CNET Content Solutions (and Me)

You probably know CNET, but do you know CNET Content Solutions? Indirectly, you do, because CNET Content Solutions’ content appears not only on CNET but also on CDW, Dell, Insight, MSN Shopping, Yahoo! Shopping, and hundreds of other sites around the world.

CNET Content Solutions’ content is product data: detailed specs, images, descriptions, and related-product links. This is the stuff you see on product pages and comparisons all over the Web. Without it, e-commerce sites would be empty shells.

CNET Content Solutions database comprises more than 3 million computer and consumer-electronics products in 35 markets and 15 languages. If you’re an e-commerce site, having manufacturers spray this information at you from all sides is not an answer. The scale of data is a problem, but the show-stopper is rampant inconsistency in the content provided, specs included/omitted, and terminology used. It’s the e-commerce Tower of Babel.

And thus the opportunity for a win-win: CNET Content Solutions does the heavy lifting of acquiring, normalizing, and internationalizing a world’s worth of product data; each customer pays a small fraction of the total cost to get the full benefit.

Put another way, in an era of infinite shelf space, CNET Content Solutions allows sites to keep the cost of merchandising that space under control.

I entered the picture at the end of 2004, when CNET acquired a company I co-founded, ExactChoice. We specialized in creating software applications that did analytics and mining of complex product data. Now, as CNET Content Solutions’ Analytic Products Group, we have the largest product-data operation in the world as our foundation.

The CNET.com Web site has carried forward ExactChoice’s showcase application, a personalized computer recommender. Meanwhile, as VP of Analytic Products for CNET Content Solutions, I am in charge of defining and executing products that add value to the existing database of detailed product information. Intelligent Cross-Sell is the first such product.

[This post is a revision of a post from September 18, 2005, “CNET Channel and Me.” In late 2008, CNET Channel changed its name to CNET Content Solutions.]

Understanding 0.02 Parts per Billion

Some measures are so extreme that the numbers are hard to grasp. For example:

The chemical that provides the dominant flavor of bell pepper can be tasted in amounts as low as 0.02 parts per billion.

A fraction of one-billionth? Perhaps an analogy would help.

One drop is sufficient to add flavor to five average-size swimming pools.

Touché!

[The quote is from Eric Schlosser’s Fast Food Nation, excerpted in The Atlantic magazine. The original link on The Atlantic’s site is dead, so here is an alternate. For another variant of this theme, see How Big Was That Squid?]

Tidal Waves Are Not Tidal

I had not thought about it before, but tidal waves are not tidal.

Tidal forces, which cause normal ocean waves, are from the sun’s and moon’s gravity. This explains why the cycle of high and low tides is regular—because the orbits and rotations of the sun/earth/moon system are regular.

So, tidal wave should just mean a normal wave. But most people understand tidal wave to mean a gigantic wave, a freak of nature.

The problem is, such waves have nothing to do with tides. They are caused by sudden displacements of ocean water due to earthquakes, volcanoes, or other major disruptions. Thus, scientists prefer the term tsunami to describe one or more massive waves caused by an irregular event.

I had always assumed that tidal wave and tsunami were either equivalent or subtle variants. Now I know, tidal waves are just big misnomers. Thanks to Jacqueline for enlightening me.

Review: Ian Ayres’ Super Crunchers

“You must be a Super Cruncher!”

Over the past year, several people have told me that. They had read Ian Ayres’ book Super Crunchers, and whatever he was talking about, that must be what I do.

From the first time I heard it, I disliked the term “Super Cruncher.” If it referred to a machine that rendered cars into pellets, that would be fine. But as a description of someone that does data mining and analytics, it doesn’t work for me unless that someone is a comic-book character.

So I avoided the book despite numerous accusations of my involvement with Super Crunchery. Yet when I eventually bought the paperback, Super Crunchers won me over.

For the general reader, it provides an engaging tour of real-world, data-driven decisions and their increasing effect in business, medicine, and government. For example:

• An algorithm that successfully predicts the best wines of a given year before they are even shipped
• A Web site, Farecast, that not only shows current fares but advises when to buy based on predictions of whether a fare will go up or down
• A medical campaign to save 100,000 lives from six improved procedures, derived from a statistical analysis of hospital-related mortality data
• An analysis of whether longer prison sentences affect whether prisoners commit crimes after their release

Such examples appear throughout the book. Ayres organizes them into a larger story about how the science of data-driven decisions works. Of course he covers how predictions can be made from existing data, but he also highlights the value of generating data specifically to answer questions. For example, “Instead of being satisfied with a historical analysis of consumer behavior, CapOne proactively intervenes in the market by running randomized experiments. In 2006, it ran more than 28,000 experiments—28,000 tests of new products, new advertising approaches, and new contract terms.”

Although he only discusses it near the end of the book, Ayres rightly raises the risk of people overrelying on algorithms. That is, much data mining occurs on data that is noisy, incomplete, inadvertently biased during collection, and otherwise on the edge of a garbage-in/garbage-out scenario. Algorithms, and the applications thereof, can have flaws. Even randomized trials can ask the wrong questions, sample the wrong audience, or otherwise put an unseen tilt on reality.

In this context, Ayres makes the point that human intuition and expertise will always have a role in sanity-checking results, as well as framing the questions to ask and choosing the methodologies for answering them. In fact, I’d agree strongly with Ayres’ statement, “The future belongs to the Super Cruncher who can work back and forth and back between his intuitions and numbers.”

Finally, regarding the book’s title that I dislike so much, I still dislike it as a label for people who do data mining and analytics. But it appears to be an effective title for selling books. To his credit, Ayres tested the title against an alternate, using a Google text-ad campaign. “Super Crunchers” got 63% more clickthroughs than the alternate, “The End of Intuition.” Although I could quibble with the quality or number of alternatives in Ayres’ test, the fact the book made it to the New York Times Business Bestseller suggests the title did its part of the job.

So I’d say Super Crunchers deserves its success, and I’d recommend it without hesitation to the general reader.

That said, even if judged by the standards of a largely anecdotal and nontechnical book, Super Crunchers will no doubt catch flak from some in the data-mining field. Most obvious, many of Ayres’ examples do not qualify for his definition of Super Crunching, which involves “really big” data sets. He never specifically quantifies “really big,” but I can all but guarantee that the wine-prediction example above, as well as many of the social-science examples in the book, are based on a few thousand to perhaps tens of thousands of records. By today’s standards, those are nowhere near “really big” data sets.

In addition, one could argue that Ayres’ coverage of randomized trials is actually about the opposite of Super Crunching. That is, the point of most randomized trials is to generate a clean and relatively small data set that answers a question. Done right, there is little need for sophisticated crunching.

Yet these objections just reinforce that Super Crunchers and Super Crunching are somewhat misleading labels for what the book is actually about. Although this will irritate insiders, I suspect general readers won’t care about the semantic distinctions but will benefit from the wider coverage beyond large-scale data mining.

Here’s a link to Super Crunchers at Amazon.com.

Art Auctions’ Self-Serving Numbers

Writing in The Wall Street Journal, Lee Rosenbaum explains how the numbers reported for art auctions have a twist:

Contrary to what you might expect, press accounts, relying on the information released by the auction houses, don’t normally measure a sale’s success by comparing an object’s hammer price — the last amount announced by the auctioneer — with the presale estimate of hammer price. Instead, they almost invariably compare the estimate of hammer price to a figure arrived at by adding hammer price to the commission that the auction house charges the buyer.

The result is an apples-to-oranges comparison that makes the sale results look better than they actually are, because they’ve been inflated by the commission....For example, Bloomberg News reported that a work by Abstract Expressionist Arshile Gorky, one of 16 drawings consigned to Christie’s by Richard S. Fuld Jr., chief executive of the failed Lehman Brothers Holdings, and his wife, sold last Wednesday “for $2.2 million, at the low estimate.” But its hammer price was, in fact, $1.9 million — $300,000 below the low estimate of hammer price. Only after the auction house’s commission was added did the price reach the predicted amount.

Of course, the auction houses prefer media coverage about auctions that exceed the predicted outcomes. Accordingly, the auction houses’ numbers serve that interest, especially when reporters pass them along as unqualified facts.

Kudos to Rosenbaum for challenging that form of business as usual.

SVD for You and Me

During Personify’s heyday, we were featured in a Business 2.0 article. It doesn’t seem to exist on the Web anymore, but the main thing I remember was a sentence that talked about Personify’s “algorithm-based software”—a phrase as useless as describing a car engine as “moving-parts-based.”

Certainly no one fed the author that phrase, and I doubt he or she invented it. More likely, the author wrote something that actually described our software, which an editor took the liberty of simplifying—to the point of pointlessness—for Business 2.0’s audience. Such things happen. It generated some smirks around the office, and that was that.

