HESA

Higher Education Strategy Associates

Category Archives: Innovation

December 08

Innovation Ecosystems: Promise and Opportunism

We sometimes think of innovation policy as being about generating better ideas through things like sponsored research.  And that’s certainly one part of it.  But if those ideas are generated in a vacuum, they go nowhere – making ideas spread faster is the second pillar of innovation policy (a third pillar – to the extent that innovation is about new product-generation – has to do with venture capital and regulatory environments, but we’ll leave those aside for now).

Yesterday, I discussed why the key to speeding up innovation was the density of the medium through which new ideas travel: basically, ideas about IT travel faster in Waterloo than in Tuktoyaktuk; ideas about marine biology travel faster in Halifax than in Prince Albert.  And the faster ideas travel and collide (or “have sex” in Matt Ridley’s phrase), the more innovation is produced, ceteris paribus.

Now, although they don’t quite use this terminology, the proponents of big universities and big cities alike find this logic pretty congenial.  You want density of knowledge industries?  Toronto/Montreal/Vancouver have that.  You want density of superstar researchers?  U of T, McGill, and UBC have that (especially if you throw in allied medical institutes).  That makes these places the natural spot to invest money for innovation, say the usual suspects.  All you need to do is invest in “urban innovation ecosystems” (whatever those are – I get the impression it’s largely a real estate play to bring scientists, entrepreneurs, and VCs into closer spatial proximity), and voila!  Innovation!

This is where sensible people need to get off the bus.

It’s absolutely true that innovation requires a certain ecosystem of researchers, and entrepreneurs, and money.  And on average productive ecosystems are likelier to occur in larger cities, and around more research-intensive universities.  But it’s not a slam dunk.  Silicon Valley was essentially an exurb of San Francisco when it started its journey to being a tech hub.  This is super-inconvenient to the “cool downtowns” argument by the Richard Floridas of this world; as Joel Kotkin has repeatedly pointed out, innovative companies and hubs are as likely (or likelier) to be located in the ‘burbs, as they are in funky urban spaces, mainly because it’s usually cheaper to live and rent space there.  Heck, Canada’s Silicon Valley was born in the heart of Ontario Mennonite country.

We actually don’t have a particularly good theory of how innovation clusters start or improve.  Richard Florida, for instance, waxes eloquent about trendy co-working spaces in Miami as a reason for its sudden emergence as a tech hub. American observers tend to attribute success to the state’s low tax rate, and presumably there are a host of other possible catalysts.  Who’s right?  Dunno.  But I’m willing to bet it’s not Florida.

We have plenty of examples of smaller communities hitting tech take-off without having a lot of creative amenities or “urban innovation strategies”. Somehow, despite the lack of population density, some small communities manage to get their ideas out in the world in ways that gets smart investors’ attention.  No one has a freaking clue how this happens: research on “why some cities grow faster than others” is methodologically no more evolved than research on “why some universities become more research intensive than others”, which is to say it’s all pretty suspect.  Equally, some big cities never get particularly good at innovation (Montreal, for instance, is living proof that cheap rent, lots of universities, and bountiful cultural amenities aren’t a guarantee of start-up/innovation success).

Moreover, the nature of the ecosystem is likely to differ somewhat in different fields of endeavor.  The kinds of relationships required to make IT projects work is quite different from the kinds that are required to make (for example) biotech work.  The former is quick and transactional, the latter requires considerably more patience, and hence is probably less apt to depend on chance meetings over triple espressos in a shared-work-environment incubator.  Raleigh-Durham and Geneva are both major biotech hubs that are neither large nor particularly hip (nor, in Raleigh’s case, particularly dense).

It’s good that governments are getting beyond the idea that one-dimensional policy instruments like “more money in granting councils” or “tax credits” are each unlikely on their own to kickstart innovation.  It’s good that we are starting to think in terms of complex inter-relations between actors (some, but not all of which involve spatial proximity), and using “ecosystem” metaphors.  Complexity is important. Complexity matters.

But to jump from “we need to think in terms of ecosystems” to “an innovation agenda is a cities agenda” is simply policy opportunism.   The real solutions are more complex. We can and should be smarter than this.

