says that aspiring entrepreneurs who don’t meet these standards shouldn’t be put off:
What I remind [my students] is thatÂ great grades and successful founders / technology entrepreneurs have at best a zero correlationÂ (andÂ anecdotalÂ evidence suggests that the correlation may actually be negative.) [â€¦]
There’s a big difference between being anÂ employeeÂ at a great technology company and having the guts to start one. Â You don’t get grades for having resiliency,Â curiosity, agility, resourcefulness, pattern recognition and tenacity.