I tell this story because this weekend’s New York Times Magazine has a welcome counterpoint: an article about the Netflix Prize that could easily have hand-waved the details, per “algorithm-based software,” but instead made the details approachable and interesting for an audience even more general than Business 2.0’s.

Ironically, the algorithmic star of the article is singular value decomposition (SVD), a core component of, you guessed it, Personify’s algorithm-based software. Author Clive Thompson and his editor deserve credit for explaining SVD in everyday language, sprinkling plenty of movie examples from the Netflix contest. I’ll let you read it in the article (link below), but understanding SVD matters to Thompson’s larger questions of how predictable human tastes are and whether humans have limits to comprehending why certain predictions work.

A final irony: The New York Times Company may be running SVD to analyze behavior related to, among other things, Thompson’s article. I say that because The Times was a Personify customer, and last I heard (as of mid-2008), they were still running it at terabyte scale, six years after we discontinued official support. Just goes to show, many weird connections exist out there.

Now, onto the main attraction: Thompson’s If You Liked This, You’re Sure to Love That in The New York Times Magazine. Enjoy.

Water-Based Data Centers

Every once in a while, an idea comes along that combines breakthrough creativity with utter practicality. Google’s water-based data center is such an idea.

The problem: A huge cost in Google’s business is building and running data centers. An individual data center houses thousands of computers that together run Google’s services. Operating the computers requires a lot of power. Moreover, because many computers are packed tightly together, keeping them cool is a major issue.

The solution: Float a data center on an ocean ship. The power comes from converting tidal motion into energy. The cooling comes from sea water, pumped through. An undersea cable carries the data to shore. If that sounds good, also consider that the facility may not be subject to taxes or government regulation, depending on where the ship is positioned. Finally, the transportation world already has an infrastructure for moving standardized containers around. Thus, Google can build its data-center in containers-sized modules, truck them to a container port, and drop them on a ship.

Of course, implementing this idea will have many obstacles. Maybe it will never work because of devils in the details. Whatever the outcome, the idea itself deserves praise just for the ingenuity.

Poundstone’s Gaming the Vote

In the United States, the normal way to elect an official goes like this: Each voter picks a single candidate, and the candidate with the most votes wins. Call it a simple plurality vote—plurality referring to the requirement that a candidate only needs the most votes, not necessarily a majority. In presidential elections, the Electoral College complicates matters, but even the Electoral College is (mostly) based on combining states’ simple-plurality votes into a higher-level vote.

Although every presidential election renews the debate about the Electoral College, it’s worth asking a more fundamental question: Electoral College or not, is simple-plurality voting the best way to do an election?

In Gaming the Vote, William Poundstone argues it is far from the best way. The main problem is vote splitting, which can occur when an election has three or more candidates. An example: 60% of voters would vote for either Alice or Bob, who have similar policies. However, because each of these voters must choose either Alice or Bob, the total ends up split: Alice gets 30%, and Bob gets 30%. Meanwhile, only 40% of voters would ever vote for Carol, whose policies are the exact opposite of Alice’s and Bob’s. But because Carol has no vote-splitting competition, she wins the election, 40% to 30% to 30%. Thus, 60% of the electorate gets exactly the opposite of what it wanted.

If that seems abstract, recall the U.S. presidential election of 2000. Gore and Bush were in a close race that came down to a disputed count in Florida, which Bush won by 532 votes. Meanwhile, the Green party candidate, Ralph Nader, had received more than 97,000 votes in Florida. In post-election opinion polls, Nader voters preferred Gore to Bush by 2 to 1. So without Nader as the vote-splitting spoiler, Gore would have likely won Florida and the presidency.

Spoilers are enough of a problem when they occur naturally, but Poundstone makes the case that spoilers are increasingly being engineered. For example, he profiles several races from 2006 where supporters of one campaign sponsored a competitive campaign as a spoiler against the lead candidate. Not all were successful, but Poundstone’s larger point is that sponsored spoilers are cost-efficient bets, even if they don’t succeed. For example, in the 2006 campaign for a Pennsylvania U.S. Senate seat, supporters of Republican Rick Santorum paid $66,000 to aid the Green Party candidate’s drive to get on the ballot. As Poundstone observes, paying $66,000 to help the Green Party siphon off even 1% of the Democratic candidate’s vote is a lot cheaper than Santorum’s actually gaining that amount for himself, which would require million-dollar ad buys. (However, this particular ploy backfired when the Green candidate failed to make the ballot anyway.)

So, spoilers are bad. What to do?

The good news is, plenty of alternate voting systems exist. The bad news is, they all have flaws.

In 1948, economist Kenneth Arrow created a logical proof showing, in Poundstone’s words, “vote splitting and worse paradoxes can corrupt almost any reasonable way of voting.” From the 1970s, the Gibbard-Satterthwaite Theorem further showed that no voting system can be immune to strategic voting, where it is in the rational self-interest of some voters to not vote their true preferences. For example, in a “ranked choice” election, where voters rank each candidate, incentives arise to bury the serious contenders to one’s favored candidate. If everyone does that, the winner can end up being a pawn in the middle: some unqualified candidate that no one wanted to win but that happened to get a lot of second-place votes.

Poundstone provides a tour of various systems, down to the details. Interleaved with the theories, he dishes real-world examples and anecdotes from a rogue’s gallery of elections. (“The 1844 race was enlivened by the interesting claim that Henry Clay had broken every one of the ten commandements.”)

Poundstone also profiles various academics in the field. Individually, they seem like dedicated pursuers of truth, but collectively they achieve little beyond savaging each other’s favored theories. Meanwhile, the one person who has made clear progress in getting alternative voting systems accepted in several U.S. cities—Rob Richie of the advocacy organization FairVote—has done so by advocating the system that’s easiest to sell to politicians and the public: instant runoff voting (IRV). According to Poundstone, practically every academic agrees IRV is better than simple-plurality voting, but because IRV is not their preferred system, most academics have attacked Richie as they have attacked each other.

Given its fratricidal nature, the movement for better election systems leaves much to be desired as a movement. But even if the movement’s players worked together rather than against each other, they would still be on an uphill climb. The United States’ two major parties, because they already are the major parties, have more to lose than gain from changing the rules. Yet they often control the rules, directly or indirectly.

Poundstone raises these issues to no conclusion, although he does conclude that a particular election system is best. It’s called range voting, and its main feature is rating candidates on a numeric scale rather than ranking them in a sequence. The key thing range voting achieves is representing intensity of preferences, which turns out to address many issues.

Notably, range voting came from outside the election-systems academic community. A mathematician simulated a wide variety of voting schemes to see which one was best in practice, since in theory they all have some problem or other. He found that range voting had the best fidelity in representing voters’ true preferences, across simulated elections with various configurations of candidates and voting strategies.

Although Poundstone apparently could not elicit from the academic community a fatal flaw with range voting, neither could he get an endorsement. So the book does not have the satisfaction of ending with a thumping “case closed!” If anything, the case is just being opened.

With Gaming the Vote, Poundstone has done a service by making these important but obscure issues worth a read for the interested voter.

October Surprise or Ambiguous Reference?

While scanning news headlines, the following from the Associated Press caught my eye:

Obama ads in GOP turf; McCain says he’s leftist

Was John McCain outing himself as a leftist? In the tradition of October Surprises, what could be more “maverick” than that?

I could imagine the instant analysis from cable-TV news: “With Sarah Palin attacking from the right, and now McCain targeting disaffected Kucinich voters, will Obama be left helpless in an ideological pincer?!?”

Then I clicked the article. Turns out McCain was talking about Obama.

So maybe the subhead of the story should have been, “Associated Press commits ambiguous pronoun reference; electorate momentarily confused.”

Different Ways to Do Percentage Differences

Kitty weighs eight pounds. Fido is 300% heavier than Kitty. How much does Fido weigh?

24 pounds is the intuitive answer for many people, but 32 pounds is correct.

To clarify, let’s try this: Kitty weighs eight pounds. Fido is 24 pounds heavier than Kitty. How much does Fido weigh?

32 pounds, of course.

In the second example, it’s clearer that “24 pounds heavier” refers to the difference between Fido’s and Kitty’s weights. Now apply that same concept to the original example, so that the difference between Kitty’s and Fido’s weights is 300% of Kitty’s weight. That difference is 8 pounds multiplied by 300%, which is 24. Thus, Fido is 24 pounds heavier than Kitty, which makes Fido’s weight 32 pounds.

Got it? Well, there’s one more twist, which is the part worth remembering.

I could have made the original question easier by saying Fido’s weight is 400% of Kitty’s weight. This means the percentage applies directly to Kitty’s weight, so we’d just multiply 8 pounds by 400%, which is 32 pounds.

