Part 4: Technology and a global health pandemic
This is the fourth part of an eight-part essay, ‘So, You Run a University?’. This essay is authored by Darcy W.E. Allen, Chris Berg, Sinclair Davidson, Leon Gettler, Ethan Kane, Aaron M. Lane and Jason Potts. Previous parts: Part 3, Part 2, Part 1.
Understanding universities as platforms provides much more than an unpopular defence of administrators. Our theory has predictive and strategic power. We can use these theoretical tools to understand both why universities have evolved into the peculiar 15-sided markets that they are, and to navigate our way through a global health pandemic and a suite of frontier digital technologies. To develop university strategy, we must first understand these technological trajectories and how a virus accelerated them. That is the task of this part.
Universities are remarkably stable institutions. The vast buffeting and grinding forces of history that have shaped and carved modern societies, cultures, economies, cities and even landscapes over the past 800 years have barely touched universities. Walk into one of the lecture theatres or libraries at one of the top universities—say Sanders Theatre at Harvard University, where you might take the legendary CS50 (the course that launched Bill Gates and Mark Zuckerberg, among other tech visionaries)—and you’ll have to look closely just to figure out what century you're in. Electric lighting is the main concession to industrial modernity, and Occupational Health and Safety signs near the exits are the give-away that you’re in the twenty-first century.
While universities are the origin of many of the foundational technologies of the industrial world, they are poor consumers of technology. The production technologies developed 23 centuries ago in some olive groves outside of Athens (the Lyceum), or in some fields on the outskirts of twelfth century Paris (University of Paris), or by the student’s guild in eleventh century Bologna (the Studium), are still more or less still in use today. Of course, universities embraced the printing press early on. And email was widely used by academics before almost anyone else. We move with the times. But compared to adoption of new technology by modern industry, universities are ‘late adopters’.
So, what could possibly shift a 2300 year old rock? Interestingly, a virus. And technology which has allowed it to navigate around the virus.
Digital technology and the future of universities
Universities have long had an uneasy relationship with digital technologies. To be sure, academics have developed many frontier technologies in their laboratories. But the university platform has been incredibly poor at utilising them.
Just as the printing press washed over the universities of the middle ages, the internet washes over our universities today. Computers and the internet have mainly been deployed in universities for simple tasks: to run messages between departments and deliver the same education goods to the same customers (but digitally).
Universities are poor adopters of the technologies they develop because there is an underlying assumption that the business model remains static. The general idea is that academics keep doing what they’ve been doing forever, but now the internal communications are digital. This digital delivery track is both complementary and substituting.
Our aim here is to provide some broad insights into the technological shock that universities face by observing five technology trends: the falling cost of communication, automation of operations, digital adoption resistance and Web3 as digital infrastructure. As we will see, these trends have accelerated with the COVID-19 pandemic. And understanding them gives us the vision of the university platform into the future.
The falling cost of communication
Many of the expected and realised benefits from deep adoption of digital technologies by universities and moving things online—whether as clickbaity ‘7 ways the internet will transform higher education!’ or as tricked-out $200,000 ‘Digital University Futures’ and EdTech strategy consultancy reports—really come down to just one thing: falling costs of communication.
Most academic production, whether teaching, research or engagement, is really just moving information around. Teachers use the university platform to jointly process and share information with students. Researchers must communicate with other scholars and the discipline to advance knowledge. And modern scholars are increasingly tasked with developing new communications channels to engage with industry and the public.
Investment in communication technologies lowers communication costs. Economics tells us that demand curves slope downwards, so when things cost less we consume more. So when the cost of doing all those different modes of communication falls, universities in effect become more productive.
Communications technologies are widely understood to usher in so-called distance learning. While universities have traditionally been highly urban, they have recently used communications technology to expand their footprint virtually across distances and jurisdictions, boosting their productivity and reach. The Open University has been a very successful pioneer in developing this capability and product. Communications technologies mean that the university can come to you, or you can come to the university, with open classrooms called Massive Open Online Courses (MOOCs) or other open educational resources.
Improved communications technology also has a qualitative dimension. New digital communication channels enable greater bandwidth and processing. Phone calls go to multimedia calls and libraries move to digital collections, and then to networked access. Thes communications improve the potential quality of many trades on the university platform.
But the technology trends pushing at the university business model go much further than distance or online learning.
