by Janja Komljenovic
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.
Universities worldwide are increasingly interested in digital technologies and how they can support higher education. A recent study by the European University Association found that most European universities are already using or planning to use data-rich products and services, such as artificial intelligence, machine learning, learning analytics, big data, and the internet of things (see Figure 18 on page 36). Indeed, it is precisely these data-rich operations that are central to the idea of the disruptive potential of education technology (edtech), as argued by my colleague, Javier Mármol Queraltó, in the recent UU project report. The discourse of investors and edtech companies promises thoroughly improved higher education based on personalisation, automation and efficiency. But how deliverable are these promises? Who innovates in the space of data-rich operations, for which services and for which users? Who profits? These are some of the questions we address in the Universities and Unicorns project, which aims to understand forms of value and ways of creating it in digital higher education. In this blog post, I will address three possible trends that can be identified from the interim findings of our quantitative analysis. But before proceeding to discuss these trends, I will contextualise our analysis.
We used Crunchbase to build three databases covering 2,012 edtech companies, 1,120 investors in edtech, and 1,962 edtech investment deals. We identified those relevant to the higher education sector, and our data reflects the state of the sector as of July 2021. Based on this analysis, we identified four key service models in the higher education edtech industry. First, the business to business (B2B) model includes digital platforms serving universities and companies, such as virtual learning environments. Second, the business to customer (B2C) model includes platforms targeting individuals directly. Third, the business to business to customer (B2B2C) model serves institutions that use or further develop the platform to reach individuals, such as Massive Open Online Courses (MOOC) or Online Programme Management platforms (OPM). Finally, the business to the customer to customer (B2C2C) model includes platforms that connect individuals, such as skills and knowledge sharing platforms. B2B2C and B2C2C platforms, in particular, act as the kind of infrastructural intermediaries that are so popular in other sectors of our social and economic lives.
Our analysis found that half of all investment went into B2B platforms, followed by investment into B2C, while B2C2C and B2B2C together received just under a quarter of all investment. However, platforms with the fastest pace of increasing investment are those targeting individuals directly or through intermediation, ie B2C and B2C2C models. This might indicate emerging parallel or alternative higher education products and services that compete with traditional university provision, especially in the context of lifelong learning.
Digital platforms that say they incorporate data-rich operations in their products and services are not the priority area for investors. While we noticed an increasing investment in data-rich platforms, it was still only less than a quarter of all investment going into innovating such products. Nevertheless, we identified three possible trends that are especially worthy of our attention: (1) data-rich operations are being innovated largely in B2B platforms; (2) there is notable unevenness in terms of the location of edtech companies and investments in those platforms who innovate in data-rich operations; and (3) there might be potential for monopolies in data-rich innovation. Let’s delve into each of these possible trends.
Almost all investment in the companies developing data-rich operations in their platforms went to the B2B service model. Looking only at higher education institutions as the target customer, already half of the investment supports data-rich innovation. Most of that went into platforms that act as the institutional digital backbone, indicating that the intention might be to support all institutional functions beyond teaching with data-rich operations, such as artificial intelligence, machine learning and various kinds of analytics beyond learning analytics. There seems to be a trend towards data-rich digital ecosystems at universities that harvest all user and other data in the near future.
There is high unevenness in where the investment in data-rich platforms is allocated. Regarding the number of companies, 239 in our database declare that they offer data-rich operations on their platforms. Almost half of those (101) are based in the USA, 21 in the UK and 19 in India. Companies based in Africa are entirely missing from the list. In terms of investment amounts, 88% of all investment in companies offering data-rich services in their platforms went into companies based in the USA, 3% each to those based in Norway and the UK, and 6% to the rest of the world. The discrepancy between the number of companies and investment size indicates that investment amounts are higher in the USA than elsewhere in the world.
Finally, if we compare different indicators of investment in companies that innovate data-rich solutions for higher education institutions, we notice interesting dynamics. Looking at the money raised, half of B2B investment went into those companies with a platform that included data-rich operations. But this is only 30% of deals and 25% of companies. This indicates that the concentration of investment in data-rich operation platforms for higher education institutions goes into a smaller number of companies who get higher investments. We wonder if this signals potential for monopolies in the future. Moreover, if we compare granted patents, we notice that a higher percentage of companies offering data-rich solution platforms own patents (30%) versus those offering other kinds of service or product platforms (10%). Digital platforms are typically still protected by a licence, but that differs from a more restrictive patent protection. We wonder if such discrepancy in patent share might indicate black-boxing of data-rich operations in higher education?
Our research on digitalising higher education is showing the complex impact of digital technology and datafication on the sector. This impact includes potential positive and supportive measures, but also many potentially worrying trends. However, further research is needed into these trends and the role of different actors, particularly financial investors and edtech companies. Please follow our project in which we will share the findings from this further work as it unfolds.
Janja Komljenovic is a Senior Lecturer and co-Director of the Higher Education Research and Evaluation at Lancaster University in the UK. She is also a Research Management Committee member of the Global Centre for Higher Education with headquarters at the University of Oxford. Janja’s research focuses on the political economy of knowledge production and higher education markets. She is especially interested in the relationship between the digital economy and the higher education sector; and in digitalisation, datafication and platformisation of knowledge production and dissemination. Janja is published internationally on higher education policy, markets and education technology.