How come the EdTech startups are still struggling to penetrate and transform the higher education market? One reason is to the digital players’ poor apprehension of the university’s value chain. Will higher education institutions will resist digitization forever? It seems unlikely.
Since Chard’s learning machine in 1809, Skinner’s teaching machine in 1958 and, more recently, with the advent of the Internet, many have announced the end – or progressive disappearance – of universities. While some have announced the diversification higher education models, even their assembly by individuals based on different digital tools (Kamenetz, 2010), others announce a real tsunami (Davidenkoff, 2014) that will shake the foundations of an institution born in the Middle Ages.
And yet, after the wave of e-learning, of Moocs and now, of adaptive learning, we need to acknowledge the fact that universities haven’t disappeared yet... In spite of many difficulties to face massification, globalization and digitization, they are resisting, all over the world. Failures to digitize higher education are both numerous and old (Guri-Rosenblit, 2006).
How does one explain that students did not massively turn towards online courses? Why do they continue pouring into universities? Why don’t they build themselves portfolios of so-called “online validated skills”, presented as the new paradigm? How come education start-ups (EdTech) are still struggling to penetrate and transform this market?
Monopoly of diplomas? Conservatism? Corporatism? All these arguments fail to explain the resistance to technological advances and to profound changes of uses in society over the last twenty years with the ever more intensive use of digital technologies. Therefore, the explanation needs to be sought elsewhere. In our opinion, it is due to the digital players’ poor apprehension of the university’s value chain. The latter integrates several components that new actors neglect or simply ignore. However, the demand addressed to the university is that of a package, not only of digital content.
Does this mean that higher education will resist digitization forever? It seems unlikely. In other sectors, digital actors have devised strategies to break down the integrated value chain and subsequently rebuild it through the development of an ecosystem driven by digital platforms. In this perspective, the university could also be very strongly challenged by new integrated players, recombining the entire value chain.
Under these conditions, what strategies should universities implement to avoid a disruption of their business model, like in many other industries?
If several models of higher education exist in the world, a university’s business model systematically combines several components to build a student-focused value proposition, which in a market largely dominated by a logics of reputation, students discover and identify by a brand.
Teaching is a good that is based on experience. Its quality is poorly assessed and its reporting mechanisms are imperfect (rankings, accreditations, etc.). Therefore, on such a market, reputation effects rely on brand logic (Hemsley-Brown & Goonawardana, 2007).
The demand addressed to universities, especially for first-time entrants, is a global demand. The latter values a complete offer, based on an image reflected by the brand. Students rarely choose a university for a specific course offer, especially when bachelor courses are so similar over all institutions.
What does the university offer that, in our opinion, makes it irreplaceable? It basically aggregates five components: pedagogy, ancillary services (housing, scholarships, financing, etc.), services focused on professional integration (internships, apprenticeship, network of graduates, job offers, incubation of entrepreneurial projects, etc.), socialization via different activities (associative life, sports life, etc.). This offer is based on a solid foundation: the production of knowledge through research activity.
Universities all provide an offer combining these different features in a differentiated, yet integrated way. Thus, aggregated value isn’t limited to that of a component but reflects the experience offered and valued through a brand.
By focusing on a single component of the offer, EdTech startups offer only one aspect of the value chain. Many of the offers are focused only on knowledge and skills (MOOC), professional integration services (Jobteaser or LinkedIn) or ancillary services (Studapart). However effective and relevant they may be, these offers cannot trigger alone an overhaul of the university’s organization.
Even if Kamenetz imagined the possibility for some students to build their own training offer by combining different services, it is clear that, to this date, the demand for DIY universities remains – and will most probably remain – marginal. The aggregation of offers has a cost and the demand for socialization is a crucial dimension of this offer – whether it is assumed by these institutions is another question. It is difficult to imagine how digital offers will really transform it.
Moreover, whatever the relevance of digital services, none of them are able, at the moment, to develop a global offer, i.e. the only alternative that could seriously threaten higher education. Does this mean that all threat has been averted?
Answering yes seems too bold a claim, for two reasons.
