On Signal Density

LXII

“So me think, why waste time say lot word when few word do trick?”

Sea World

There’s a funny scene in The Office in which one of the characters, Kevin, decides to reduce the amount of words he says to save time. When asked to complete a task, instead of saying something like “Sounds good, I’ll do it now,” he responds, “me do now.”

When you say or write or otherwise communicate something, you are producing information. The part of that information that communicates meaning is signal, while the part that does not, is noise. I agree with Kevin’s underlying sentiment that it might behoove us to focus more on communicating just the information—I know that I for one could “learn write fewer word.”  

However, compression is an art, not a science. Kevin runs into a  problem when he says he wants to “See world,” which is mistaken for him wanting to go to “Sea World.”  Kevin, unfortunately, removed too much of the signal with his lossy compression.

Thankfully, there are some ways to think about information and compression that can help us go forwards without sounding like a cave man.

GPT, My Copy Editor

Last week, when I was writing BirdDog’s application for YCombinator, I had GPT edit each of my responses. I noticed, however, that it’s edits followed some patterns. So, I asked it about the sorts of edits it tended to make with my writing.

Information compression was a theme. An example:

• Original: “We picked this idea because we got to learn a lot about sales people in the last company we were both involved in.” 

• New: “We chose this idea because we learned a lot about salespeople in our last company.”

If we’re using word count as a proxy for total information, this represents a 35% reduction in information without any loss of meaning–excellent, lossless compression. This may not seem significant, but if you’re trying to communicate complex ideas, every word counts. 

On average, my blog posts have been roughly 1500 words. I think that’s too long, and not because of their absolute length. Rather, I think it’s too long because I can say the same things better in maybe 1000 words.

Show, Don’t Tell

While the above is a great example of compressing information without loss of signal, there are plenty of examples of lossy compression. That becomes even more true when you add in the emotional axis of communication.

Show, Don’t Tell, is a classic piece of advice I originally learned in the context of writing that can also apply to theater, sales, and I’m sure a million other things. It instructs you to bias towards communicating information with descriptions & evidence rather than explicit language. An example:

• Context: “There was a pensive look on his face as his gaze slowly wandered across the cold sea that dominated his field of view. The bitter wind whipped against him; it felt as if it were almost freezing the tears on his cheeks. He didn’t care.”

• Compressed: “He was depressed.”

Labelling someone with an emotion like depressed is akin to putting a layer of abstraction over the human experience. If you’re trying to actually evoke that emotion in someone, it can be more meaningful to paint a picture of what their experience looks and feels like than it can be to use a one word descriptor. 

Likewise, when selling a sales tool, you can say, “we’ll make you money,” or you can say, “In the past, we were able to generate over $600K in pipeline for a client in two months.” Sometimes, giving the recipient of the information more context can help evoke the emotions you want to experience more than compressing the information can.

While this maybe makes it seem like the trade off is between succinctness and meaning, it is rarely so binary. Even when adding in context, we can still compress the information further. Back to our poetic example:

• Context, Compressed: “His countenance was pensive as his gaze slowly wandered across the cold sea. Bitter wind battered him; it felt as if it were freezing the tears on his cheeks. He didn’t care.”

With fewer words, this new version communicates as much or more signal than the first version that had context.

Signal Density

Signal density is a measurement that, while abstract, captures the sentiment of striving to communicate information as succinctly as possible without losing meaning. An equation might be something like this:

Signal Density = Value of Signal / Total Information

Even though it’s hard to quantify the value of signal, this framework is useful in the sense that it forces you to decide what meaning you’re trying to communicate. That way, you yourself have the context needed to attempt to estimate the value of your signal.

If you’re selling a product, a few powerful customer testimonials may be the highest value signal you can share. On the other end, if you’re recruiting an engineer, a description of some of the cool technical tricks you’ve used in the code base may be more valuable signal. 

This means that if you had one pitch that contained both of those pieces of information, you could potentially double the signal density for both parties by sharing the half of the pitch with each of them that focused only on the information that is valuable for them.

All of that being said, on a completely human end, if you’re just talking to communicate that you’re comfortable with someone, then the value of the signal might be a product of the length of time it takes you to deliver it. Sometimes, there’s nothing wrong with that.

Context is everything.

Blog post today strong signal density. Much value, few word. 

Live Deeply,