December 07

H > A > H

I am a big fan of the economist Paul Romer, who is most famous for putting knowledge and the generation thereof at the centre of  discussions on growth.  Recently, on (roughly) the 25th anniversary of the publication of his paper on Endogeneous Technological Change, he wrote a series of blog posts looking back on some of the issues related to this theory.  The most interesting of these was one called “Human Capital and Knowledge”.

The post is long-ish, and I recommend you read it all, but the upshot is this: human capital (H) is something stored within our neurons, which is perfectly excludable.  Knowledge (A) – that is, human capital codifed in some way, such as writing – is nonexcludable.  And people can use knowledge to generate more human capital (once I read a book or watch a video about how to use SQL, I too can use SQL).  In Romer’s words:

Speech. Printing. Digital communications. There is a lot of human history tied up in our successful efforts at scaling up the H -> A -> H round trip.

And this is absolutely right.  The way we turn a patterns of thought in one person’s head into thoughts in many people’s heads is the single most important question in growth and innovation, which in turn is the single most important question in human development.  It’s the whole ballgame.

It also happens to be what higher education is about.  The teaching function of universities is partially about getting certain facts to go H > A > H (that is, subject matter mastery), and partially about getting certain modes of thought to go H > A > H (that is, ways of pattern-seeking, sense-making, meta-cognition, call it what you will). The entire fight about MOOCs, for instance, is a question of whether they are a more efficient method of making H > A > H happen than traditional lectures (to which I think the emerging answer is they are competitive if the H you are talking about is “fact-based”, and not so much if you are looking at the meta-cognitive stuff.  But generally, “getting better” at H > A > H in this way is about getting more efficient at the transfer of knowledge and skills, which means we can do more of it for the same price, which means that economy-wide we will have a more educated and productive society.

But with a slight amendment it’s also about the research function of universities.  Imagine now that we are not talking H > A > H, but rather H > A > H1.  That is, I have a certain thought pattern, I put it into symbols of some sort (words, equations, musical notation, whatever) and when it is absorbed by others, it generates new ideas (H1). This is a little bit different than what we were talking about before.  The first is about whether we can pass information or modes of thought quickly and efficiently; this one is about whether we can generate new ideas faster.

I find it helpful to think of new ideas as waves: they emanate outwards from the source and lose in intensity as they move further from the source.  But the speed of a wave is not constant: it depends on the density of the medium through which the ideas move (sound travels faster through solids than water, and faster through water than air, for instance).

And this is the central truth of innovation policy: for H > A > H1 to work, there has to be a certain density of receptor capacity for the initial “A”.  A welder who makes a big leap forward in marine welding will see his or her ideas spread more quickly if she is in Saint John or Esquimault than if she is in Regina.  To borrow Matt Ridley’s metaphor of innovation being about “ideas having sex”, ideas will multiply more if they have more potential mates.

This is how tech clusters work: they create denser mediums through which idea-waves can pass; hence, they speed up the propagation of new ideas, and hence, under the right circumstances, they speed up the propagation of new products as well.

This has major consequences for innovation policy and the funding of research in universities.  I’ll explain that tomorrow.

October 07

Party Platform Analysis: Science and Innovation

In the platform analyses I’ve done so far (for the Greens, the Conservatives, the NDP, and the Liberals), I’ve focused mostly on the stuff around student finance.  But in doing so, I’ve left out certain platform elements on science and innovation, specifically from the Liberals and the New Democrats.

There are some pretty broad similarities between the two parties’ programs, even though they package them somewhat differently.  Both are long on promises about process.  The Liberals will appoint a Chief Science Officer; the NDP will go one better, and appoint an Office of the Parliamentary Science Officer AND create a Scientific Advisory Council to the Prime Minister.  Both promise to “unmuzzle” scientists; both promise to bring back the long-form census (which I personally find irritating – shouldn’t we at least try to move into 21st century with an administrative register?).  Both promise to make government data “open”; additionally, the Liberals promise to ensure their policies are “evidence-based”.  The word “independence” shows up a lot: Liberals want to give it to Statscan, without actually specifying what the word means; the NDP want to restore it to the granting agencies, without specifying what the word means.  They also want to re-establish scientific capacity in government, but apparently aren’t allocating any money for it, so you know, take that with a grain of salt.

