Kisito Futonge Nzembayie explores how in the digital age, the micro-level activities of digital entrepreneurs in new venture creation continue to digitally transform and disrupt economic systems at macro-levels.

Pervasive digitization has raised significant implications for entrepreneurship in the digital age. Virtually all sectors of the economy have been affected by digital technologies to varying degrees. Not surprisingly, therefore, digital technology-based firms are today the main drivers of economic value creation. Among the top five companies by market capitalization in 2021, four were digital technology-based companies – Apple, Microsoft, Amazon, and Alphabet (Google). These companies have one thing in common – they are digital platform-based organizations.

However, if we journey back 15 years, the opposite is true. Traditional organizations such as ExxonMobil, General Electric, and Citigroup were among the top 5 companies, with Microsoft being the only digital technology-based company. What this shows is a seismic shift in the basis of economic value creation in about a decade. We are indeed in a Second Machine Age or Fourth Industrial Revolution, marked by the ‘digitization of just about everything’ as pointed out by MIT and Stanford scholars Andrew McAfee and Erik Brynjolfsson. In this new age, ‘software is eating the world,’ as Marc Andreessen figuratively puts it.

But does pervasive digitization imply that all new venture creation in the digital age is somehow digital entrepreneurship? Our answer to that is a resounding No! However, we are sympathetic to the fact that the blurring of lines between digital and traditional forms of entrepreneurship presents both conceptual and practical difficulties for those looking to engage with the subject. So what is digital entrepreneurship?

Digital entrepreneurship specifically refers to entrepreneurship in which digital artifacts and digital platforms (software-based products and systems) form the core of new venture ideas and market offerings. It manifests in two main typologies – pure and hybrid.

But what is the significance of making distinctions between typologies of entrepreneurship in the digital age? Without critical distinctions, we risk arriving at misleading generalizations in research and offering the wrong advice to aspiring digital entrepreneurs. In fact, upon realizing that traditional entrepreneurship models are not reflected in practice, digital entrepreneurs began to develop innovation models such as the Lean Startup, Agile Development and its variants such as Scrum, XP and Kanban, Customer Development and Design Thinking, which more accurately speak to practice in their world. The academic world found itself playing catch up. To understand why we must examine digital entrepreneurship in its own right, it is important to begin by identifying what unites all forms of entrepreneurship.

So, What is Common to all forms of Entrepreneurship?

Entrepreneurship is a complex, multidimensional process whereby individuals initiate ideas and act to pursue them as opportunities, leading towards various outcomes. Action, called new venture creation, is central to this process. It leads to outcomes such as new market offerings – manifested in new products, new organizations, and new markets. Higher-level outcomes may also result in new societal norms and behaviors. New venture ideas are often externally enabled by changes in the environments in which entrepreneurs are embedded – changing technology, consumer behavior, regulation, environmental and ecological conditions, and others. Entrepreneurs need not be fully aware of external enabling changes in order to initiate new venture ideas or to take action. Additionally, ideas are often motivated by the need to solve problems for segments of society through the creation of a product or service combination. Problems are therefore the needs and wants of consumers or customers. Given this problem-solution motive, the purpose of all productive forms of entrepreneurship is to create value for society.

There are several moving parts in this conceptualization – hence the complexity. But focus your attention on two main concepts here: New Venture Ideas and External Enablers. These concepts in the entrepreneurship literature refer to the objective WHAT of most entrepreneurial processes. Anyway, let’s return to digital entrepreneurship.

So, How is Digital Entrepreneurship Different?

• The New Venture Idea – Digital Artifacts & Digital Platforms as Core

The new venture idea is a major differentiator of various typologies of entrepreneurship. It is that on which entrepreneurs act. New venture ideas are metaphors for new market offerings. Digital entrepreneurship is uniquely differentiated by the fact that digital artifacts and digital platforms form the core of digital business ideas and market offerings. When something is core instead of peripheral to an entity, it means that entity cannot exist without it.

