|Matt Offord
I am an academic working in a business school. There are two things I really enjoy: teaching and research about teaching (which is called scholarship). And like most people, I really don’t like admin. Is it because I am sensitive to admin that I think I am always doing it and that it distracts from teaching? I suppose you might say there is teeny bias at play here.
As a try-out data visualisation, I thought I would record my emails for a week to see how many are, in fact, admin e-mails and whether my hunch that I am doing way too much is actually true. Collecting data is very easy, just rummage through my inbox for a weeks emails. As it happens I colour code my emails as admin, scholarship and teaching. I have a system. I split my working day roughly three ways giving a certain amount of time for each category. I bias my hours towards teaching because I figure that’s mainly what I get paid for, I also really love teaching. I started to do this when I noticed that admin was taking over my working day.
So this fairly straightforward data collection is ideal for a first go at data visualisation using hand-drawn methods. In the week I chose (week 2 2021), I received 244 emails, of which 177 were admin, 53 teaching and 14 were scholarship. Ha ha! as I thought! I am still spending too much time on admin. Hand drawing the data gave me time to really think about the data itself. I was initially reminded of a time before digital, of hand-written notes and also memos and letters. In 1989 I joined the Royal Navy as an officer. On basic training, as well as the usual running around, we had to learn how to write various letters, such as memos, routine letters, official and demi-official letters. Official letters were signed:
I have the honour to be,
Sir,
Your Obedient Servant
Can you imagine that? You couldn’t make mistakes on official letters, but in other kinds you could cross out the mistake neatly and then write it correctly. In the digital world we just edit, but then it took too long to start again every time. On the postcard, you can see I made a mistake on the total 244, which I wrote as 144, and then just wrote over it. I really couldn’t start again.
The visualisation shows an overwhelming number of admin emails, I could barely fit them in. The other types of email look pitiful. So job done?
Williams (2017:29) points out that the data we select should really be called capta because it is only the data we select not the whole data set that we observe. Selwyn and Gasevic (2020) discuss the limitations of data in learning analytics. The fact is, in learning analytics, and other data analysis we cannot escape our biases, something the analysts themselves freely admit (Ibid.). The limitations of these data are that all emails are not equal in terms of th time theye take to process or action, some are read and deleted, some are deleted and not read, others are the start of a huge project. There is no way from my analysis to tell which are for information and which for action. I also do a lot of teaching communication on MS Teams, running courses is an operational task and Teams is better suited for this than email. In short the visualisation has dramatic effect but the devil is in the data selection.
As someone who also gets a constant stream of emails during their day, I really appreciated this visualisation! Emails can very easily end up being someone else’s ‘to-do’ list for you, if you’re not careful and/or determined to use your time wisely.
I’m curious if you collected any data around the time when the emails came through, e.g. did you find that the admin emails come in at a specific time of day? Also, did you collect data around how much time it took you to respond or take action on the admin emails versus scholarship or teaching?
I didn’t but that is a very good idea. I imagine there will be a significant run on Friday afternoon when colleagues empty their inbox into yours!
That’s a great start, Matt! I believe the topic you opted for is relevant to all of us, especially now when we are working from home. In the face-to-face times, information could reach us through announcements on the board, during lunch with a colleague or in a meeting with the manager. Now it’s mostly emails and Teams channels. For the better or the worse…
As I see, you chose to look into the incoming messages, what about those you produce, would the correlation be different?
Following Gasevich’s logic, ‘the purpose of learning analytics is not tracking’, but rather ‘understanding and improving learning environments’ (p.528). So drawing on your small data set, even if it is biased as you mention, do you see how your working life could be enhanced? Are you going to optimize your routines somehow? Is it possible?
Thanks very much. I definitely think it helps; if nothing else I can see volume is a problem with email in general. Being a child of the ’70’d I remember a time before email. Email replaced letters and memos, which took longer to create, so was used less often. I think over time, the original idea has faded and email has become a channel for everything. This becomes very unmanageable very quickly. Consequently, I try to use other channels with my 318 students, as it would become untenable. Moving beyond tracking I believe would highlight this even more, once you unpick the value added for each email. This for me, does indeed suggest an optimisation. I am going to ‘switch off’ my email and only look at it at certain times of the day. Seeing the steady drip drip of admin emails there convinced me that you need to control the email, or it controls you.
Thank you for showing us some insights into your mailbox! I felt like in reading your visualisation, the sheer amount of admin emails definitely outweighs the other categories. It actually got me (as the audience) more interested to know whether you find you take the same amount of time resolving each admin email compared to other categories. Not trying to get you share more details here, but it is just interesting how your visualisation got me to want to ask more questions.
I guess that’s one of the impact of visualisation. It stimulates a discourse with its audience.
Thanks very much Enoch, I think I definitely spend less time on admin emails!
Hi Matt,
As you so rightly point out, we have only recorded a fraction of the data that it’s possible to capture and have to be realistic about the limits (especially here, where we are being asked to record manually). And unfortunately, simple counting is so much more achievable than coding the whole experience attached to dealing with a single email (e.g. how much time it took to compose, degree of influence on others).
Look forward to seeing more visualisations.
Thanks so much, yes I think coding the emails would make for a much deeper and useful analysis, you are right though this would take a lot of time, but more meaningful. I think you have to work hard for good data