The Growing Chasm in the Online Higher Education Market (2014)

A chasm is beginning to appear between institutions of higher education that offer online programmes. The divide is the result of the different strategies taken for designing, sourcing and managing online education programmes.

A small number of institutions in the U.S. have adopted methods for producing and supporting online courses that have the potential, if not the likelihood, to improve learning outcomes, increase the speed with the institution improves the quality of teaching and learning, increase value (quality/cost). If present trends continue, these institutions could reconfigure the deeply embedded hierarchy that organises higher education.

A Couple of Scenarios

An acquaintance of mine, currently an Assistant Professor at a mid-size university, was asked in mid-July by her institution to create and deliver a new online course for the Fall (September) semester. In the time available, she had to define the new curriculum, determine the instructional tactics to be used, collect existing resources, and create new materials, including assessments.

Throughout the process, she worked alone. Although an instructional designer was on-hand, the staff member had little time and offered not much more than a checklist of best practices. The Instructor's budget for the course development? Nil.

Her experience contrasts sharply with practices at a handful US universities. These institutions typically focus, sometimes exclusively, on online education, offer open-admissions, and have centralised management of teaching and learning. Consider this depiction; a composite of a few institutions I've had a chance to investigate:

An academic department - after conducting a thorough, regularly scheduled review of learning outcomes - determines that a full rework of a key programme is required. Starting what will be a twelve-month process, the department conducts a deeper analysis of the current programme, consulting with student support staff, faculty, academic leadership, and industry advisors - to define the overarching set of objectives and instructional strategies for the revamped programme.

A team is assigned to the project, including specialists in learning analytics, subject matter experts, managers of assessment systems, faculty, teaching assistants, student support staff, and technology managers.

The institution's team identifies a number of things they want to offer their students that can be done more efficiently by forming partnerships other universities, consortia, and vendors, so as to complement internal strengths. The course development process ultimately involves more than a dozen people, three external organisations, and costs more than 100k per course, when including internal labour costs. Following the first year of the new programmes' delivery, a review is conducted to identify where refinements are needed.

Consequential Impact

There are a number of issues of note:

All things being equal, this handful of institutions will offer students higher quality education. By bringing the right mix of talent, resources, funds, and processes together, the institution has a much better chance of providing students with a well-conceived, thoughtfully-executed, and well-resourced learning experience.

These institutions have considerably greater ability to scale-up learning to meet demand. They can build new courses anprogrammesms more quickly, and with greater assurance that each will meet institutional standards for quality.

These institutions pay considerably more attention to the results of their instructional strategies. Internal reviews are common, and many are now turning to analytics to generate even more detailed and extensive insights into what's working and what isn't. This knowledge provides the basis for better decision-making, which in-turn can provide progressively better learning experiences for students.

This last quality needs to be emphasised.

Knowledge about how to design and support learning in higher education held by individual faculty - whether online or not - is rarely systematically shared with the institution. Teaching is approached as individual pursuit. Indeed, faculty members can work in the same department as other academics for several years without ever seeing each other teach. Each Instructor operates individually. Strictly speaking, this isn't by design: it's a by-product of the traditional organizational structure of the institution and conventions of the academic occupation. But the effect of this characteristic is that it limits the flow of knowledge across the institution about effective teaching.  It fits nicely the centuries-old conventions of the occupation, it may ultimately limit the breadth and depth of the knowledge that is brought to bear on each course within the institution.

These upstart universities see knowledge about teaching and learning as the domain of the institution. The institution, not the individual educator, captures, interprets and applies knowledge about how best to serve students.  Knowledge is applied on an institutional level, not on a course-by-course, instructor-by-instructor level.

Of course, the downside of this approach is the potential to suppress the kinds of innovations that can arise from radical decentralization - letting a "hundred flowers bloom", if you will.

But supporters of this more centralized approach contend that the benefits of a collective, institutional approach to knowledge building and sharing may be greater at this point in the evolution of online education. Higher quality learning, they argue, requires a more deliberate and disciplined approach. At times, I can appreciate this perspective: conference presentations about "how to teach online" offered in 2014 have striking resemblance to those we heard in 2001. We don't seem to be making significant headway by placing the burden of course design and delivery primarily on the backs of under-resourced individual Instructors.