Digital artifacts is a collective term for software-based products and objects. By ‘software-based,’ we mean software itself, such as mobile and desktop applications, Artificial Intelligence and machine learning algorithms, and more. It also refers to by-products of software such as media content and other types of digital content such as eBooks, infographics, and the rest. Meanwhile, a digital platform is a software-based system designed to host complementary offerings. Digital platforms are matchmakers. They match producers and consumers.

When entrepreneurship is based on the creation of software-based products and services, the HOW of traditional entrepreneurship gets upended. In fact, many business schools continue to teach entrepreneurship with underlying assumptions of the creation of physical and tactile offerings – with their corresponding spatial and temporal limitations. Such spatial and temporal constraints are seen to impose rigidity and undue linearity on entrepreneurial processes. However, when software-based offerings form the core of entrepreneurship, those limitations either evaporate or are greatly minimized. For these reasons, we need to place digital entrepreneurship in its own category and examine it differently.

The reasons for this distinctiveness can be explained by examining the characteristics of software-based objects and their implications for new venture creation. As we shall see, these characteristics translate into agility and extreme flexibility in new venture creation, which are possible but less feasible when creating physical products and tactile services. It, therefore, questions our core logic of how to bring such products and services to market and what constitutes success. For instance, do you begin new venture creation with a deliberate business plan or experiment towards an emergent one?

Software-Based Offerings and Implications for DigitalEntrepreneurship

Software-based products are digitized goods and services. By this, we mean they exist merely as bits of data in the form of ones and zeroes. Digitized goods are highly modifiable and instantly distributable over cyberspace. Together, these characteristics allow products and services to remain incomplete by design and subject to infinite expansibility. It explains why your software-based products tend to have an endless number of updates – Windows 8, 9, 10, 11, and so on. Also, software-based content such as eBooks or videos can be continuously edited, updated, and distributed at will over the internet. Compare that to a physical book or print media, which, once printed, is hard to edit without enormous costs. Physical products lack such extreme modifiability. Plus, they also suffer from the tyranny of distance – i.e., they need to be stored and shipped, and that takes time and added costs. Compared to software-based offerings, the result is limited flexibility regarding how new venture creation can unfold and how business models can be innovated.

Moreover, digitized goods are also decomposable and re-combinable. This is a product of the extreme modularity and granularity of the technology and its standardized protocols. Extreme modularity and standardization allow software-based components to be broken down into the tiniest possible bits and then re-combined later to form a finished product. This decomposability and re-combinability allow multiple participating actors to co-create a product concurrently. Furthermore, since decomposed components can be instantly distributed over cyberspace, multiple participating actors can create a software-based product at a time that suits their availability. The result is extreme agility, flexibility, and dynamism in new venture creation, unlike traditional entrepreneurship, based on the creation of physical and tactile offerings. Such instant, location-independent, and geographically dispersed co-creation supported by digital infrastructures (more on this later) enable digital entrepreneurs to concurrently enact new venture creation at velocities not observed in traditional forms of entrepreneurship.

Wait! It gets better. Software-based goods are characterized by non-rivalry. Non-rival goods can be consumed by many people simultaneously without being depleted. When you watch a YouTube or Netflix video, for instance, multiple people watch at the same time, yet the video is not being used up. That’s non-rivalry for you! Moreover, non-rival goods can be reproduced at nearly zero marginal cost. By contrast, physical goods such as a car and even your cup of coffee can only be consumed by a limited number of people at any given time. Non-rival goods may even get better as they are consumed as virality enhances their value. The more people watching that ‘Despacito’ video by Lius Fonsi on YouTube, the more valuable it gets (over 7.7 billion views as of this moment!) – more on network effects later. Similarly, the value of a digital platform improves when consumed. Software-based products never expire or perish like your groceries or medication.

