I’m pretty sad that I’ll be missing the 2014 Quantified Self Europe Conference this weekend. From what I can tell of the lineup, it’s going to be a great conference that’s full of insights, sharing ideas, and learning about all the amazing ways that people are looking internally to understand themselves better. Seriously, if you’re there, I’m jealous. Have a fantastic time. If not, and you’ve never been to a quantified self event, consider checking out a nearby meetup.
Not to mention Amsterdam looks absolutely amazing.
I suspect many people will come away from the conference energized and inspired for some new tracking projects, so I wanted to offer up a few tips for how to effectively make use of the data in your RescueTime account. Of course, we try to make the default reports as informative as possible, but here are some power-user moves that should help you dig a little deeper.
A number of these are premium features, but if you are on the free plan and would like to try them out, you can click here to upgrade at a 25% discount until the end of May.
1. Export your data to a spreadsheet.
Most of the reports can be exported to a .csv file (premium version only). This lets you bring them into your spreadsheet program / database / visualization engine of choice to do some further analysis or compare with other data sets. I used this extensively for a project I did last year comparing my sleep and physical activity levels to my time spent in email and software development.
Just look for the green “Export / Share” button underneath the graphs on the reports.
2. Use time filters to compare your time in different periods
One of the most straightforward explorations you can do is to see how your computer time looks like when you’re working vs. when you’re not. That’s pretty easy to do with time filters in RescueTime. You can restrict your time in a given period to specific days (“weekends” for example), or specific times of day (“After lunch”).
You can find the time filter controls on the date picker widget that is available on most reports. There are a few default time filters available for people on the free version of RescueTime. The premium version of RescueTime allows you to customize the filters and create new ones.
Some ideas to explore:
- How do my weekends differ from my weekdays?
- What types of activities do I spend more time on in the morning? what about the afternoon?
3. Use the RescueTime Data API
If you are comfortable with a scripting environment, you can request data from RescueTime programatically as JSON or CSV data. This can be great if you have already written another tool to consume data from another service.
The API is available to people on both the free and premium version of RescueTime, and will allow you to get the same data that you can find from most of the reports on the website.
Check out the API documentation to learn more.
4. If you are trying to use your data for behavior change, have a look at our integration with Beeminder.com
Beeminder is an interesting service. They allow you to state a goal that you’d like to stick to (“Less than 30 minutes a day on Reddit.com”, for example), and they will track your progress for you and give you daily updates on how you are doing. But if you fail to stick to your goals, you will “derail”, and getting back on track will cost you money. It’s a form of commitment device and it can be a really helpful incentive if you have a habit that you would really like to break.
You can read more about Beeminder and RescueTime here.
5. To find correlations between your RescueTime data and other sources, use Zenobase
Zenobase.com is an analysis tool for personal time-series data. In other words, anything about you that can be expressed as data points that occurred at distinct points in time. I’m going to be honest, it has a learning curve, but once you get over it, you can do some really interesting things with it. You can do simple exploration of your data in ways that other services may not offer (for example, in RescueTime there’s not a way to see a histogram of the time you spend per day, normalized to the nearest hour). You can also mash up several data sets and look for correlations.
Use RescueTime alerts and Zapier to automatically log milestones about your time in an online spreadsheet
RescueTime’s alerts are highly configurable and can let you know when you have spent more than a specified amount of time in a productivity level (example: “all productive time”), a category (example: “design and composition”), a specific application (example: “microsoft word”) or a website (example: “mail.google.com”).
These alerts are delivered by an email or popup on your desktop, but they can also be used to log when the threshold for that activity was reached. You can connect your RescueTime account with Zapier.com and whenever an alert is triggered, you can insert a row in a Google Spreadsheet, or mark down the timestamp as an event on a calendar. Zapier has interfaces for a lot of applications, so you aren’t limited to spreadsheets or calendars. There are many other places you can log your alert data as well.
Check out our integrations page to learn more.
Good luck with your tracking projects!
I hope these tips are helpful. If you’re looking for some more inspiration on things you can do by tracking your time, check out these talks from past Quantified Self events. If you come up with some interesting insights based on your RescueTime data, let us know. I’d love to hear about them!
