by Sam Sellar

This blog is based on a presentation to the 2021 SRHE Research Conference, as part of a Symposium on Universities and Unicorns: Building Digital Assets in the Higher Education Industry organised by the project’s principal investigator, Janja Komljenovic (Lancaster). The support of the Economic and Social Research Council (ESRC) is gratefully acknowledged. The project introduces new ways to think about and examine the digitalising of the higher education sector. It investigates new forms of value creation and suggests that value in the sector increasingly lies in the creation of digital assets.

In a lecture delivered to Stanford University in 2014, which was provocatively titled Competition is for losers, Peter Thiel argued that ‘[m]onopoly is the condition of every successful business.’ Thiel’s endorsement of monopoly over competition has become business strategy orthodoxy for Big Tech firms, which, as Birch, Cochrane and Ward (2021, p6) argue, have ‘often been willing to accept low revenues in the short- to medium-term with the longer term goal of capturing markets and monopoly rents through their expected future control over data’. Assets are replacing commodities in contemporary capitalism, and an asset can be defined as ‘something that can be owned or controlled, traded, and capitalised as a revenue stream … [and] the point is to get a durable economic rent from them’ by limiting access to the asset (Birch and Muniesa, 2020, p2). We can see these assetisation dynamics emerging in EdTech markets serving UK higher education, and in this article I offer early insights into how these dynamics, driven by the growth in use of digital platforms during the Covid-19 pandemic, are shaping university strategies and practices.

This article reports on findings from the second phase of the Universities and Unicorns: building digital assets in the higher education industry project. The project is led by Dr Janja Komljenovic at Lancaster University and it aims to investigate new processes of value creation and extraction-assetisation-in the HE sector as it increasingly digitalises its operations. In Phase 2 of our project, we are conducting a series of university case studies in the UK, along with the investor and the company case studies. The university case studies are designed to help us understand how universities work with their commercial partners and what are the synergies and tensions. We are also curious about how universities view changing business models that focus on assetisation.

Importantly, we are not evaluating the use of EdTech in the context of teaching and learning or evaluating the strategies of individual institutions. Our concern is with how the HE sector is evolving in connection with EdTech markets. We are interviewing senior leaders, academic staff, directors of IT departments, IT developers and staff working in procurement, commercialisation and legal departments. We are also collecting a range of documents relating to digital strategy, business and data management plans, technical reports, financial records, and contracts with EdTech companies.

Our fieldwork with universities is a work in progress, and in this blog post I will outline three of our emerging findings, which relate to: (1) the ways that universities think about digital strategy; (2) the value of data from a university perspective; and (3) emerging processes of assetisation.

Digital strategy

None of the universities that we have studied so far have had formal and distinct digital strategies. Rather, digital strategy is embedded in IT, teaching and learning (T&L) and library strategies. In most cases, universities appear to be ‘between’ official strategy documents that cover this area. COVID-19 clearly shifted the short-term focus to tactics – working urgently to adjust and develop digital ecosystems to accommodate new demands of large-scale shifts online – and these universities are just now catching their breath and starting to update their strategies. However, despite this lack of formal strategy, some universities are very clear regarding the use of digital platforms to lead the sector and create value. In these cases, there clearly is an overarching strategy, it just isn’t described or formally presented as such.

Universities see themselves as developing institutional digital ecosystems by joining up platforms and focusing on the interoperability of their systems. Decisions about specific platforms are increasingly shaped by their potential integration into these ecosystems, and how data can be managed and integrated across platforms.

Interestingly, digital strategy is being driven by teaching and research strategy rather than shaping it. In one case, the point was made very strongly that digital is not separate, but rather a way of delivering the core business. Digital platforms are largely being used to deliver existing activity in digital form, rather than to create new forms of economic activity and new sources of value. However, questions are being raised about the relationship between IT and teaching and learning. For example, should IT departments simply support other business functions, or might they lead on digital strategy to enable new possibilities for the university?

