Here is a short story about IT systems in higher education. It is sourced from pandemic charged conversations with colleagues in academia and given focus from friends who work in finance. Let’s call it a tale of two techs: #fintech and #edtech

Let’s set the scene positively: many of us have been able to work at home for almost a year of a global pandemic due to IT systems that connect us to our work and those we work with. This is an amazing achievement and a privilege.

Yet the everyday is punctuated by events driven by frequent breakdowns of these systems to do what they are meant to do, the proliferation of work that comes from supporting them, and the constant implementation of new systems that are meant to do more and better. And don’t.

As far as I understand it, this is part of the character of innovation in IT. Things are introduced (always slightly late but also too early), they are user tested to some extent (time-consuming so not always with the right people), and initial 60% success rates are seen as good.

Things are meant to improve. This requires lots of monitoring and intermediate workarounds, which involve lots of input from the people whose work they are meant to help. And when they work well, these people may be made redundant. It is not necessarily a happy story.

However, the narrative arc diverges between #fintech and #edtech. In financial services, people fill out time sheets and their time is visible as a cost to the same decision-makers who decide that introducing fintech in the first place is a good idea.

There is a period when the investments in fintech require more support from people. New people may be employed to train the robots. (They are not actually robots but this makes everyone feel slightly futuristic and less exploited.) Even so there is lots of moaning in this period.

Eventually, the idea is the robots will get better at doing what they are meant to do. Staff costs will come down, roles routinized and outsourced, people made redundant. This makes a small number of people happy. Perhaps the robots are satisfied. Perhaps new roles open up.

In academia, the story gets stuck at the point when the investments in #edtech proliferate both work and complaint. The vision sold by the external software provider was compelling, but here no one took account of the initial additional staff time needed to make them work.

With workload models broken, academic staff find creative workarounds or self-exploit, professional services staff work weekends. Both are mainly and mercifully free from time sheets, but this means no one quite realises the scale of the issues.

The narrative structure here is a more conventional tragedy. The new software system is meant to help student welfare, make research more efficient, improve academic productivity. Yet, it generates more student emails, increases research admin, heightens alienation.

#Fintech systems are task-focused, with clear patterns of governance. You have to learn how to use them. #Edtech systems reflect the multiplicity of academic roles with obscure lines of responsibility. Few staff end up using them all well. Few know how students use them at all.

Complaints are received with an overabundance of poorly targeted training documentation, new workarounds, new roles, new plugs in, even new IT systems, with which this time, it is assured, things will be better. The process continues, gaining complexity and contradictions.

Meanwhile, the things meant to improve have moved out of focus. Student welfare dives as stressed students value human interaction over apps. Teaching and learning experiences are dissipated as feedback is lost in the ether. Research accounting doesn’t.

The space between promise and reality fills with suspicions about the purpose and processing of staff and student data. #Fintech is painfully transparent about its hunger for data. #Highered is still opaque about its role in crafting data and as data itself.

I remain grateful to my own institution for the tools that help me do my work well. But if I do ever decide to leave academia - no plans at the moment - bad and badly implemented software systems will likely be a key protagonist in any associated academic quit lit

Can this story have a happy ending? Be open and honest when setting the aims of new system. Factor in the costs of staff time in purchasing decisions. Be inclusive and consult those who are meant to benefit. Obtain rights to change off the shelf IT systems and innovate internally