What the non-rivalry of digitized products offers entrepreneurs is extreme flexibility in business model innovation. We are all too familiar with many software-based products being given away for free as part of a business model that captures revenue from advertising and other models. Try giving away too many free copies of your physical products, and you will soon be out of business. Physical products are characterized by rivalry and expensive costs of reproduction, storage, and distribution. Thus, the economics of physical products, unlike software-based products are different, leading to differences in business models and limitations on business model innovation. Furthermore, since software-based products are usually knowledge-intensive, costs tend to tilt in the direction of acquiring or coordinating individuals with relevant software-based knowledge and skills – programmers, graphic designers, digital marketers, and more.

Additionally, software-based products are traceable and interactive. Traceability is the ability to find digitized goods over cyberspace. This is usually done by specialized software-based products such as search engine algorithms. Search engines such as Google and Bing interact with, trace, and locate digital artifacts across the internet. Interactivity allows functions of digital artifacts to be activated without changing their underlying code. These characteristics together, assist in unlocking their value through data-driven operations. Similarly, human users can interact with digitized goods without changing their source code. For instance, when playing a computer game, you interact by dragging and dropping objects and so on. Usually, every interaction leaves a digital trail that can be traced, tracked, and analyzed. Data logs may reveal the journey a digital object takes through cyberspace and how it has been used. Traceability and interactivity are, therefore, the reason digitized products promote data-driven operations, which can unlock more value than the sale of standalone software. This, in turn, translates into flexibility in business model innovation that creates and captures more value. Typically, physical products are hard to trace once distributed. As such, their value creation potential gets limited to a single service and single transaction. Unless we turn them into smart connected products such as IoT devices. So valuable are the characteristics of software-based products that hybrid typologies of digital entrepreneurship increasingly seek to merge software and hardware to create ‘smart’ connected products that unlock greater value. Think about how your smart grid and smart metering help optimize electricity consumption and reduce waste. 

The characteristics of digitized goods and their implications outlined above, challenge our assumptions of new venture creation and performance. Speaking of performance, other metrics relating to network effects become more important at early phases than traditional growth KPIs such as profitability, break-even, and the number of employees. Network effects refer to the idea that the value of a service is enhanced by the number of people consuming it. If you were the only one with a phone, that phone’s value will be greatly diminished. Indeed, network effects drive some 70 per cent of the value of software-based companies. Facebook, for instance, derives much of its value from the over 2.7 billion active monthly users accessing the service. Data-driven value allows advertisers to target potential customers with pinpoint accuracy. The value for advertisers is the reduction in marketing costs and a potential higher return on investment (ROI). Consequently, growth in user base leading to positive network effects is often more of a priority than profitability at early stages, with the software being used as bait to gain traction. Companies such as Amazon and Uber grew their user base unprofitably for several years before turning a profit. Moreover, with disruptive innovations, first-mover advantage and market dominance are critical to ensuring that future profits can be harvested. Indeed, the digital environment promotes winner-take-all market dynamics. Digital marketing skills become critical to driving venture growth through network effects. Therefore, the skills we emphasize in digital entrepreneurship education also need to be carefully considered.

Digital Infrastructures as External Enablers

Now let’s turn to that other important concept in all forms of entrepreneurship called External Enablers. They are the result of changes in the environment that have the capacity to elicit a response from discerning actors. So digital entrepreneurs create and distribute software-based products. But software-based products cannot be created without enabling digital tools and systems. Digital infrastructure is the collective term for several enabling technologies such as the internet, broadband, 5G networks, microprocessors and storage, cloud computing and computing devices, and open technical standards. They are the primary external enablers of digital entrepreneurship. However, they are also external enablers of all typologies of entrepreneurship in the digital age. Today, almost every business is enabled by computers and the internet, but that does not automatically suggest that they are digital ventures. Of particular interest today is the role of cloud computing as a primary infrastructural enabler of current and next-wave digital entrepreneurship. It is one technology change that has truly democratized access to critical computing resources which were previously beyond the reach of under-resourced digital entrepreneurs. There is more to talk about on this subjectbut let’s just leave that for now and move on to discuss hybrid typologies of entrepreneurship.    