The differences, such as they are, are about where to spend the lucre.  The Liberals have set aside an extra $600 million over three years for an “Innovation Agenda”, which will “significantly expand support to incubators and accelerators, as well as the emerging national network for business innovation and cluster support”.  This, apparently, is meant to “create successful networks like the German and American partnerships between business government and university/college research”.

Genuinely, I have no idea what they are talking about.  Which German and American programs?  The Fraunhofer institute?  The Tories already did that when they converted NRC to an applied research shop.  As near as I can tell, this seems to be innovation-speak for “let’s give money to middle-men between academia and business”.  Which is not promising.  I mean, even assuming that early-stage commercialization is the real bottleneck in our innovation system (and where’s the evidence for that, evidence-based policy guys?), why is this the right way to go about fixing it?  Weren’t the Centres of Excellence for Commercialization and Research supposed to do the same thing, albeit from another angle?  Shouldn’t we – you know, wait for some evidence about what works and what doesn’t?

The Liberals also are promising another $100 million over three years to the Industrial Research Assistance Program, which would normally make me want to tear my eyes out, but apparently it’s all going into something that is meant to mimic the US Small Business Innovation and Research Program, which does tend to get high marks.  But, significantly, there is not an extra cent for educational institutions, and not an extra cent for the granting councils.

The New Democrats, on the other hand, are talking much smaller sums: $105 million over four years to “support researchers in post-secondary institutions”.  A helpful NDP staffer has clarified for me that this actually means money to the granting councils, which would make the NDP the only party to commit to more council funding.  That said, unless inflation dips below 1% (unlikely, but not impossible), that amount is not enough to cover inflation.

So, take your pick here.  On non-financial aspects of their policies, the two parties are essentially singing off the same sheet.  Financially, the Liberals have more money on the table, but none of it appears to be heading to institutions.  The NDP has a much smaller package, which will benefit researchers via the granting councils, but not by a whole lot.

Back next Friday with a final summary of the election and higher education.

October 06

Party Platform Analysis: The Liberals

Two quick things at the outset.  First, this will only look at the Liberal’s Monday announcement on student financing.  Tomorrow, I’ll look at their science/innovation policy in conjunction with that of the NDP, which apparently released a similar platform in conditions of complete secrecy last week.  Second, in the interest of full disclosure: I was asked by the Liberals to comment on a draft of their platform a few weeks ago.  I did so, as I would have for any party had they asked.  Judging by what I see in their platform, they took at least some of my comments into account.  So bear that in mind when reading this analysis.

The main plank of the Liberal announcement is that they are planning to increase grants for low income students by $750 million, rising to $900 million by the end of the mandate (which more than doubles the total amount; however,it’s not clear if this increase includes alternative compensation to Quebec… if it does not, add another $200 million).  The Canada Student Grant for Students from Low-Income Families (CSG-LI) will rise in value from $2,000/year to $3,000/year, and the Canada Student Grant for Students from Middle-Income Families (CSG-MI) will rise in value from $800 to $1,800.  The thresholds for both will be increased, meaning more students will receive the low-income grant, and more students with incomes in the $80-100K family income range (precise values not set, but this looks like about what they are going to do) will receive the middle-income grant.  In addition, the Liberals propose raising the repayment threshold (i.e. the level below which borrowers in repayment are not required to make payments on their loans) from just over $20,000 to $25,000.  It’s unclear what this would cost (take-up rate is uncertain), but a good bet would be somewhere in the neighborhood of $100 million.

So, a $1 billion promise.  Except the Liberals are promising that this will all cost the taxpayer… nothing.  And the reason for that is that the Liberals have decided they will axe the education amount and textbook tax credits (something I, and, others have been suggesting for many years – for instance here).  Now, I actually don’t think this will quite cover the entire spending bill, but it will be within $100 million, or so (basically, it will cover the grants, but not the loan threshold change).