This latter method is simpler to calculate and to explain. So if you need to compare numbers using a percentage, and especially if the percentage is going to be above 100, avoid terms like “heavier,” “greater,” and the like, and don’t calculate on the difference.

Just remember X is n% of Y (like “Fido’s weight is 400% of Kitty’s weight”). It is easier to understand and calculate.

The Wandering Albatross

In a museum recently, I saw what appeared to be a seagull the size of a turkey. Had the taxidermist supersized this specimen? No, it was a real bird—and, as I learned, an extraordinary and endangered bird: the Wandering Albatross.

From BirdLife, here are some albatross facts:

• Wandering and royal (‘great’) albatrosses have the largest wingspans of any bird in the world, reaching up to 3.5m (11ft).
• Albatrosses are miracles of nature’s engineering – their long, narrow wings enable them to glide for thousands of miles on wind currents without flapping their wings.
• Simply by angling their wings and their flight path, albatrosses can use the variation in air speed and direction near the waves to soar over the oceans. This phenomenon is called dynamic soaring.
• A grey-headed albatross from South Georgia has been recorded circumnavigating the globe in a mere 46 days!

A scientist who instrumented Wandering Albatrosses found:

[T]he soaring flight of the albatross is among the most energy-efficient forms of avian travel known. The heart-rate monitors showed that albatrosses’ heart rates during flight are only 10 to 20 percent higher than they are when the birds are at rest. In contrast, the heart rates of other birds in typical flapping flight can rise to as much as 200 percent higher than the baseline level....

During a single foraging trip, which typically lasted between ten and fifteen days, the birds flew more than 1,800 miles from their nests and covered as much as 9,300 miles.

Out of 22 albatross species, 19 are endangered or on the way to that status. Technically, the Wandering Albatross is “vulnerable,” with decreasing numbers. Current estimates put the number of Wandering Albatross breeding pairs at less than 10,000 worldwide.

A major cause is longlining, a practice in which fishing boats drag lines that are miles long. Each line has thousands of hooks baited with squid and fish. While the lines are being set, albatrosses go for the bait, get tangled in the lines, and are pulled under. An estimated 100,000 albatrosses of all types die this way per year.

Longlining affects other species too, but albatrosses are hit hard because they breed slowly, one egg at a time. Thus, as a species, they do not have the reproductive capacity to counteract their losses from longlining and other human activities.

Solutions to these problems exist. For example, longlines can be modified with materials that scare away birds, or they can be set at night. However, many countries have longlining fishermen, and there is little incentive to absorb the cost of doing the right thing if your competitor from another country isn’t.

To help address this issue, an international agreement exists: the Agreement for the Conservation of Albatrosses and Petrels (ACAP). Last week, President Bush recommended that the U.S. Senate ratify ACAP and create laws that implement the agreement.

Outside governmental action, BirdLife has a campaign to raise awareness of these issues, promote countries’ participation in ACAP, and educate fishermen about the albatross problems and solutions. With such efforts, albatrosses have a chance to continue existing both in and outside museums.

[The image is from Wikipedia’s Wandering Albatross page.]

The Evolution of Children’s TV

News flash: A television show for preschoolers had a segment about the value of charts for visualizing information. Please take two minutes to view the evidence yourself.

The show is PBS’s Sid the Science Kid, which my preschooler and I watch. It does a good job of educating while entertaining.

Sid the Science Kid an example of a pleasant surprise that came with parenthood: Children’s TV has a lot more to offer than back in my younger days. Even outside public television, the big commercial entertainment shows for preschoolers—for example, Dora the Explorer, Go Diego Go, and Little Einsteins—have an education component.

Note that these are not Sesame Street replacements; that show is still going (if you haven’t tuned in for a few decades, I’ve got one word for you: Elmo). Rather, the new shows are cartoons that today’s tots want to watch like my generation wanted to watch Bugs Bunny, Yogi Bear, and other classic cartoons that were as educational as Twinkies were nutritional.

Combine today’s shows’ educational fortification with the fact that they are commercial-free (within the shows) not just on PBS but also Nick Jr., Disney, and Noggin, and it’s a different TV world from my toddler times.

Given that most little kids watch TV (hopefully not too much), I’ve got to think that today’s children’s TV is making kids a little smarter, a little sooner. So if you hear a three-year-old distinguish a tapir from a sloth (as Diego fans are wont to do), or tout the virtues of charts, you’ll know why.

[Thanks to information aesthetics for finding the Sid video online.]

Points, Percentages, and Stock-Market Plunges

Monday’s stock-market plunge brought plenty of headlines like this: “Dow plummets record 777 as financial rescue fails.”

That was from the Associated Press. The article’s subhead said, “Dow dives 777 points, biggest single day fall ever, as House rejects financial bailout package.”

The “biggest single day fall” sounds more dramatic and newsworthy than the “18th biggest single day fall.” Yet they are both true for Monday: By points, it was the largest single-day fall; by percentage, it was only 18th.

If these rankings are both true, can one be truer? I’d say yes if “truer” means a fairer comparison.

Let’s start with an axiom: If you are comparing daily changes to the Dow over the time frame “ever”—as in “biggest single day fall ever”—you should consider every trading day since the Dow’s inception.

The Dow debuted in 1896 at 40.94 points. It did not reach 777 points until the 1960s. So if you compare Monday’s drop to the past using points, you effectively eliminate from consideration any day before then—and, from a practical point of view, most days until the very recent past.

Too bad, because eight of the ten largest percentage drops occurred before 1935. The Great Depression years account for five of them, but the all-time winner for percentage losers is December, 12, 1914, when the Dow lost more than 24%. [Update: While technically true that the Dow lost more than 24% that day, it turns out this was due to a recalculation of the Dow, not a plunge of the overall market. The Wall Street Journal’s “The Numbers Guy” explains.]

A close second is 1987’s Black Tuesday, when the Dow lost 22%. But even with that relatively recent event, 22% of the Dow was only 508 points then. In contrast, yesterday’s drop was around 7%, less than a third of Black Tuesday by percentage but 219 points more.

So, to the issue of fairness, it’s not fair to compare point changes when the point scale is different, as it is with a Dow of 40 points versus a Dow of 10,000 points. In contrast, percentages can factor-out the magnitudes of different point scales, thus making changes more comparable.

Megapixels Begone (Comparative Metrics That Won't Go Away)

When you see a digital camera for sale, the first thing listed is usually the megapixel count: the camera’s maximum resolution in millions of pixels.

It’s the most important attribute because more megapixels means better pictures, right? With today’s digital point-and-shoot cameras, the answer is somewhere between “not necessarily” and “no.”

I noticed this issue last year when shopping for a point-and-shoot digital camera. Various roads led to the Fuji FinePix F30/31 series, which Digital Photography Review described like so:

In the fast-moving, ‘bigger better faster’ world of the digital compact the Fujifilm FinePix F30 will be one of the rare few that are remembered after they have gone (the nearest this throwaway business gets to a ‘classic’). The reason this unassuming, blocky little camera stands out from the scores of other cameras launched last year - and why it has a mantelpiece covered in industry awards - is simple; image quality, or more specifically, high ISO performance. The F30’s low light capabilities come from a combination of clever technology (Super CCD and Real Photo Processor) and a ‘swimming against the tide’ attitude to specification, which means a bigger sensor with fewer pixels. The F30 also, against all the odds, actually sold pretty well, going against the conventional wisdom that consumers buy on pixel counts alone. Although it has its share of faults the F30 became the benchmark by which all compact cameras in the 6-8 megapixel sector were judged.

But at the time I was shopping, Fuji had moved on to the F50 series. Here is what DP Review had to say about it:

Fujifilm has finally caved under the pressure and joined the mainstream with the F50fd, doubling the F30/F31fd’s pixel count to squeeze a whopping 12 megapixel on the tiny 1/1.6in sensor....

The good news is that - forgetting the F31fd for a moment - the F50fd is an excellent point and shoot camera that deserves a place near the top of its class. Sure, Fujifilm listened to its marketing department and installed a 12MP sensor, but the F50fd’s high ISO performance is still surprisingly good. On a per-pixel basis it is certainly not on a par with its predecessor but on an output level, i.e. on a print of the same size or a computer monitor the difference isn’t huge. Of course it would have been a lot better with 8 million larger pixels, but I’m afraid even Fujifilm isn’t brave enough to launch a premium compact camera so ‘under powered’ in today’s market....

The replacement of the F31fd means the end of the line for a sensor that over four generations of Fujifilm compact cameras has shown that there is an alternative to pointless megapixel increases and noisy results at anything over base ISO. Whilst the F50fd still has a lead over its conventional CCD competitors that advantage has been cut down to little more than a whisker, and this is a regrettable and slightly depressing indication of where the compact camera manufacturers’ priorities lie.