Consortia as a Driver of Innovation (2016)

In the late 90s -- during the "early years" of online higher education -- many colleges and universities didn't have the internal resources required to build, support and market online education. Some institutions saw fit to join online consortia; by pooling limited resources, each institution gained access to the resources they needed. Many of these early initiatives are still operating.

Access and/or Innovation

In a recent review we conducted of online higher ed consortia, we found that the majority of consortia, and the vast majority of those that started ten or more years ago, are designed primarily to increase access. That is, these initiatives define success by the number of online courses created and/or supported by the consortia and the number of students enrolled in these courses. More courses means more access.

Access is obviously important. However, for a number of reasons, we believe that a recasting of the consortia model would be beneficial. Given the state of online education, the focus needs now to shift from ensuring institutions can launch and support online courses, to stimulating innovation and improving quality.

Time to Focus on Innovation

First, and most obviously, the needs of member institutions have changed and consequently consortia need to change, as well. Over the last decade-and-a-half, most colleges and universities have significantly augmented their internal capacity to develop, support and market online education. The LMS is now near universal. The majority of university leaders see online education as fundamental to institutional strategy, and far more instructors have experience teaching online.

Moving Beyond the Basics

As internal capacity of member institutions increase, the functions that can't be done well (or at all) within each member institution change too. Although this may seem so obvious as to be not worth mentioning, our review suggests otherwise. Many consortia we reviewed continue to provide only the basic requirements of creating and supporting online courses. One consortium, for example, simply assigned a single instructional designer to work with a lone instructor from the member institution to develop an online course. No meaningful quality standards are employed, the instructor isn't even paid for the course development. Fewer and fewer institutions need these basic services. It isn't surprising that our review found that institutions that have set more ambitious goals for online education are less interested in participating in consortia.

Focus on Innovation

Our review suggested that more consortia should focus less on providing basic, increasingly common, services and more on helping institutions test and scale more ambitious online learning strategies that can improve outcomes and drive down costs. If the fundamental value proposition of consortia is that it enables member institutions to do what they can't done alone, then the initiative should be deliberately and systematically focusing on those functions that are anything but "basic". Services that fall into the category of "ambitious" in 2014 might include the development of rich media, the use of learning analytics, and the development of competency-based programs.

Why Consortia

Consortia align particularly well with three trends in online higher education:

  1. A slow migration to the software model of course development, in which upfront costs for course development are relatively high, but maintenance and distribution costs are marginal. By pooling resources, consortia can accommodate higher upfront costs and then coordinate distribution at scale.

  1. Growing use of analytics to inform and personalize learning. The more data is shared and compared across institutions, the greater its value. Again, consortia are well positioned to facilitate the proper movement of data-generated insights across institutions.

  1. Online education will continue to demand new, increasingly complex skills and knowledge that are not readily available within each institution. Consortia can serve as a central, shared source of talent and technology across individual institutions.

Defining ROI

Consortia need to define and then share clearer and more concrete objectives with member institutions. In particular, it would be useful for consortia to provide members with more robust assessments of the initiative's ROI. If success is defined by the consortium (as noted above) by the number of online courses and students that are supported by the consortia, then members should be able to assess whether the cost of running the consortia is greater than the actual increase in enrolment and number of courses. ROI is always difficult in education, but consortia -- given their frequently tenuous financial stability -- may be less inclined to produce this kind of information. Member institutions should demand it.

Built to Change

Lastly, consortia must be built to change. If, as suggested, the basic purpose and value proposition of the consortia is to do what member institutions can't do separately, then the services offered must change as technology, costs, and objectives change. Again, this may seem obvious. But consortia struggle with change like other organizations. Nevertheless, the value proposition of consortia requires that they continually adjust their services to meet changing conditions.

Services offered by consortia to member institutions include the following:

  • Course registration and course registration systems

  • Help desk (technology and/or administrative) for students

  • Professional development for instructors

  • Learning management systems

  • Video conferencing (hardware, software and support)

  • Webinar hosting and management (hardware, software and support)

  • Sharing of online courses between institutions

  • Instructional quality assessment and rubrics

  • Development of new applications

  • Multimedia development (instructional material)

  • Market research services

  • Instructor training on educational technology

  • Instructional design

  • Tutoring services (student online/phone)

  • Learning object repositories

  • Project management/coordination

  • Marketing / clearinghouse of members courses and programs

5 Factors Influencing Design in Digital Education (2013)

When we shift the focus of higher education from the physical classroom to the digital environment, design becomes a much greater factor in creating successful student experiences.