However, what this means is that the plan creates winners and losers.  The value of those federal tax credits for full-time students is $558/year (for part-time students it is $168).  Everybody will lose that amount.  For those who currently receive the CSG-LI, and those who receive CSG-MI and remain in the CSG-MI bracket after the thresholds move, the extra $1,000/year the Liberals are offering means they will be better off by $442 (but they will also benefit by getting the entirety of their $1,000 sooner in the form of grants, rather than delayed in the form of tax relief).  For those in the CSG-MI moving into the CSG-LI category, the net benefit will be $1,642.  For those who currently do not receive grants, but will now become eligible for CSG-MI, the net benefit will be $1,242.

So there are winners.  But there are losers, too.  Families with incomes over $100,000 (or so) will simply be out that $558.  And part-time students, who are ineligible to receive CSGs, will also be out $168.  But this is what happens when you try to do big policy without spending (many) additional dollars.  And there’s always the risk that they will come under political fire for “raising taxes”, which is arguably what cutting tax credits amounts to.

So, full marks for creativity here: these policies would make the funding system somewhat more progressive (in a slightly quirky way).  And full marks for putting out a backgrounder that makes it clear that these moves will create costs for provinces (their co-operation will be needed in order to raise the loan threshold) that need to be mitigated, even though the Liberals are vague on how this will actually work.

But it should be noted that by their own claim (which, as I said above, is probably not quite true), Liberals are choosing not to invest another dime in the sector, which puts them last among political parties in new spending commitments.  As pleasing as the re-arrangement of inefficient subsidies is, wouldn’t it have been better if they had added some funds on top of it?

April 23

The State is not Entrepreneurial

If you’re interested in innovation policy, and haven’t spent time under a rock for the last couple of years, you’ve probably heard of Mariana Mazzucato.  She’s the professor economics at the University of Sussex who wrote The Entrepreneurial State, which is rapidly becoming the source of an enormous number of errors as far as science and economic policy are concerned.

Mazzucato’s work got a fair bit of publicity when it was released for pointing out that a lot of private sector tech is an outgrowth of public sector-sponsored research.  She has a nice chapter, for instance, outlining how various components of the iPhone – the touchscreen, the GPS, the clickwheels, the batteries… hell, the internet itself – are based on research done by the US government.  This is absolutely bleeding obvious if you’re in science policy, but apparently people out there need to be reminded once in awhile, so Mazzucato found an audience.

Where Mazzucato goes wrong, however, is when she begins to draw inferences; for instance, she suggests that because the state funds “risky” research (i.e. research that no one else wold fund), it’s role in R&D is that of a “risk-taking” entity.  She also argues that since the state takes a leading position in the scientific development of some industries (e.g. biotech), it is therefore an “entrepreneurial” entity.  From this, Mazzucato concludes that the state deserves a share of whatever profits private companies make when they use technology developed with public science.

There are two problems here.  The first is that Mazzucato is rather foolishly conflating risk and uncertainty (risk is tangible and calculable, uncertainty is not).  Governments are not a risk-takers in any meaningful sense: they are not in any danger of folding if investments come to naught, because they can use taxing power (or in extremis, the ability to print money) to stay afloat.  What they do via funding of basic research is to reduce uncertainty: to shed light on areas that were previously unknowable.  Individual companies do very little of this, not just because it’s difficult and expensive (if a company is big enough, that’s not a problem – see Bell Labs or indeed some of the quite amazing stuff Google is doing these days), but because the spillover from such research might allow competitors to reap much of its value (a point Kenneth Arrow made over fifty years ago).

The second issue is that nearly all of the examples Mazzucato offers of public research leading to technological innovation and profit are American, and a fairly high percentage of these examples were funded by the Defense Advanced Research Projects Agency (DARPA).  To put it mildly, these examples are sui generis.  It’s not at all clear that what works in terms of government investment in the US, with its massive defense infrastructure, huge pools of venture capital, and deep wells of entrepreneurial talent, hold very many lessons for countries like Canada, which are not similarly endowed.  Yet Mazzucato more or less acts as if her recommendations are universal.

