Words & Numbers

Why Omnivark?

2012-05-07T07:37:00.000-07:00

When I introduced Omnivark a few months ago, many people asked, politely: “Why?” (Quick recap of what it is: The Omnivark Web site helps users discover great writing. Each daily edition highlights three new, nonfiction pieces on the Web, plus a recommended book.)

Omnivark is not about me clicking around the Web all day looking for great writing; it’s about teaching a computer to do that. I did not previously mention the computer’s role because I wanted people to evaluate Omnivark for its content, not its process.

Behind the scenes, the process includes software programs that sift thousands of new Web pages per day, looking for a rare gem. The problem is, physical gems have standardized measures of clarity, cut, and size. The written word lacks equivalent measures, especially to discern great writing from good writing. (Quantifying bad from good is more tractable.)

Lack of measures does not mean lack of agreement about greatness—for better or worse, there are widely acclaimed publications, writers, and pieces. The problem with measuring greatness is the diversity of ways writing can be great. Hemingway’s terseness and Faulkner’s complexity are opposites, yet they are both literary legends from the same era. A gentle eulogy, a political rant, an ironic cultural commentary—should they be judged with the same scorecard? And if great writing transcends mere communication to accomplish something higher, isn’t that beyond the realm of a scorecard?

For me, cutting into this thicket of questions is fun. However, it’s the type of fun suited to a personal project, where walking the path can be the reward. I say that because it’s unclear how far, or where, the path can go. Emulating a human editor’s expert judgement of great writing—based on its content, not on source or popularity or social filtering—is technically hard, if not conceptually quixotic. But that’s what makes it fun. And that, in turn, is the answer to “Why?”

The Fastest Human in History

2012-04-10T07:15:00.000-07:00

A small voice said, “Don’t let me fall, daddy.”

She was on the bike, wobbly, her confidence gone with the training wheels. I was holding her, gently pushing her forward.

“I’m falling!”

“I’m still holding you.”

“Hold me tighter or I’ll fall!”

■

I don’t remember learning to ride a bike. I only remember the moment of transition, when I realized I was doing it. The memory has no visual component, but I imagine my father trailing off behind as I self-propelled forward.

■

On October 14, 1947, a B-29 bomber dropped test pilot Chuck Yeager from 20,000 feet. Yeager was in the Bell X-1, a rocket with wings. Clear of the B-29, Yeager lit the engines.

The X-1 shot upward an additional 20,000 feet, accelerating to 0.92 Mach, 92% of the speed of sound. Then the shaking started.

Other pilots had hit this resistance, which they called the sound barrier. It got worse as you got closer to the speed of sound—how much worse at the extreme, no one knew.

The shaking intensified as the Machmeter read 0.93, 0.94, 0.95, 0.96. The X-1 engineers built the plane for this, but even they didn’t know exactly what this would be. The only way to find out was to go there.

Yeager did, as the X-1 blew through its own shock waves, past the speed of sound. A sonic boom echoed across the desert. Inside, Yeager recalled, it became so smooth that “Grandma could be sitting up there sipping lemonade.” At that moment, he was the fastest human in history.

The B-29 that launched the X-1 trailed off, mission accomplished.

■

We had already done the preliminaries: scooting the bike with her feet, coasting a bit from a small push, and pedaling as I jogged along holding her. All fine. But we were stuck at my letting go while she kept pedaling.

“I don’t want to fall!”

I convinced her it was okay for me to let go a few seconds at a time as she pedaled. Yet when I tried to stretch the counts, she would put her feet down, her shoes skidding the bike to a stop.

She knew she needed to keep pedaling, that more speed meant more balance. But knowing and doing were different things.

■

Amid growing frustration, a friend of hers happened by. A recent success story on two wheels, the friend had a simple statement: If you want to do it, you can. With that, the friend rode off matter-of-factly.

It was the right message, from the right messenger, at the right time. As she watched the friend ride away, I could see my daughter reframing the problem in her mind. It was no longer about wanting to learn, like at school; it was about wanting to graduate.

In our next pass down the street, she pedaled faster. She trusted me to let go as long she was staying up, allowing my catches to steady her as she continued pedaling. She was beginning to instinctively adjust the front wheel for balance.

Then I was hands-off for five, ten, fifteen strides. “You’re doing it! Keep going!”

She did, accelerating.

I kept running with her, a few steps back. In the retelling, I imagine myself trailing off as she self-propels. At that moment, in our little world, she is the fastest human in history.

New Name, Look, and Features

2012-04-01T12:24:00.002-07:00

After 5+ years and nearly 300 postings, this blog is getting a new name, look, and features.

The name, “Words & Numbers,” is what I would have called it from the beginning, had I known what this blog would be about. But I discovered its aboutness along the way.

The new look and features come with a change of blog platform, from TypePad to Google’s Blogger. Most of the features are minor improvements, such as better support of mobile devices and social sharing. However, I also took the opportunity to redo the topic labels, improve the typography, and add a Best Of section.

Finally, for people who follow via RSS: Sorry for the old items in your RSS reader. The platform change caused that. If you mark everything read, all will be back to normal going forward.

Intelligent Cross-Sell: The CNET Years

2012-03-29T08:04:00.000-07:00

After integrating ExactChoice into CNET.com, my main task was to create something new for CNET. That became Intelligent Cross-Sell, a product used by four of the top ten brands in the Internet Retailer 500, among others.

I was part of CNET Channel, since renamed CNET Content Solutions. Its customers are e-commerce sites that sell technology and consumer-electronics products. Its primary product is a detailed database of products. E-commerce sites use this database to display products and specs in a standardized way. For example, if you see a product page for a computer on CDW.com, much of the page’s content is actually from CNET.

