On this page:
  • Quantified Self Toronto: Where the Time Went
  • Quantified Awesome: Time and building mastery
  • Quantified Self: Learning from a year of time data and planning what to tweak in 2013

Quantified Self Toronto: Where the Time Went

Update 2013-6-6: Added a link to the video!

Carlos Rizo convinced me to quickly throw together a presentation for today’s Quantified Self Toronto meetup. Here are my slides!

Check out quantifiedawesome.com for my data, dashboard, and source code, and read through my Quantified Self blog posts for more geekery.

Quantified Awesome: Time and building mastery

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There’s an often-repeated number in studies on expertise: it takes 10,000 hours of deliberate practice in order to build a skill to mastery.

Last year, I logged 265 hours writing, or around 45 minutes a day. Don’t be scared off by that. If you’re repurposing something you’ve already done, blogging takes maybe 5-10 minutes. It takes an astonishingly long time to think through new things. I can type at 90-110 words per minute, but my brain chugs along at 16 words per minute when reflecting, and I haven’t quite gotten the hang of using speech recognition or dictation to get past that barrier. I suspect I won’t be significantly faster. Thinking takes time. That 265.5 hours is butt-in-seat time. Yes, that’s the professional term for it. I have surprisingly little of it, considering how much I perceive writing to be a part of my life. (Really? Just 45 minutes a day? What would happen if I doubled that?)

Generously including quick blog posts as part of this practice, assuming that I’ve maintained a similar pace since around 2003, neglecting the fact that real writing involves a whole lot more rewriting (which I tend to do out of forgetfulness rather than deliberate improvement), and ignoring the assigned writing I slogged through in school (or the countless e-mails I dash off), the calculations show that I’ll probably be inching closer to awesomeness… oh… when I’m 57 or so. I know life doesn’t quite work out like that, but let’s pretend for the sake of calculation.

It doesn’t actually look half-bad, you know. If I can get a decade or two of great writing out right around the time I should have tons of experiences to write about, that should be fine. Of course, with the unreliability of memory (both mine and the computer’s), I’ll just have to hope my blog will survive the years. And if I turn out to be a passably good writer who can package up what I’ve learned and turn it over to the next generation of young whippersnappers, then that’s great. Don’t need to win any awards.

On a similar note, I logged 198 hours drawing last year. This does not include the times that I filed drawing under “Business – Plan” or “Personal – Plan” instead. Even less revision going on over here, but I’m working on ways to improve that, and other ways to increase the proportion of writing and drawing in my life. Malcolm Gladwell’s Outliers: The Story of Success broke down that 10,000 hours into around 10 years of daily 3-hour practices.

I have spent a ton of time coding. I’ve been coding since I was six or so, and I worked on quite a few web development engagements at IBM. I’m still nowhere near “master” level. I can point to lots and lots and lots of people who are way better than I am. I have fun with it, though. I can make stuff happen.

It’s good to remember that invisibly sunk time, the accumulation of experience over years. That way, I don’t get frustrated about drawing if it feels less natural than coding, and I can see all this writing as building a skill step by step.

Thank goodness for visible progress. Hooray for a blog that lets me go back in time! Compared to a year ago, I draw so much more than I used to. I feel a little more organized and coherent as a writer – headings for my paragraphs, an index for my posts. I still don’t have the deft interweaving of personal story and insight I envy in Penelope Trunk’s blog or the lyrical geekiness of Mel Chua (no relation), but I’m growing into my own style.

I think it would be fascinating to have 10+ years of time data. It’ll be interesting to see how I change things along the way. Not that quantity of time controls everything, but it’s fun to ask questions and realize that the composition of your time doesn’t always match up to what you think it is. Then you can tweak it.

