I’m starting an experiment in restructuring my life to reduce decision fatigue.
If you’re like me, and not very familiar with the concept of decision fatigue, it is well-outlined in a 2011 New York Times article. At its core, decision fatigue is the assumption that we possess a finite amount of willpower, and that we expend this willpower as we make decisions throughout a day. This can lead to unintended (and often undesirable) psychological effects, such as a selection bias towards leniency after lunch, suffered by judges and even greats like Paul Graham. Fortunately, there are factors that can abate this fatigue. As the lunchtime anecdote alludes to, one of these is glucose levels, which this study from the University of Kentucky shows even happens in animals. The factor on which I would like to focus, as part of my desire to design a simpler life, is reducing the number of decisions that I need to make each day.
After a very brief analysis of my daily routine, there are several obvious areas in which I expend my decision-making energy unnecessarily. These wastes include:
- meeting schedule
- exercise routine
- content consumption (reading books, watching movies)
With the goal of minimizing waste in decision-making energy throughout a day, one approach is to cluster all of these low-value, low-risk decisions into a particular time of my day, such the night before. I’ve experimented with this for a few days with my eating habits, by using MyFitnessPal not as a post-consumption recording device, but as a meal-planning tool. I have notice the following benefits:
- I feel less decision stress just before mealtimes because I’m just executing on an existing plan
- I’ve been able to better avoid temptations to stray from my intended diet, because I’m not making decisions in-the-moment (a low-glucose moment, at that)
While the are only preliminary observations, they’re sufficient to convince me to continue this experiment. A few ways to expand this include planning my wardrobe in weekly batches (perhaps, on Sunday evenings), or selecting in one session all the books I’m going to read throughout the year. I’d really like to experiment with ways to make this easier with retail shopping, but that topic is deserving of its own post.
What are some ways in which you can reduce decision fatigue in your life? I’m really curious to hear your thoughts in the comments section.
Hat tip to @MarkWittman for sharing this concept with me.
I have a love-hate relationship with sleep. I acknowledge that there are likely benefits of an 8-hour night of sleep, but there are so many exciting things to do while I’m awake! I spent most of my K-12/college years sleeping just enough to stay awake during (most of) class, which turned out to be roughly 6 hours per night. A few years ago, I tried an experiment with polyphasic sleeping, but it proved to be a tough adjustment to fit into my unpredictable schedule. I might revisit polyphasic at some point (I like the everyman 3-nap), but for now what should I do? If sleep affects my overall health, as well as athletic performance and creative productivity, how can I optimize my sleep habits to maximize those outputs, while maintaining the smallest possible input?
About a year ago, I decided to start collecting some real data on my sleep habits. I found an app that provided some basic sleep data (for the curious, Zeo is a much better option). Once I started collecting data, I found out that my average night of sleep lasted about 6.5 hours. With this baseline, I set a new goal: 7 hours. As of yesterday, 373 days into the experiment, I achieved my goal of averaging 7 hours of sleep per night! You can see some of this presented on my personal dashboard, or check out the full source data.
So, how did this data collection help me increase my sleep average? For starters, “what gets measured gets done“. Simply keeping track, actively paying attention, helped me increase my amount of sleep. An even more effective tool (and you’ll see this if you look at my source data) was providing myself with timely feedback on fluctuations in my sleep time. I chose a basic analysis: a running weekly average for my sleep. I decided to alert myself whenever this weekly average fell below 7 hours. Typically, I have greater control over when I go to sleep than when I wake up, so my countermeasure was to “go to sleep before midnight”. Since I implemented this countermeasure, I’ve found it easier to maintain a consistent sleep pattern.
A missing piece of data in this process is a performance-related dependent variable. While I’m excited that I was able to increase my amount of sleep, I haven’t found a good means of measuring long-term health or professional performance improvements. Anecdotally, I do feel more alert throughout the day, I don’t fall asleep during meetings/lectures/etc, and I have been reasonably healthy over the past year. For the next phase of this process, I would like to find a means of correlating changes in my sleep to quantifiable life-performance data.
By the way, if you like this kind of stuff, you should check out the Quantified Self event happening during this Fall’s IdeaFestival in Louisville. I’ve been working with Chris Hall to bring together some of the leaders in quantified self from this region, as well as a few special guests, to share stories of personal experiments and insight on the latest tools.