Circa 2005, having attracted a large number of e-commerce customers worldwide, CNET was looking for something new to sell them. My job was to determine what it should be and then to build it with my own team.

The industry term for this role is intrapreneur. It can mean anything from “leader of a CEO’s pet-project skunk works” to “random guy building something not elsewhere classifiable on the org chart.” In my case, I was fortunate to have both a specific place in the org chart and a high degree of autonomy. I also had strong executive support.

By choice, I worked as part of a two-person team, with my ExactChoice partner Howard Burrows. We knew how to explore concepts quickly and cost-efficiently, having practiced what today would be called lean-startup techniques since founding ExactChoice in 2002.

At the outset, I talked with dozens of CNET customers about their e-commerce businesses, looking for the pain points we could reasonably address, ranking them by risk and reward. The opportunity that kept winning was a tool to automate cross-selling. Although everyone was familiar with Amazon.com’s “people who bought this also bought that,” tech and consumer-electronics sites could not use it to determine, for example, the right carrying case with a computer.

Among the challenges with “people who bought this also bought that” were:

If a few consumers mistakenly bought the wrong-sized case for a computer, the algorithm would start recommending the bad combo, causing a slew of returned products.
It was useless for new products without sales history—no people who bought this, then no people who bought that.
It left no room for merchandising. For example, as computers began appearing with the Bluetooth wireless standard, cross-selling Bluetooth mice made sense. But how could merchants tell the algorithm to do that when it was only looking backward at the non-Bluetooth past?

Because of these issues, many large tech and consumer-electronics sites were using humans to manually configure cross-sells. These sites had tens or hundreds of thousands of products, changing rapidly. The humans could not keep up. We would later attract two of our early customers—billion-dollar e-commerce sites—by showing them their percentages of empty cross-selling slots.

The beauty of the opportunity was that it played to CNET’s strength. The CNET product database, DataSource, had the size of most computers. It also had the size capacities for most carrying cases. A trivial math operation could prevent a sizing mismatch. This is what the humans were doing in their heads, one product combination at a time. This is what we could do nearly instantly, across an entire product catalog.

In addition to preventing bad cross-sells, we could also enable good ones: Bluetooth mouse to Bluetooth computer? No problem. Match the mouse’s brand with the computer’s brand? Easy. CNET’s database had more than 100 million product attributes to fuel such rules, which would emulate how a person intelligently chooses cross-sells.

Of course, the system would measure itself, so we would have additional data about each product’s sales, its effectivness as a cross-sell, even its behavioral performance in “people who did this also did that.” I liked that, because attribute-driven rules and behavioral data were together likely better than either approach separately.

Finally, the system would need to support hands-on use by merchandisers. Rules would be customizable, in a drag-and-drop way. And reports would link back to rules, so a merchandiser could see which rules caused which numbers.

That was the vision for Intelligent Cross-Sell. We announced the product in February 2006 and released it later that year, with paying customers.

By the first release, we could already see Intelligent Cross-Sell was substantially increasing customers’ cross-selling revenue. We later did case studies with Office Depot and Dell that reported a doubling of cross-sell and upsell revenue. (Upsells are another type of production recommendation that Intelligent Cross-Sell does. Whereas a cross-sell offers a carrying case with a computer, an upsell offers a better computer in place of the one you are considering. When doing this, Intelligent Cross-Sell can automatically generate “pitch text” based on an analysis of each computer’s specs, such as “Faster processor and 50% more storage.”)

Although we hit the market as the housing-bubble-induced recession was starting, we managed to get a decent core of customers in the 2007 to 2009 timeframe. By 2010, among our customers were four of the top ten brands in the Internet Retailer 500’s list of e-commerce sites. We had also gone international, at sites in the United Kingdom, France, Germany, and Denmark. Later, we reached sites in Sweden, Norway, and the Baltics.

As we grew Intelligent Cross-Sell’s revenue, we hired a small team to help evolve and support the product. Things were good in our little world.

But 2010 was a turning point. In the previous few years, several venture-funded startups had emerged as competitors, each with vastly more resources than our small group. They had all started with “people who did this also did that” technology, applying it not just to tech and consumer electronics but to all e-commerce categories. Although Intelligent Cross-Sell was still superior for cross-selling tech and consumer-electronics products, the best start-ups were using their greater resources to offer a broader set of capabilities, with cross-selling and upselling being just one aspect.

We knew the game was changing when, in mid-2010, two customers who had been highly satisfied nevertheless defected to other vendors. The other vendors simply offered more stuff. It was like being a bakery in a town that starts getting supermarkets. Our bread was better, but we didn’t have a deli counter or a produce aisle.

We could have adapted by becoming even more specialized, like an artisanal bakery of cross-selling. But it would have been hard to do within CNET, which had become CBS Interactive when the media giant CBS acquired CNET in 2008. As an enterprise software-as-service player, we were already an outlier of a business within CNET, more so for CBS. I did not want to make us even more marginal. So I concluded that everybody—CBS/CNET, the Intelligent Cross-Sell team, our customers—would be better off if we could partner with one of the other players whose only business was doing what we did.

The right match turned out to be RichRelevance, the personalization company with, by far, the most blue-chip customer base, as well as the most complementary approach to the market. In the partnership, RichRelevance would run the Intelligent Cross-Sell technology and employ the team; CNET would license its data and provide sales collaboration. The best supermarket would now offer artisanal bread.

The deal proved to be a win for everyone. For me, having spent five years on the product, having built a team without ever losing an employee, and having worked directly with every customer, I wanted Intelligent Cross-Sell to continue on the best footing possible. It did, and still is.