Automating university operations
Universities are automating their operations. They are utilising new technologies to partially and fully automate the administrative infrastructure that supports a well-functioning university platform operations.
Previously labour-intensive operations—campus security, teaching assistants, student inquiries—are being transformed through technologies such as the Internet of Things (IoT), Virtual Reality (VR) and Artificial Intelligence (AI). These transformations not only promise lower-cost operations through substitution away from high-cost labour, but also the introduction of new learning experiences and products.
The automation is deeper than you think. Smart classrooms and campuses integrate digital and physical spaces through IoT, wireless presentation technologies and access control. AI chatbots and conversational interfaces act as virtual teaching assistants. New augmented learning environments create AR/VR clinical practice simulation for medical procedures or human services or learning languages. Data analytics assist the tracking and monitoring of student progress, facilitating specialised and bespoke learning and identifying locations of intervention. New financial products enable securitization of investment in education. Blockchain and distributed ledgers track credentials, proof of work experience, and verify references. This granulated information can be combined with data analytics software to provide career advice and deeper information about student cross-life-cycle activity.
Of course not all aspects of the university will be automated. But these examples all represent a shift from manual university operations—performed by in-house staff or contractors—to digital alternatives.
Private technology partnerships
Universities have never had more technology partnerships. Private sector partnerships are enabled by digital technology adoption and bring new customers and expertise into the university platform.
Many technology partnerships are spin-out organizations from universities, such as EdX (out of MIT), Coursera (out of Stanford) and RMITOnline (out of RMIT University). A particularly interesting example is Swinburne Online, now Online Education Services, bought by Seek, and which is as much a platform and administrative service as a delivery model.
As universities develop digital capabilities in administration and delivery it becomes easier to integrate with other companies. Those companies may have specialist knowledge that can be offered as plug-in education offerings into a broader credentialled program. Specialist engineering modules, for instance, might be taught by an engineering firm into a dual business and engineering degree program.
Partnerships not only provide unique education experiences, but also lower the costs of having industry expertise in-house. In reverse order, large organizations might seek to outsource specialist and firm specific training and certification back to universities.
Partnerships shift the boundaries of the university platform—and the scope of trades that can happen on it—in new and interesting ways. But that shift doesn’t come without resistance. It shifts the existing patterns of trades and cross-subsidies described earlier.
A build-up of digital resistance
We have been how digital technology has the potential to lower costs, facilitate productivity, and grow markets for universities. While these are all welcome technological trends for the platform as a whole, existing stakeholders resist them.
Universities are notoriously bad at adopting new technology because many academic staff resist it. These same staff are for the most part smart and capable people who are perfectly comfortable living in a technologically saturated world. But they resist its implication for the university. They might be automated out of a job, or outsourced to a technology partner.
It’s not just the faculty who resist digital change. The entire university sector is incentivised to resist as regulatory protection and the brand value of university credentials in effect protects against breakaway first-to-digital models. Digital adoption in other industries—such as banking, music, publishing or news media—was driven by the competitive advantages of companies that could successfully adapt to a digital world, but it was also constrained by the need for industry wide coordination of standards.
Student surveys by and large report a disappointing experience with online delivery. The most obvious reason for this is that learning and teaching practices have hardly changed at all, and moving online means that a practice that is optimised for one environment almost by definition is going to be worse when forced into another. “Pockets of innovation are found in almost every institution” explains a recent report, “but few have fundamentally changed how they teach.”
Web3 and digital infrastructure
The internet is not a single invention. It has had distinct phases, with different effects on the structure of our economy. For universities, Web1 and Web2 have largely driven the advances in communication efficiency and productivity gains, as well as the structural changes through learning technologies (the adaptation of information and communications technology to learning). We are slowly seeing Web2 filter through the university business model.
But Web3 is yet to hit. It is a raft of new technologies—including blockchain and smart contracts—for digital and distributed record-keeping and contracting. Web3 is distributed digital infrastructure for coordination and contracting on the internet. While Web2 is shifting the front-end of the university platform, Web3 will disrupt the very foundations of the centralised platform.
One vision of a Web3 university future is the blockchain university. Blockchain-based university credentials are now a relatively well-understood application where a distributed ledger provides a new infrastructure layer for the recording of credentials (e.g. marks, degrees). The trust in the credential is provided through a distributed ledger rather than by contacting the university platform directly.