Hybrid Typologies of Entrepreneurship in the Digital Age

Yes, those hybrid typologies do blur the lines between pure digital and pure traditional forms of entrepreneurship. Software is indeed eating up the physical world. We identify two main hybrid typologies of entrepreneurship in the digital age – hybrid digital and hybrid traditional. Hybrid digital entrepreneurship combines software-based products with physical artifacts and tactile services to jointly form the core of new venture ideas and market offerings. Your smartwatch, such as Fitbit, Garmin, and similar IoT (Internet of Things) devices, make good examples of new ventures that emerged under this typology. Likewise, we have services such as Deliveroo and Just Eat in the food industry. These ventures are digital platform-based innovations that tightly couple a software-based service with a physical operation of food delivery which jointly forms the core market offerings.

As for hybrid traditional entrepreneurship, there is a subtle distinction in terms of the significant but peripheral development of software-based products, which mainly enhance the core traditional offering. For example, the traditional bank has leveraged software-based products such as a banking app and platform to deliver operational efficiencies for itself and its customers in a significant way. Similarly, a conventional technology such as a car has today been enhanced significantly by software-based services such as Android Auto and Apple Car Play, as well as AI-powered driving assistants. In these examples, the software-based component is significant but remains peripheral – meaning, without it, the essence of the core product remains intact. At the end of the day, your Tesla Model Y or S is still fundamentally a car in spite of its significant software ‘bells and whistles’. But when cars become fully autonomous, will that be hybrid digital or hybrid traditional entrepreneurship? That’s a good one for debate, isn’t it?

Under hybrid traditional and pure traditional forms of entrepreneurship, the main research interests include digital transformation and digital disruption. Such transformation is the result of software-based products ‘eating the world’. Today’s digital new venture ideas are increasingly motivated by the need to develop and apply software-based solutions to existing traditional industries, thereby rendering them efficient. There are all sorts of implications for the economy and society, which opens up new avenues for research. Take Uber as an example – a software-based new venture sets out to render more efficient, the process of hailing a ride, and an entire market system gets upended as a consequence. Even our vocabulary is changing. We no longer ‘grab a cab’, we ‘grab an Uber’. Likewise, we ‘google’, not just search online. Digital entrepreneurship has far-reaching consequences for society, making it paradigm-shifting and therefore research-fertile.

Summary and Conclusion

Through this short blog piece, we hope that we have helped you to begin wrapping your head around the complexities of digital entrepreneurship and, more importantly, to understand how it differs from other typologies of entrepreneurship in the digital age. In sum, digital entrepreneurship is new venture creation based on software-based products and services. However, like all forms of entrepreneurship in the digital age, it is externally enabled by digital infrastructures such as the internet and computing capabilities. By unbundling the role of the different types of digital technologies in entrepreneurship, conceptual fuzziness gives way to further clarity. As such, our framework gives academics and practitioners alike, an accessible approach to the digital entrepreneurship phenomenon.

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Why universities are under threat? What do they need to do if they are to survive? Mark Farrell and John A. Davis argue that universities outside the elite must embrace disruption or succumb to it.

Barely surviving relegation in the previous season and against odds of 5,000 to 1, Leicester City won the English Premier League (EPL), a league that for the last 20 years has been won by only four clubs, (Arsenal, Chelsea, Manchester City and Manchester United – the Ivy League of the world of football).

To put it into perspective, each of the previous winners had paid more for one of their current players than has the Leicester manager for his entire team.

The 2015-2016 season of the EPL has been subject to the most wonderful disruption imaginable. Despite having less financial muscle than the top clubs, Leicester used technology and statistics to discover players ignored by others and, against the prevailing thinking of “possession football”, deployed a lightning-quick counterattacking style, conceding few goals and winning many games 1-0. Their use of technology, the ability to keep costs down and develop a strategy to outwit their opponents has been a lesson for all of us who work in higher education.