Meet Omnivark

2012-01-24T01:53:00.000-08:00

Along with taking some time off and doing consulting, I’ve been working on a new project:

Omnivark is a highlight reel for the written word. Each weekday we short-list the best new writing on the Web—the kind of writing that delivers such surprise and delight that you feel bad for not having time to find or read it. ;)

Omnivark creates that time for you. It fits the best stuff into an idle moment on your mobile phone or tablet or computer.

From writers famous to obscure, on topics familiar to foreign, Omnivark curates the well-said for the well-read.

I’ll be explaining more about the motivations and technology behind Omnivark soon. In the meantime, please check it out if you’re so inclined. (And if I may tilt your inclination, see last Friday’s edition, first entry, which you are statistically likely to appreciate.)

You can get Omnivark each weekday free via email, Twitter, Facebook, or RSS.

Just Follow the Signs...

2011-12-01T13:34:00.000-08:00

[From the corner of Market and Morgan in Hartford, CT]

Nuclear Weapons and Murphy’s Law

2011-11-10T12:23:00.000-08:00

Murphy’s Law says, anything that can go wrong will go wrong. In 1958, as the Cold War’s nuclear-arms race was accelerating, researchers at the think tank RAND worried that something—the ultimate thing—could go wrong with a nuclear weapon.

By that time, at least a dozen nuclear-weapon mishaps had occurred, including accidental drops, jettisons, and crashes. Due to technical and human safeguards, the nuclear material did not detonate. But the researchers saw ways the safeguards could fail or be intentionally defeated. Thus the question: Could Murphy’s Law go nuclear?

The researchers’ report, “On the Risk of an Accidental or Unauthorized Nuclear Detonation,” was declassified in 2000 and is now on the Internet. It is an interesting example of how to think about the risk of something happening when it has not happened before.

Normally, risks are associated with odds, and odds are based on past observations. For example, during the 1950s, the U.S. Air Force’s B-52 bomber had a number of accidents. Dividing that number by the total B-52 flight-hours gave odds of one accident per 25,000 flight-hours.

Lacking a record of nuclear-detonation accidents, the researchers could not calculate odds in the same way. Zero divided by anything would be zero.

The RAND researchers argued the actual risk was not zero. They cited numerous plausible scenarios in which technical flaws, human errors, sabotage, or some combination of these factors could cause a nuclear detonation. The bad scenarios were all highly unlikely, but no one knew how unlikely. In contrast, it was certain that the likelihood of an accident was increasing with the number of nuclear weapons.

The researchers also saw increasing risk in a key trend of the time, having more planes on continuous ground alert, or staying continuously aloft, with nuclear weapons ready to strike. This trend would greatly increase the number of flight-hours in which an accident could occur, as well as opportunities for various other human mistakes.

Finally, the researchers delved deeply into the possibility that an insider could deliberately override safeguards in an act of nuclear sabotage. Precedents existed for non-nuclear saboteurs, including military personnel with mental disorders. Against this backdrop, the researchers noted that many then-current nuclear weapons could be detonated singlehandedly by an individual with the right access and knowledge.

In response to these scenarios, the researchers recommended new efforts to develop technical and process safeguards to further reduce risk without sacrificing readiness. For example, the researchers suggested a lock for nuclear weapons, the combination for which would only be transmitted with the order to use the weapon.

The researchers also praised the idea of an acceleration switch, then under development, that would prevent a weapon from detonating while being handled on the ground. To illustrate the value, the researchers cited training incidents that would have caused a nuclear detonation if they occurred in the field.

Unlike many research reports, this one influenced the highest levels of decision-making. As told in Sharon Bertsch McGrayne’s The Theory That Would Not Die, the Commander of the U.S. Air Force’s Strategic Air Command, General Curtis LeMay, ordered new safeguards for nuclear weapons because of the report.

(McGrayne’s book is a popular account of the historical uses of Bayesian probability, a techique that incorporates degrees of subjective belief in addition to direct observations. The Bayesian approach can be useful when there aren’t enough observations to analyze or when the observations have uncertainties. Some of the statistical analyses in the RAND report used a Bayesian approach, which was unusual for the time.)

Since the early 1960s, the United States has continued to improve nuclear-weapons safeguards, not just due to research reports but also due to close calls. For example, in 1961 an air accident plunged two hydrogen bombs into a North Carolina field. One of the recovered bombs only had a single safeguard—out of six—remaining to prevent a nuclear detonation. Other accidents also avoided a detonation but spilled dangerous nuclear material.

Compared to early nuclear weapons, modern nuclear weapons have far stronger safeguards. They include a more sophisticated version of the combination lock suggested in the RAND report, physically requiring two people to unlock; arming components designed to fail under adverse conditions such as a crash, thus making them “fail safe”; and special types of conventional explosives and containment devices to prevent leakage of nuclear materials in an accident.

In addition to having safer weapons, the United States now has far fewer nuclear weapons deployed, on lower levels of alert, than during the height of the Cold War. So, the RAND researchers (Fred Charles Ikle, Gerald J. Aronson, and Albert Mandansky) would be pleased.

I am pleased too. Reading their report reminded me of the time I toured a decommissioned Titan II nuclear-missile silo in Arizona. Although it was a relatively low-tech artifact of the 1960s, I was impressed with how well considered its design and operating procedures were. It felt like those involved were up to the enormous responsibility attached to their jobs. That included everyone from the thinkers at RAND to the systems designers to the hands-on crews.

May they all continue their success, in the United States and wherever else Murphy’s Law and nuclear weapons could meet.

Witold Rybczynski’s One Good Turn

2011-10-17T06:41:00.000-07:00

When you see a bucket of screws at the hardware store, you probably don’t think of them as technology. After reading One Good Turn by Witold Rybczynski, you will think different.

