Book Metrics^
Every week Brandon Sanderson releases a vlog on his YouTube channel that provides weekly updates. He frequently holds out his hand and shows a graphic indicating the degree of completion for a novel or trilogy.
This got me thinking on what kind of metrics I could collect from my own process.
Lead and Lag^
Performance metrics can be divided into your lead and lag measures.
Lag Metrics^
How do you define success? Not in life or the world but one particular thing you have done. How do you know the thing was done well? What makes it a win?
Let’s make the exemplum more concrete: Say you have published a book. You think the book is successful. You want to tell your friend it’s successful. What are the things you cite to indicate success?
Reviews from the nation’s top literary critics?
Viral trends on social media.
Sales figures?
The fact it is in print?
The fact that you have a deal with a publisher?
The fact that you have an agent?
The fact that you wrote a book?
These are your lag metrics. Called “lag” because they lag behind the thing they measure. If these are your only metrics then you won’t know whether or not a book is successful until you’ve already expended the effort to write the book.
Lag metrics stem from your definition of success.
Lead Metrics^
Lag metrics work best when you have already done the thing and want to know how it stands in the world. But, if you’re a writer like Umberto Eco, the gulf between the conception of a book and a reader finding the opportunity to give you five stars might span several years. But, during those years, how are you to know you’re on the right path?
Lead metrics show you that you are on the right path to generate lag metrics. Over the course of producing a work, what are the things that rise to the surface that indicate that you are on the right track.
Draft Stages^
Important to note in the consideration of lag and lead metrics is the iterative draft process I employ.
Texts start out as a series of notes in my Zettelkästen. In the notes, I work out the theme, plot, characters, setting, conflicts, and structure.
Draft α starts out with a migration of notes content into a LaTeX document. Each point gets expanded on, working from a few sentences to a short paragraph or complete thought.
Draft β begins where the α draft left off. In each scene wherein two characters interact, I write out a treatment on the conversation. What does each character believe going in, what do they want, how do those beliefs and wants change, which all gets broken down into a series of exchanges that note how the conversation progresses.
Draft γ takes the dialogue exchanges from draft β and works to build them out into final dialogue. The goal is to produce something you can read like a play, with light notes here and there on how action breaks up the exchanges.
Draft δ is about building out the text and the dialogue exchanges into their final form. At which point, the text shifts into a review state.
Note, this process is a starting point. I’ll come back as I complete novellen to talk about how things went and what went wrong.
Literary Applications^
As an old writer coming new to the publication of fiction, this whole process is a shakedown operation. I want to identify what works and how it works best. But, you need to start somewhere and so I’m starting here.
My initial lag metrics are the completion of the book and the completion of certain stages within a reasonable time frame. But, what’s reasonable?
The book in question is a collection. It is composed of ten or twelve novellen. As a starting point, I’m going to assume each novelle is in the neighborhood of ten thousand words. I want the α and β drafts for each story minimum complete by January 2027.
So those are my lag metrics: completion and deadline. What about lead metrics?
To complete the α and β drafts for ten stories in ten months I have a roughly thirty day time frame for each novelle. The development process and the completion of the α draft should be done within a week. The β draft should be done within the following three weeks.
Using Task Warrior I can lay out the planning and writing process for each draft and break the drafts down into the particular structural components as I go. This allows me to produce a summary on my desktop that ensures that my progress through the book is always visible.
Word Count Progressions^
In my current technological setup, I don’t have an easy way to record word counts and show progress towards word count targets. But, that’s something I’m working on and should have ready to roll out in a week or two, Deus le veult.
Ten thousand words is the target count for the δ draft. I don’t have a reasonable target yet for the α, β, and γ drafts. For this first project, I’ll keep a record of where each story lands and use the average for each stage as a projection for the next.
In one of the YouTube lectures, Sanderson gave word count metrics as two to four hundred words per hour as a good target when working on a rough draft. The lower end indicates opportunities for performance improvements for good habits. At fifty words per hour you’re distracted or fretting too much over each word. A fast writers are up at seven-fifty to a thousand words per hour. At two fifty, you can write the first draft a hundred thousand word book in a year at eight hours a week.
Given my specific draft targets, I’m leaning towards a four thousand words a week as an initial goal.
Data Collection^
The problem with all this math is that I don’t yet have a system in place to consistently record and track word counts. This concern is going into planning a CLI tool, which I’ve given the initial internal designation of C3.1.
The aim for the tool is to check in on active LaTeX projects every thirty minutes. If it finds a change in the mtimes, it responds by running texcount and checking the chapter word counts against the last recording. If there is a change it adds a new row to the table and if the delta is positive it records it as well.
What do we get from this?
Current word count in relation to projected word count gives me what I need to feed into a simple progress bar on Conky.
The cadence of changes in each chapter at each stage allows me to project a probable date of completion at relatively early stage of the project.
The word count delta per bell on average allows me to calculate the number of hours left on the book.
Performing these calculations on a database means that the output adjusts as I make progress. So, the good days and the sluggish balance out in the reporting.
The end result is that I have reasonable figures I can report on this blog and do a Sanderson-style ding I’m 27% done on xyz moving forwards.