Design, here, refers to graphic and industrial design, where aesthetics and function merge.

In previous posts, I made a number of assertions:

  • There’s a growing recognition that the ‘look and feel’ of products is fundamental to their value.

  • Design is not merely about surface aesthetics. Design involves aligning the needs, sensibilities and behaviors of people with the things they use.

  • The value of screen-based experiences (e.g., laptops, tablets, smartphones) is highly dependent on the quality of design.

  • Design is a powerful tool for making it easier for us to live with technology’s  over-caffeinated rate of change.

  • After centuries of classroom education, design can help us make the transition to digital education easier.

For a variety of reasons, the software and content created for digital higher education has largely ignored the role of design - and it shows.

However, there are five factors at play that may give the field of design a more central role in digital higher education in 2014.

1. Design and learner data

The use of analytics is driven by a growing interest in measuring the efficacy of learning. As the education sector sharpens its focus on results of its investments and strategies, ambitious and innovative institutions are paying more attention to how courses are designed and developed.

Well-designed courses can increase retention and improve learning. They are easier to use, allow students to focus on learning rather than courses logistics, reduce demands on support, and present the right instructional resources at the right time. Intelligently crafted analytics captures these improvements, which leads to greater attention to course design.

2. Design as a competitive differentiator

Pundits have been talking about the highly competitive landscape of online higher education for almost 15 years. Yet, it is only recently that colleges find themselves offering very similar online programs as their competitors, and at similar prices. (For now, this is only acute in certain disciplines, such as business and nursing.)

Real choice leads to real competition. And competition requires differentiation. Design is one of the few tangible ways - beyond price - that institutions can demonstrate the value of their online programs to prospective students. (For more on differentiation and the use of “surrogates of quality,” see Lloyd Armstrong’s excellent post on competitive higher education).

3. Consumer-Education Apps Crossover

Educational technology has historically advanced less quickly than consumer technologies. This is also true in terms of the quality of design. But consumer-industry design is finding its way into education in two ways:

  • Educators now regularly use consumer applications in their courses, such as Twitter, WordPress, and Facebook. For more information on using Twitter in higher ed teaching, check out this article and YouTube video.

  • Edtech vendors are adopting the qualities and characteristics of consumer technologies. An example is Instructure’s Canvas learning management system, which gained favorable reviews for its ease of use, and more broadly, its consumer-style user interface.

4. Big media investing in education

There is growing interest in digital higher education among traditional media companies.  While many in education bristle at this trend, these corporations bring deep experience in packaging and delivering information-related products with high-quality design.  Among them: News Corp. (Amplify), New York Times (The Learning Network), The Washington Post (Kaplan Inc.), Bertelsmann AG (Brandman University), and Condé Nast (Condé Nast College of Fashion and Design).

5. The rise of apps

A 2010 Wired article by Chris Anderson pronounced, “The Web is Dead” making the point that more people are accessing the Internet from applications than browsers. Internet traffic is increasingly managed by applications like Netflix, Facebook, and Xbox. And as more people access the Internet via mobile devices, the trend will continue.

Applications offer a superior user experience. Possibly more so than any other consumer product category, applications compete on the basis of design.  Consider task management apps. These tools compete largely on the quality of the experience they offer; the way they manage and display information. The actual information available through these tools is pretty much the same, but the user experience isn’t. The consumer can quickly and easily switch from one app to another in seconds, without disruption. Good design is the difference between success and failure.

These five factors – for different reasons and in different ways – are elevating the role of design in digital higher education, and specifically, in the course design and development process. Those institutions that find ways to leverage design to improve their digital learning programs will benefit.

Why Design Matters in Digital Higher Education (2013)

Design is having its moment.  Apple’s  Jonathan Ive, Philippe Starck and Michael Graves are among a growing number of designers enjoying rock-star status. Businessweek, Fast Company and other pubs now dedicate entire issues to design. Enrollment in college design programs has spiked.