In other words, the F50fd was among the best point-and-shoot cameras of its time for image quality. However, the cameras of its time all had taken the same step backward by squeezing too many pixels into a given size of sensor. Thus, all the newer models were inferior to the F30’s image quality, especially in less than perfect lighting.

So what happened? Over to photography blogger Micah Marty, from late 2007:

Here’s a first: a digital camera that has appreciated in value. That’s right: if you had bought a truck full of new Fuji F30/31 cameras and just parked it in a warehouse for a year before selling them, you’d have no problem paying those holiday bills. Contrary to conventional wisdom (“Digital cameras always decrease in value when the successor model is introduced”) those two discontinued Fujis have almost doubled in value since they were current.

This happened, of course, because a few months ago Fuji decided to forgo its primary edge over the competition (“Less noise”) in favor of being more like the competition (“More megapixels!”). As a result, discontinued-but-new F30s that once could be bought new for $230–260 are now up as high as $400 on eBay, while the discontinued-but-new F31s that once could be bought new for $250–275 are now approaching the $500 mark on the same auction site. Those two cameras each have six megapixels; their shiny new successor (the F50), with twice as many megapixels but also more noise—and, by the way, a shorter-lived battery—currently is selling for $228 new at B&H.

The persistence of megapixels as digital cameras’ key advertised feature is a case study in a particular flavor of numbers abuse: the comparative metric that won’t go away. Such metrics typically made sense at some point in the past but, as with megapixels, outlived their usefulness as descriptions of quality. Yet they remain because, like kids studying to the test rather than learning the subject, manufacturers keep designing products to excel at the metric—after all, it’s what the market (thinks it) wants.

Having designed their cameras for more megapixels, the manufacturers are then obliged to tout their new cameras’ excellence on that metric, thereby reinforcing the metric in consumers’ minds.

It’s a vicious cycle, and the fate of the Fuji FinePix line demonstrates how hard it is to stop.

[Sidenote: Technically, the megapixels issue is not about an absolute limit. It’s about the number of pixels in relation to the size of the sensor. Thus, digital SLRs (the pro-looking cameras with swappable lenses) can get better quality from, say, 12 megapixels rather than 8 megapixels because the 12-megapixel sensor is typically larger in the digital SLR. In contrast, point-and-shoot cameras’ smaller bodies resist larger sensors, so manufacturers have packed more pixels into the same sensor size—despite the evidence that, above 6 megapixels, it hurts more than helps. For more details, see Image Engineering’s 6 Megapixel site, a public-interest plea in the name of 6-megapixel point-and-shoot cameras.]

The Inverse Out-of-Office Message

A few weeks ago at work, one of my team members was on vacation. He had left the office physically, but his mind was partly still there.

Now I’ll be the first to salute someone who takes time out of a vacation to address an emergency, but otherwise a vacation is for getting away. I had made that point to the team member, yet he was dashing-off emails from the Mexican seaside along the lines of, “Hey, how did that meeting go?”

By mid-week, the rest of the team decided an intervention was necessary. So I took our vacationer’s out-of-office message, changed some words, and sent it to him in response to one of his messages, autoresponder-style.

From: Steve Krause
Sent: Wednesday, August 27, 2008 2:03 PM
To: XXXXXXXXXXXX
Subject: RE: seller_update/verify_run_metis_client

Thank you for your E-Mail,

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And thus was born the Inverse Out-of-Office Message. May you be so fortunate to have an employee so enthusiastic that he or she needs it.

The Metrics of High Gas Prices

In the United States, gas prices hit all-time highs this year, even in inflation-adjusted dollars. This new reality has motivated some rethinking about metrics related to cars, gas, and money.

Total Cost of Ownership for Cars

Total Cost of Ownership (TCO) is a metric that includes not only the purchase price of a car but also the costs to run and maintain the car over time. While a business would likely use TCO to evaluate buying a fleet of cars, relatively few consumers use it when buying their own cars.

However, new-car buyers are increasingly doing a rough form of TCO as they abandon gas-guzzling SUVs and trucks in favor of fuel-efficient cars. Moreover, according to this New York Times article, many consumers are using their future savings at the pump to load up on options like leather seats and fancy car stereos.

In this new math for the auto industry, gas mileage often trumps sticker price for consumers.

“Affordability is not so much the issue as fuel economy,” said George Pipas, Ford’s chief sales analyst. “Just because you want more fuel efficiency doesn’t mean you don’t want a moonroof or leather interior.”

Gallons Per Mile

Earlier this summer, a pair of Duke University professors published research that suggests people often misinterpret the “miles per gallon” metric when comparing different cars. For example, which of the following saves the most gas?

(a) Replacing a 20-MPG car with a 40-MPG car

(b) Replacing a 10-MPG car with a 20-MPG car

(c) The previous two choices will have an equivalent effect

Many people don’t realize the answer is (b). However, if you flip the metric to be gallons per mile—or better, gallons per 10,000 miles—things clarify. (Gallons per 10,000 miles just means the number of gallons of gas necessary to drive 10,000 miles.)

Per this spreadsheet...

...a 10-MPG gas guzzler requires 0.10 gallons to go a mile; that is 1,000 gallons for 10,000 miles. In comparison, the 20-MPG normal car takes 500 gallons to go 10,000 miles. And the 40-MPG efficient car takes 250 gallons to go 10,000 miles. So switching from the gas guzzler to the normal car saves double the gas as switching from the normal car to the fuel-efficient car. At $4 per gallon, that’s a $2,000 versus $1,000 savings.

This result is worth considering in light of government policies that simply promote ownership of fuel-efficient cars. Such policies might instead want to base the subsidy on the fuel-inefficiency of the owner’s previous car, thereby creating greater incentives to get the worst gas guzzlers off the road.

We Feel It Because We See It

Behavioral economist Dan Ariely, author of Predictably Irrational, had a recent piece about why there’s so much angst about gas prices. He argues that we care more about gas prices than the prices of other necessities because when we buy gas, the cost adds up right before our eyes.

Looking back at my family’s expenses over the past few years, I see big increases in our health care costs and in how much we pay for food. The rise in what we spend on gas is not nearly as extreme as our increases in categories like electricity and telephone. So why does the amount we spend on gasoline feel so enormous? I think it is because of the way we buy gas.

For the several minutes that I stand at the pump, all I do is stare at the growing total on the meter — there is nothing else to do. And I have time to remember how much it cost a year ago, two years ago and even six years ago.

Yet I have no such memory about the prices of items in any other category. I have no idea how much milk was six years ago, how much bread was three years ago or how much yogurt was a week ago. But I suspect that if I stood next to the yogurt case in the supermarket for five minutes every week with nothing to do but stare at the price, I would also know how much it has gone up — and I might become outraged when yogurt passed the $2 mark.

I like the spirit of the example, but I don’t know anyone who buys $50 worth of yogurt per week or whose livelihood relies on eating yogurt. In contrast, large numbers of people have those situations with gas.

I would have rather seen Ariely use health care as the example. At various points in people’s lives, it’s an absolute necessity, yet few people understand exactly how much they pay (through some combination of direct, employer, and insurer payments) or how that amount has changed over time.

How Not To Do Customer Service

Once upon a time, a cable TV installer arrived at my house. He didn’t know which services I ordered, but he knew he was there to install something. As first steps go, this one was not a confidence-builder.

I told him which services I ordered. As he was doing the install, I noticed he was providing the wrong set top box for our service. When I asked him about this, he was surprised I knew the difference and said that he “just ran out” of the correct boxes, but this one would work.

I pointed out that it wouldn’t work as well. I asked him to get the correct box and come back. He said he couldn’t do that; I needed to make another appointment.

I asked him why that was my problem to solve, considering it was he who did not have the correct equipment. He didn’t have an answer, but he suggested the fastest solution was for me to take the wrong box and swap it at the local cable store, nearby on Bloomfield Ave. He said this in a knowing tone, as if I’d eventually end up there anyway.

Later, I went to the cable company’s Web site but couldn’t find a store locator to get the store’s exact address. I ended up finding the store locator by Googling the cable company’s name and “store locator.” Sure enough, it was on the company’s Web site, but there was no obvious way to get to it.

I put in my zip code. The only store that came up was a Best Buy somewhere in West Hartford—literally “somewhere” because there was no address or phone number provided. Perhaps the store locator was hard to find because it was not meant to be used.

So I moved on to the cable company’s “live chat” feature. Having started a session, the screen said, “Status: You are waiting for an analyst to assist you.”

While waiting for the chat feature to do something, I called the cable company’s support number. It told me they were experiencing higher than normal call volumes. “If your call is not of an urgent nature, please call back later.” I rechecked the chat window...no change.

