Using RescueTime to Answer the Question: When Do I Write?

I‘ve written quite a bit about how much I write, and that I find ways to write every day. What I haven’t talked about much is when I do my writing. Remember, I have a full time day job, and two little kids, so my time is very limited. In order to write every day, I needed to adjust to the fact that I couldn’t count on a fixed time of day, or a fixed duration of time in which to write. I had to learn to write whenever the time became available.

Since early this year, I have been using RescueTime on all of my computers. For those not familiar with it, RescueTime is an application that tracks what you do on your computer and provides you with data about your productivity. RescueTime has a database of applications and websites and ranks them anywhere from Very Unproductive to Very Productive. It gives you a “productivity pulse” from 0-100 telling you how productive your days were. One of the things that RescueTime captures is when you used an application and for how long.

Yesterday, I finally got around to playing with RescueTime’s API, and was able to pull out data about my use of Google Docs, which is where I do all of my writing. I learned a lot about when I write by looking at that data. I also confirmed some things that I already knew.

When do I write each day?

I went back to March of this year and took data from March 1 through yesterday. I filtered the data to look at just the “Writing” activity in RescueTime–that is, applications that are related to writing. I further filtered those down to Google Docs to ensure that I was capturing my regular daily writing, all of which I do in Google Docs. I aggregated the data by hour to see when during the day I typically do my writing. Here is the results:

When Do I Write

You can see that the vast majority of my daily writing is done between 7-9 pm. Indeed, of the 102 hours of writing that RescueTime has logged since March, more than half–53.1 hours–has taken place between 7-9 pm.

This data aggregates all days in the date range, including weekends. I sometimes write early on Saturday or Sunday mornings, especially when I know I have a big day ahead, so there is a spike there. Also, I sometimes write when the kids nap on the weekends (something that is increasingly rare), and so you see a small spike between 1 – 3 pm as well.

If I break things down by weekday/weekend writing times, here’s how things look:

Weekday-End Writing

The pattern on weekends is roughly the same as weekdays, and yet the chart is a little deceiving because it makes it look like I write a lot less on weekends than on weekdays. But remember, there are only 2 days in a weekend, and 5 days during the workweek. From March to the present, I’ve spent 76 hours writing during the workweek. This averages out to 15.2 hours per weekday.

However, I’ve spent about 30 hours writing on weekends in that same period. This averages out to 15 hours per weekend day. Put another way, I’ve written a total of 15 hours for each day of the week in the period from March to the present. I write just as much on the weekends as I do on weekdays.

An important note on the data collection

One thing I want to emphasize here. All of the data was collected automatically by RescueTime. I did not have to log my writing time. I did not have to take any extra steps, beyond opening my document and typing. RescueTime captures it all, automatically. Indeed, there is a gap in the data. When I was on vacation in Maine, I took a laptop with me that I forgot to install RescueTime on, so none of my time that week was captured.

But the key point here is that all of this data was generated without my having to take a single action beyond doing what I normally do. Of course, I did have to spent a few minutes creating the charts for this post, but the data was already there. I just had to grab it and process it. This, in my opinion, is a vital element to consistent tracking. If I had to take steps to log my time each time I was writing; if I had to “clock-in” and “clock-out” I would never have collected the data in the first place.

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