The book’s recommendations amount to: government should own a share of young innovative companies by gaining shares in return for use of publicly-funded knowledge.  But this is pretty tricky: first, there are very few cases where you can draw a straight line from a specific piece of publicly-funded IP to a specific product, and even where you can, there’s no guarantee that the piece of IP was publicly-funded by your local government (Canadian start-ups benefit from knowledge that has been created through public subsidies in many different countries, not just Canada).  And while there’s a case for greater government investment in emerging companies (economist Dani Rodrik makes it here for instance), the case is not in any way predicated on government investments in R&D.  In Canada, the CPP could adopt such a policy right now if it wanted – there’s no reason why it needs to be linked to anything Industry Canada is doing in science funding.  To the contrary, as Stian Westlake points out, countries that have been most successful in converting public science investments into private hi-tech businesses eschew the idea of equity in return for scientific subsidies.

Worst of all – though this is not entirely Mazzucato’s fault – her argument is being picked up and distorted by the usual suspects on the left.  These distortions are usually variations on: “Someone said the state is entrepreneurial?  That means the state must know how to run businesses!  Let’s get the state more involved in the direction of the economy/shaping how technology is used!”  This way disaster lies.

So, Mazzucato did everyone a service by forcefully reminding people about the importance of publicly-funded R&D to any innovation system.  But her policy prescriptions are much less impressive.  Treat with care.

October 23

Where the Questions Are

I had planned to continue on today with my series about operating budgets by taking a look at some scenarios for Central Canada, but I’ve been on the east coast for work the past couple days, and so that post will have to wait.  We’ll get back to it shortly, I promise.  But for now, let me turn to something I’ve been thinking about lately.

One of the maddening things about many discussions that concern higher education and business is the crudeness of many popular views on their relationship.  Mostly, we hear about how business’ role is to “contribute” to higher education, either via taxes, or philanthropy, or both (depending on where you are on the political spectrum).  Often times, the role of business is to hire “our” graduates (and if that’s not happening then let the agonized introspection begin).

And while those things are all true, what these analyses actually miss is the true role of business, particularly with respect to science: it’s a huge, incomparable reservoir of questions to be answered, and problems to be solved.  Of course, people get this at the level of applied research – by definition, when companies engage with higher education on applied research, it’s to solve specific problems – but they have trouble understanding when it comes to “pure” research.  Partly, that’s due to rhetorical confusion – the wording of “pure” research (a rhetorical device of Vannevar Bush designed to keep money flowing to universities after World War II) implies that interaction between scientists and pretty much anyone else will “contaminate” research.

But a quick history of 20th century science will show you that this is nonsense.  Much of Einstein’s early work was hugely influenced by being immersed in commercial technology at the Swiss patent office.  Quantum physics was an accidental discovery made by German scientists who were trying to design more accurate instruments to measure very small weights.  The Manhattan Project wasn’t about meeting commercial needs, but as research goes, it’s about as applied as it gets.  Etc., etc.

The point here is that there are parts of commercial science that are up banging against the frontiers of the unknown just as much as university science is: just think of what was discovered at Bell Labs, or what Craig Ventner has accomplished.  It’s where the rubber hits the road: where the most advanced academic science gets put into practice and tested in real-world conditions.  Under commercial pressure, commercial science looks for every little advantage when learning how to cure disease, design better buildings, and develop new technology.

Even Vannevar Bush didn’t believe “pure” research happened in a vacuum.  Indeed, the justification for “pure” research is always that someone, somewhere, will find an application for it.  If you don’t have an inkling of where your “pure” research findings might actually be applied someday, you probably aren’t conducting your “pure” research in a way that’s very effective, because you’re not asking the right questions.

And this is the real reason universities need to engage with industry: it’s where the best questions are.  And you’re not going to get top-notch research without top-notch questions.

October 17

Innovation Literature Fail

So, I’ve been reading Mariana Mazzucato’s, The Entrepreneurial State.  It’s brilliant and irritating, in equal measures.  Brilliant because of the way it skewers certain free-market riffs about the role of risk and entrepreneurialism in the innovation process, and irritating because it’s maddeningly cavalier about applying business terms to government processes (in particular, the term “risk”, which Mazzucato doesn’t seem to understand means something entirely different in government, if losses can be made whole through taxation).

Anyways, one thing that occurred to me while reading was just how America-specific much of the literature on innovation is.  Take the Defence Advanced Research Projects Agency (DARPA).  In innovation policy circles it’s generally considered a wicked-cool way of organizing Big Science: it’s project-based, it brings teams together from both academia and business, and it has substantial independence.  And, of course, the basic research has produced things like GPS and the Internet (still the core anecdotes used to back the “government-should-be-involved-in-research” argument). 