While waiting, I searched Google for the cable company’s name plus the name of towns in the immediate vicinity. It provided a listing, not on Bloomfield Ave. I called the number. No one answered, and the voicemail box was full.

I had left the support number on speakerphone, and it eventually got me a person who gave me the address of the cable-company store where I could exchange my box. It was neither on Bloomfield Ave., nor at Best Buy, nor at the office where the voicemail was full.

Having gotten an answer on the phone, I bailed out of the chat feature, which was 25 minutes into waiting for an analyst. In doing so, I got a customer-satisfaction survey for my Web visit. Eager to express an opinion or two, I was disappointed to find that most of the questions were irrelevant to my visit. For example, the first question was, “Please rate the ability to limit sharing of your personal information on this site.” There were multiple screens, largely filled with such irrelevant questions. I skipped the whole thing.

Later, I went to the store. I waited a while. When my number was called, I found that the store itself “just ran out” of the correct boxes. I expressed frustration that my time was being wasted. I asked whether I had done something wrong in the process. No, said the person, but perhaps my expectations could have been set better.

Let us examine and extend that insight.

Maybe the cable guy could have said, “Hey, I’m sorry, but I just realized I don’t know what you ordered or if I have the right equipment. Let me get your order now, and if I’m not set to do this right, I’ll schedule myself to come back first thing tomorrow with the right gear.”

Or, lacking that, the cable guy could have said, “I’m sorry it’s a hassle, but your best bet is to swap this box at the local cable store. I think it’s on Bloomfield Ave., but let me call them to make sure they have the box you need and to get the exact address.”

Or, lacking that, the cable company’s Web site might have had a findable and functioning store locator.

Or, lacking that, the cable company’s chat feature and support line might have had one of those messages that estimates how long until a person would be available.

Or, lacking that, the person I eventually reached might have suggested that I call the store to make sure they had the box I needed because sometimes the boxes are out of stock. (Actually, this would not work because the store apparently does not have a public phone number. Rather, the only number given was the cable company’s general support number.)

The irony is, if one of the first few scenarios above would have happened, I probably would have said the overall experience was good, because I would have appreciated someone’s taking the initiative to fix a problem. But with failure at every turn, it’s harder to be understanding. And irony upon irony, the company’s one attempt to solicit my feedback (the customer-satisfaction survey on the Web site) was so poorly executed that it wasn’t worth using.

Having read this far, you might be wondering if I ever got the right box.

While at the cable store, I asked whether they had a waiting list or some other way to notify me when the correct box was available. Looking as if he was taking pity on me, the guy asked for my name and number. He wrote it on the back of a piece of scrap paper. He also offered that I could set up another appointment and maybe the correct box would be on that truck. “Maybe?” I asked. “Why would the truck come if the box wasn’t on the truck?”

That was like asking why things fall down, not up. It just works that way.

A day later, I happened to be driving near the cable store. Having zero expectation of success, I went in anyway, skipped the line, and asked someone if the correct type of boxes were available. The person said yes. I took a number. I got the box. Everyone lived happily ever after—the key word being “after.”

Enlightening about Lightning

In Connecticut today, we had three separate waves of thunderstorms, the last of which is still going. Earlier I was near enough to a lightning strike that the thunder had no rumble; it was a bomb-like detonation, right after the flash.

Having recently moved from San Francisco, where thunderstorms are rare, the summer thunderstorms in New England are still novel for me. According to statistics from the National Lightning Detection Network, Connecticut has between five and six times the lightning flashes per square mile as California.

Yet that’s only enough to rank Connecticut 36th among U.S. states for cloud-to-ground flash densities. The southeast dominates the top five, with Florida leading by a substantial margin. (Florida has seven times Connecticut’s lightening flashes per square mile. It also leads the nation in lightning deaths.)

Having addressed where you’re likely to see lightning, we might as well also cover the following:

People ask, “Who is most likely to be struck by lightning?” Something stirs in the mind about metal objects, and you might guess golfers, out there on the open fairways with four-irons raised to the sky, or fisherman clutching their metal rods. But you might not think of farmers, perched on their tractors and insulated by rubber tires, and, in fact, farmers it is. Where we need protection is overhead, not on the ground. Closed vehicles act as Faraday cages — named after Michael Faraday, the nineteenth-century British physicist and chemist, who specialized in electromagnetism — and are a good choice for cover, because the metal that encases them channels the charge into the ground. As it descends to earth, lightning current is drawn to isolated objects, anything taller than others in its field. This might be a lone tree, a skyscraper, a mound of granite in a riverbed, or you in your small craft on open water. Farmers are vulnerable because of where they are when they’re out in their fields — the tallest object in an open space, plowing or haying as the summer day heats up.

The quote is from a fine essay by Jill Frayne in the Canadian magazine The Walrus. In addition to enlightening us about the science of lightning, she narrates a few close encounters: “The strike shot through the radio antenna, exploded in the living room into a blue fireball that roared down the hall, lifting up the linoleum runner by the tacks, ripping the nails out of the floor, splintering the house walls as fine as kindling before it ran off over the bedrock outside and died.”

Here’s the link again. It’s a good read.

And with that, I’ll post this before the power goes out.

[The image is from Wikipedia’s Lightning article.]

Dan Ariely’s Predictably Irrational

Dan Ariely is a Duke University professor specializing in behavioral economics. In Predictably Irrational, he explains his field like so:

According to the assumptions of standard economics, all human decisions are rational and informed, motivated by an accurate concept of the worth of all goods and services and the amount of happiness (utility) of all decisions are likely to produce....Behavioral economists, on the other hand, believe that people are susceptible to irrelevant influences from their immediate environment (which we call context effects), irrelevant emotions, shortsightedness, and other forms of irrationality.

Ariely provides many real-world examples of economic irrationality. For example, here’s an anecdote about a restaurant consultant who learned that...

...high-priced entrees on the menu boost revenue for the restaurant—even if no one buys them. Why? Because even though people generally won’t buy the most expensive dish on the menu, they will order the second most expensive dish. Thus, by creating an expensive dish, a restaurateur can lure customers into ordering the second most expensive choice (which can be cleverly engineered to deliver a higher profit margin).

While a book of such anecdotes would make for good reading, Ariely’s academic work is about going beyond the anecdote to the experiment. Thus, much of the book covers controlled experiments (often by Ariely) designed to test people’s rationality in decision-making. And to Ariely’s credit, he still makes it a good read.

Among the experiments Ariely describes:

• Seeing if people who knew they were starting an auction from an arbitrary price (the last two digits of their social security number) would nevertheless bid relative to that price. Without knowing others’ bids, each participant made a single “best offer” bid, which could be either up or down from his or her social-security-number starting point. “In the end, we could see that students with social security numbers ending in the upper 20 percent placed bids that were 216 to 346 percent higher than those of the students with social security numbers ending in the lowest 20 percent.”
• Exploring the distorting effect of free pricing. Given a choice between a single ultrafancy chocolate for 15 cents (well below normal price) and a single Hershey’s Kiss for 1 cent, 73% chose the ultrafancy chocolate. But when the price of each was reduced 1 cent—to 14 cents and “FREE!”, respectively—69% chose the Kiss. Note that it was one chocolate per person, so everyone faced an either/or choice, and the relative price difference was unchanged at 14 cents. “According to standard economic theory (simple cost-benefit analysis), then, the price reduction should not lead to any change in the behavior of our customers....And yet here we were, with people pressing up to the table to grab our Hershey’s Kisses, not because they made a reasoned cost-benefit analysis before elbowing their way in, but simply because the Kisses were FREE!”
• Testing whether people value items more highly after buying them. Because of high demand and limited supply, Duke ran a lottery to determine who could buy tickets to Duke basketball games. After a lottery, Ariely and another researcher called more than 100 students who either won or lost in the lottery. “In general, the students who did not own a ticket were willing to pay around $170 for one....Those who owned a ticket, on the other hand, demanded about $2,400 for it.” In other words, there was initially a single group of students, “all hungry for a basketball ticket before the lottery drawing; and then, bang—in an instance after the drawing, they were divided into two groups—ticket owners and non-ticket owners. It was an emotional chasm that was formed, between those who now imagined the glory of the game, and those who imagined what else they could buy with the price of the ticket.”

Having found that people can indeed be predictably irrational, Ariely makes the move from descriptive to prescriptive:

The good news is that these [irrationalities] also provide opportunities for improvement. If we all make systematic mistakes in our decisions, then why not develop new strategies, tools, and methods to help us make better decisions and improve our overall well-being?