One of the cool, helpful new features on RescueTime’s new website is the availability of Day Timers. Users can activate a timer to give themselves a stand-alone, heads-up display of cumulative logged time and their current productivity ranking for the day. This appears in the form of a re-sizeable browser window. Personally, I activate the timer and then put the window in back of the other browser tabs and application windows I am using. I use this timer to keep track of my work time for the day and check in periodically to see where I am. I find that this provides both confirmation of work done and motivation to reach my daily goal. I also use the timer to schedule breaks, taking some time after every hour of completed work for coffee, other tasks, or a short walk. This keeps my mind fresh throughout the day. One additional way of using Day Timers is to keep track of time spent on particular activities. If you are looking at an activity in your reports and activate a timer, it will show cumulative time spent on that specific application or website. This is a good way to monitor use and be aware of how close you are coming to your positive and negative productivity goals. It is often surprising to me how my experience of time spent on something differs from actual time spent.
How to use Day Timers
Timers can be opened from any report, just look for the green button that says “Day Timer”. You can create timers for applications, categories, productivity levels, or goals. The timers will update continuously throughout the day, so you can just leave them open in a spare corner of your screen or a second monitor and watch your time add up.
We’ve been using these timers internally for several months, and we’ve gotten some great feedback from some of our users (thanks to Joos Buijs in particular!). Check them out, and let us know what you think!
Stop beating yourself up about “all that time” you waste on Facebook, it’s probably less than you thinkPosted: November 6, 2013
When I tell people about RescueTime and what it does, one of the most common things I hear is:
“Oh wow! I don’t even want to think about how much time I waste on Facebook!”
When people have actually been using RescueTime for a little while, I often hear something different:
“Ya know? I really thought I spent more time on Facebook than that!”
Two things jump out at me when I hear this. First, many people think they spend more time on Facebook than they actually do. Second, they seem to feel guilty about it. The first observation makes the second one sort of sad. I don’t want anyone to feel bad about themselves, and certainly not for something that’s not really even true!
That’s why I LOVE telling people about the following study.
Rey Junco, a professor of library science at Perdue University, recently investigated how students’ estimates of their time on Facebook differed from the actual time they spent on the site. Since many studies that focus on social media usage rely on self-reported data, this is a pretty important thing for researchers to understand. He asked test subjects to report how much time they spend each day on Facebook, then used RescueTime to monitor their actual time on Facebook. The results were very surprising.
“students significantly overestimated the amount of time they spent on Facebook. They reported spending an average of 149 minutes per day on Facebook which was significantly higher than the 26 minutes per day they actually spent on the site (t(41) = 8.068, p < .001).”
When I first read these results, I did a double take. Subjects were overestimating their Facebook time by 473%. Four Hundred Seventy Three Percent?!?! It seems almost unbelievable. In his blog post, Rey covers some factors that could have affected the data, but it seems like the gulf between the estimate and the actual time on Facebook is real.
It’s interesting to contrast that overestimation with something else I’ve noticed. Many people fairly drastically underestimate the amount of time they spend in email. According to a study from last year by the McKinsey Global Institute, up to 28% of the average desk worker’s week (or around 13 hours) is devoted to managing email. While it’s necessary for work, it’s often a distraction, due to its tendency to pop up every few minutes on someone’s screen while they’re trying to focus on other work. People are usually not that great at accurately adding all this time up, and that’s not even taking into account the refocusing time that comes when trying to get back to the original task that the email interrupted.
I wonder if there isn’t some sort of guilty pleasure factor at work there? For whatever reason, do people’s negative judgements about their time on Facebook (or Twitter, or Reddit, etc…) cause whatever time they DO spend to be over-inflated in their minds? On the other hand, email doesn’t have this problem, because very few people think about email in those terms. That’s just a theory of mine, which is partly based on my own experience, but I’ve seen a lot of anecdotes that back it up. If it’s actually true, it’s sort of a bummer. It means people have a general tendency to beat themselves up over things that feel too much like an indulgence.
To me, this is a great illustration of the awesomeness of RescueTime. Having an accurate, real record of how your time is spent can totally change your perspective. When you’re sitting at a computer all day, it’s too easy for it all to just blur together. With a real understanding of how little time I actually spend on sites like Facebook or Hacker News, I’ve been able to let go of any negative judgements I had about them.
Last month, I spent some time digging around with two big personal datasets of mine – my RescueTime logs and the information about my physical activity and sleep that I’ve collected with my FitBit. After comparing over 8.5 million steps and 5,000 hours of my sleep with around 7,000 hours of my RescueTime data, I noticed that my physical activity seems to have a generally positive effect on how I spend my time on the computer. Or it’s the other way around, I’m not quite sure. But there definitely seems to be a link between the two.