But, I hear you say, what can we learn from 22 players kicking a ball around a muddy field? It is that type of thinking that leads to complacency. And you only have to ask the likes of the top four clubs in the EPL to know where complacency leads to – comfort, followed by deep discomfort.

In short, it is time to get comfortable being perpetually uncomfortable. The known, mostly predictable rhythms associated with universities of the past 100 years have given way to syncopation caused by two off-beat troublemakers: technological change and cost pressure.

Taken individually, these twin dynamos of disruption are not unfamiliar. Indeed, both have been found residing side-by-side with the business world, upsetting the status quo, frustrating otherwise well-intentioned people and forcing less nimble competitors out of existence or into extreme makeovers just to survive.

We have seen such cycles of disruption in industry before, from the invention of the horseless carriage to the veritable dissolution of the newspaper industry. Transitions like these rarely occur easily and many unprepared organisations have quickly found themselves in the dustbin of history. For the glass–is-half-empty crowd, such change is fraught with danger, pain and loss. But for the glass-is-half-full believers, the changes represent opportunity and the chance to revive and revitalise one’s future.

The challenge lies not in deciding which half of the glass represents your perspective but in how you plan to thrive in this decidedly uncomfortable new world.

This dilemma today confronts universities around the world, especially those we describe as “non-elite”. We are quite familiar with the “elite”: from Duke, Stanford, Oxford, Cambridge, MIT, the Ivy League, to the University of Tokyo and more, the names are familiar to all. These universities have attained an extraordinary level of prestige, with international reputations for excellence in multiple domains. Their qualifications confer prestige on individuals and are perfect examples of positional goods.

In a survey in the US, respondents ranked Princeton in the top 10 law schools in the country. This is a remarkable achievement given that the law school in Princeton began in 1846, graduated seven students and ceased operating in 1855. Despite its short-lived status, in the minds of respondents “Princeton Law” was a top 10 institution.

Non-elite institutions may be perfectly competent and known in their local markets but they increasingly struggle for relevance and visibility in a global higher education world where over 17,000 universities are competing for the best talent (students, faculty, staff, partners). With technological change bringing new content delivery platforms and, along with them, radical new cost models (ie free), the need for non-elite institutions to redefine who they are, what they do and how they do it is essential if they are to survive, let alone thrive, against the superior funding and resources of elite institutions and the elegant simplicity of technologies offering free content.

In effect, technological changes and cost pressures mean universities must do more than just deliver content. They must take clear advantage of the contexts in which they operate to have a differentiated position that resonates with target stakeholder audiences.

If you are reading this article in the faculty lounge in an elite research university then you may well be quite comfortable with the discomfort wrought by technological change and cost pressures. After all, your institution has weathered the storms of change for decades if not centuries. Elite institutions are in a unique position of marketing a product with relatively inelastic demand. College tuitions and fees rise every year, typically faster than inflation. US universities, for example, have experienced tuition increases outpacing inflation for decades, yet demand remains stronger than ever.

According to US News & World Report, Stanford University had the lowest acceptance rate in the US in autumn 2013 at 5.7%, and the first 10 schools on the list had acceptance rates under 9%, with acceptance rates for the top 25 institutions under 15%, including seven of the eight Ivy League universities.

Of course, most institutions are not among the elite nor even recognised beyond local markets. The main ranking bodies review only the top 500 institutions yet we suspect non elite institutions operate in highly competitive markets and compete for many of the same talented students as the better known schools.

While we do not believe that all of these universities are under threat, we do believe that a good number of them will struggle to survive unless they develop a value proposition that not only resonates with their stakeholders (students, faculty, employers, the professions, government) but also clearly articulates what makes them different and why that distinction is relevant to the market.