Among the new strategies he mentions is Save More Tomorrow, a program designed by behavioral-economics proponents Richard Thaler (University of Chicago) and Shlomo Benartzi (UCLA):

When new employees join a company, in addition to the regular decisions they are asked to make about what percentage of their paycheck to invest in their company’s retirement plan, they are also asked what percentage of their future salary raises they would be willing to invest in their retirement plan. It is difficult to sacrifice consumption today for saving in the distant future, but it is psychologically easier to sacrifice consumption in the future, and even easier to give up a percentage of a salary increase that one does not yet have.

Save More Tomorrow is a poster child for behavioral economics because it famously succeeded in a real-world test at an actual company, nearly quadrupling savings rates. Aiming for a similar real-world win, Ariely tried to sell the credit-card industry on the concept of a “self-control credit card,” where the consumer could self-restrict spending by category. There were no takers, but he is still holding out hope.

I’ve gone on at length about Predictably Irrational because I thought it was well worth my, and probably your, time. It’s a great combination of data-driven insight, real-world application, and well-told stories—by one of the principles in the field, no less.

Here’s the link to the book at Amazon, which has an excerpt and some author videos. See also Ariely’s Predictably Irrational site.

Social Norms versus Market Norms in Daycare

“Any questions?” asked the daycare-center director. She was a pleasant mix of smart and caring. She no doubt wished her center could accept all the applicants. But this being one of the few daycare centers near downtown San Francisco, the wait list dwarfed the enrollment.

“Wait list” was a misnomer. The center chose children based on unspecified factors, only one of which was place in line. So, all parents on this tour for applicants were listening attentively, mustering questions that demonstrated thoughtful consideration for their childrens’ welfare, and otherwise exhibiting best behavior.

Until the following exchange:

Parent: What is the policy if I’m late to pick up my child?

Director: We understand that once in a while you get stuck in traffic or can’t get here for extraordinary reasons. Just give us a call at the time, and we’ll make sure someone stays with your child until you get here.

Parent: Is there a fine or penalty?

Director: We’re not going to fine you for a rare event that’s totally out of your control.

Parent: But what if it happens repeatedly? How many times do I have to be late before you start fining me, and what’s the fine?

Director: Uh, we haven’t had to deal with that before.

Parent: Well how do I get that question answered?

Director: Let me get back to you on that.

As this exchange progressed, the questioning parent’s demeanor went from neutral to baffled, like a boss mystified by a subordinate’s inability to answer a simple question. Meanwhile, everybody else in the room was looking at each other like, “There’s one person we don’t have to worry about getting in before us.”

At the time, I didn’t ask myself why everyone except Baffled Parent knew something had gone awry. However, the incident came back to me when I read Dan Ariely’s Predictably Irrational. The book is about how people’s decisions—not just individually but in aggregate—can be skewed by factors beyond traditional economics’ view of rationality.

Ariely would explain that Baffled Parent tried to apply traditional economics’ “market norms” in a situation where “social norms” prevail. In fact, Ariely has an example of what happened when a day care center tried doing things Baffled Parent’s way:

A few years ago, [Uri Gneezy of UC San Diego and Aldo Rustichini of the University of Minnesota] studied a day care center in Israel to determine whether imposing a fine on parents who arrived late to pick up their children was a useful deterrent. Uri and Aldo concluded that the fine didn’t work well, and in fact it had long-term negative effects. Why? Before the fine was introduced, the teachers and parents had a social contract, with social norms about being late. Thus, if parents were late—as they occasionally were—they felt guilty about it—and their guilt compelled them to be more prompt in picking up their kids in the future. (In Israel, guilt seems to be an effective way to get compliance.) But once the fine was imposed, the day care center had inadvertently replaced the social norms with market norms. Now that the parents were paying for their tardiness, they interpreted the situation in terms of market norms. In other words, since they were being fined, they could decide for themselves whether to be late or not, and they frequently chose to be late. Needless to say, this is not what the day care center intended.

I’ll have more to say on Ariely’s book—of which social versus market norms is a small section—in a subsequent post.

What Is a Vegetable?

That was the question posed to me by my two-year-old daughter. She already knew examples of vegetables. She wanted to know what makes a vegetable a vegetable.

I didn’t know, and I later found that the answer has a few twists and turns. From Wikipedia’s Vegetable article:

The term “vegetable” generally means the edible parts of plants. The definition of the word is traditional rather than scientific, however. Therefore the usage is somewhat arbitrary and subjective, as it is determined by individual cultural customs of food selection and food preparation.

Generally speaking, a herbaceous plant or plant part which is regularly eaten as unsweetened or salted food by humans is considered to be a vegetable. Mushrooms, though belonging to the biological kingdom Fungi, are also generally considered to be vegetables, at least in the retail industry. Nuts, seeds, grains, herbs, spices and culinary fruits are usually not considered to be vegetables, even though all of them are edible parts of plants.

In general, vegetables are regarded by cooks as being suitable for savory or salted dishes, rather than sweet dishes, although there are many exceptions, such as pumpkin pie.

For a livelier version of the same topic, I liked “What is the difference between a fruit and vegetable?” from YES Mag, a Canadian youth science magazine:

The answer depends on your relationship with the two items. If you’re stocking the produce department at a grocery store, a tomato is a vegetable. If you’re a plant scientist—a botanist—a tomato is a fruit. Cucumbers, pumpkins, avocados, and peppers are all fruits. Culturally, however, the grocer is going to call them vegetables.

A fruit is the ripe ovary or ovaries of a flower—the mature ovary of a seed-bearing plant. Let’s say you’ve got a tomato plant with those little yellow flowers all ready. A bee comes along and fertilizes the flower. The flower starts developing into a fruit with the seed inside. (There are four kinds of fruits, which explains fruits such as pineapple and blueberries, but let’s not get into that.) And, hey, guess what? Nuts are fruits. True nuts that is, chestnut and filberts come to mind.

Vegetables, however, are the roots (eg, carrot), tubers (eg, potato), leaves (eg spinach), stems (eg, celery), and other bits of plants that you might eat. For a botanist, a vegetable is sort of like the umbrella word for all the edible parts of a plant. Just to keep life interesting, mushrooms aren’t plants at all, they are a kind of fungus.

Let’s just keep with the cultural distinctions!

I’m still working on how to explain this to a two-year-old.

The State Motto Grotto

Except in New Hampshire, where the license plates proudly assert the state motto, “Live free or die,” you don’t usually see state mottos. Far more often you’ll see state nicknames, like Missouri being the “Show Me State.“ You may recognize that nickname, but how about Missouri’s state motto, Salus populi suprema lex esto?

Other than “Live free or die,” state mottos are apparently kept in a cave somewhere, a cave we’ll call the State Motto Grotto. Prepare to behold the many beasts of language that dwell there.

A word of caution first. Like Missouri's, many state mottos are in Latin. For example, who can remember Alabama’s “We Dare Defend Our Rights” without the crutch of the official Latin version, Audemus jura nostra defendere? Obligingly, I will provide non-English mottos in their original language and then an English version.

As a starting point, you might be surprised how few state mottos are about geographic identity.

• Minnesota: L’étoile du Nord (French, “The star of the North”)
• Indiana: “The crossroads of America”
• And with an extra bit of marketing panache, Michigan: Si quaeris peninsulam amoenam circumspice (Latin, “If you seek a pleasant peninsula, look about you”)

Beyond those, state mottos are more about concepts than places. For an extreme example, North Carolina: Esse quam videri (Latin, “To be rather than to seem”). Don’t look for it on a license plate soon.

Or how about Maryland’s Fatti maschi, parole femmine? The direct Italian translation is, “Manly deeds, womanly words.” But before your imagination runs wild, think of it as something like Theodore Roosevelt’s, “Speak softly and carry a big stick.”

Arizona, Colorado, Florida, Kentucky, Ohio, and South Dakota: God gets a mention in each of their mottos. Apparently, they’re not taking too literally the “state” in “separation of church and state.” (Florida, you clever one, your choice of “In God We Trust” kicks any complaints upstairs to the federal government, which features that phrase on its money.)

In the secular-inspirational genre, we have New York’s Excelsior (Latin, “Ever upward”), Wisconsin’s “Forward,” Alaska’s “North to the Future,” California’s Eureka (Greek, “I have found it”), and New Mexico’s ominous Crescit eundo (Latin, “It grows as it goes”).

Less manifest-destinational is South Carolina’s Dum spiro spero (Latin, “While I breathe, I hope”), which Rhode Island reduces to “Hope.” And Connecticut brings us the unusual Qui transtulit sustinet (Latin, “He who transplanted sustains”), which is so 1639.

More contemporary sounding, albeit from 1873, is West Virginia’s Montani semper liberi (Latin, “Mountaineers are always free”). Or consider the following mottos, pulsating with the poetic minimalism of the Standard Industrial Classification.

