With so many mergers and acquisitions around us, as well as the consistently high levels of interest in innovation, how can we anticipate what will stick and what won’t? We see new technologies that can help us in every way from attracting authors, to supporting research, to enabling better discovery, to making our operations more efficient, what should we incorporate into our organization, and what should we be passing on? 

As a proxy for that dilemma, this month we asked the Chefs: If you were a VC investing in scholarly communications, where would you be placing your bets?

play card with money,  chips

Joe Esposito: Let’s separate heart and head. My heart wants investment in a new online bookstore that is optimized for academic and professional books, including reading apps that take into account the ways scholars interact with their texts (which the Kindle app does not do, wonderful as it is for straight narrative text). I would like the online service to be easily customizable for social media feeds, and I would like it to support strategically located physical stores (urban areas, near universities).

But my head, which operates about 50 years ahead of my backward heart, would be investing in cloud-based applications for Big Data. Not the data itself (no one can aggregate enough) but tool sets that organizations can upload their data to and get a result. The outputs would all be things that only machines can do (hence the Big in Big Data). Humans need not apply. So a biologist, for example, would develop a large data set and be able to have it mined, turned, linked, and whatever from a third party. This would expedite research because it would spare researchers the need to invent all of their information processing tools. I don’t see a role for publishers in this.

Of course, someone will say in the comments that this is going on already and will adduce an example of Small Data. Big Data is what people cannot do without machines.

Charlie Rapple: I brainstormed this one with my colleagues at Kudos! Firstly, we considered what VCs want from an investment. Primarily, it’s a high return – a factor of some ten times their investment. Part of the game they play is backing several horses knowing that the majority won’t make it over the line. Hence, they want every horse they pick to have the stature of one that might just grow a twinkly horn and turn into a unicorn.

The next question is, what in scholarly communications has the potential to give them that sort of return? Let’s take a modest VC investment of $20m. They need that to turn into $200m. That in turn requires an even greater potential for revenue – either directly, or through the value your horse can add to someone else’s stable.

There are some very big numbers in scholarly communications – $200 billion spent on Higher Education R&D, $19b on scientific publishing … likely hundreds of million on data and impact products, at a guess. There are some rich pickings here. Whose pie is it easiest to take a significant chunk out of?

There are some very big numbers in scholarly communications – $200 billion spent on Higher Education R&D, $19b on scientific publishing … likely hundreds of million on data and impact products, at a guess. There are some rich pickings here. Whose pie is it easiest to take a significant chunk out of?

The impact agenda is a good bet. There are national movements afoot here (e.g. the UK REF where $650m of annual funding for Universities is determined by scores received from impact case studies) that are likely to spread as data supporting this kind of analysis gets better and better. Mind you, tracking impact is notoriously difficult and long-term. But the prize is a big one.

The really big money is on the funding side of research – the $200 billion spent on R&D through higher education institutions globally really makes the VCs sit up; and academic investment in R&D is dwarfed by corporate investment in R&D. How can we help funders get more bang for their bucks? Assisting with dissemination and impact is part of that, but it’s also after the horse has bolted. Of even greater value is getting the money into the right hands, with the right tools, to achieve impact (however each funder chooses to measure impact) as effectively and efficiently as possible. Now that’s really worth something.

Michael Clarke: You know that a market sector has been discovered by VC firms when it acquires a tortured name used to describe the sector to investors. This must have happened recently to the scholarly communications market as I have heard several individuals (all from the West Coast) refer to the space (with a straight face) as “ScholComm” (not to be confused with “FinTech” or “MedTech” or “EdTech” even though there is, of course, some overlap, especially with the latter). Imagining that we have raised money explicitly for a ScholComm fund (which we will optimistically name “ScholComm Fund 1” or “SCF1”), where would we place our bets?

If the exhibit hall at last month’s SSP meeting is any indication, all the action today is with companies focused on data and analytics. This is a big bucket that includes publisher and library analytics, research data support and services, text and data mining, and so forth. Another area of focus might be author services. Every time I turn around there is another outfit offering language editing. Rolling up this market and automating the heck out of it is the sort of thing that the SCF1 management team might contemplate wistfully over a few beers at the Rose and Crown. A third area is that of production services, and particularly software that completely automates XML mark-up – a long-held objective of publishers (and of anyone that has ever had to manually edit XML) that is finally within reach. A fourth area would be open access publishing – there is likely room for a few more “born-OA” publishers of the non-predatory variety (one of our investors notes is likely to observe that it ain’t called “Gold OA” for nothing). And finally, we would be remiss if we neglected to invest in the rapidly growing online piracy and university network hacking space. To this end, we will review the SciHub prospectus with great interest.

