The results are in! Over the past month I have been logging my work patterns. I explained my motivation in a post before I started. I wanted to know how long I spent working, and what I was doing during working hours. The question was: can a PhD student get away with just working 9-5?
The answer is, broadly, yes.
How long do I spend working?
On an average working day I spent 8.57 hours ‘at work’. This is rather loosely defined, but essentially it means I am either at my desk on somewhere else on the university campus. I am not actually doing anything PhD-related for 2.17 of those hours. That brings my daily work time down to 6.4 hours.
Before I began, I estimated that I would spend 6 hours a day working. I may have overestimated my actual work time because I tended to round my working half-hours up (see the Methods section below).
The graph above shows the number of hours worked per day. The 8-hour line represents the standard length of a 9-5 working day. Some days were rather unproductive with large amounts of time ‘greyed out’ where no work was done. You can see at the start of the month, coming back from Christmas, I was very keen. I even did some reading on the weekend. Later on my working time waned slightly. You can also see that the second Friday was a very short working day. It snowed that day and I was finding it difficult to concentrate so I took the afternoon off!
What was I doing?
I spent the biggest chunk of my time coding. This applies to making plots as well as analysing data. Since climate modelling is necessarily computer-based, it’s no surprise coding comes out on top. Next comes my ‘nowork’ category, which I discussed above. I had just over two hours off per day. I rarely take clearly-defined lunch and tea breaks, but I suppose these two hours can represent them. In reality those hours were spent procrastinating on the Internet or doing other things not related to my PhD. This includes organisational tasks like booking transport to meetings and conferences, maintaining websites, and so on.
‘Understanding’ covered research I did with a specific purpose, like finding out how to do a particular type of analysis, or comparing my results with others. This explains why the time I spent ‘reading’ was comparatively small. My purposeful research obviously involved plenty of reading. The ‘reading’ category was specifically for reading new and interesting papers to develop my background knowledge, rather than to find a specific piece of information.
I was surprised how much time I spent in meetings. I think the proportion is artificially large because the Department held a Research Day in early January, when representatives of research groups give summaries of their work to the rest of the Department. Then again, I only went to an afternoon’s worth of talks. I value meetings. Obviously those with my supervisors are very important, but seminars are an excellent way to broaden my education. Recently I have also been thinking about acquiring new skills for analysis, and one of the best ways to learn about these is through seminars.
Finally, the ‘writing’ part: it’s very small, but that is because I haven’t really started my thesis in earnest yet. If I was at a loose end I would do a short stint adding some material or reorganising what I already had.
There is enough time
These results have shown that I haven’t been overly efficient during working hours. I don’t work very hard (in terms of work out versus time in), and yet my output is reasonable, as is the quality of my work. I worked slightly over the standard 8-hour day, but if I really wanted to I could trim this down without sacrificing quantity or quality. In fact, I might gain productivity by constraining my working day, because I’m likely to become less lazy and less easily distracted.
I used a Google Doc spreadsheet to record the time spent at work. I recorded my predominant activity in half-hour blocks. Work doesn’t fall neatly into blocks like this so I had to do some subjective re-jigging. For example, if I start work at 9:15, so I write in the 9:00 – 9:30 slot that I did some work? I went by the rule of thumb that, if I worked for more than half the time in the slot, I would record it. I categorised my time as follows:
- understanding – active research, including reading, to find out specific things
- coding – making plots or running models
- meeting – talking to other scientists
- writing – thesis or other smaller piece of writing; blog posts
- reading – reading papers and other articles without a clearly-defined purpose
- nowork – breaks, organisational stuff, admin
I think there is more information to be pulled out here. I actually find it quite interesting to just look at the colour-coded allocation of time in my spreadsheet rather than the graphs above. One can pick out, by eye, that I tend to do coding in long, uninterrupted blocks. I find it easier when I have got into the ‘flow’; plus it is simply time-consuming. Please do take a look at the spreadsheet. I would be interested in hearing comments on the results or the method, since I may be trying this again in the future!