Firstly, the observation of some markets shows that disruptive players have initially focused on one part of the offer to gradually recompose the entire sector through a platform strategy based on ecosystems. In this respect, AirBnB offers an enlightening case. By initially focusing on overnight stays, the company started by breaking down the packaged offer of hotel groups (i.e. overnight stays, concierge service, room services, meals, transport, etc.). But after reaching maturity on this first segment of the value chain in a differentiated manner, they recently started to add benefits to their initial offer: recreational activities, tourist guides and itineraries, concierge services and meals at home.
At the end of the process, the initial packaged offer has been fully re-engineered thanks to a digital platform that combines third-party partners delivering various components of the value chain. It is therefore possible to imagine that actors of one component or another will eventually rebuild a complete value chain, starting with their initial service – particularly those that are able to provide services of professional insertion. A company such as LinkedIn, for example, already offers a number of components in its value chain: identifying skills sought by companies through the analysis of job offers against short-staffed sectors; ability to target potential students and training offers (LinkedIn Learning). But also many other actors, such as Coursera, that could repackage a complete offer based on their training offer.
The second reason is due to one of the most specific parts of the value chain: research. Universities remain the best place to develop research. And yet, in several fields of research (biotechnology, medicine, but also the human sciences), the paradigm shift triggered by digital technology related to the processing of digital data and traces questions the university’s ability to master resources and skills needed for this new science. At the age of artificial intelligence, when data-computing and data-gathering capabilities are two necessary conditions for the production of research, how do universities intend to participate in this transformation? It must be noted that resources are better managed by private actors far from the world of teaching and research. Could these players therefore constitute a threat to universities’ main activity?
Under these conditions, what strategy can we devise for institutions of higher education? If they wish to avoid a possible disruption of their business model, they must by all means become the heart of an ecosystem that they control and drive through a digital platform with a governance they organize themselves. The phenomenon of platformization is transforming many sectors. Higher education is no exception. It is therefore urgent to understand its foundations in order to deploy such a model rather than being forced to join platforms created by other disruptive players.
Implementing a platform requires thinking about the heart of the ecosystem made possible by a digital platform based on which actors co-construct a value proposition. This logic of building a value proposition allows to broaden it, based on resources – including teaching resources – offered by partners. It also allows to focus on activities that are difficult to imitate or digitize (e.g. learning by project, problem-based learning), notably socialization, by transforming interactions on campuses redesigned as spaces for self-construction, both in personal terms (who do I want to be) and professional terms (which activity do I wish to create or join?).
The question of the technical architecture of the platform is a strategic decision.
This requires redesigning a great part of the value proposition to focus on producing a learning experience and getting third-parties to deliver some parts of the value chain. Those who fear to lose control in such an approach must understand that value doesn’t depend as much on its components then on the ability to select and intelligently assemble a brand experience. The mastery of value architecture, the selection of partners and the aggregation of different skills on the digital platform also lead to a reflection on the core of value and its associated skills.
From this perspective, the question of the technical architecture of the platform is a strategic decision. In this sense, it enables and organizes collaborations and the development of the ecosystem for third-party partners. It is an open architecture controlled by rules that govern collaborations with members of the ecosystem. This is played out in the way information system interfaces, the so-called APIs (Application Programming Interface), are designed. They are the true connectors of value in a digital, networked world. The ability to renew research methods is also at stake, by building new tools to produce, collect and process data in a digital world. It is all the more necessary in a logic of Open Science and now, of open research data.
Kamenetz A., (2010), Diy U: Edupunks, Edupreneurs, and the Coming Transformation of Higher Education, Chelsea Green Publishing Company
Davidenkoff, E. (2014), Le Tsunami numérique, Stock
Guri-Rosenblit, (2006), “Eight paradoxes in the implementation process of e-learning in higher education,” Distances et Savoirs, Vol. 4 (2), p. 155-179
Hemsley-Brown J., Goonawardana S., (2007), “Brand harmonization in the international higher education market,” Journal of Business Research, Vol. 60 (9), pp.942-948