As a general rule, SCF1 will value companies inversely in proportion to the content they produce, and directly in proportion to the amount of righteous indignation they are able to muster in explaining why they are entitled to make commercial (re)use of content under copyright by others without compensation.

If the exhibit hall at last month’s SSP meeting is any indication, all the action today is with companies focused on data and analytics. This is a big bucket that includes publisher and library analytics, research data support and services, text and data mining, and so forth.

Judy Luther: I would invest in new publishing software where the opportunity for disruption is the greatest. Our existing legacy publishing platforms were developed when print was considered the standard output. Today’s content is born digital.

Last year the rapid adoption of mobile reached a tipping point with more users accessing the web from mobile devices than from desktops and notebooks. Google is encouraging content suppliers to be mobile ready as it can affect the page rank in search results. This is just one of many changes that need to be accommodated. Every new requirement adds cost to the existing systems whether it is to display content on mobile devices, to incorporate newer standards [JATS], to expand metadata for new identifiers [ORCID], and to track article impact through social media metrics.

New systems that are evolving that take full advantage of born digital content and incorporate three separate functions (1-submission/peer review, 2-editing/production, 3-hosting platform/distribution) into a single continuous stream that can more easily handle the variety of formats used today. These systems may be based on a framework of modules (COKO) or a suite of apps. They also promise to expand capabilities while reducing both time to publication and cost of operations while increasing functionality of the content.

New tools for authors to collaborate such as Overleaf and Smashdocs enable the submission of manuscripts that reduce the burden on reviewers and production.

Given the current economic pressures in the market a reduction in the cost of producing scholarly content opens the door for a wide range of possibilities both for researchers and publishers. While change is seldom easy, the opportunities will be compelling to utilize the next generation of tools to reduce the burden on researchers, reviewers, editors and publishers and optimize the value of digital content.

David Smith: The answers to this question depend on the the goals of the investor. Paul Graham, one of the founders of the VC investor Y Combinator, described start-up investing as follows:

“The two most important things to understand about startup investing, as a business, are (1) that effectively all the returns are concentrated in a few big winners, and (2) that the best ideas look initially like bad ideas.”

He expands further in a superb essay called “Black Swan Farming.”

So where would I put my hypothetical cash? Sensible ideas are immediately out. Those are for fools looking for a modest return; getting their investments bought up by Elsevier and the like. Nope, I’m fishing for bigger fish. Monsters. Denizens with a LOT of cash. Folks who think about things, differently.

What if I put a billion into SciHub? That would shift the centre of gravity wouldn’t it. You can pay for some seriously pro-grade PR and legal with that kinda dosh. Would we survive that? Would we? Recall the US publishing industry got started by protected piracy. (Go read Gotham, a history of New York City to 1898).

Meta was struggling to pay the bills just before the Chan Zuckerberg Initiative came calling (having burned through $10 million in six years). We don’t know how much they paid, but they have a pot of (at least) $3 billion in which to make some serious bets.  CZI have (perhaps not surprisingly, considering their DNA) gone for a big data (That’s ‘our’ data by the way — ponder that) AI play to start with. Apparently that $10 mil paid not only for the tech and the servers and pizzas and Red Bull but also a bunch of content deals from us publishers. As John Lydon put it “Ever get the feeling you’ve been cheated?” Meta took a look at the data inherent in scholarly content and bet they could do something very novel and crazy with it. And, powered by Facebook, CZI think that they can do even more.

Gates is throwing cash around. Welcome AND Goldman Sachs are investing in ResearchGate — an offering without a lot of things, including anything approximating a business model. But they have that sweet sweet data and some sort of large scale user base. Somebody somewhere thinks differently about that; Thinks there’s real money to be made.

But you want to know where I’d put my money right? Two places. In no order, I’d invest in:

  1. Hypothes.is A non-profit who could build a fascinating data set of who marks up insight and comment about things on the web.
  2. Code Ocean who are looking to get the the most cutting edge research code from the smartest minds on the planet and put it all in a system that allows it to be inspected, run, manipulated etc across all the major fields of scholarship.

Just think how that could be exploited at scale. If you can think differently enough.

Alice Meadows: Every year at the APE conference in Berlin, the audience gets a chance to do a version of just this. In a session chaired by Eefke Smit of STM, startup companies from across the scholarly communications ecosystem get to pitch their business and answer questions about it. The audience is then invited to vote for (among other things) the organization they’d most want to invest in. I’d like to think that I voted wisely — though given the high standard of organizations represented it’s often a tough choice. Looking back I see that I tend to gravitate toward companies that focus on truly facilitating openness and collaboration between researchers — something that I passionately support and that will, I hope and believe, continue to be absolutely central to successful science and scholarship. So — if I had money to spare and were a betting woman — I would be investing in organizations like Overleaf (making collaborative authoring easier), Paperhive (ditto for reading), and Hypothes.is (open annotation). But since I’m neither rich nor a gambler, please don’t come knocking on my door!