Even with a clear value proposition, departments within universities may not all be protected, despite the valiant efforts of the faculty within to maintain viability, forcing some to close down entirely or merge with others. For the least prepared institutions in extreme situations merger or even demise may be their only options.

Clayton Christensen’s work in innovation and growth provides useful insights about the challenges posed by organisations that fail to innovate and the opportunities for those that do.

In 2002, Christensen and colleagues contended that disruptive innovation represented a growing threat to education in the US. More than 500 institutions had closed down in the previous decade and more than 2,000 corporate universities and online/distance learning institutions had grown rapidly. Disruptive innovation appeared to be a key driver of these changes.

Christensen argues that disruptive innovation explains why corporate training constitutes a disruptive threat to traditional approaches to business education. Why? Simply put, corporate training offers a more accessible, often uncomplicated and tailored product well suited to problem solving at work at a price that compares favourably with the high cost of a top-tier MBA programme.

In addition, Christensen cites the University of Phoenix (enrolment 200,000-plus) as another example of an education disruptor because it targets non-traditional education consumers and emphasises a student-centric philosophy through its online course offerings designed for the busy lives of adult learners.

Technological advances have impacted businesses and industries around the world so we should not be surprised that higher education is also being affected. Companies everywhere are using new technologies to contain costs by streamlining back office operations and supply chain activities and universities are facing their own cost pressures for which these technologies offer practical solutions.

Beyond operations, new technologies are impacting one of higher education’s most hallowed traditions: knowledge dissemination.

The advent of MOOCs (massive open online courses) have made course knowledge accessible to anyone with a computer, tablet or mobile device far less expensively, or even for free, and dramatically increasing the reach to hundreds of thousands of students for the most popular MOOCs.

Coursera, a leading MOOC (along with edX and Udacity) has more than 10 million users. The early media buzz for MOOCs in 2012 mirrored the excitement that ushered in the dot.com era in the late 1990s, with many reports suggesting that traditional bricks and mortar universities would go out of business. As we now know, traditional retailers did not disappear and, indeed, are thriving while online retail has also thrived.

By the same token MOOCs have not replaced universities. Instead, they may well be serving a more complementary function, even inspiring faculty to deliver content in innovative ways.

Adaptive learning platforms are yet another example. Offering students a range of new media and related instructional tools designed to adapt to their learning needs, including dynamic e-books, video tutorials, animated case studies, games and simulations, adaptive learning technologies are a potentially powerful complement to existing in-class instruction. The software identifies a student’s knowledge weaknesses, redirecting them to the content requiring additional study. Periodic assessments can be designed to measure progress at intervention points designated by faculty. Data captured by the system helps it adjust to each student’s unique learning needs.

However, even with the potential represented by new technologies to enhance and complement higher-education delivery and student learning, legacy structures within most universities will increasingly hinder their ability to successfully adapt and, thereby, avoid being disrupted.

For example, academic promotion, tenure and salary increases are primarily dependent on research productivity and quality. While teaching is an expected responsibility, it is a far less influential factor in tenure decisions. The challenges are clear: there are not enough incentives for faculty to practise innovative teaching approaches since rewards are skewed toward research productivity. And many academics perceive teaching as a distraction from their research initiatives, reinforcing the view that the emphasis on research productivity negatively incentivises academics to only satisfy the minimum requirements in their teaching.

Despite the research emphasis of most universities, actual research productivity and quality is not evenly distributed among academic staff. According to one study, research output per academic was a median of three journal papers over a five-year period. Another study of 18 economics departments in Australia revealed that the average economist published less than one refereed journal paper every two years, and 25% had no publications over a five-year period.

Yet another research productivity study of 22,271 economists from 600 European institutions in 18 countries revealed the following: a) economists published 2.7 articles each between 1971 and 2000 on average (journal quality was not factored into this figure); b) even more interestingly, nearly two-thirds (60%) of the sample published nothing. When research outputs were divided by length of career, the top 1% of leading producing economists published an average of two papers per year and, across the entire sample, the average economist published one paper every five years.