Brilliant, right?  So why doesn’t everyone have a DARPA?  Why doesn’t Canada?

The answer is that DARPA wouldn’t make any sense here.  Our government agencies don’t have enough of the “big problems” that DARPA is designed to solve – or, at least, that could be solved at a price we can afford.  And frankly, we don’t have enough private-sector research scientists to make headway into these kinds of projects, anyway.

More broadly, the American system of funding science works because of a particular combination of factors: the problems needing to be solved, the presence of major private sector research efforts, a particular type of venture capital industry, and scale.  Canada – like most countries in the world – would, at most, get part-marks on any of those four criteria.  So why do we think that policies based on American examples work for us?

Take questions of “applied” vs. “basic” science.  Maybe the classic Vannevar Bush formulation of, “government funds universities to do basic research, and companies do the applied stuff” only makes sense in the US context.  Maybe without the VC culture, or the private sector research culture, the idea that government should only be playing in the “basic” side of the continuum doesn’t make any sense. Maybe countries who aren’t quite at the technological frontier don’t get as much bang for their buck in basic research as America does.

This is just speculation on my part, of course.  But I’m tired of the innovation literature assuming that US-inspired solutions will work here.  Just for once, I’d like to see some literature and policy prescriptions based on what works in Korea, the Netherlands, and Scandinavia.  There’s probably a whole other set of policy lessons to be learned, if only we looked for them in the right places.

May 24

The Best Idea I’ve Seen All Year

I travel around a fair bit, and I get to see a lot of interesting stuff that’s going on at universities in Canada, and abroad.  People often ask me: what’s the best thing you’ve seen recently?  The answer this year, hands down, is UBC’s Start-up Services Voucher.

Now, UBC’s been a leader in commercialization and spin-off companies for at least twenty years.  They caught a lot of attention when they created a $10 million Seed Fund, capitalized by donations from alumni and the BC Innovation Council, which was designed to promote entrepreneurship by making early stage, pre-seed investments in start-ups founded by students or recent alumni.

But more quietly, the university has done something else which I think is much more interesting: about two years ago, it created the Start-up Services Voucher.  If you’re a UBC student, staff, or faculty member, and want to start a business, you’re eligible for up to $5000 worth of business services (though, in practice, most use far less).  And unlike virtually every other entrepreneurship system in Canadian PSE, there are no requirements whatsoever with respect to using UBC technology, nor is there any stipulation that the business be some kind of technology enterprise.  Want to open a flower shop?  This fund’s for you.

There’s no catch.  UBC certainly isn’t interested in equity, for instance.  All they want is recognition.  All companies that move through the program must display a logo declaring themselves as “UBC-affiliated companies” for a period of five years.

How brilliant is that?

First, it creates a great, dense network between an institution and small businesses in its community (which will no doubt pay off philanthropically, down the road).  Second of all, it allows the institution to get a much better handle on the post-graduation activities of its entrepreneurs, and hence allows UBC to highlight its larger role in job creation and innovation in British Columbia.  Frankly, UBC could pay for this out of the Government Relations budget, and it would make complete sense – how great will it be to be able to walk into an MLA’s office and rattle off the names of all the new, “UBC-affiliated” businesses that have started-up in his/her riding?

Students learn a lot in PSE, and not just inside the classroom.  When they start their own businesses, it’s the ultimate expression of the mix of hard, soft, and creative skills that they’ve gained at school, and are now applying in innovative ways.  It’s a huge, practical impact that universities and colleges have on their communities that no one’s ever been able to quantify or publicize.

Until now.  Bravo, UBC.  A great idea that deserves more attention – and some imitators.

April 24

Canadian Innovation, Seen from Abroad

So, I came across this quite remarkable little document yesterday – it’s a report prepared by MIT-Skoltech on the universities around the world who contribute the most to their local innovation systems.