But what role does - or should - design play in education, specifically digital higher education? A lot, it turns out. As we move from the classroom to the screen, design matters more than ever.

The qualities that create great design are also the qualities needed to create great online learning experiences. 

The relationship of design and higher education is the theme of a series of posts we’re kicking off.  This first post highlights what great design and great educational experiences have in common. The parallels are many.

Next, I’ll explore the forces of competition and change driving the need for design in higher ed. The third installment will review the state of design in higher ed.  I’ll wrap up the series by exploring the parallels between design and learner data.

So, exactly what is design?  There isn’t a single definition; the field is broad and expanding. In the context of this series, think of design more as user experience (UX), than instructional design.

Design in digital higher ed is about how people interact with screens, software, interfaces and information in a holistic, multidisciplinary way.

Similarities between design and education:

  • Great design and great education is user/student-centric.

  • A great designer, like a great educator, takes what is complicated and makes it easy to understand.

  • Well-designed services and systems are elegantly integrated and easy to use; so are the best educational web sites, services and systems.

  • Great design leverages the user's existing knowledge, just as great education builds upon the learner’s prior knowledge.

  • Great design connects users with information and experiences in ways that makes it memorable and "sticky." So does great education.

  • Great design attracts the user by making the experience as compelling as possible. Great education strives to engage learners and increase interaction - a key determinant of learning success.

  • Great design evokes an emotional response, which can alter the user’s cognitive state. Great education can evoke positive emotions that make students more creative and open to new approaches when learning.

  • Great design saves time by focusing the user's attention on the most important information. Great online learning experiences maximize students’ time by focusing their attention on the key learning objectives and outcomes of the course.

  • Great design seeks to transcend passive, one-way communication towards active engagement with the user. Isn’t this the goal of all great educators and institutions?

We know from retention and completion rates that just providing knowledge is not enough. Other sectors and industries have recognized this. Design is a differentiator in the market because it adds real value. It’s a lesson that higher ed is just beginning to learn.

Notes on "Beyond Retrofitting: Innovation in Higher Education" (2013)

Debate about the revolutionary potential of technology in higher education has never been more intense, nor greater in volume. For spectators and participants alike, it’s great fun. Me, I’m just glad people outside of the academy are finally paying attention to higher education.

There are two particularly loud camps in the debate. On the one hand, there are those that believe that technology is revolutionizing higher ed, providing us with better, cheaper, and faster ways of learning. The more extreme wing of this camp believe that this will very soon lead to the toppling or “disruption” of the traditional higher education system. (They can be identified by their almost complete lack of knowledge of how technology is currently used in higher ed or the constraints placed on professionals that work on-the-ground in digital higher ed.) Then there are those that believe that the promise of educational technology is little more than hype, pushed by vendors and edtech evangelists. They contend that the actual improvement in value offered by technology is overblown and ultimately limited. (This camp loves to make reference to the low retention rates in MOOCs.)

A Third View

In a recent essay entitled “Beyond Retrofitting: Innovation in Higher Education”, Andrew Kelly and Frederick Hess offer a useful third perspective. They argue that educational technology indeed has the potential to revolutionize higher education, however, “cheerful claims that American higher education is undergoing an irresistible change driven by digital technology are unduly optimistic.” Use of technology has not significantly altered the value of higher education. This is because our use of technology, to date, amounts to little more than "retrofitting“ - the ”grafting on“ of new technologies to a traditional higher ed system that is fundamentally largely incapable of leveraging the revolutionary potential of technology. Traditional higher education + technology does not = a revolution. Consequently, the current reform efforts in higher education constitute simply a ”doubling down“ on the traditional model - an attempt to stretch the capacity of the system to do more - rather than ”real innovation."

Real innovation, in contrast, requires fundamental changes to the institution - new business models, essentially. However, it is notoriously difficult for established and successful institutions to recreate themselves and employ new business models (and there are few more established or successful institutions than Western higher education). It’s for this reason that innovation tends to come from new organizations, not from incumbents.

The solution according to Hess and Kelly is to ensure that new organizations can participate in our higher education system. We need to redesign the higher education system to allow these new organizations to influence, inform and, yes, disrupt the traditional model.

