#newPI: Where do faculty spend their time?
A lot of ink has been spilled on how much faculty work and where they spend their time. Walking through the campus hallway or hopping on Zoom call with a colleague elsewhere, I might ask, “How are things going”. The most common response is “Good, but busy”. I’ve never had a colleague respond with things are good and I’m looking for more work. I see two reasons for the “busy” response. First, faculty are generally just busy people. Faculty jobs involve many sub-roles, including mentoring, budgeting, teaching, and more. Second, there is enormous peer pressure to buy into the myth that we must work long hours to succeed. Further, I think there is a pervasive and cancerous culture of bragging about how busy we are in academia.
Faculty workloads are typically divided between research, teaching, and service, with certain institutions having "standard" allocations. For example, a faculty member at an R1 (R1: Doctoral Universities – Very high research activity), might have 20% time for teaching (which could refer to two courses), 20% for service, and the balance reserved for research. A faculty member at a community college might be 80% teaching with four courses each semester and the remaining time for service. However, these percentages mask the wide variation in workloads between institutions, departments, and individual faculty.
My goal here is to debunk some myths about faculty work and lab leadership. I'll also share my own calendar details before discussing the importance of transparent workload policies.
Myth: You have to work 80 hours a week to be a faculty member
One of the most persistent myths in academia is the idea of an 80-hour workload. Although the hours given might vary, there is certainly the idea that you have to work an incredible number of hours to be successful as a faculty member and lab leader. Megan Duffy does a fantastic job at busting this myth. She notes, “Why does this myth persist? Probably it’s in part because, if you think that everyone else is working 80 hours a week, it can seem risky to admit that you aren’t, since that could make you seem like a slacker.”
Fact: Faculty workloads can be uneven and unpredictable.
Later in this post, I outline my “average” week as a faculty member. However, I find it hard to define my average or typical week. During a semester, I might have some regular course times and meetings scheduled, but a lot might change from week to week. Grant deadlines are sometimes regular, but I’ve also had some come up with only a week to turn around a pre-proposal. My workload shifts a lot from semester to semester and of course during breaks in the university schedule. I also travel to conduct fieldwork and attend conferences.
I like the flexibility, but it also takes a lot of discipline and practice to organize one’s week.
As a corollary of the above and the differences between institutions, there is no average week for a faculty member.
Fact: Men and women spend their hours differently
Men and women faculty members have different work days. Although both men and women report working around 60 hours per week, men spend more time on research whereas women spend more time on teaching and university service (see below). Importantly, the authors note, “gender differences in time allocation continue to persist after controlling for work and family factors”. The survey was of 783 tenured or tenure-track faculty members employed at 11 public universities, with around half being R1 institutions. The authors also found that the gap between men and women in university service was more pronounced at lower-intensity research institutions.
Myth: There is such a thing as an average faculty member
The above findings about men and women clearly debunk the idea that there is an even playing field. These effects are especially pronounced for women of color and other underrepresented groups.
What I find striking in the above survey is not the mean hours worked, but the standard deviation in hours worked. I don’t have the raw data from the above study, but below I’ve plotted a negative binomial distribution for the hours spent on research by men and women.
I highly doubt the actual distributions look anything like the above, but the point here is the distribution spread. The spread in the data given the high standard deviations is enormous. It is completely inappropriate to think everyone, even those in the same department, has similar weeks in terms of their time allocation. I think this is why it can be so harmful to compare yourself to others. I think comparing yourself to other researchers at other institutions certainly doesn’t make sense, yet we do it all the time. In promotion and tenure or hiring decisions, we might ask if someone is a leader in their field. We fail, however, to consider whether leaders in the field have remotely similar workload or personal obligations.
Where do we go from here?
At the individual level, there are four steps that I think are critical in considering your own workload.
Assess your weekly workload and where you spend your time
Understand the requirements for promotion and tenure at your institution
Build semester and weekly plans (i.e., multi-scale planning)
Execute using time-blocking
In a future post, I’ll dive more into each of these points. For now, I’ll note that it is critical to assess where you spend your time and to see if that aligns with the metrics of success at your institution or within your field. Without this alignment, you may be spending unnecessary effort in some areas. Points three and four above can help align your current work with your long-term goals. Cal Newport has written extensively on these points in his blog and his books. He advocates for building multi-scale planning, which involves thinking about long-term, then semester, and finally weekly time scales. Within each week, he schedules “time blocks” to clearly give time to important work and then protects these blocks.
Below, I’ve published my “average” week as a faculty member for the first time. A few caveats are needed. First, I am on a 2-1 teaching load (meaning two classes one semester and one the next). My schedule below is during my heavier teaching load, but they are both courses I have taught previously, so I also need less prep time. I also have a relatively large research lab in terms of personnel, so I have more 1-1 meetings than what might be typical. Lastly, and most importantly, this schedule is more idealized than what happens in any given week. I try to protect my morning writing and Friday deep work blocks, but I often fail to do so when something urgent comes up.
With an 8-5 schedule, my work week is 45 hours long. I spend about 25% of my time on teaching activities, 50% on research, and the remaining 25% on service activities. Again, my schedule here is idealized and is not comprehensive. For example, nowhere above do I schedule time for emails or impromptu meetings. I try to contain my work to this 8-5 block of time each day, but that doesn’t always happen. In general, however, I can avoid working later in the evenings or on the weekends. My schedule looks very different over the summer and in the semester where I only teach one course.
I won’t dive into the details of my strategies for getting work done here, but I’ll make three observations. First, I have defined time blocks to ensure progress on important work. I have to write consistently to achieve my goals. I also have scheduled reoccurring tasks, like teaching prep and managing lab finances. I prefer short 1-1 meetings with my mentees where we can then book a longer time slot during Friday afternoons. I also reserve some office hours exclusively for graduate students. These are time slots that they know they can stop by my office and ask questions.
Transparent workload policies
I believe we have significant control over our workflows and the activities we choose to engage in each day and week. However, there are numerous institutional constraints, particularly regarding workload. Moreover, focusing on individual behavior can absolve institutions of responsibility for systemic issues that faculty—especially women and those of color—face.
I’ll expand on this topic in a future post, but I think one systematic solution is the introduction of transparent workload policies. As I mentioned earlier, most institutions have workload policies that include some combination of research, teaching, and service (e.g., mine is roughly 50%, 30%, and 20%, respectively). Institutions may also define a course as 10% of the workload. However, many institutions stop there. The lack of clarity means that research—and especially service—can quickly take up more and more time in a faculty member's job.
Some institutions, though still very few, have introduced more transparent workload policies. These policies not only outline the distributions across research, teaching, and service but also define individual activities. For example, a more transparent policy might assign a higher workload percentage to large lecture courses. Service responsibilities can also be defined more clearly: a committee might account for 5% of workload, advising could be another 5%, and serving as a journal editor could count for 10%. These percentages could then roughly correspond to hours in a work week.
The goal of transparent workload policies is not to achieve perfection but to make workloads clear and equitable. When introduced and enforced, I believe these policies can reduce animosity between faculty members who might suspect others of not working as much as they do. Transparent policies can also protect junior faculty and those often asked to take on excessive service responsibilities.
Where do you spend your time as a faculty member? Does your institution have transparent workload policies?