The value of digital data

The primary value of digital data for universities appears to be reputational, and responses from our participants thus far have been remarkably consistent in this regard. Digital platforms can help to enhance the university’s brand and extend the business over a wider geographic range. This primacy of reputational, rather than financial, value is a distinctive feature of university perspectives on digital platforms, in contrast to companies.

Engagement with digital platforms was also seen to be valuable insofar as it generates market intelligence, supports student recruitment, changes perceptions of teaching and learning (eg blended approaches); and change perceptions of students (eg enabling particular cohorts to engage in new ways with benefits for their learning outcomes). Most interviewees are not thinking about the data generated by digital platforms as an asset, but it is clear that digital content (eg recorded lectures) are being seen in these terms insofar as they can be controlled by intellectual property rights and re-used over time.

Interestingly, our participants clearly hold the view that there is more potential for universities to make use of the digital data generated by platforms they use. However, in the case of learning analytics there is also scepticism regarding what it promises and its true value at this time. Despite a number of trials and experiments, many in UK universities are yet to see the benefits beyond what can be achieved using more prosaic approaches to data analytics.

Assetisation

The universities that we have studied so far do not appear to be using data to develop new products or services that generate value through economic rents; this kind of activity appears limited to commercial providers of digital platforms. However, universities increasingly understand the potential value of the data generated by their staff and students, and they are actively pursuing access to these data in their contractual negotiations with partners.

This is where we are seeing the emergence of assetisation dynamics in EdTech markets, which reflect the business strategies that Thiel promotes in his celebration of monopolies. Even if universities are able to negotiate favourable terms in individual contracts, providing rights to access and use data generated by university users on a given platform, they do not have access to aggregated data collected by companies through the use of this platform by other universities.

There is thus concern about the assetisation of data by commercial providers, for example, in relation to the use of aggregated data sets to develop new products and services that automate aspects of academic work (eg assessment). Turnitin is a primary example that came up in many of our discussions. The monopoly created by Turnitin leaves universities with little choice but to use their platform and pay whatever is asked, and relationships with Turnitin have become strained in many cases. The value of Turnitin is based on the data they have collected, and this data could be used to develop new services that automate, and thus substitute for, aspects of teaching currently delivered by lecturers. Work is being pursued through industry bodies to negotiate fairer distribution of the potential value generated by digital platforms in such cases.

Conclusion

While our university case studies are a work in progress, these three themes are already emerging quite consistently across our research sites. The value of data for universities is primarily reputational, extending the reach of teaching and learning functions, enhancing recruitment and supporting innovation in teaching and learning. Universities see digital strategy and the use of digital platforms as a way to extend their core business, not as a means to create new kinds of economic activity. In this respect, tech sector business strategies focused on creating value from data as an asset are not yet evident in the strategies of universities. However, we are seeing early signs that data is being assetised by EdTech companies, in an effort to extract monopoly rents by locking-in users through subscriptions to digital platforms. In this sense, we are curious to see whether monopoly will be a condition of every successful business in the burgeoning HE EdTech space.

Sam Sellar is Dean of Research (Education Futures) and Professor of Education Policy at the University of South Australia. Sam’s research focuses on education policy, large-scale assessments and the datafication of education. Sam also works closely with teacher organisations around the world to understand the impact of digitalisation on teachers’ work. His most recent book is titled Algorithms of education: How datafication and artificial intelligence shape policy (University of Minnesota Press), co-authored with Kalervo N Gulson and P Taylor Webb. Contact here: sam.sellar@unisa.edu.au

References

Birch, K, Cochrane, DT, and Ward, C (2021) ‘Data as asset? The measurement, governance, and valuation of digital personal data by Big Tech’ Big Data & Society, 8(1), 20539517211017308.

Birch, K, and Muniesa, F (eds) (2020). Assetization: turning things into assets in technoscientific capitalism Boston: MIT Press

Thiel, P (2014) ‘Competition is for losers’ The Wall Street Journal Available from: https://www.wsj.com/articles/peter-thiel-competition-is-for-losers-1410535536