Hess and Kelly’s work draws heavily on Christensen’s theory of disruptive innovation. This brilliant, but regularly misused theory, describes how “disruptive innovations” typically emerge from new, rather than established organizations, by leveraging technologies in better ways through new business models. At first these new solutions are ignored and often restricted to niche markets (e.g. online education in the 1990s). In time, though, the value of the new approach increases, and ultimately challenges more established providers who - given their commitment to widely accepted notions of excellence and best practices, can muster only “sustaining innovations.”

This recurring process of new solutions replacing older ones is happening at an ever increasing clip (c.f. Blue Ocean Strategy for more on this). But change in higher education is unfolding far slower. Hess and Kelly believe policy is the means by which we can stimulate faster change. They propose four changes:

  1. Focus on outcomes rather than the act of delivery.

  2. Openness to new providers.

  3. Unbundling (Enable institutions to draw on a range of service providers in order to facilitate better quality, lower costs.)

  4. Portability (Allow students to learn from a variety of providers and to have this learning validated. e.g. badges as certificates.)

The Role of Policy as a Driver of Innovation

Some will likely see Hess and Kelly’s argument solely as support for a more market-style higher education system. That wouldn’t be wrong. And the fact that the essay comes by way of a conservative think-tank won't make its' reception in higher ed more welcoming. But I think if we focus exclusively on the market-friendly nature of this work, we may miss the more important contribution - the call for greater attention to policy as a tool for driving positive change in higher education. In a similar vein, I’ve written previously about the importance of business models. Like policy, business models provide the overarching framework in which we work; they structure the possibilities. While a good deal of discussion in digital higher education focusses on instructional practices and technology, to a considerable extent, these are determined  by broader, structural conditions - such as policy. Put another way, the right policy (or business model) makes it possible for great educators to use the best instructional strategies and technologies to help students learn.

Disruptive AND Sustaining Innovation

Although the focus on policy is useful, I think the essay - like many before it - may over-simplify innovation. The authors position disruptive innovation as the end-game, our single objective; other less revolutionary types of innovations (sustaining, incremental) seem to be of little consequence. Although I am as impatient as the next educator to see dramatic improvements in higher education (I think my colleagues will vouch for me on this matter), I think it’s important that we don’t let our desire for big wins cloud our judgement. The distinction between disruptive and sustaining innovations is almost always less clear than theory suggests. Sustaining and disruptive innovations don’t operate in separate realms, untouched by each other. They interact constantly and feed off of each other. Forensic analyses of any disruptive innovation will show that sustaining innovations made it possible. Yes, disruptive innovations are exciting and satisfy our desire for quick changes, but they are one part of a large set of innovations required to improve the value of higher education for our students, faculty and other stakeholders.

Faith in Algorithms (2018)

Tech is powerful, but only when applied with in-depth knowledge of the sector in which it’s used.

Two-sided markets

Two-sided markets are platforms that bring together two parties - buyers and sellers - to help them meet their respective needs efficiently. eBay is a now classic example: designed to bring together people who want to sell item with those that may wish to buy them.

Though rarely discussed, two-sided markets are far more valuable (and ultimately successful) when the needs of both parties can be clearly defined, which isn’t the case in many contexts. Airbnb works well because the needs of the buyer (those seeking accommodations) can be defined through a set of straightforward questions. How many bedrooms are needed? Within what price range? Which neighbourhood? The sellers on Airbnb (those with property to rent) are able to define the accommodations with equal clarity.

two_sided_marketplace.001.jpg

Education and Labour: lack of precision

The needs of buyers and sellers cannot always be as easily defined, though, such as in the sphere of education and employment. The implications of this lack of clarity are considerable.

A fast-growing start-up in Canada has generated a great deal of attention by applying the two-sided market model to the field of recruitment. Like many other start-ups, the company’s product seeks to bring together graduates seeking employment (sellers) and employers seeking graduates (buyers). They hope to displace student job fairs, which have played the same role.

The platform captures the relevant student information - the program of study, work experience, and other relevant information. Employers, likewise, share job requirements. Algorithms are then applied to match the two parties.