Daily step count vs. meaningful work
The first thing I looked at was the number of steps I’ve taken each day for the past two years. I compared it to the amount of time I spent on the computer, and what activities I was doing while on the computer. On days when I take more steps, I tend to spend a greater percentage of my time on the computer writing code. For me, software development is an activity that I feel is pretty meaningful, and I’d rather spend more time on it than, say, meetings or email. I’d also like to be more active, so it’s really great to see that days where I walk around more don’t seem to hurt my work productivity.
It’s not really clear to me which one of those things influences the other. Could be that more physical activity makes it somehow easier for me to focus? Or it might be the other way around. A solid day’s work makes it more likely that I’ll be motivated to get out and get some exercise. Or, there could be some unknown factor that’s influencing both of them. It’s still interesting, nonetheless.
Also interesting, it seems like I shouldn’t get too crazy with it. On days when I get more than 12,000 steps in a day, the percentage of software development time goes back down.
Sleep vs. Time on the computer
I also found that I seem to be more focused on days when I get more sleep. Focus is a hard thing to measure, and this isn’t a perfect metric, but I looked at the amount of time I spend writing code (something I’d like to be doing more of) vs. the amount of time I spend on email (something I generally try to minimize). When I get less than six hours of sleep, things are pretty much even. As I get more sleep, the percentage of time in email goes down, and the time spend on software development goes up.
What does this mean?
The really cool bit about these observations is they suggest that it’s not only possible to balance good amounts of physical activity with a productive workday – they may actually reinforce each other. Another RescueTime user saw similar effects on his sleep last year. He summarized the results in this guest post.
To get these two datasets together, I used the RescueTime API and John McLaughlin’s fantastic FitBit-to-Google Docs script that I found on the Quantified Self website.
Have you ever found an interesting link like this between your physical activity and some other metric? I’d love to hear about it.
I recently came across an Austrian article that raises some interesting questions about the use of technology in “measuring” our lives (http://www.format.at/articles/1328/940/362012/die-vermessung-ich[in German]). The scope of this technology continues to increase and there are more opportunities for its insertion into our lives than ever before.
Here are some examples of the latest technology:
– an armband that measures physical activity, including steps taken, distance walked, and calories burnt; length and quality of sleep; and with auxiliary links to mobile devices and a scale, meal planning and weight management (http://www.fitbit.com/)
– work productivity software that measures active computer use and trends very precisely (http://www.rescuetime.com/) [That’s us]
– a strap-on device for posture and movement monitoring and correction (http://www.lumoback.com/)
– a fork that measures eating habits and mechanics (http://www.hapilabs.com/)
– an all purpose physical activity device for multiple kinds of exercise (http://www.runtastic.com/)
– a scale that provides body anaylysis by measuring weight, BMI, body fat, and heart rate (and also local air quality to boot) (http://www.withings.com/scales)
– a diabetes app testing blood sugar (http://mysugr.com/)
– comprehensive health management software (https://www.dacadoo.com/)
Those who embrace this technology often self-identify as members of the “Quantified Self movement,” which is characterized by the search for informative feedback from devices such as those listed above. Some see in the wealth of available data a “digital reflection” of their lives – this is felt to be empowering, allowing individuals to achieve a greater degree of self-awareness and to take proactive steps to optimize efficiency, health, and happiness based on adjustment of recognized patterns. Sometimes the motivation for self-monitoring is a desire for improvement, sometimes for identifying and solving problems.
There are potential negative consequences to the adoption of this new technology and the hyper-analytical mindset and lifestyle that can result. Having such a wealth of data at one’s fingertips, and a feeling of overarching responsibility for this data, can lead a person to believe that they are accountable and culpable for everything that happens in their lives. There is also a danger of misinterpreting data – a person can mistakenly identify correlations among metrics and activities where there are none, or miss important ones that do exist. This misinformation can then be used to make lifestyle decisions with potentially harmful consequences. There are also issues with ownership of this data, its security, and its potential uses by others.
This raises a number of questions for debate:
1. Are there specific uses of self-measurement technology that you find seriously problematic?
2. Do we need some degree of education about understanding certain data to draw out the positive benefits of self-analysis and avoid pitfalls? If so, what would this education involve?