Rybczynski argues that the screw was an exceptionally creative solution to the problem of fastening things. To illustrate what we take for granted today, he provides this capsule history of another fastener:

[A] useful device that secures clothing against cold drafts, [the button] was unknown for most of mankind’s history. The ancient Egyptians, Greeks, and Romans wore loose tunics, cloaks, and togas. Buttons were likewise absent in traditional dress throughout the Middle East, Africa, and South Asia. True, the climate in these places is middle, but northern dress was likewise buttonless. Eskimos and Vikings slipped their clothes over their heads and cinched them with belts and straps; Celts wrapped themselves in kilts; the Japanese used sashes to fasten their robes. The Romans did use buttons to ornament clothing, but the buttonhole eluded them. The ancient Chinese invented the toggle and loop, but never went on to the button and buttonhole, which are both simpler to make and more convenient to use. Then, suddenly in the thirteenth century in northern Europe, the button appeared. Or, more precisely, the button and the buttonhole. The invention of this combination—so simple, yet so cunning—is a mystery. There was no scientific or technical breakthrough—buttons can easily be made from wood, horn, or bone; the buttonhole is merely a slit in the fabric. Yet the leap of imagination that this deceptively simple device required is impressive. Try to describe in words the odd flick-and-twist motion as you button and unbutton and you realize just how complicated it is. The other mystery of the button is the manner of its discovery. It is difficult to imagine the button evolving—it either exists or it doesn’t. We don’t know who invented the button and the buttonhole, but he—more likely she—was a genius.

I have quoted at length because the passage is a miniature version of the book. Replace button with screw, and you’ve got Rybczynski’s thesis: Whereas nails came from spikes, which were crude and obvious implements, the screw came from what? Its key feature—and the source of its superior holding power compared to a nail—is the helical thread that winds around the shaft. The helix was neither obvious to conceive nor easy to implement in materials.

Like a genealogist tracing older and older descendants, Rybczynski searches for evidence of the earliest screws and screwdrivers. He profiles key innovators along the way, such as those who created the precision machine tools necessary for mass-manufactured, standardized screws; or inventors that improved on the flathead screw, namely Phillips’ x-shaped socket and Robinson’s square socket. The patent wars of yesteryear were about such things.

As much as One Good Turn is about screws, screwdrivers, and other tools, it is also about an intellectual quest. Unsatisfied with the literature on the subject, Rybczynski narrates his way through libraries and museums, each holding clues to the further history of the screw. He assembles new evidence of screws as fasteners in the Middle Ages. Then he keeps going in search of the ur-screw, back to ancient Greece.

Like the societies that had the button but not the buttonhole, the Greeks (and later the Romans) had the screw but not for fastening. Rather, the Greeks had large-scale helical screws for mechanical use. It was there and then that Rybczynski believes the original insight of the helical screw occurred, likely by the great engineer Archimedes.

So the next time you think about technology and a computer comes to mind, One Good Turn will remind you that technology has a far longer thread back through history.

Changing Gears

2011-10-06T02:38:00.000-07:00

Having reached a good outcome with CNET Intelligent Cross-Sell’s transition to RichRelevance, I will be taking this opportunity to switch gears: I am going into independent-consultant mode. That will include remaining on the RichRelevance team in a consulting capacity. I will be working with a few other consulting clients as well. I will also be using the flexibility of consulting to reserve some time for myself.

I realize that some people say they’re doing consulting as a euphemism for looking for a job. To be clear about my situation, consulting is currently what I want my job to be. Having been deep into a single thing for five years, with very high-stakes customers, I’m ready to come up for air. And if I’m coming up for air, I might as well breathe deeply. ;)

I’m fortunate to have clients right out of the gate, but I am always happy to hear of interesting opportunities where a little bit of my expertise and abilities can have significant impact. The areas I’m covering are product design, product marketing, strategy, company evaluations for M&A and venture capital, and advising middle- to later-stage startups on internal innovation for “next act” products (those that come after the core product that the entire company has been built around).

Feel free to drop me a line if there’s a connection or discussion to be had.

CNET Intelligent Cross-Sell @ RichRelevance

2011-10-06T02:35:00.000-07:00

Six months ago, CNET Content Solutions announced a strategic partnership with RichRelevance regarding Intelligent Cross-Sell, the product I co-created and the team I led at CNET. This blog post by RichRelevance’s CEO, David Selinger, describes what Intelligent Cross-Sell does and how it adds value to RichRelevance’s product line.

Other than posting a link to the CNET-RichRelevance announcement on Twitter, I didn’t say much about the deal when it was announced. My feeling was, I’ll talk about it when we’ve accomplished something more than announcing the partnership. Now is the time.

Having spent six months working closely with RichRelevance, I am pleased with the result: 100% of the customers are transitioned, the technology is migrated, the ICS team is at RichRelevance, and we’ve already done deals for new customers as part of RichRelevance. Meanwhile, CNET Content Solutions continues to bring product data, industry expertise, and sales support to the partnership. It’s a win/win as both sides now benefit from a bigger Intelligent Cross-Sell business than would have been possible from CNET alone.

In the next post, I’ll say what this means for me going forward.

My Perestroika

2011-09-25T13:15:00.000-07:00

My Perestroika is a documentary film about the lives of five Russians. They were children of the Soviet Union, which fell down as they grew up.

Now middle-aged, some have ridden the waves of change; others have treaded water. The film splices their present-day selves with their home-movie pasts with their uncertain futures.

I thought it was superb, but you can judge the trailer for yourself:

Simon Winchester’s A Crack in the Edge of the World

2011-09-17T06:58:00.000-07:00

Call it coincidence, but as I was writing about em dashes and long sentences lately, I was reading Simon Winchester’s A Crack in the Edge of the World. If you like long, lyrical sentences, festooned with em dashes, read on.

