Consortia as a Driver of Innovation (2016)

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.

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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.

Higher Education is Not a Newspaper, Except When It Is (2014)

It has often been suggested that higher education is undergoing the changes we've seen unfold in other sectors - notably music recording and journalism. The Internet will do to us what it did to them. Apparently, we won’t like it.

"Look at the music industry. It's been completely overturned by the Internet. My vision of the world is that everywhere will be like the music industry, but we've only seen it in a few places so far. Journalism is in the midst of the battle. And higher education is probably next." Tyler Cowen

The nature of these changes is described using one or both of these related concepts: disintermediation and unbundling.

Photo by  Flipboard  on  Unsplash

Photo by Flipboard on Unsplash

Disintermediation: The Internet makes it easier for people to bypass certain types of gatekeepers and mediating organizations to get products and services directly from the source. (Investing directly in the securities market, rather than through a bank, is a well-known example.) What constitutes the “source” differs by sector, but in most cases disintermediation tends to increase the intensity of competition between providers, improve choice for consumers, and drive down prices. In higher education, the vision is that students will be able to find learning experiences beyond what's available from accredited institutions.

Unbundling: The concept of unbundling is applied in very different ways, depending on the industry. For education, I think the most relevant variety of unbundling is that which involves marketing goods and services separately, rather than as part of a package. A music album, for example, is a bundle of songs; iTunes makes it easy to unbundle albums. A university degree, similarly, can be understood as a bundle of courses. Making it possible for students to enrol in a single course is a form of unbundling. This is a long-standing practice of continuing / extension education units in North American colleges and universities.

The value of this sort of unbundling increases greatly when the education provider (or employer - but that’s a topic for another time) apply some sort of formal validation for the student’s successful completion of that one course (enter “digital badges”) or these discrete courses can be combined with credentials earned in other settings, such as through volunteer work or, of course, both.

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There's no question that higher education is subject to these forces: more learning will occur outside of accredited institutions (disintermediation) and more institutions will make it easier for learners to pick and choose courses from multiple colleges (unbundling). But in their zeal to shake us from our complacency, writers that use these comparisons to the music and newspaper industries often understate important differences between higher education and these other, information-intensive industries.

"Substitute goods are two goods that could be used for the same purpose"

The key difference that warrants more attention is in the degree to which "substitute goods" are available. Consumers of music and journalism are relatively free to select new providers and to use them in new ways without the value of the goods declining appreciably.

Music recording industry (global) has seen its revenue flatline from 38 billion in 1999 to 16.5 billion in 2013. Music fans are purchasing single songs, rather than albums, p2p remains a factor, new platforms allow people to listen songs without paying (e.g. 8track.com), and while revenue from streaming services (e.g. Spotify) is increasing quickly, its yet to make a sufficient dent in earnings.

Consumers of news have access to a wider range of sources, many of which are free - some of them by professionals, most new sources are simply other news consumers, passing on information via social media.

When consumers seek out and consume news or music from new types of providers or use them in new ways, there's no penalty or disadvantage. New distribution models for music offer far greater value.

Not so in higher education and the difference, of course, is accreditation - the ability of the provider to offer recognized credit courses and bestow degrees and diplomas. In higher education, accreditation remains a key source of value. A student needs assurance that the education in which they invest their time and money will be widely recognized by other institutions and, in particular, future employers. In an increasingly mobile and mass society, the universality of credits earned becomes only more important. Learning is important, but no more than the ability of the degree to function as a signalling device in a world where CVs are read by computers (seeking keywords), and we apply for work at organizations we'd not heard of until we read the "help-wanted" ad. The importance of formal, widely recognized credentials won't fade quickly, and as a result, disintermediation and unbundling will unfold far more slowly in higher education than elsewhere.