The promise here is not just lower-costs of verification (not having to pay $50 for a new testamur), but also the sharing of credential information across organisational boundaries, including between different universities as students move platforms. This is a fundamental shift in the relation between students and the university platform. They can take control of their records, add credentials such as non-credit courses, internships and other experiences. The student may also provide assessments, endorsements and other validating materials. Blockchain technologies, as part of Web3, facilitate the trend towards decentralization of the university.
Blockchains won’t just transform credentials and the student-teacher trade on the university platform. They also introduce new publishing models for research. They facilitate time stamped proof of priority linked to academic identity. Blockchains can track citations and use of research, including even possibility for trailing payments. A similar argument can also work on the production of educational materials (including notes, textbooks and the like).
The types of disruptions that Web3 technologies are bringing to creative industries, media and publishing will also wash through the education sector. These trends began in the decades before 2020. And then there was a global pandemic.
COVID-19 and a tech acceleration
In late 2019, a highly infectious novel coronavirus began spreading around the world. In May 2020, the World Health Organisation officially declared it a pandemic. In response to expert public health advice, governments around the world introduced policies including ‘social distancing’—the avoidance of social contact or physical proximity to others—to limit the spread of the virus. Some of the team on this essay wrote a book published in May 2020 that examined the economic policies required to steer the global economy out of the pandemic.
Universities have been on the front line of the global COVID-19 response. They marshalled resources, people, materials and facilities to the immediate challenges of a global pandemic. They have searched for vaccines, designed and manufactured ventilators and responded to the mental health challenges of self-isolation. University research groups such as Johns Hopkins University’s Coronavirus Resource Centre and Imperial College’s infectious disease modelling unit analysed and shared data to inform policymakers and the public. The latter’s modelling triggered policy shifts on both sides of the Atlantic.
The research and models that universities develop in response to COVID-19 has a clear and demonstrable impact on the world. But we are concerned here with something else: what is the real and lasting effect of the COVID-19 pandemic on universities? Even the deep scars that will be carved into university budgets for decades to come—due to the disruption in particular of the foreign fee paying market on those markets heavily reliant on overseas income such as Australia, Canada, the US and the UK—will not be the main effect.
The most important long-run consequence of the COVID-19 pandemic is to accelerate rapid structural changes and the ‘creative destruction’ that was already taking place in the education sector. For three or so decades, universities have sought to make digital upgrades to their production technology. The digital trajectories we introduced above have been here for decades—but they just sped up in response to a virus. Their effect is not just to make universities slightly more digital with more distance-learning. There will be fundamental shifts in how the university platform operates (and, as we will see in coming parts, this will be different for each university).
Many of the fundamental barriers to digital adoption in universities were swept away. The deep resistance to digital technology adoption in universities was cast aside. Moving online wasn’t optional anymore, it was necessary. COVID-19 unleashed a wave of reluctant but ultimately successful adoption of methods and procedures for digital delivery.
Previously universities faced no real force of disruptive competition—unlike in say retailing or the media industries—where companies that refused to change could be outcompeted by those who adopted new technologies. Universities are well protected by governments and social and cultural expectations with respect to credentials and the way you get them, so change is hard. A virus shifted this dynamic, forcing rapid change.
COVID-19 forced a coordinated digital adoption. One of the deep problems in taking universities digital was that this couldn’t be a partial shift. When one part of a university went digital but other parts did not, then effectively nobody did. Despite its potential, digital online delivery of learning has been a profoundly inferior product.
Technological adoption had been developed and trialed over several decades but had never been fully scaled up. All at once, universities rapidly accelerated the adoption and scale of things they were doing at a smaller scale earlier. What was a secondary mode of delivery became the primary engine. In only a few months universities also experimented with new ways to teach, research and administer from home.
The organizational geography of universities has shifted. Universities are rapidly learning to function as more distributed organizational units. They may not need the vast campus-based teaching operations or administrative headquarters in anything like the scale they had before. However, like all large corporate forms, they need now to solve new management problems related to monitoring staff, building culture and communicating strategy and vision. The role of next generation digital platforms will be key to holding them together as functional organizations.