3. What type or types of measurement are the most important in the search for self-improvement?
The Quantified Self movement, in all it’s various shapes and sizes, is giving us the opportunity for an unprecedented view of ourselves. Examining ourselves through a lens of data holds the promise for better health, increased productivity, even greater happiness.
But what does self-tracking do to your creativity?
Now, it could be argued that all this careful measurement and instrumentation is really just a misguided way to optimize all spontaneity out of life. Albert Einstein said “Everything that can be counted does not necessarily count; everything that counts cannot necessarily be counted.” There’s absolutely truth to that. Today’s knowledge workers need to be creative. It’s probably the most important skill to have, especially as more process-oriented work is increasingly automated. The problem, from a self-tracking standpoint, is that creativity is subjective, and damn near impossible to express in a structured way. Some people are certainly trying, but I think it will be a long time (if ever) before any broadly agreed upon metric is established.
I think that’s just fine. Self tracking can still do amazing things for your creativity.
New problems, new solutions
Just as we’re faced with problems we didn’t have 20 years ago (when you could work for more than three minutes before being interrupted by email), we need to discover new coping strategies. A data-based approach makes a lot of sense.
Sure, it’s true, quantifying creativity is problematic. But do you know what’s not problematic? Quantifying emails, meetings, workflows, and all the other process-oriented stuff that takes up increasing amounts of our day. All of that is easily measurable, and self-tracking paints a pretty interesting picture in the negative space around our creative output. One of the observations we hear over and over from RescueTime users is “wow, I spend WAY more time in email than I thought!” Multiple studies have shown that the average desk worker spends about 30% of their time in email. It doesn’t feel that way because it’s generally spread out across the day in small chunks.
Switching back and forth on tasks takes a toll on our cognitive performance, and some research suggests that heavy multi-tasking diminishes our ability to recognize a breakthrough idea. Humans are nearly universally bad at multi-tasking, but it’s increasingly difficult to escape. But we can at least keep track of it, and that can bring an awareness that allows us to take steps to minimize it.
Different strokes for different folks
It’s easy to imagine creativity as this innate quality that manifests in spontaneous bursts of genius, but if you look at creative minds throughout history, you’ll see a very sophisticated creative process that’s been refined over time. It’s part of mastering your chosen craft. But what works for one person may not work for others. Hemingway only wrote in the morning, and had a very specific flow from handwritten pages to the typewriter. Picasso on the other hand, worked late into the night and slept in. Self-tracking can enhance this process, allowing individuals to methodically tweak their behaviors to find the ideal state of flow. Is the time you wake up more or less important than the total amount of sleep you got the night before? What about the quality of your sleep rather than the duration? Or is the really important thing the strong cup of coffee you drink before work? These are questions you can answer with self-tracking.
Let’s admit that maybe some of that creative output can be measured, and that’s really awesome
Even though there’s really no way your creative genius will be fully expressed by some numbers sitting in a spreadsheet (unless you are a mathematician, I suppose), most any creative endeavor has output that can be be revealing when tracked. Hemingway kept a daily log of his word-count “so as not to kid myself”. He used this to keep track of his progress, but also to reward himself. After a particularly productive day of writing, he could spend the next day fishing, guilt-free.
Motivation is key to creativity, and consistently measuring output is a fantastic way to stay engaged, especially with creative projects that require long slogs of work before seeing a finished outcome. It’s the digital equivalent of turning around after an exhausting uphill hike and beholding the beautiful view you’ve trudged into. Services like iDoneThis make this as easy as giving a short reply to a daily email. Another example is National Novel Writer’s Month, where daily word count is celebrated as a way of keeping authors pumped up about writing their novels.
Your turn. Do you think self-tracking impacts your creativity?
Obviously, we’re a little bit biased here at RescueTime. We think the greater awareness that comes from self-tracking has a huge benefit on one’s creativity. But I’m curious what you think? Do you agree? Or is it too clinical of a lens for such a organic thing? Or, is it simply navel-gazing, and a distraction in and of itself?
A few weeks ago we looked at several beautiful things you can do with your personal self-tracking data. Here’s another great example. Vincent Boyce is an artist, surfer and skateboarder. He’s created a system of sensors that records the kinetic data from his surf and skate sessions, then translates it into beautiful abstract compositions. The results are fantastic, even though the visualization totally obscures any information in the data. As someone who spent the better part of his childhood on a skateboard, I’m totally jealous and really interested to see what other types of visualizations he comes up with. You can see the full gallery here.
Here he is explaining the project at a recent NYC Quantified Self meetup.