The geology of the northern half of California—whether we are talking about San Francisco Bay or the Central Valley, the Coast Range or the Sierra, the Monterey headlands or the cost of Humboldt country or Mount Diablo itself—is all interlinked, subtly confusingly and, for the geological mapmakers, often maddeningly. These links go far beyond the borders of the state—political lines that pay no heed, in this case, to the absolutes of geology. They spread far, far beyond—as we shall discover, they reach up to Alaska, they percolate across to Wyoming and Montana, they reach back west across two oceans as far, in fact, as India and Australia. One might say, indeed, that the story of what makes California so complex and so interesting and so dangerous—and what makes Diablo so similarly geologically alluring—has implications for, and connections to, the planet in its entirety.

It’s a marathon of a paragraph, but I like its layered, controlled complexity. Yet taken too far, that style can delineate itself to death:

[The basalts] spilled over and laid themselves down on the old Pangaea-Columbia-Arctica-Ur granitelike continental rocks that exist underneath, making the confection of geology that—in juxtaposition with all the ice and snow of climate and the storms and winds of weather, the polar bears and lichens of biology and the Eskimo and Inuit and Danes and Americans soldiers of anthropology—constitutes the great and mysterious island known today as Greenland.

The good news is, that specimen is the exception, not the rule. Winchester’s long and winding sentences are usually a pleasure to parse. Like poetry, they require more of you, but they reward the effort.

The same can be said of A Crack in the Edge of the World’s subject matter. The 1906 San Francisco earthquake is the center of a narrative constellation that includes a roadtrip across North American geologic points of interest, a people’s-eye history of California from Gold Rush to early twentieth century, a seminar on geologic science, and ruminations about the fragility of human existence versus nature. Consult the 27-page index for other topics covered.

Put another way, if books were beer, A Crack in the Edge of the World would be an earthy, flavorful stout: gaggingly thick for some people, satisfyingly rich for others. I found myself in the latter camp.

Friends and Strangers

2011-09-11T11:46:00.000-07:00

On the tenth anniversary of 9/11, I’ve been thinking about two stories. First, there was Abe Zelmanowitz, a worker at the World Trade Center. His co-worker and best friend, Ed Beyea, was a quadriplegic. As the building burned and people streamed down the stairwells, Abe stayed with Ed on the 27th floor landing. Because Ed weighed nearly 300 pounds, they were waiting for a rescue team to safely carry him.

Ed had a health aide, Irma, in the building. Although she found the two men, Irma was having trouble breathing from the smoke. Abe told her to go, that he would stay with Ed.

Both men called their families to say they were okay. Abe’s mother pleaded with him to get out while he could. He stayed.

Abe and Ed died in the building that day.

A family member recalled of the two, “If Ed was going to make [dinner] arrangements, he’d make sure it was kosher, and if Abe was going to make the arrangements, he’d make sure it was wheelchair-accessible. They always had each other’s best interests at heart.”

The second story is about Mike Benfante, who was also working in the World Trade Center. During the evacuation, he found wheelchair-bound Tina Hansen. He was a stranger to her, but Mike and colleague John Cerqueira carried Tina down 68 flights of stairs, often in darkness and smoke, sloshing through areas flooded by building sprinklers. It took 90 minutes. The building collapsed five minutes after they got out.

As the tenth anniversary of that day approached, Mike deflected attention from his heroism to the larger lesson of what 9/11 summoned in friends and strangers alike: “I’ve learned that 9/11 showed us that there are enormous, untapped reservoirs of extraordinary human kindness and generosity just waiting for a trigger, that this trigger should be pulled daily as most of us are basically good people.”

The Long and Short of Average Sentence Length

2011-08-07T04:26:00.000-07:00

For an earlier post, I analyzed the text from 616 articles in Slate’s sections “The Good Word” and “Books.” The purpose was to answer a question about the use of em dashes, but since I had all 697,422 words at the ready, I asked another question: Of all the articles, which had the longest and shortest average sentence length?

For context, the average sentence length across all articles was 25.4 words per sentence. The winner for longest average sentence length was nearly twice that. The shortest was about a third less.

And now, the drumroll please....

The winner for longest average sentence length, at 49.7 words per sentence, was Daphne Merkin’s review of Decca: The Letters of Jessica Mitford. Here is the opening paragraph:

Although it is not uncommon for big families to produce a rebel or two along with the chip-off-the-old-block offspring, there are few that can lay claim to as much dissension within the ranks as the aristocratic clan of Mitford. This gaggle of wayward sisters (six in all, with one brother, Tom, who was killed in combat in 1945 at the age of 36) included Diana, the family beauty, who married the dastardly Oswald Mosley, head of the British Fascist party; Nancy, the family wit, whose novel The Pursuit of Love kick-started the proliferation of novels, memoirs, and biographies that would come to be called the Mitford “industry”; and the family madwoman, Unity, who went bonkers for Adolf Hitler and put a pistol to her head when Britain declared war on Germany.

Compare and contrast with the winner for shortest average sentence length, Jason Sokol’s commentary on The Presidential Recordings: Lyndon B. Johnson: Mississippi Burning and the Passage of the Civil Rights Act: June 1, 1964-July 4, 1964. Sokol’s average of 16 words pers sentence was less than the length of the title. Here is the first paragraph:

President Lyndon Johnson, domineering and manipulative, lives on in American memory as the classic power broker. He bullied opponents, sweet-talked skeptics, and chewed out subordinates. He oozed confidence as he passed one piece of landmark social legislation after another, even as his cockiness helped to mire the country in Vietnam. Yet this is not the Johnson who emerges from volumes seven and eight of The Presidential Recordings, a transcription of his phone conversations from June 1 to July 4 of 1964.

