
- Will Florida be soon deeply affected as well?
- Will a hurricane stir up the oil even further?
- Will the oil flow around the Florida Keys and wash up on the Eastern seaboard?
- When will it end?
- Will BP pay?



How does an analytic company like Google make its most important decisions?
If we are to believe the Google myth, we learn, first and foremost, that they test everything:
We test everything at Google. While any company would prefer real-life data to hunches and guesses, Google is more focused than most (or any) on getting conclusive proof that a new feature or function improves the user experience. We release many of our products in beta on Google Labs to get this kind of feedback early in the process so that we can influence the design and iterate quickly.
The ability to test lots of products and features on hundreds of millions of users is enormously valuable. This test-bed of users (otherwise known as google.com) provides Google with an incredible advantage over enterprise-only search vendors. Bad ideas can be discarded quickly and great ideas can be implemented rapidly, because we have confidence and data to show that they'll improve the user experience.
Of course, when all decision-making is data-driven, it can lead to "madness."
Here's how Douglas Bowman explains why he quit Google:
When a company is filled with engineers, it turns to engineering to solve problems. Reduce each decision to a simple logic problem. Remove all subjectivity and just look at the data. Data in your favor? Ok, launch it. Data shows negative effects? Back to the drawing board. And that data eventually becomes a crutch for every decision, paralyzing the company and preventing it from making any daring design decisions.
In the end, said Bowman, he "won't miss a design philosophy that lives or dies strictly by the sword of data."
The testing culture doesn't end there. On the Google Testing blog, James Whittaker describes the testing frameworks he's observed among the job applicants he's looking to hire:
Which one of these frameworks will be best for Google, asks Whittaker.
Which leads us to the topic of
this blog post: Just how do the executives at Google
make
decisions?
Do they base their decisions on the data? Let's look at one well publicized executive decision and the executive decision-maker: Eric Schmidt and his decision to buy YouTube.
On October 9, 2006, in a deal valued at $1.65 billion, Google outbid a number of other competitors to snag YouTube, the online video site which was growing at a rate far outpacing Google's own Video site.
The official Google line was as follows:
The YouTube team has
built an exciting and powerful media platform that complements Google's
mission
to organize the world's information and make it universally accessible
and
useful," said Eric Schmidt, Chief Executive Officer of Google.
"Our companies share similar values; we both always put our users first
and are committed to innovating to improve their experience. Together,
we are
natural partners to offer a compelling media entertainment service to
users,
content owners and advertisers."
So how did Eric Schmidt value Google? Was he analytical, precise, objective?
By his own admission, Schmidt says, in a deposition by lawyers in the Viacom copyright lawsuit, that there was very little revenue coming into YouTube to justify the price his company paid.
Schmidt says that he told his company's board of that YouTube was worth $600 million to $700 million.
Via CNET, we get Schmidt's own words:
Viacom attorney Stuart Jay Baskin: And what was management's valuation?
Eric Schmidt: Much lower than we paid for it.
Baskin: And how was that communicated to the board?
Schmidt: I told them.
Baskin: So why don't you tell us what you remember telling the board in connection with the valuation?
Schmidt: I believe YouTube was worth somewhere around $600 million to $700 million.
...
Baskin: What methodology did you use to come up with that number?
John P. Mancini, an attorney working for Google, objects.
Schmidt: My judgment.
Baskin: Was it based on cash flow analysis? Comparable companies? What were you using as the basis for your judgment?
Mancini objects.
Schmidt: It's just my judgment. I've been doing this a long time.
...
Baskin: I'm not very good at math, but I think that would be $1 billion or so more than you thought the company was, in fact, worth.
Mancini objects.
Schmidt: That is correct.
Later...
Baskin: Can you tell us what reasoning you explained?
Schmidt: Sure, this is a company with very little revenue, growing quickly with user adoption, growing much faster than Google Video, which was the product that Google had. And they had indicated to us that they would be sold, and we believed that there would be a competing offer--because of who Google was--paying much more than they were worth. In the deal dynamics, the price, remember, is not set by my judgment or by financial model or discounted cash flow. It's set by what people are willing to pay. And we ultimately concluded that $1.65 billion included a premium for moving quickly and making sure that we could participate in the user success in YouTube.
What this tells us is that even in the most analytic company in the world, the big decisions are still made on intuition.
Here's why. Analytics can only tell us about the past. We have no data on the future. So Eric Schmidt was making an intuitive decision about Google's own future through examining the intangibles.
For example:
1. YouTube's popularity was sky-rocketing, making
it the
runaway market leader among video-sharing sites.
2. It was crushing his company's own site, Google Video.
3. YouTube was up for auction and would be sold to a competitor unless
Google
jumped first.
4. Google overbid to ensure YouTube didn't fall into rival hands.
And that doesn't take into account two other points which made the deal a winner. From the very beginning, the Google philosophy has been - get attention first, then monetize it. And that is what this bet was all about.
Schmidt saw the attention trajectory in YouTube's growth, and he knew that if anyone could monetize that attention it would be Google. To leave YouTube for Murdoch, Microsoft, or Yahoo was not an option.
In hindsight, it may have been a brilliant move. Although the monetization has proved difficult, Google is breaking even today, which is far better than what has happened at MySpace, for example.
Analytic decision-making approaches a problem systematically. Leaders analyze a problem, generate several possible solutions, analyze and compare them to a set of criteria, and select the best solution. The analytic approach aims to produce the optimal solution to a problem from among those solutions identified. This approach is methodical, and it serves well for decision-making in complex or unfamiliar situations by allowing the breakdown of tasks into recognizable elements. It ensures that the commander and staff consider, analyze, and evaluate all relevant factors.
It may help inexperienced leaders by giving them a methodology for their lack of experience. The analytic approach to decision-making serves well when time is available to analyze all facets affecting the problem and its solution. However, analytic decision-making consumes time and does not work well in all situations--especially during execution, where circumstances often require immediate decisions.
Intuitive decision-making is the act of reaching a conclusion that emphasizes pattern recognition based on knowledge, judgment, experience, education, intelligence, boldness, perception, and character. This approach focuses on assessment of the situation versus comparison of multiple options. It is used when time is short, or speed of decision is important. Intuitive decision-making is faster than analytic decision-making in that it involves making decisions based on assessment of the situation rather than a comparison of multiple COAs (Courses of Action). It relies on the experienced leader's ability to recognize the key elements and implications of a particular problem or situation, reject the impractical, and select an adequate (rather than optimal) COA.
Intuitive decision-making is especially appropriate in time-constrained conditions. It significantly speeds up decision-making. Intuitive decision-making, however, does not work well when the situation includes inexperienced leaders, complex or unfamiliar situations, or competing COAs. Additionally, substituting assessment for detailed analysis means that some implications may be overlooked. Commanders use intuitive decision-making when time is short and problems straightforward. It is usually appropriate during execution.