• Utah: “Industry”
• Tennessee: “Agriculture and commerce”
• Montana: Oro y plata (Spanish, “Gold and sliver”)

Finally, we have the classic American theme of liberty and freedom, rendered variously as:

• Delaware: “Liberty and independence”
• Iowa: “Our liberties we prize and our rights we will maintain”
• Massachusetts: Ense petit placidam sub libertate quietem (Latin, “By the sword we seek peace, but peace only under liberty”)
• New Jersey: “Liberty and prosperity”
• Pennsylvania: “Virtue, liberty, and independence”
• And, of course, New Hampshire’s commandment-style “Live free or die.”

Now, having toured the State Motto Grotto, perhaps you’ll agree that “Live free or die” deserves to bask in the reflected headlights of motorists everywhere, or at least New Hampshire. By comparison, most other state mottos lack the pith and punch, which explains why they linger in silentium (Latin, “in obscurity”).

[Should you wish to audit every state motto, see Wikipedia’s List of U.S. State Mottos. The license plate image is from Wikimedia Commons.]

John Gruber’s “Daring Fireball”

The mainstream tech media has always had plenty of pundits and prognosticators. And now with the Internet, anyone with an opinion and a Web site can play along.

The good news is, amid a spectrum of awful to awesome, the best amateurs can be as good or better than most pros. Case in point: John Gruber, a Web developer and technical writer whose Daring Fireball blog tracks the world of Apple.

You’ve got to care inordinately about the Appleverse to read everything Gruber writes, and there’s no shortage of people who do. Me, I rely on tech-news aggregator sites like Techmeme and Hacker News to link to Gruber’s more general-interest stuff. Having clicked that direction many times over the years, I’ve been conditioned to expect insightful, well written, and righteously right (as in correct) views.

I was reminded of this with Gruber’s take on this week’s iPhone 3G announcement. His opening line is roughly what others said, but he then nails the story behind the story.

Today’s message is pretty simple: Apple is going for iPhone market share in a big, big way....

So, step one: sell a ton of iPhones and grab a huge chunk of worldwide smartphone market share. That’s the new $199 iPhone 3G. Step two: introduce features that people and companies love but which tie them to the iPhone. That’s the SDK — games and apps from App Store, and custom in-house apps for the enterprise market.

The physical phone is not the story. A year from now, the iPhone 3G will be replaced by another new model. The platform is the story. Platforms have staying power, and, once entrenched, are very hard to displace.

Although that was good, where Gruber really gets interesting is when he dissects others’ Apple coverage. For example, check out his prosecution of a Fast Company cover story on Apple that, to put it kindly, Gruber found lacking.

Here’s a sample, with quotes from the Fast Company article in italics and Gruber’s mix of intellect and umbrage in normal text:

In an age increasingly defined by interoperability and technical collaboration, Jobs still refuses to license Apple’s operating system.

Because there are so many companies making so much money “licensing their operating system”, other than Microsoft. Worked out great for Apple the last time they tried it a decade ago, and it’s worked out great for Palm now, right?

(Note also that all these decisions are, again, solely attributed to Jobs’s personal whim, rather than to Apple as a company.)

He won’t allow music and videos downloaded from iTunes to be played on other MP3 players.

Except for all those iTunes Plus tracks that have no DRM, and which Jobs has stated explicitly, in a widely-publicized open letter, he’d like to see the entire iTunes Store switch to, if the music labels would allow it.

He won’t permit music downloaded from competing stores to play on the iPod.

Except for all the music from any store that sells DRM-free music, like Amazon’s or eMusic’s. Otherwise what’s being argued here is that Apple should support Microsoft’s DRM platform, formerly known as PlaysForSure, recently renamed to “Certified for Windows Vista”, which Microsoft itself doesn’t support in its own Zune players. There’s a lot of stupid packed into the above 13-word sentence.

Maybe he could be more polite, but being a self-appointed messenger of truth takes its emotional toll—the title of Gruber’s Fast Company critique being, “Yet Another in the Ongoing Series Wherein I Examine a Piece of Supposedly Serious Apple Analysis From a Major Media Outlet and Dissect Its Inaccuracies, Fabrications, and Exaggerations Point-by-Point, Despite the Fact That No Matter How Egregious the Inaccuracies / Fabrications / Exaggerations, Such Pieces Inevitably Lead to Accusations That I’m Some Sort of Knee-Jerk Shill Who Rails Against Anything ‘Anti-Apple’ Simply for the Sake of Defending Apple, and if I Love Apple So Much Why Don’t I Just Marry Them?”

Whether you find his attitude entertaining or annoying, don’t let it distract from his ability to marshal facts to puncture others’ flimsy assertions. For this, as well as his own original analyses, Gruber is a welcome addition to the tech-media landscape—so much so that after years of doing Daring Fireball in his spare time, Gruber now makes enough income from the blog to have it be his primary job.

Good for him, good for us.

Zappos Makes It Pay to Quit

The online shoe retailer Zappos has an interesting option for new hires in its customer-service call center. After the first week of a four-week training program, you can take that week’s pay plus $1,000 and walk away. Yes, they will pay you $1,000 to quit.

Presumably, you take this offer if you realize the job isn’t going to work out. It’s like getting a bonus for making a mistake.

That’s the employee perspective. Now let’s look at Zappos’ angle.

10% of new hires take the money. Giving these people a reason to self-select themselves out saves Zappos the additional three weeks of training and avoids the marginal performance likely to follow until they move on.

And it saves far more if it removes bad hires who would otherwise never move on—the disgruntled employees who find it easier to stay and complain than get another job. $1,000 is nothing compared to the cost of keeping, or eventually firing, these employees. (Assuming they are capable of being happier elsewhere, these employees actually might be the biggest beneficiaries of having a specific incentive to leave.)

Although Zappos’ system is not quite to the level of a garden where the weeds pull themselves, it seems to be a clever approach in that direction.

[Original source on Zappos’ pay-to-quit program: Bill Taylor’s Why Zappos Pays New Employees to Quit—And You Should Too at Harvard Business Publishing’s Web site]

Intelligent Cross-Sell at Office Depot

At work, we just released a case study that’s a nice progress report for Intelligent Cross-Sell, my group’s main product. The featured customer is Office Depot, which runs one of the largest e-commerce sites in the world at officedepot.com—it’s currently ranked #3 in the Internet Retailer 500, the Fortune 500 of retail e-commerce.

Here’s the main story:

In 2007, Office Depot deployed CNET Channel’s Intelligent Cross-Sell solution to automate and optimize merchandising on its e-commerce site, www.officedepot.com. Doing so caused a doubling of online cross-sell revenue for the multi-channel global retailer. Cross-selling is an important tool that involves recommending accessories to products, such as a memory card with the sale of a digital camera.

One of the keys to success was utilizing Intelligent Cross-Sell’s “guided automation,” which combines merchandisers’ knowledge with the automation and scalability of a recommendation engine. For example, Intelligent Cross-Sell’s point-and-click interface allowed Office Depot merchandisers to target cross-sell opportunities by factors such as key selling features, popularity, compatibility, and brand affinity. Then, Intelligent Cross-Sell executed the rules across millions of possible product combinations. Compared to Office Depot’s previous cross-selling functionality, the result was a significant increase in the number and relevance of accessories offered as cross-sell opportunities across the site. This combination of more and better cross-sells drove the increase of cross-sell revenue.

Needless to say, I’m pleased. In my line of work, results are measurable, and these are the kind of results we like to see.

Kindle and Amazon.com’s Big Thinking

I admire Amazon.com, both as a long-time customer and as a student of business. Amazon.com pioneered much of what makes online retailing useful: one-click ordering, personalized recommendations, and user reviews, to name a few standouts.

Beyond that, Amazon.com long ago transcended the category online retailer by providing a platform where other retailers can merchandise their wares alongside Amazon.com’s or via their own Amazon.com-hosted stores. In addition, Amazon.com created the first large affiliate-marketing program, where individuals or companies can merchandise Amazon.com products on their sites.

And in a more recent step, Amazon.com generalized its infrastructure to offer a cloud-computing service (basically, a giant on-demand computing system, available over the Internet) that other companies can rent time on, for almost any purpose, not just online retailing.

These developments have a common theme. They all anticipated important changes to how business could be done, and Amazon.com executed those changes early, before others grasped the concepts. However, as some of Amazon.com’s recent initiatives have gone further afield from Amazon.com’s core retailing business, critics have questioned whether Amazon.com is going too far. Is the company investing in areas that, at the end of the day, aren’t a retailer’s business?

