Workload Models

In my experience, at Universities there are two issues that are guaranteed to generate heated debate. The first is car-parking, and the second is workload models. We have had a single workloads model in SAgE that each school has been using (theoretically at least), and when it was introduced (before I relocated to Newcastle) it was agreed that we would review the model 12 months hence. Thus we felt that a review of the model was overdue, and we discussed it at the last Faculty Executive Board (FEB).

Before I decsribe the outcome of our deliberations, it is worthwhile discussing the purpose of workload models. In essence, they are simply as they are named, i.e. a means to ensure that every member of academic staff has an equitable and manageable workload. That’s not to say that the workload should be completely prescriptive. It should be only a guide to workloads – a management tool. Everyone has different skills, and if we used a workloads model to prescribe and assign work in a purely arithmetic manner, we end up with ‘management by spreadsheet’. For this reason a workloads model cannot be particularly accurate, and indeed during our discussions it was suggested that we would be lucky if they are accurate to more than a week or two at best per annum. Hence, arguing about a few hours here or there is rather missing the point.

I’d like to suggest that, given the dramatic changes in the sector over the last couple of years, workloads models increasingly serve a second purpose. Not so many years ago there was much less ‘management’of academic staff time. Universities enjoyed substantial block funding from the Government for teaching, and in the pre-RAE days we weren’t required to justify the quality of our research to such levels that we see currently. Halycon days? – maybe. Irrespective, this is gone forever, and we are relentlessly moving towards an environment that is dominated by market forces, and the need (quite rightly) to justify spending from the public purse. In this regard, now more than ever a University needs to work as a coherent, well-oiled machine that has a clear vision and purpose – hence Vision 2021. The price of failure is very high. It follows that we need to manage our time so that we are doing the things that are important for the organisation, within the scope of academic freedom of course that we all rightly cherish.

Isn’t this what Performance Development Reviews (PDR) are all about, I hear you ask. Indeed, and that brings me to our discussions last week. While the current workloads model has served some schools very well in the past year, it is quite complex. In particular, it requires significant staff time to input the data for every member of staff, and we are in danger of propagating a Cottage Industry. The general consensus at FEB is that we should simplify the model, recognising that its is impossible to capture everything. We agreed therefore to trial such a simplified model. Specifically, we aim to capture everyone’s workload data on a single sheet of A4 paper. As usual there will be the conventional drivers converting e.g. ‘contact hours’ to ‘workload hours’, and allocations for administrative duties and the like. Many of these will be adjustable locally, in recognition of the fact that in a Faculty as heterogeneous as SAgE, it is impossible to regularise these drivers across disciplines. In the background, there will also be a mechanism to report on workloads across various ‘TRAC like’ activities, such as research and teaching administration. These data will be available at both school and faculty level, for reporting to external agencies as and when needed. Our thinking is that the workloads data can be made available for each individual’s PDR, so that the reviewer and the reviewee can see workloads at a glance.

Dr. John Appleby has kindly agreed to undertake the job of coding this model, and we anticipate that it will be ready around Easter. It is our intention to create a simple, reasonably robust model that will stand the test of time.

Here’s a final thought – should everyone’s workload data be shared and visible to all members of a  given unit (e.g. School)?

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About stevehomans

Professor Steve Homans is a structural biologist with an international reputation in the study of biomolecular interactions. He obtained his first degree and DPhil in Biochemistry at Oxford University, and secured his first academic position as Lecturer at the University of Dundee. In 1998 he received the Zeneca award from the Biochemical Society and was elected Fellow of the Royal Society of Edinburgh. Prior to his current appointment he was Dean of the Faculty of Biological Sciences at the University of Leeds. Professor Homans brings extensive expertise of academic leadership and management, with a particular emphasis on organisational change.
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One Response to Workload Models

  1. > Re: Here’s a final thought – should everyone’s workload data be shared
    > and visible to all members of a given unit (e.g. School)?

    I was surprised not to see some comments or discussion about this point. For me workload models should always be visible to everyone with a given unit. That’s not to say that everyone should have the same workload (or the same distribution of different classes of load within their workload) as there will be differences which stem from both strategic and/or operational decisions that a unit’s management team will have made (one would expect so anyway).

    Getting people onboard with these decisions means being open about the impact they have on everyone’s workload. For example, where someone is seemingly “lightly” loaded for everything except research (that is not associated with a funded project), then it is important to communicate the management logic behind such a decision (hopefully that will be a logic other than “it is hard to persuade X to do anything else”).

    Discussing workload models (and other people’s workloads) among your colleagues, the assumptions behind these models, and the management decisions made using them, are also an important way to gain agreement on their form and use, and should help to improve the models themselves as a management tool.

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