Other 2012 numbers to put this into perspective, because I have the data anyway:

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  • 3024 hours of sleep – 8.3 hours per night and I’m still fidgety when I go to bed; I wonder how one deliberately practises sleeping
  • 729 hours socializing (in person, answering e-mail, etc.) – not much deliberate practice going on there, but good to spend that time
  • 411 hours connecting with people for business (in person, answering e-mail, etc.) – a little bit of systematization and experimentation
  • 102 hours reading fiction, 88 hours reading nonfiction – funny, I thought it would be the other way around, although some of it did get classified as “Business – Drawing” instead
  • ~75 hours playing LEGO video games

More time analysis looking at percentages

So that’s where all the time went!

Quantified Self: Learning from a year of time data and planning what to tweak in 2013

Last year, I decided to move from tracking my time using off-the-shelf applications (Time Recording, then Tap Log Record) to building my own system using Ruby on Rails so that I could tailor it to my quirks. Quantified Awesome now has more than a year of time data, and I wanted to see the patterns in how I use my time.

How I categorize my time

For ease in comparison with OECD time studies, I use the following high-level categories:

  • Sleep: What it says it is. Important!
  • Discretionary: Hobbies, socializing; anything optional or chosen
  • Personal: Morning and evening routines, personal care, exercise
  • Work: Working on IBM projects
  • Business: I split this out from work because I wanted to see how much time I was spending on building my business or improving my skills
  • Unpaid work: Commuting and other unpaid work/business-related activities; also, tidying up, getting groceries, cooking, doing laundry, and any household tasks that I could theoretically outsource
  • Within the categories, I have one or two levels of detail, which I’ll discuss later.
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    This graph shows the major changes in how I used time this year. To account for the varying numbers of days in a month, I’ve expressed each category as a percentage of the time available for the month. The major change was the swap between working with IBM and experimenting with running my own business, but all my other categories are surprisingly stable.

    Here are some basic statistics looking at the monthly and weekly variation. There’s a bit more variation on the weekly level, but it smoothens out a lot when it gets to the monthly level. Also, the overall numbers tell me I should probably work less and spend more time on discretionary activities.

    OECD 2011 – Canada   Mean ~ total hours / week Monthly STDEV Weekly STDEV
      Sleep 35% 58 2% 3%
    22% Business + work 28% 47 5% 6%
    21% Discretionary 16% 28 5% 7%
      Personal 14% 23 2% 4%
    14% Unpaid work 7% 12 2% 3%

    Sleep + personal for me = 49%; OECD 2011 stats for Canada: 42%

    Sleep

    I get an average of 8.3 hours of sleep per day, which is a familiar and fairly stable number, and right in line with the OECD 2011 leisure time study’s findings. Looking at the inter-day statistics for sleep, I see a standard deviation of 1.63 hours, which means my sleep pattern is a little jagged. Here’s a daily chart that shows the variation.

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    It doesn’t look so irregular on a weekly scale, though. I tend to be pretty good at taking it easy after I catch myself getting tired due to lack of sleep.

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    Business

    Business-wise, I was thrilled to have a running start. Here’s billable time as a percentage of total time (out of 7 days a week). May was a little crazy because I was helping out two clients at the same time. I took time off in September and December to focus on other interests, and I’m generally scaling back consulting because I need to make myself learn how to do other kinds of business too.

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    Here’s some more information in a table, showing that while I don’t reach the utilization ratios I remember from my performance review days, I still do okay.

      Billable time  
      % of total time % of business time
    Mar 2012 17% 61%
    Apr 2012 16% 71%
    May 2012 24% 76%
    Jun 2012 17% 60%
    Jul 2012 21% 66%
    Aug 2012 18% 66%
    Sep 2012 1% 5%
    Oct 2012 11% 37%
    Nov 2012 14% 42%
    Dec 2012 2% 10%

    Going forward, I should probably plan for a 25% billable : 75% marketing/overhead mix (or even more weighted towards marketing).

    On average, I spend about 10 hours a week connecting with people for business, which is a surprisingly large chunk of time. It’s good, though. I’m learning a ton and helping lots of people along the way. The weekly standard deviation for this is 7.8 hours, which probably points to “introvert overload” kicking in – after an intensely social week, I’ll hibernate for a while in order to recharge.