(What is Skoltech, you ask?  Well, it’s a university located in a nascent science and tech hub, just outside Moscow, in a place called Skolkovo, and is the pet project of the Medvedev wing of the Kremlin.  Anchoring this tech hub is the new Skolkovo University of Science and Technology, or Skoltech.  To emphasize its difference from the rest of Russian Academia, the institution’s hired an American, Edward Crawley, from MIT as its first President. In the stuffy world of Russian Academia, this was a Big Freaking Deal.  MIT quickly signed up for a long-term partnership deal to develop Skoltech; hence, MIT-Skoltech).

Anyways, since the whole point of the Skolkovo project is to create a self-sustaining economic cluster which isn’t totally penetrated by the usual gang of oligarchs and kleptocrats, the role universities can play in developing technology-based ecosystems is much on the minds of campus leaders.  And so they hired a consultant to interview some of the world’s leading thinkers on innovation, higher education, and tech clusters, and asked them to name, i) the universities around the world which have the most highly-regarded tech ecosystems, and ii) the universities that do the most to develop tech ecosystems in challenging circumstances.

Here’s what they had to say about Canadian universities…

Nothing.  Absolutely nothing.

Maybe it’s not a surprise that none of our universities would make the top ten in the world; though Technion, ETH Zurich, and the National University of Singapore all cracked the top ten’s inevitable Anglo-American cartel.  But the identities of the schools that made it into the “doing most with the least” category ahead of any Canadian university should raise eyebrows: Sophia Antopolis (France), Aalto University (Finland), and KAIST (Korea).  Oh, and the University of Auckland.  At innovation, we rank below hobbits.

Of course, this is just expert opinions; it’s not in any sense “factual”.  Maybe if one were to delve into some metrics (the paper actually has a very useful section on measuring innovation at universities, though it does not use them in its comparisons), one would find that places like Waterloo and UBC “deserve” a place at the top table.  But experts usually aren’t that far off the mark.  And even if they are, the fact remains: people who matter in this field don’t think of Canadian universities and “top innovators” in the same sentence.

Universities with a reputation for innovation and entrepreneurship attract investment and top-class industrial partners.  If that’s not the image we’re projecting, we should be asking ourselves some pretty tough questions.

January 14

Better, not Cheaper

If there is one clear meme concerning higher education coming out of America during this recession, it’s this: “higher education is too expensive and it’s delivering a sub-optimal product.”

Zeitgeist statements like this one have to be handled carefully.  Even if you don’t agree with this meme, failure to engage with it can expose one to charges of being “defensive,” or “part of the problem”.  So, for the moment, let’s accept this statement at face-value, and focus on how one might respond to it.

From a business perspective, there’s simply no question that in a quasi-monopolistic system like higher education, the choice between cheaper and better is obvious.  Only a chump gives up the revenue.  If consumers perceive that the quality – however that may be defined – isn’t there, that’s what needs to be fixed.

Given this, it’s absolutely astonishing to me how quickly the debate in America has focussed around cost.  Everywhere, the mantra is about “bending the cost-curve” (tellingly, a phrase consciously borrowed from the health-care debate), and states like Florida, Texas, and California are all making serious moves to implement so-called $10,000 degrees (that’s not the price, it’s the cost).   Faced with the proposition that, “higher education isn’t delivering the goods, and it costs too much”, the dominant reaction in America seems to be, “well, let’s make it cheaper, then”.  Now, obviously, this response is being driven by political actors rather than educational ones, but it’s stunning nonetheless.

Canada hasn’t quite seen the same level of disillusionment with higher education, mainly because youth unemployment hasn’t spiked in anything like the way it has in the US (the irritating but inevitable fact: higher education will take blame, and credit, for preparing young people for jobs in direct relation to the amplitude of the economic cycle, over which it has zero influence).  But the “cheaper-not-better” agenda could easily take root here, too; Lord knows, in Ontario, we’ve only recently escaped the clutches of a Minister who was in thrall to exactly that vision.

So, here’s a thought: let’s be proactive about this.  Instead of waiting for the next crisis to pop-up, let’s get ahead of the curve by improving the value proposition of undergraduate education.  As I’ve said before, what people really want are graduates who are effective, engaged, and innovative, so let’s find a way to deliver on that.

Put aside for awhile the pitches for more grad students and more research.  Winning the battle for public trust in the system is going to depend first and foremost on how our system delivers on undergraduate education.  Only by being better can the system avoid the call to be cheaper.

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