Based on these findings, the evidence suggests that even with a promotion and tenure model structured to reward research activities, universities are not always getting the proverbial bang for their buck.

Examining academic salaries leads one to wonder how long institutions can continue to invest in research using the current model when the returns are uneven at best.

In the US full-time academic salaries range widely, from $99,000 at private non-profit doctoral institutions, to $85,400 at private non-profit institutions, to $73,900 at public institutions, and $45,700 at private for-profit institutions.

As one study showed, the ROI expectations are further complicated because a faculty’s research-centric orientation was inversely related to their student-centric orientation, which was also negatively related to salary compensation.

More simply, being a productive research scholar was counterproductive for teaching excellence. As the studies show, faculty that emphasised teaching excellence were more likely to have lower salaries, reinforcing a dilemma many universities face as they confront a future in which they must increasingly justify how they will survive, let alone thrive, alongside better-funded,better-known elite institutions.

At the risk of sounding heretical, bold thinking is in short supply at many, if not most, universities. Rather than chart a new direction and work towards conceiving ways to innovate their education model (a variation of the old maxim “necessity is the mother of invention”), most universities and their leadership continue to imitate the legacy standard represented by the top-tier institutions even though the deck is stacked decidedly against them.

In one sense this is understandable since most university leaders are products of the system in which they gained their expertise. Few are therefore brave enough to be disrupters or have the perspective born of pushing boundaries working in other organisational contexts. One can almost hear them collectively rationalising “imitation is flattery (cost effective), and innovation is foolhardy (expensive)”.

But we wonder if the real cost comes from a misguided belief that maintaining the status quo, or making tiny incremental changes, will allow non-elite institutions to survive. Most universities as we know them today continue to operate a very costly business model, saddled with brick and mortar facilities requiring constant upkeep (and, in the case of the US, a plethora of collegiate sports-related investments), a proliferation of expensive graduate programmes and an expensive reward/incentive model that disproportionately favours research productivity over teaching excellence yet too often with underwhelming results in both areas.

We believe universities must address these challenges head-on. The vast majority of students will not study at the world’s elite institutions, enrolling instead in programmes that offer a compelling education and prepare them for life post-graduation.

With the rapid advances in technology providing affordable access to higher education almost anywhere in the world along with the promise of lower costs, we believe the time is ripe for university leadership everywhere to disavow imitation and instead exhibit bold thinking designed to unleash the tremendous intellectual capital that is otherwise constrained by a static education model designed for a bygone era.

It was the American baseball player Yogi Berra who famously said “The future ain’t what it used to be”. Higher-education institutions are facing a perfect storm in the shape of reduced government funding, stiffer competition from non-traditional providers, industry demanding higher-quality graduates and students behaving as consumers, demanding returns on their human and financial capital.

For higher-education institutions we suspect that the future will be very different depending upon their reputation, brand image and prestige factor. When we add to this the ability to actually deliver the “transformational experience” promised on the website, not to mention graduates with knowledge and skills to compete in a technology driven, global economy, we suspect many universities are going to end up being outmanoeuvred by the Ubers of the educational world or displaced by their prestigious counterparts.

Choosing where, what and how to study is becoming more important in relation to a return on investment. According to The Times newspaper in the UK; “students appear to be attracted to those [institutions] with a strong academic reputation or high quality vocational courses with good links to employers”.

Like the taxi industry that is being turned upside down by Uber or the EPL being disrupted by Leicester, non-prestigious institutions that do not harness the power of technology, do not reduce their high cost base and do not recognise that the needs of students can be met with a variety of innovative delivery models will become extinct.

Those institutions that bravely embrace this imperative, place students at the centre of learning and pursue imaginative new initiatives will find themselves thriving, even with continued cost pressures and technological advances. And if you don’t believe us, ask Leicester fans.

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