    Discretionary

    All work and no play makes for a boring sort of life, so this is where discretionary activities come in. Discretionary – Social is by far the juggernaut of this category, with 46% of all discretionary time use (average per week: 13.7 hours, stdev 11.9 hours – same introvert overload kicking in). Business networking + discretionary socializing works out to an average of 20.8 hours per week, with a standard deviation of 15.1 hours. Here’s the sparkline, with a spike around the September trip where I went to a conference and hung out with family.

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    The graph below shows that I’m not necessarily substituting business connecting for discretionary socializing. There’s actually a very slight positive correlation between them. I do need my breaks afterwards, though.

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    On to other things I do with my discretionary time. Because the Social sub-category is so much bigger than the other categories, these sparklines all use different vertical axes instead of using a shared axis for inter-category comparison. They show percentage of discretionary time, with the peak time highlighted. (Remember, we can’t compare heights across categories!) The third column shows the total percentage of discretionary time spent doing that activity.

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    The sparklines show that my interests tend to shift. They also show some categories that I’ve forgotten to use, such as Discretionary – Family which tends to get lumped under Discretionary – Social, and Discretionary – Read – Blogs, which has become more of either Personal – Routines or Unpaid work – Travel. Looking at this, I can see that LEGO games tend to give us about three months of obsession time, which may not be a good thing. Winking smile Fortunately, W- plays them too, so it’s actually “sit on the couch and chat” time, with bonus scritching of kitties who like sitting in our laps.

    Unpaid Work

    Duty comes before pleasure, though, so I need to make sure chores are taken care of before I settle in for some writing. Here’s how the chores worked out.

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    For scale: I spend about 3.3 hours a week cooking, which is really spending maybe 6-7 hours every other week or so cooking a whole batch of things. Or at least that’s what I think it works out to. The weekly data shows me that I tend to cook in cycles (mean = 3.5 hours, STDEV = 2.3 hours):

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    Other interesting things: Why, yes, biking and subway time are negatively correlated (coeff = -0.53). Yay biking! The weather’s been decent, actually, so I should totally break out the bicycle and bike some more. (Biking: 209 hours this year, average of 7.2 hours per week during biking season)

    % of total time Personal – Bike Unpaid work – Subway
    Nov 2011   2.4%
    Dec 2011   0.6%
    Jan 2012   0.9%
    Feb 2012 0.1% 1.6%
    Mar 2012 0.1% 4.5%
    Apr 2012 7.3% 0.3%
    May 2012 5.9% 0.2%
    Jun 2012 4.6% 0.3%
    Jul 2012 3.6% 0.7%
    Aug 2012 2.5% 1.2%
    Sep 2012 0.8%  
    Oct 2012 3.7% 1.1%
    Nov 2012   6.9%
    Dec 2012   3.6%

    Personal

    The personal category includes all the little things that keep life running, like having breakfast and brushing my teeth. On average, I spend 2.1 hours a day dressing up, eating, brushing my teeth, and so on. That’s 815 hours over the last 386 days! Biking, walking, and exercising account for 408 hours over that time span, which works out to be an hour a day. Not bad.

    So, what does this mean for 2013?

    I’m planning to:

    • Spend less time commuting; spend more time biking and exercising – extend biking season earlier and later (November was totally bikeable, but I chickened out and got a Metropass!), and ramp up personal exercise to ~4 hours a week.
    • Spend less time working as a whole (and yes, trying to not panic about this shift either); spend more time writing and doing other discretionary activities – keep business-related time to ~40 hours a week
    • Spend less time working on billable projects; spend more time marketing/selling/learning (and trying not to panic about this shift) – shift to 25-30% billing as a percentage of total business time

    Glad to have the numbers! You can actually see my time data on Quantified Awesome.  I’ve just added a “Split by midnight” option that makes analysis a little easier for me and other people who use the system to track their own data.

    Onward!