Academic workload modelling: Friend or foe?

One of the concerns that I hear most frequently from university senior managers is that they have no idea how members of their academic staff are spending their time. And a common complaint from academics themselves is that the ‘centre’ just doesn’t understand the huge number of different activities that they have to contend with. Workload modelling provides a way to bridge this gap.

A workload model identifies the different activities undertaken by members of academic staff and allocates an agreed time ‘budget’ to each one. This allows academics, their departments and their institutions to construct a clear and comprehensive picture of who is doing what and how much time they are dedicating to it. It covers all members of academic staff, all activities and all work-related time.

And once you have a workload model, its uses are myriad. Individual academics can use it to understand what is expected of them and to demonstrate their contribution to their department’s activities. Heads of department can allocate activities equitably, ensure balanced workloads and identify capacity issues before they become critical. And university management gains an overview of what is happening on the ground.

If your model is sufficiently detailed, you can use it for course costing. And if you integrate it into your annual planning and review cycle, you can even use it to replace the TRAC (transparent approach to costing) time allocation survey.

Most universities already measure or monitor workloads in some way. Departments allocate teaching loads and management responsibilities, groups manage their research portfolios and individual academics juggle their responsibilities to their students, their department and their research funders. Workload modelling takes this one step further, bringing the data together in a coordinated fashion so that it can be used more effectively.

All universities can do more, for example, to ensure that members of academic staff have a better work-life balance. I’m writing this late on a Sunday evening and my wife – a researcher in a Russell Group university – is sitting downstairs doing her marking. And how many other academics are in the same position, working well beyond the standard week just to keep on top of their teaching and administrative responsibilities, let alone to do all of the other things that attracted them to academia in the first place?

Workload modelling won’t solve these problems of course. It won’t find us more time in the week or create additional resources out of thin air. But by being more open and more honest about the different things that people are doing and the amount of time they are spending on them, it can help departments and institutions gain greater insight into the specific challenges they face and what they can do about them.

And in these financially straitened times, when departments and universities alike are under pressure to demonstrate that they are using their resources efficiently, it can provide them with just the evidence they need.

A good workload model is one that is transparent, fair and based on what actually happens across the institution. It is not a one-size-fits-all thing. A model designed around your institution will work much better than a generic one that doesn’t take account of your specific ways of working. It is unlikely that the physics department, the sports science department and the sociology department all work in the same way, so the model needs to be able to cope with this. It can’t just be thought up by the finance department – it needs to be designed in conjunction with members of academic staff or experience shows that it won’t work.

To be honest, once you’ve got people on board with the idea, the model itself isn’t that hard. First, identify the different things academics are involved in, like teaching, research, postgraduate supervision, management and administration. Then break each one down into activities, such as specific taught units, management roles or doctoral students. Second, allocate a suitable ‘tariff’ – usually in hours per year – to each activity. Finally, collect the data.

If this sounds complicated or unrealistic, you probably already have most of the data you will need. One of my clients, for example, extracts information on research projects and postgraduate supervision directly from central records systems. And data on teaching, management and administration roles will usually be held within each department or faculty, too.

Developing an effective workload model takes time and effort. However, done well it can provide valuable insight into academic workloads and yield tangible benefits for academics, departments and institutions alike. It can also, crucially, facilitate a more constructive dialogue between academic departments and the university administration. And that’s worth spending time on.

This article was first published on the Guardian Higher Education Network website.

3 thoughts on “Academic workload modelling: Friend or foe?

  1. Hi! Your piece lacks detail. How does your new model actually differ from the work-hours planning that has been in place since the year dot? How can it achieve realistic representations of the time it actually takes for each individual to do the work assigned to them? Even when, if done realistically, that shows the impossibility of doing the job within all the hours God gave. My experience, when I worked in HE was that it could be a basis for claiming rough justice in workloads but not an actual measure of the work required. What is your new ingredient or technology?

    1. Hi James,

      Thanks for your response to my article. I agree that it doesn’t go into much detail on the specifics, as I was bound by the Guardian HE network’s word limit when I initially drafted it. I could easily write a book on this topic, especially on how models can (try to) reflect accurately the time that it takes to undertake specific activities.

      A number of institutions seem to use a ‘points’ system, which allocates points to specific activities, but this really isn’t transparent and can be extremely subjective. I prefer to look at the number of hours that it actually takes, which means working closely with academics to make sure that the allocations in the model are a reasonable reflection of reality. It’ll never be perfect, but it’s better than some arbitrary allocation that nobody agrees with.

      Another aspect of workload modelling, as you suggest, is what you then do with it. It’s really important that, before introducing workload modelling, institutions think about what they will do with the results. For example, if the models show that some members of staff are hopelessly overworked, what will managers do about it? If the model raises issues that are then simply ignored, then it loses all credibility.

      Perhaps unusually for a consultant, I’m not claiming any new magic ingredient or miracle cure. Indeed, much of workload modelling is what Heads of Department have always been doing. But I think it can be done so much better than is often currently the case.

      Anyway, thanks again for getting in touch. I appreciate your comments.


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