When Reed Hastings was incubating the idea for Netflix, he started by thinking very high-tech. That is, if your definition of “high-tech” includes a Ford Country Squire wagon stuffed with cassette tapes.
“It turns out that’s a very high-speed network,” Hastings said at a conference earlier this year. Hastings’ computer science professor at Stanford in the ’80s had asked Hastings’ class to work out the data transmission speed of a station wagon driving cross-country with a bunch of data storage tapes in the way-back. The transmission speed, measured in bits-per-second, far exceeded speeds over either the wired or wireless channels of that era.
This got Hastings thinking about other unconventional transmission channels. DVDs through the U.S. Mail turned out to be pretty efficient too, and it was that “technology” that launched Netflix. In the intervening years, broadband improved in almost every U.S. household, Netflix now streams over the internet, we all binge-watch everything, and Hastings is a billionaire.
When we think of sending information in a digital format, that is the kind of engineering solution that comes to mind: more bandwidth, faster data speeds, and more powerful signals that reduce noise and distortion.
Those solutions are certainly where computer pioneer Claude Shannon began when he laid down the essential principles of information theory in his 1948 treatise, A Mathematical Theory of Communication. (Shannon’s life and work are the subject of an excellent new biography, A Mind at Play: How Claude Shannon Invented the Information Age, by Jimmy Soni and Rob Goodman.)
The 1948 paper’s goal was to address the “fundamental problem of communication,” which Shannon presented as “reproducing at one point either exactly or approximately a message selected at another point.” Shannon formalized the problem in a way that allowed him to deploy heavy-duty mathematics, much of it around brute-force engineering elements like bandwidth, transmission speed and signal strength. His paper laid much of the groundwork for the way today’s communication networks function.
But Shannon left the door open for a little mischief. Two defined terms in Shannon’s framework are “redundancy” (the repetition of information in a message) and “data compression” (techniques to shorten a message without losing its information content). The benefits of sending a message quickly and efficiently are pretty evident. If you’re trying to put a bunch of information through a narrow pipe, it’s probably good to minimize redundancy and compress data, right? The smaller the message, the less bandwidth and speed required, allowing more and bigger messages to go from point A to point B.
Redundancy cuts both ways, however. Repetition can be merely…repetitive. On the other hand, repetition can provide a check on information that may have been corrupted the first time through. A message can be garbled on its first trip from sender to receiver, but the second iteration may survive intact.
To draw a connection between the goals of human communication and machine communication, repetition can also provide emphasis and structure to a message, making it resonate with an audience’s own expectations. Your high school public speaking coach’s classic advice—”Tell ’em what you’re going to tell ’em, tell ’em, then tell ’em what you told ’em”—is a testament to the value of redundancy.
Data compression techniques also come in many forms. In the middle of a particularly math-heavy stretch of his paper, Shannon surprisingly name-checks James Joyce’s epic, abstruse novel Finnegan’s Wake. Shannon says that Finnegan’s Wake “enlarges the vocabulary and is alleged to achieve a compression of semantic content.”
What? Where is the data compression in Finnegan’s Wake? And where did the bits and wires and engineering stuff go?
This is where artistic creativity comes in. The way the message’s content is expressed—in ad industry parlance, “the creative”—carries a lot of weight in delivering the message’s meaning and richness. When you consider people as part of a communication system, the sender has an opportunity to reduce the size of a message by taking advantage of what’s already in the audience’s heads.
Think of acronyms. “NBA” summons three words in a basketball fan’s brain, but also a host of connections, experiences, memories, and facts. All that data—some of it shared by many, some of it unique to you—is “compressed” in the acronym. Whether you’re referring to the three-word literal meaning or related information, saying “NBA” saves time and characters when you say it, write it or send it over a network. Even if the network is just guys in a bar talking smack about the Knicks.
Acronyms are just the beginning. Jargon, mnemonic devices, metaphors, memes—all summon the wealth of information stored audiences’ brains.
And don’t forget stories—maybe the most powerful data compression technique of all.
In his book The Storytelling Animal, Washington & Jefferson College professor Jonathan Gottschall describes a streamlined template for stories, connecting three elements:
Story = Character + Predicament + Attempted Extrication
Once humans recognize a situation as a story, we instinctively frame it in that three-way archetype, drawing in all the associations that we infer based on our knowledge of stories.
Think what happens when you sit down to watch The Godfather. From the first moment, you are presented with overwhelming amounts of information—the titles, the music, the opening line by Bonasera, the undertaker: “I believe in America.” There is no way to divine the story from this disparate, multimedia collection of information. That won’t stop your brain from trying. It is immediately looking for the character and the predicament. You may soon settle on Vito as the main character. You learn about him, and you begin to start looking for the predicament. The Godfather doesn’t tell you to do that—you just do. The film provides the inputs to the algorithm; you put it all together in your head.
If you weren’t continuously arranging even these early bits of information as a story, your brain would be drowning. The story archetype gives the information order and meaning, building a vessel for the flood of information still to come.
In 1997, Apple knew enough about the brain’s ability to fill in the gaps to do something very bold. That date marked the launch of a memorable Apple ad campaign that seemed to have nothing to do with computers. Rob Siltanen was creative director at Apple’s agency, TWBA/Chiat/Day, and he described the message this way.
It was a billboard campaign that had simple black and white photographs of revolutionary people and events. One ad had a photo of Einstein. Another had a photo of Thomas Edison. Another had a photo of Gandhi. Another had the famous photo of flowers placed in gun barrels during the protest of the Vietnam War. At the top of each image was the rainbow-colored Apple logo and the words “Think Different.” Nothing else.
Memorable. Evocative and exciting. Irreducibly succinct. But hardly direct. As Siltanen said, “The work seemed in need of explanation.”
Fine, but nobody considered placing footnotes on those billboards. The campaign was designed to invite several interpretations, all flattering to Apple:
- Apple helps you think differently
- Apple can help you be great
- Einstein, Edison and Gandhi would have used Apple
- Technology can help you be great…but only if it appreciates the revolutionary
Even the single word “different” was loaded because it was either (a) short and slang for the adverbial phrase “in a different way,” (b) short and slang for the prepositional object “about different things.” “Think Different” is not correct English grammar—and using non-standard grammar is itself an example of “thinking different.”
Finally, the campaign was an old-fashioned act of industrial rivalry. The use of the word “Think” subtly baited then-PC rival IBM, whose long-time CEO Thomas J. Watson famously posted a “THINK” sign in every IBM office. IBM’s laptops were called “ThinkPads” and an IBM ad campaign of the era used the slogan “Think IBM.” Apple’s new tag line did not shy away from the comparison.
When it comes to data compression, the Think Different campaign’s felicitous melding of image, logo–and that provocative text–was a masterpiece of efficiency.
We already know it takes top-grade engineering skill to design the biggest, fastest, most-powerful pipes to deliver all those bits. It also takes very skilled artists, writers, and designers to create the sounds, images and words that will make the greatest impact on an audience. And it takes a combination of the best analysis—these days, drawing on the conclusions of both machines and people—to figure out how to put it all together.
It’s a very high-tech undertaking…especially if your definition of “high tech” includes stories, metaphors, slogans, logos and layouts.
Tom Rutledge is Boston-based investor and advisor to media-tech companies, including WEVO.
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