The quality of the matches made within the platform is wholly dependent on the quality and breadth of the information provided by the buyer and seller. Without good input, the output will be flawed. However, students, first of all, don’t have access to the kinds of detailed information they need. Transcripts from alma mater and college-age work experience provide little insight into the individual’s actual skills and knowledge - and even less for soft skills and general sensibilities - such as the kinds of work environments in which they are most comfortable, productive or both.

The information needed by employers is no better. The typical job description tells us very little about who will succeed in the role. They’re designed primarily to describe a baseline of skills and experience which most HR professionals admit doesn’t align with the make-up of those who have succeeded in the role in the past. Moreover, if we add the variable of generational differences - that are particularly acute at this point in history - we frequently see job applicants with higher levels of education than the hiring manager.

The point here is that some types of information can not be easily matched through algorithms; certain aspects of education and employment included.

Measuring Immeasurables

That said, the inability to produce excellent job matches - which is fundamental to this business - may not stand in the way of the venture’s success. This is because the very same factors that make aligning graduates with ideal jobs so difficult, also makes it very hard to evaluate the quality of the matches. Hiring managers may not find that the actual job applicants generated by this platform any more or less accurate than other methods used to identify ideal job candidates. It’s possible - though difficult to measure - that the belief in the power of algorithms (or more generally, the “magic” of technology) may be what determines how happy hiring managers are with the platform. If they think the technology is capable of making these matches accurately, then they may interpret it positively.

It’s important to remember that hiring managers don’t hire employees frequently. Hiring managers responsible for a typical department in a mid-sized corporation, for example, may not hire staff more than once per year - and not for the same position. So, there’s not a great deal of feedback coming to them that, over time, helps them develop a precise sense of whether the most recent crop of job applicants are any more suitable than the last time they sought to find someone for the same position. If it does seem different, they’re as likely to chalk this up to luck or changes in the quality of applicants available or some other factor. In the end, due to the need to fill a position, they’ll choose the best of those that came by whatever process they’ve used, whether driven by algorithms or recommendations by a friend.

Technically, it’s possible for this platform or others like it to add extensive testing services that help define the graduate's skills and translate it into employer job specifications. Many companies offer these kinds of tools. I can’t speak to the value of their value, but it is clear that employers are looking to improve their accuracy when making new hires. If this service is found to be reliable, it will increasingly overlap with what has traditionally been the domain of colleges and universities: the evaluation and reporting of the workforce. It’s a space worth watching.

The needs of buyers and sellers cannot always be as easily defined, particularly in the area of education and employment.

A fast-growing, high-profile start-up in Canada has generated a great deal of attention by applying the two-sided market model to the field of recruitment. They bring together graduates seeking employment (sellers) and employers seeking graduate (buyers). The company aims to displace the traditional student job fairs, in which a limited number of employers visit campuses to conduct preliminary evaluations of graduates.

The platform captures the relevant student information - the program of study, work experience, and other relevant information. Employers, likewise, share job requirements. Algorithms are then applied to match the two parties.

The quality of the matches made within the platform is wholly dependent on the quality and breadth of the information provided by the buyer and seller. Without good input, the output will be flawed. However, students, first of all, don’t have access to the kinds of detailed information they need. Transcripts from alma mater and college-age work experience provide little insight into the individual’s actual skills and knowledge - and even less for soft skills and general sensibilities - such as the kinds of work environments in which they are most comfortable, productive or both.

The information needed by employers is no better. The typical job description tells us very little about who will succeed in the role. They’re designed primarily to describe a baseline of skills and experience which most HR professionals admit doesn’t align with the make-up of those who have succeeded in the role in the past. Moreover, if we add the variable of generational differences - that are particularly acute at this point in history - we frequently see job applicants with higher levels of education than the hiring manager.

The point here is that some types of information can not be easily matched through algorithms; certain aspects of education and employment included.

measuring Immeasurables

That said, the inability to produce excellent job matches - which is fundamental to this business - may not stand in the way of the venture’s success. This is because the very same factors that make aligning graduates with ideal jobs so difficult, also makes it very hard to evaluate the quality of the matches. Hiring managers may not find that the actual job applicants generated by this platform any more or less accurate than other methods used to identify ideal job candidates. It’s possible - though difficult to measure - that the belief in the power of algorithms (or more generally, the “magic” of technology) may be what determines how happy hiring managers are with the platform. If they think the technology is capable of making these matches accurately, then they may interpret it positively.