The immediate effect of the pandemic and responses by governments business and citizens was a rapid acceleration of digital technology adoption to facilitate working from home, and educating from home, shopping from home, getting health and social services delivered to home, and so on. All of this we could do in late 2019, but we didn’t. We had little reason to systematically adapt, and no coordinating mechanism to force us to do it at the same time.
So here we are now. A global health pandemic and, at last, coordinated digital technology adoption. The 2300 year old university rock has been destablized.
Part 4 takeaways
Universities are remarkably stable and enduring institutions that look incredibly similar to their ancestors 800 years ago.
This long-running organizational statis has just been hit by two shocks: a suite of digital technologies that shift the possibilities for operating a university platform, and a global pandemic that forced coordinated technology adoption.
A suite of technological trends are disrupting the potential scope of university business models. We pinpointed five critical technological trajectories and how they relate to the university platform:
falling cost of communication changing the way trades on the university platform can occur
automating parts of university operations through capital-labour substitution
new private technology partnerships shifting the boundaries of the university platform
a build-up of digital resistance to technology adoption
the rise of web3 digital infrastructure such as blockchain
These technological trajectories have been rapidly accelerated by the COVID-19 global health pandemic.
The need to move the university platform online cast aside faulty resistance and coordinated adoption that held digital adoption back.
The university platform will never look the same.
 Saykili, A. 2019. Higher education in the digital age: The impact of digital connective technologies. Journal of Educational Technology & Online Learning, Volume 2(1), pp. 1-15; Deming, D. J., C. Goldin, L. F. Katz and N. Yuchtman. 2015. “Can Online Learning Bend the Higher Education Cost Curve?”, American Economic Review 105, p. 496–501; Neylon C, Gilles M, Montgomery L, Hartley J, Leach J, Potts J, Gray E, Huang K, Hermann-Pillath C, Ren X, Skinner K, 2018. Open Knowledge Institutions: Reinventing Universities (MIT Press PubPubs); Reich, J., Ruiperez-Valiente, J. 2019 ‘The MOOC pivot’ Science, 363(6423), p. 130-131.
 Bayern M 2019, 10 technologies that will impact higher education the most this year, Tech Republic; Marcus J 2020, How Technology Is Changing the Future of Higher Education, New York Times.
 Selwyn N 2016, Digital downsides: exploring university students’ negative engagements with digital technology, Teaching in Higher Education, Volume 21:8, pp. 1006-1021.
 Davies S, Mullan J and Feldman P 2017, Rebooting learning for the digital age: What next for technology-enhanced higher education, Higher Education Policy Institute.
 Berg, C, Davidson, S., Potts J. (2018) "Outsourcing vertical integration: introducing the V-form network," Medium.
 See Schroeder (2019) “We are moving from a degree-centric environment in which the university is engaged in the life cycle of the student while on campus to one that is more of a supply-chain design providing lifelong learning. The continuous delivery and documentation of learning will be secure, learner owned, documented and certified. That is in stark contrast to the mostly degree-centric, institution controlled and very thinly documented approach of years past. And the movement to a supply-chain approach is one that will transform higher education as certainly and radically as the iPod and its derivatives changed music as well as our mobile society.” (Schroeder R 2019 A Fresh Look at Blockchain in Higher Ed, Inside Higher Education.)
 Roebuck K 2019, 5 Ways Blockchain Is Revolutionizing Higher Education, Forbes; Tapscott D and Tapscott A. 2017. ‘The Blockchain Revolution and Higher Education’ Educause Review.
 See Smith (2019) “As intellectual property and assets have become more valuable, however, the sharing of innovative ideas has become more problematic in terms of tracking ownership, etc. Once again, setting up a consortium blockchain would allow individual professors and institutions to share information openly while also having an undisputed track record as to who owns what information. Data and innovation are often cited as the drivers of the modern economy, and increased transparency with blockchain-based solutions is a logical step…a decentralized consortium allows the sharing of courses, faculty expertise, and institutional resources across a globally accessible platform.” (Smith SS 2019 How blockchain could change higher education, Blockchain Pulse: IBM Blockchain blog.)
 Allen, D., Berg, C., Davidson, S., Lane, A. Potts, J. (2020) Unfreeze: How to create a high growth economy after the pandemic. AIER Publishing: Great Barrington, MA.
 Gann D and Dodgson M 2020 ‘How an entrepreneurial approach can help end the COVID-19 crisis’, World Economic Forum.