Ann Michael: In my opinion, everything comes back to data no matter what our strategic objective. If running any type of business (mission or profit focused) requires data, then my bets would be on innovative organizations and tools that enable the capture, normalization, and most important, the translation of data into decision-making quality information. Who is innovating around the creation of data, the tools to use it, and the “democratization” of transforming data into information? That is, making it so easy anyone with a business-focused question could come up with a trustworthy bit of analysis to guide them. That’s where my money would go!

Now it’s your turn, if you were a VC investing in scholarly communications, where would you be placing your bets?


Ann Michael

Ann Michael

Ann Michael is President of Delta Think, a business and technology consulting and advisory firm focused on innovation and growth in membership organizations, scholarly publishers, and professional information providers. Ann is Past-President of SSP.

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11 Thoughts on "Ask The Chefs: If You Were A VC Investing In Scholarly Communications, Where Would You Be Placing Your Bets?"

This is a neat topic! For myself, I’d put money into elaborating “drug discovery” software in a way that interacts with genomic information. Identify a disorder, clarify what is the pathology (biochemical and/or genetic and/or epigenetic), zero in on compounds and/or genes that can rectify the pathology. Then you tap into the immense sums spent worldwide on health care, not to mention probably doing a lot of good for the world as a whole. I see a unicorn being born.

Interesting stuff and perfect reading over a donut and coffee this morning. What I think comes across most clearly – and apologies to the contributors who are playing along with the game – is how little is truly understood about how VCs operate and the subtle differences between them and Private Equity and their relative stages of investment. As a heuristic think of VCs investing in early stage and PEs investing in later stage products. And the values and volumes are far less than assumed above.
Consider for example the high levels of PE money supporting market leading products that we all use in daily ‘ScholComm’ lives. They may not ‘own’ the product but they certainly bankroll it and exist in the background exerting the necessary commercial pressure to deliver the (much lower) multiples than stated above.
So, for me? The best option for my PE fund would be the big commercial publishers. Solid returns over long periods, market control and few threats to the fund over its investment cycle. Don’t keep looking for new when you can continue to generate good money from old rope. That’s where you’ll find the investment banks and I’d join them.

Fair point. What if the question were reframed as “What new innovations or technologies do you feel will have the biggest impact on scholarly publishers (pick your own time horizon)?

As long as this is truly Private Equity and as long as the time horizon is no more than several years, this makes sense. SpringerNature is owned by PE, if I recall correctly, and there’s no reason not to extend that to the likes of Elsevier and Wiley. For VC, however, absolutely not! The profits in this space have no where to go but down in the next decade, with all of the competitive pressures (legitimate and otherwise) and the onrush of disruptive technologies.

Fantastic. To Mike Clarke’s point, an end-to-end solution that serves publishers, authors, and platforms would be the holy grail of what we do. We are desperately trying to connect way too many systems (none of them ideal) to publish content. Multiple vendors means things fall through the cracks. But more importantly, doing any kind of competent data analysis is a nightmare.

I agree with everything David Smith said (I can’t believe I just admitted that.)

Interesting comments and responses about VC plays in our marketplace. However when you look at some recent major paydays the VC’s have stayed in ongoing businesses vs. new technology. Consider Ex Libris and OverDrive have both provided huge paydays for recent investments. Other VC plays have included Innovative Interfaces, High Wire, and even Springer. All established concerns with little new technology portfolio. VC’s are still looking for returns and in our marketplace there is still a preference for taking undervalued or under managed properties and giving those properties attention to improve their value while hoping for a major payday.

An example of what Joe and Ann talk about with respect to big data may be the TDM program run by the CCC, which offers the service of normalizing formats from multiple sources so that investigations can then be run on the normalized content.

Interesting that data and analytics popped up a few times on this list. From my vantage point there are too many platforms that are trying to “connect” researchers in essentially the same ways. I have profiles and lists of publications on Research Gate, Pivot, GrantForward, ORCID, Academia, and SciStart to name a few. Although in theory there are differences among these platforms, they are pretty much the same. Yet because the information is not aggregated across these platforms, it ends up getting watered down to information that is inconsistent and not at all useful. For institutions that track how many times we authors are cited, I suspect they rely on their own internal platforms (that are just like these) to obtain the data needed to promote or punt faculty.

VC doesn’t mean the same thing to an academic audience, by the way – it means Vice Chancellor. Just spelling out venture capitalist in the title would have saved wasted time!

It probably depends on your field — given the emphasis many universities put on patents and technology transfer, I’m willing to bet many (most?) scientists are pretty familiar with investors. But if you really want to get confusing, then we could start talking about PI’s without invoking Tom Selleck.

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