My purpose is not to claim one of these examples is better than the other. They are both well-crafted paragraphs. But side by side, they are a reminder of how stylistically diverse good writing can be.

Citizen U.S.A.

2011-07-31T10:33:00.000-07:00

Fellow Americans: If the dysfunctional circus of Washington, DC, is getting you down, let me suggest an hour’s worth of relief: an HBO documentary film called Citizen U.S.A.

Filmmaker Alexandra Pelosi visited citizenship-induction ceremonies in all fifty states, interviewing new citizens. Some originally came as refugees, some snuck in and later got amnesty, some were students, and some were standard immigrants. The lucky ones were pursuing happiness. Many, especially women, were pursuing more basic needs like living in safety, speaking freely, or being able to work to support themselves. You will feel good about what America has done for them, as well as what they are doing for America.

The stars include New York City coffee cart guys from Afghanistan, a Buddhist monk in Utah, a nuclear scientist at Los Alamos National Lab, a Nigerian paralympics athlete in Kentucky, Iraqi refugees transplanted to Nebraska, and a Mulsim mother with a dream to take a cruise to Alaska. (Most of these descriptions came from the film’s synopsis at the HBO site. See also the trailer on YouTube.)

Citizen U.S.A. is currently available on Comcast’s On Demand service, but you need to be an HBO subscriber. I assume the film will appear soon on Netflix and other venues. Be on the lookout.

The Use and Abuse of the Em Dash

2011-07-23T08:30:00.000-07:00

In Slate, Noreen Malone makes The Case—Please Hear Me Out—Against the Em Dash. She says it undercuts good writing, yet writers are using it more. To make her point, she oversalts her own prose with the em:

The problem with the dash—as you may have noticed!—is that it discourages truly efficient writing. It also—and this might be its worst sin—disrupts the flow of a sentence. Don’t you find it annoying—and you can tell me if you do, I won’t be hurt—when a writer inserts a thought into the midst of another one that’s not yet complete?

Having thus revealed the em dash’s peril, Malone later concludes, “Leave the damn em dash alone.”

I suggest not. The em dash is a good thing, albeit the kind where too much good is bad. As we say in software development, that is a feature, not a bug.

Of the em dash’s many uses, the main one is to set off a phrase with greater emphasis. Used in tandem—as here—em dashes are like commas or parentheses, only more assertive. Used alone, an em dash heightens what comes next—more drama if no comma.

Em dashes are effective for emphasis because they are rare. Use them too much and you defeat their purpose, as Malone demonstrates with her wanton em dash abuse. But is today’s writing increasingly like that? Malone asserts such a trend but caveats that it’s “just anecdotal observation; I admit I haven’t found a way to crunch the numbers.”

Here’s a way to crunch the numbers: Extract the text of hundreds of articles published in Slate from 1996 to 2011. Focus on the sections “The Good Word” (where Malone’s article is filed) and “Books.” They seem like good candidates for the at-risk writerly behavior that Malone fears.

When I did that, I found 616 articles through the end of June 2011, totaling 697,422 words. Because different years had widely varying amounts of articles, I split the articles into two periods: 1996 to 2004 and 2005 to 2011.

The earlier period had 7.6 em dashes per thousand words; the later period had 7.8. That difference is noise. Malone’s peers are not spiraling into an abyss of increasing em-dashery.

So despite Malone’s concerns, I suspect that Slate’s writers are using the em dash to good effect. They know that with punctuation, as with salt, an occasional dash will do you good.

David Eagleman’s Sum

2011-06-26T16:18:00.000-07:00

“In one afterlife, you may find that God is the size of a microbe and unaware of your existence. In another version, you work as a background character in other people’s dreams. Or you may find that God is a married couple, or that the universe is running backward, or that you are forced to live out your afterlife with annoying versions of who you could have been.”

That is from the back cover of David Eagleman’s Sum, subtitled “forty tales from the afterlives.” Each tale is a vignette about what happens when you die.

Eagleman is a neuroscientist, and Sum is a literary mind game. With imaginative what-ifs, he subverts familiar conceptions of life and death. Instead of a singular light in the dark, you get a light show.

It’s quirky, adventurous, and at times eloquent. It’s a virtuoso performance of thinking different. It’s also admirably brief.

If Sum sounds interesting, The New York Times has an excerpt with four vignettes. And here is the book’s page at Amazon.

Dreaming FIDS

2011-06-12T13:50:00.000-07:00

Dreaming FIDS (Flight Information Display System) is an artwork in San Jose Airport’s new Terminal B.

It’s a fish tank. Inside are fish, video screens, and cameras. You see not only the fish but also the cameras’ view of the fish.

And who is that in the background of the fish-surveillance video? That would be you, looking at yourself looking in.

Seeing Dreaming FIDS brought to mind the Lou Reed lyric, “This here’s a zoo, and the keeper ain’t you.” However, I appreciated the work even more after I watched this three-minute video. Check it out.

Dreaming FIDS is by Ben Hooker and Shona Kitchen. It’s located between gate 25 and 26 in San Jose Airport’s Terminal B.

Edward Tufte's ET Modern Gallery

2011-06-05T14:04:00.000-07:00

Many readers of this blog know the work of Edward Tufte. His books, such as The Visual Display of Quantitative Information and Envisioning Information, are widely regarded for their rigorous pursuit of truth and beauty in data visualization. A recent Washington Monthly profile captures his notoriety well.

Perhaps fewer of you know that Tufte’s main interest these days is sculpture. Or that he has his own gallery, ET Modern, in New York City. Or that he is often there on Saturdays, giving free tours.

Now you know. Be advised, however, that the gallery and tours are primarily about Tufte’s sculptures, which are not data-driven. They are modern art compositions made of metal, light, and space. They reveal different aspects depending on the viewer’s position, the time of day, and other environmental factors. In that sense, they are meant for the viewer’s analysis and interaction—a form of visualization more subtle and open than charts on a page.