It’s important to remember that hiring managers don’t hire employees frequently. Hiring managers responsible for a typical department in a mid-sized corporation, for example, may not hire staff more than once per year - and not for the same position. So, there’s not a great deal of feedback coming to them that, over time, helps them develop a precise sense of whether the most recent crop of job applicants are any more suitable than the last time they sought to find someone for the same position. If it does seem different, they’re as likely to chalk this up to luck or changes in the quality of applicants available or some other factor. In the end, due to the need to fill a position, they’ll choose the best of those that came by whatever process they’ve used, whether driven by algorithms or recommendations by a friend.

Technically, it’s possible for this platform or others like it to add extensive testing services that help define the graduate's skills and translate it into employer job specifications. Many companies offer these kinds of tools. I can’t speak to the value of their value, but it is clear that employers are looking to improve their accuracy when making new hires. If this service is found to be reliable, it will increasingly overlap with what has traditionally been the domain of colleges and universities: the evaluation and reporting of the workforce. It’s a space worth watching.

The needs of buyers and sellers cannot always be as easily defined, particularly in the area of education and employment.

A fast-growing, high-profile start-up in Canada has generated a great deal of attention by applying the two-sided market model to the field of recruitment. They bring together graduates seeking employment (sellers) and employers seeking graduate (buyers). The company aims to displace the traditional student job fairs, in which a limited number of employers visit campuses to conduct preliminary evaluations of graduates.

The platform captures the relevant student information - the program of study, work experience, and other relevant information. Employers, likewise, share job requirements. Algorithms are then applied to match the two parties.

The quality of the matches made within the platform is wholly dependent on the quality and breadth of the information provided by the buyer and seller. Without good input, the output will be flawed. However, students, first of all, don’t have access to the kinds of detailed information they need. Transcripts from alma mater and college-age work experience provide little insight into the individual’s actual skills and knowledge - and even less for soft skills and general sensibilities - such as the kinds of work environments in which they are most comfortable, productive or both.

The information needed by employers is no better. The typical job description tells us very little about who will succeed in the role. They’re designed primarily to describe a baseline of skills and experience which most HR professionals admit doesn’t align with the make-up of those who have succeeded in the role in the past. Moreover, if we add the variable of generational differences - that are particularly acute at this point in history - we frequently see job applicants with higher levels of education than the hiring manager.

The point here is that some types of information can not be easily matched through algorithms; certain aspects of education and employment included.

Measuring Immeasurables

That said, the inability to produce excellent job matches - which is fundamental to this business - may not stand in the way of the venture’s success. This is because the very same factors that make aligning graduates with ideal jobs so difficult, also makes it very hard to evaluate the quality of the matches. Hiring managers may not find that the actual job applicants generated by this platform any more or less accurate than other methods used to identify ideal job candidates. It’s possible - though difficult to measure - that the belief in the power of algorithms (or more generally, the “magic” of technology) may be what determines how happy hiring managers are with the platform. If they think the technology is capable of making these matches accurately, then they may interpret it positively.

It’s important to remember that hiring managers don’t hire employees frequently. Hiring managers responsible for a typical department in a mid-sized corporation, for example, may not hire staff more than once per year - and not for the same position. So, there’s not a great deal of feedback coming to them that, over time, helps them develop a precise sense of whether the most recent crop of job applicants are any more suitable than the last time they sought to find someone for the same position. If it does seem different, they’re as likely to chalk this up to luck or changes in the quality of applicants available or some other factor. In the end, due to the need to fill a position, they’ll choose the best of those that came by whatever process they’ve used, whether driven by algorithms or recommendations by a friend.

Technically, it’s possible for this platform or others like it to add extensive testing services that help define the graduate's skills and translate it into employer job specifications. Many companies offer these kinds of tools. I can’t speak to the value of their value, but it is clear that employers are looking to improve their accuracy when making new hires. If this service is found to be reliable, it will increasingly overlap with what has traditionally been the domain of colleges and universities: the evaluation and reporting of the workforce. It’s a space worth watching.