That’s the subtext to a shareholder letter by Amazon.com CEO Jeff Bezos, discussing Kindle, Amazon.com’s electronic book reader. Other e-book readers exist, but Amazon.com decided to design and manufacture its own. In the letter, Bezos makes a compelling case that Amazon.com has both the expertise and missionary zeal to deliver a successful e-book reader where others have failed, yet he leaves unsaid why Amazon.com is doing it.

Here’s why: Kindle is not just an e-book reader but also a service by which one buys books from (you guessed it) Amazon.com. If this is starting to sound familiar, recall that the iPod trumped existing MP3 players not just by providing better hardware but by linking the hardware to a well-designed service for buying music (iTunes). Thus, with both the iPod and Kindle, competitive advantage is about offering a superior total experience in buying and consuming musics/books.

Note the “total experience” concept, because it goes back to the question of what business a retailer should be in. For books, Amazon.com proved it can design a great buying experience. However, let’s say digital books go the way of digital music, where the best total experience—and the dominant market position—comes from an integrated offering of hardware, software, and service. If that happens, just being an e-book retailer won’t work. Go ask the formerly leading music retailers who watched Apple’s iTunes Store go from nothing to the largest music retailer in the world.

Of course, it’s not a foregone conclusion that the e-books business will follow the iPod/iTunes model. However, Kindle is a smart hedge in case it does, since Amazon.com has a lot to lose—or, with Kindle, to gain—in that scenario.

Whatever Kindle’s fate, its existence illustrates why Amazon.com is different. Amazon.com detected e-books’ potential for disruptive change and went well outside the standard retailer’s playbook to adapt—envisioning and implementing a better way to buy and read books. That’s big thinking.

I recommend you read Bezos’ letter (here’s that link again), plus his 1997 letter to shareholders, which is on the same page. Compared to the typical CEO missive, I think you’ll find Bezos’ letters refreshing.

(Postscript: The purpose of Bezos’ shareholder letters is to explain Amazon.com’s actions and strategy, but not too much. For example, the 1997 letter notes: “We are planning to add music to our product offering, and over time we believe that other products may be prudent investments.” Apparently, he chose that sentence instead of, “We plan to expand into so many product categories that we won’t be able to fit all their tabs across the top of the screen.” ;)

The Eric Carle Museum

Having recently moved nearby, it was inevitable that we’d visit the Eric Carle Museum of Picture Book Art in Amherst, Massachusetts. Any museum that won’t instantly bore a toddler is a worthy museum for our current lifestage. Besides, having read The Very Hungry Caterpillar aloud several hundred times, I was a stakeholder.

For the uninitiated, Eric Carle is author of so many popular children’s books that his work often commands its own shelf in bookstores. Carle’s medium is the picture book: Each page has a picture and a small amount of text. A typical Carle book tells a story about an animal while teaching concepts like colors or counting.

The Very Hungry Caterpillar, Carle’s most beloved book, seems to charm every child (and parent) it meets—to the tune of more than 20 million copies. The only risk in giving the book to new parents is that someone else already has. (If you want another Carle option, Brown Bear, Brown Bear, What Do You See? is also a sure winner.)

Visiting the museum, I was interested to learn that Carle was formerly an art director at an ad agency. In a video, I believe he even said something to the effect that he thinks of each page in his picture books as a billboard. This explains much about his simple visual style, child-like in its own way, communicating essence with little ornament.

Carle’s visual recipes typically include basic shapes, vibrant colors with varied textures, and lots of white space. His textures are from painted tissue paper—cut, pasted, and layered into figures like the famous caterpillar below.

For a selection of Carle’s work, with commentary by the artist, see this three-minute slideshow by National Public Radio.

And if you’re in the Amherst area with small children in tow, check out the museum. It’s part Eric Carle, part other picture-book authors and illustrators. In addition to the galleries, the library has thousands of children’s books, the art studio lets children create their own collages, and the smartly curated gift shop goes well beyond just Eric Carle and kids’ books.

Cameras That Make Us Better

Imagine a camera that only takes good pictures. If you combine a decent digital camera and a persistent person, it’s already reality.

Compared to the fast-receding days of traditional photography, where you had to wait until your film was developed to find that Aunt Betsy had her eyes closed in the family shot, digital cameras let you immediately see the image you just snapped. Bad image? Just erase and take it again. At the end of the day, you’ve got a memory card full of good pictures.

While this does not make you a master photographer, it increases the quality of your pictures in the same way that having multiple tries on every golf shot would lower your score.

But with photography, unlike golf, some shots don’t afford multiple tries. Your baby takes her first steps, cackling with delight at her conquest—oh, you snapped the picture just before the smile and got the grimace instead. That opportunity won’t come back again.

But wait. Recently hitting the market is the Casio Exilim EX-F1, a camera that can shoot up to 60 full-resolution images in a second. (This is not HDTV, where most of the images are compressed in a way that relies on the presence of adjacent images. Each image on the Casio is its own standalone high-resolution image.)

You can spread the camera’s maximum burst of 60 images across time—for example, 15 images per second for four seconds. You can also have it shoot continuously, only keeping the most recent 60 images. So, per our example of baby’s first steps, you could capture baby in 15-images-per-second continuous mode. When you see the smile, you can save the last four seconds and later choose the perfect image of beaming baby.

Folks, that is cool. It’s the next step in the world of cameras that only take good pictures—or more precisely, only keep good pictures.

Alas, the Casio Exilim EX-F1 is both expensive ($1,000) and, per David Pogue’s review in the New York Times, laden with tradeoffs. However, its special functionality will get less expensive, and the tradeoffs will be smoothed out. At some point, continuous, high-resolution shooting will be part of all digital cameras.

As a regular photographer of, as Pogue describes it, “wildlife (including children),” I look forward to that day.

When Stupid Isn’t: Product People Behind the Scenes

Long ago, I was a technology analyst. I tracked the technical and market development of new technologies in areas like artificial intelligence and digital video. The purpose was to forecast which technologies, companies, and products would be winners.

On a regular basis, I’d come across products where something was obviously wrong: nonsensical features, out-of-whack pricing, positioning for seemingly nonexistent audiences, and so on.

As consumers, when we see such things, we just shrug and move on. As a technology analyst, part of my job was to understand such anomalies. Were the people behind these products woefully misguided, or were they seeing something that others could not?

Over time, I met many product managers, product marketers, product evangelists, and the like. They were usually smart people who had reasons for why the seemingly wrong was right. Of course, those were judgment calls at the time; they were only right or wrong in retrospect. But most of the time, their perspectives were at least plausible, if not occasionally inspired.

This experience came to mind when I noticed Chris Anderson’s post about why the publisher Random House is not necessarily stupid. Author and prominent netizen Cory Doctorow had gone off on Random House’s Crown imprint for a limited-time free download of Scott Sigler’s Infected before its publication:

Publishers are schizophrenic and often end up acting really dumb in the service of trying to do something smart. Crown is putting Scott’s book online for free as a PDF, but they’re taking it down after only four days — presumably just in time to kill whatever momentum the downloads are generating....There’s no coherent explanation for a ticking-bomb download like this one; it’s like the hesitation marks on the wrists of a half-ass suicide.

Anderson contacted Crown and talked to Shawn Nicholls, Crown’s Online Marketing Manager, who provided a coherent explanation.

“We definitely subscribe to the believe that offering something online isn’t going to take away from sales,” says Nicholls. “The one thing I tried to do when we started this was to make a distinction between free music and free books. A MP3 can be a substitute for a CD, but we’re not at the place where a pdf is a substitute for a hard book.”

But Crown also believes in the concept of artificial scarcity: “Our goal was to create some buzz. Four days of availability gives a sense of urgency and makes it more of an event,” he says. And although Crown did take the book down from its official site, Nicholls said that they wouldn’t stop people from mirroring it elsewhere for as long as they want.

Nicholls also provided numbers that suggest the promotion worked.

Reading Nicholls’ comments, I not only recalled similar conversations but was glad to see such conversations are increasingly happening in the public (blogo)sphere. To take another example, here is Glenn Keels, Dell’s Sr. Manager, Commercial Products Team, responding to critiques that Dell’s Latitude XT tablet computer is overpriced:

Probably the most important thing to note about tablet PCs is that we are talking about cutting-edge technology here.  If we just released the exact same technology as our competitors, we would be missing opportunities to drive this market to the next level - and this is an opportunity we did not want to miss.  The result is that our product does carry a slight premium to our competition (emphasis on the word “slight”).

We believe that when you take a look at like-to-like configurations AND the incremental technology (that customers have overwhelming told us they want to have), the value equation for the Latitude XT far exceeds that of competitive systems.

Keels goes on to provide a table summarizing key feature differences with competitive models from Lenovo and HP. Although product people at those companies would likely have their own representations of the playing field, I say bring them on. If the conversation can be had at this level, rather than through glossy one-sheets and other marketing shellac, consumers will be the winners.