In his gallery tour, Tufte’s voice is familiar from his books: professorial, authoritative, on a mission. He wants you to understand what he is doing and why. He makes connections to his previous data-visualization work, but just as often he makes distinctions. In the tour I attended, he said he had explored the conceptual territory of data visualization to the point that he is now more a guide than an explorer. For discovery and exploration, he has his art.

So if you visit the gallery with that mindset, and you get the chance to see a Tufte tour, you will be rewarded.

Correlation Exploration

2011-05-28T08:19:00.000-07:00

Google Correlate has a feature where you draw a curve along a timeline, then click Correlate. You get back a list of search terms that varied in popularity by that same curve.

Below is the result for the first curve I drew.

If butter production in Bangladesh can be a leading indicator for the S&P 500, then I’ll allow that the above terms can be correlated.

Counterintuitive College Rankings

2011-05-22T14:45:00.000-07:00

Given a list of the top 400 colleges worldwide, which U.S. college would you guess is better: the one ranked higher than 81% of all other colleges worldwide, or the one ranked higher than 69% of other colleges in the United States only?

Most people would say the one that’s better than 81% of all other colleges worldwide. But maybe you’d sense a trick question and say the other one.

It’s a double trick question. The two choices represent the same college, from the same ranking. If that does not sound possible, read on.

We will use the rankings from U.S. News’ World’s Best Universities: Top 400, which are sourced to Quacquarelli Symonds. Of the top 400 colleges worldwide, 86 are from the United States. However, the U.S. colleges tend to be higher ranked than the non-U.S. colleges: The average rank of U.S. colleges is 164, whereas the average rank of non-U.S. colleges is 210.

Let’s see an example of what this means in practice. Washington University in St. Louis is 75th out of 400 worldwide. However, it is 27th out of the 86 U.S. colleges on that same list. In terms of percentile rank, these numbers mean that Washington University ranks higher than 81% of other colleges in the worldwide top 400, yet it ranks higher than only 69% of other U.S. colleges in the worldwide top 400.

The chart below shows all the U.S. colleges on the list. The light bars are percentile ranks against the other 399 colleges worldwide. The dark bars are percentile ranks against just the other 85 U.S. colleges. As you can see, most colleges have a significant gap, ranking better against the world than against U.S. colleges only. So keep this in mind next time you see a U.S. college tout a “world-class education.”

Review: The Yugo by Jason Vuic

2011-05-15T15:13:00.000-07:00

In the mid-1980s, a cowboy capitalist teamed with socialist Yugoslavia to regift a decades-old Fiat onto the American market as the Yugo, a car that redefined the word cheap. Such is the true story of The Yugo by Jason Vuic.

Each chapter’s subheading is a Yugo joke: How do you make a Yugo go faster? Use a tow truck. How do you double the value of your Yugo? Fill the tank with gas. What’s included with every Yugo owner’s manual? A bus schedule.

Jokes aside, Vuic rightly asks: How does something like the Yugo become an icon of bad? And what were the Yugo’s creators, investors, and buyers thinking?

Enter Malcolm Bricklin, an entrepreneur long on salesmanship but short on discipline. He had a knack for raising and then quickly spending lots of money. Prior to the Yugo, he had already notched multiple failures in the car business, each time emerging from the crater to do it again.

Bricklin’s vision for the Yugo was radical affordability. Introduced in 1985, the Yugo cost $3,990, far cheaper than any other new car, and cheaper than the average used car. This price breakthrough generated a media sensation, which made the Yugo famous.

The price was possible because of state-subsidized Yugoslavian labor, which made the cars. However, with a socialist workforce came low productivity and quality.

When most Americans went [to the factory in Yugoslavia],” [Yugo executive] Pete Mulhern recalled, “they expected to see something like a printing press rushing by. And the Americans would say, ‘Hey, why is it stopped?‘ But it wasn’t stopped. It was just moving really slowly.”

The Yugo quickly gained a reputation as cheap in the bad sense. Nevertheless, thousands of bargain hunters bagged a Yugo in its first year of availability. That included Yugos given to buyers of certain Cadillac models during a Pittsburgh dealer’s “buy one, get one free” promotion.

But after the bargain-hunting vanguard, customers became harder to find. Ultimately, the Yugo could not compete with its reputation as a joke.

Like Bricklin’s previous ventures, Yugo of America spent far more than it made. Ironically, investors pushed out Bricklin before the company went bankrupt, which allowed him to sell his stake when it was still worth something. The investors that pushed him out later lost everything.

The Yugo’s story includes cameos by Kissinger Associates, Armand Hammer, a Savings & Loan that would be subsequently seized by federal regulators, the government of New Brunswick, Canada, and various other unlikely players. It should also be said that Vuic gives an honorable voice to the unsung managers and executives who toiled to make the Yugo real. For those people, it made sense at the time.

Which brings us back to the question of what were they thinking. Vuic argues that while the Yugo was far from a good car, it was not out-of-bounds bad for the price. He cites surveys of mostly satisfied owners who didn’t expect much for what they paid. He makes a convincing case that objectively worse cars had been sold in the United States—for example, one of Brickin’s earlier imports “burned a quart of outboard motor oil every 260 miles, and had front and rear bumpers that were several inches lower than any car on the road.”

Rather than blame the Yugo alone for its infamy, Vuic also indicts the American 1980s consumer culture. Unlike the 1960s, which had a counterculture that embraced the cheap and simple VW Beetle, the 1980s were about aspiring to the next level up. Whereas the 1960s wanted the Beetle, the 1980s wanted the BMW 3 Series.

So perhaps it was bad timing that pushed the Yugo from being just another mediocre car into the reputational abyss it now occupies. Which reminds me of a joke: How do you make a Yugo go from 0 to 60 in less than 15 seconds? Push it off a cliff.

[Here is the Amazon link for The Yugo by Jason Vuic. The photo of the Yugo ad is from Wikipedia.]

How Pizza Hut Got Its Name

2011-05-08T02:50:00.000-07:00

This didn’t fit anywhere in my review of Robert Spector’s The Mom & Pop Store, but it’s still worth passing along: Spector’s story of how Pizza Hut got its name.

[When Dan and Frank Carney started a pizza restaurant in 1958 in Wichita, Kansas, they didn’t know what to call it.] The local Coca-Cola distributor provided a complimentary small outside sign that was wide at the top and tapered down at the bottom. There was room for only five letters on the top line and three letters on the bottom line. “Pizza” obviously had to be on top. But Pizza what? Pizza Pad? Pizza Inn? Pizza Pan? Pizza Jug? Dan’s wife, Beverly, mentioned that she thought the building looked like a hut. The decision was made. The name of the pizzeria would be Pizza Hut.

There you have it.

A Lot from a Little: See and Try Generative Music

2011-04-25T01:22:00.000-07:00

When you hear complex music, you might imagine a serious-minded composer, choosing each note with a learned and discerning ear. Instead, imagine clicking a few cells on a grid, then clicking “Play.”

It’s called generative music, and it will surprise you. For example, this 17-second video is a musical piece that took all of nine clicks in Otomata, a tool you can try for yourself in a Web page.

Before recording the video, I had lit up nine cells by clicking them. The music came from Otomata’s executing a simple set of rules on the lit cells:

Each lit cell has a direction: up, down, left, right.

On each beat, all the lit cells move one step in their respective directions.

If a cell hits the grid’s edge, the cell bounces back the opposite way. On the bounce, a tone will sound. The pitch (low to high) depends on the position, like a piano key’s pitch depends on its position along the keyboard.

If a cell hits another cell, each cell changes direction 90 degrees clockwise.

To avoid overly dissonant results, Otomata uses a limited set of pitches. This enforces a similar feel to Otomata pieces. However, within the general similarity is a world of potential variations.

Having experimented for a while, below is the best Otomata piece I created.

I like the way the piece moves through many different tonal relationships and densities. It was the result of my having clicked eleven cells, plus a few extra clicks to change certain cells’ directions.

Otomata is an implementation of cellular automata, a computational technique that combines simple elements and rules to create complex results—or, I should say, potentially complex results. Depending on your starting state, you can end up with simple cycles or highly complex variations on a theme.

If you try it, a little experimentation should quickly get you interesting results. (For a shortcut, you can start by running or tweaking my second piece.)

While Otomata won’t replace the serious-minded composer, it’s a fun way to see how generative music can make a lot out of a little. Thanks go to Batuhan Bozkurt for creating it and making it freely available.

Review: Robert Spector’s The Mom & Pop Store

2011-04-17T13:49:00.000-07:00

Part history, part biography, Robert Spector’s The Mom & Pop Store is about America’s corner stores, neighborhood grocers, and other small retailers. You won’t read about these businesses in BusinessWeek or Fortune, yet their human stories are as interesting as any corporate CEO’s.

There’s Rob Kaufelt, owner of Murray’s Cheese Shop in Greenwich Village, New York City, who says: “Sameness is what the larger market is about....Clearly, what we’re celebrating is not sameness. The cheese that you’re buying today is not going to be the same next week as it was last week, because the seasons are changing. The cows are eating something different. You go to McDonald’s or Starbucks for the same thing. That’s what you’re there for. You come to us for the opposite experience of going to Starbucks.”

There’s Chuck Robinson, co-owner with his wife Dee of Village Books in Bellingham, Washington, who says: “We are not in the business of selling books. The grocery store and the drugstore are in the business of selling books. We would like to sell the books off our shelves. But our business is your coming into the store looking for a certain book or idea, and our ability to connect you with that book or idea.”

And there’s Spector’s father, who ran Spector’s Meat Market in Perth Amboy, New Jersey, for four decades. As American Dreams go, Spector’s father’s was more grit than glory, but it got the job done. Spector’s Meat Market bettered the lives of both the Spector family and a local population of loyal customers.

For Spector, a mom & pop’s role within the local community is key. When employees know customers’ names, and people stop by just to stop by, it’s a great mom & pop store. Such stores have meaning beyond buying and selling things. And that’s why Spector thinks they will never go away.

To the conventional wisdom that says the classic mom & pop is an endangered species, Spector says, “Throughout the history of retail, some new format always has been ‘killing’ the mom & pop store, but somehow it always survives.” In the past hundred years, five-and-dime chains, catalogers, department stores, deep discounters, shopping malls, category killers, and e-commerce have all hit the mom & pop economy. The great mom & pops survived by adapting, by finding new ways to keep their communities.

In profiling various mom & pop stores, Spector covers a lot of ground: around America and occasionally beyond, from meat to music to jewelery to pine furniture. Along the way, he seasons the narrative with gems like this one, about a local diner: “If Perth Amboy was an ethnic melting pot, Texas Lunch was the stove.”

My main quibble with the book is it sometimes lets the great mom & pops stand as representatives of all mom & pops. But as Spector notes, “About a third of family-owned businesses survive to the second generation.” We all have had less-than-great experiences with the other two-thirds. I suspect those businesses hold their own lessons. Maybe that’s an opportunity for Spector to write a sequel.

For now, it’s enough to enjoy The Mom & Pop Store as an alternative to the usual fare of books about big businesses and hot trends. Spector brings us back to basics, in a satisfying way.