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The Underappreciated Utility of Grants
Though we love to romanticize the indefatigable entrepreneur who overcomes the odds to build a massive business, humble beginnings are more common than we often credit. Each of the above founders has gone on to build large to gargantuan businesses, but the start of each was not so hyperbolic. No, each of these entrepreneurial journeys began with the most humble of our available funding mechanisms — the Grant.
I first encountered the world of grants in grad school, at which point I became eminently aware that we could not in fact research whatever we wanted, but instead any new ideas ripe for exploration were effectively gated by third-party grantors. And not just holding the strings over future research endeavors but over the very existence of the research lab itself.
This is the challenge of research today — because most R&D is not tethered to profit-making, there is no perpetual funding mechanism (typically) available. Thus every research lab, no matter how prosperous, exists in this state of perma-dread; that the latest grant will be its last.
I left academia 15 years ago, and with it grants largely evacuated from my consciousness as I entrenched on a capitalistic path. But in recent months — as I dove deep into research on the Innovation Funding landscape, ultimately culminating in the launch of this newsletter — my interest in grants has reignited. It’s an under-used, under-researched, under-invested mechanism that requires more of our attention.
And thus I’ll be writing a lot more about grants over the next month or so, starting here with some basic principles and thinking before turning our attention to specific applications:
How to ignite talented youth
How to adjust incentives when life risks are higher
How we can better tether grants to our standard innovation investment types (VC & PE in particular)
Grants vs. Prizes
Pierre Azoulay is one of the most interesting and prolific researchers investigating the Innovation Economy, and he pays particular attention exploring the means by which we incentivize innovation. In “Scientific Grant Funding“, Azoulay lays out a useful 2x2 matrix (always a 2x2) to help categorize the various funding mechanisms typically offered to academic researchers:
Here we have two novel axes:
Nature of Idea Search: is the end point known but not yet executed? Or is the research in question more exploratory? If we refer back to the GUTS framework, this is a reframing of the “Divergence vs. Convergence” axis.
Appropriability: Is the given idea well-suited for first-order market returns? Or more simply, is the given idea knowingly commercializable?
“We argue that grants are likely to be the most effective—and feasible—way to fund basic research when two fundamental conditions simultaneously hold. First, when the social value of a scientific finding likely exceeds its privately appropriable value.”
This is interesting — the researchers argue here that grants unlock research that is so foundational that any commercial exploitation thereafter cannot conceivably be captured by the researchers alone. This resembles Bill Gates’ definition of a platform — that it creates substantially more value for third-parties than can possibly be captured by the platform creator itself.
“Second, when specifying the parameters of a desired research solution ahead of time is impossible.”
Said differently, grants are best positioned for tackling both known and unknown unknowns. In GUTS-speak, this is the “Play” quadrant in particular:
“We will also discuss two subsidiary arguments in favor grant funding over alternative mechanisms:
When potential research performers face financial constraints
When investments take the form of general-purpose research infrastructure (as opposed to specific projects).”
Thus the researchers effectively make two additional claims about the utility of grants:
That they provide a financial safety net to incentivize research.
That enabling freedom of research is key. Put differently, this is an argument for funding people over projects, a concept we’ll return to shortly.
“Grants may be particularly effective in cases where researchers are financially constrained. Stanford graduate student Sergey Brin was supported by a dissertation fellowship from the National Science Foundation (NSF) when he teamed up with fellow graduate student Larry Page to design BackRub, a prototype world wide web search engine that leveraged hyperlinks between pages to develop an “importance” ranking for a set of 24 million web pages”
We’ll dive much further into the “financial safety net” argument with the next two pieces in this series, though tl;dr I’m very much a proponent of matching grants to the actual “need state” of the given innovator, rather than focusing grants on those with highly limited means.
Fund People not Projects
“The research-project approach can be pernicious. If it is administered so that it produces certain specific end products, or if it provides short periods of support without assuring continuity, or if it applies overt or indirect pressure on the investigator to shift his interests to narrowly defined work set by the source of money, or if it imposes financial and scientific accounting in unreasonable detail.” James Shannon, NIH Director (1956)
Thus began the “fund people not projects” movement, which unfortunately nearly 70 years later continues to struggle against the dominant “fund projects not people” default. This is of course a challenge, both because talented researchers tend to be talented beyond a given project’s scope, and because these talents are far more likely to identify and uncover value if provided greater bandwidth.
As Derek Thompson writes, we “trust science,” but our government doesn’t (often) trust scientists to pursue their favorite projects. This ultimately leads to the specialization paradox — we force scientific specialists to specialize not only in increasing narrow niches but also in grant writing, as researchers spend 10-40% of their time on grant proposals. This hearkens back to my laments about the increasing bureaucracy ratios inherent to growing companies.
“When Fast Grants surveyed its recipients, more than 70 percent of grantees said they would change their focus “a lot” if they could deploy their grant money however they liked. This made Patrick Collison feel certain that science needs more institutes that fund people rather than projects.”
“Arc’s co-founders told me they have sympathy for the NIH’s low tolerance for risk, because voters might not support their tax dollars going to some cockamamie ideas.”
Methinks that funders with such purse string control should perhaps have a bit more courage when it comes to funding such cockamamie ideas!
I’m in favor of a concept offered by Nicholson Price — person-focused and project-weighted. This is effectively how early-stage VC already operates. The grantor focuses on the funding of exceptional people, but a heavy part of the initial evaluation (especially when there’s no track record for the person) is the quality of their idea (project). In such an arrangement, we are not tethering the funding to a specific project, such that the funds can exclusively be used for the given idea, but instead the novelty/perceived quality of the ideas/projects is the significant weight in the grant underwriting algorithm.
Certification vs. Prototyping
We’ve thus far discussed different mechanisms of fund disbursal and briefly touched on whom the recipient of the given funding should be, but we haven’t actually touched on the actual value that a grant provides. The obvious value resides in the use of funds, for prototyping — the funding provided by a grant creates most value by enabling the recipient(s) to build a prototype and de-risk the “is this impossible” stage.
But there’s a second, less utilitarian value for the grant — one of certification. If a competition/grant is prestigious enough, it may be a signaling vehicle for investment. This feels quite similar to the value venture capital funding bestows upon a new startup — funding to actually build the thing, sure, but also a signaling mechanism (especially to talent) that this given startup is worthy of attention.
My go-to for all things grants and science research is, founder of Speculative Technologies and writer of insanely long “blog” posts on DARPA. From his piece “Grants Only Go So Far”:
“Grants are humble, fast, low time commitment, and maximize the chance that you’ll support something successful — their appeal and popularity makes a lot of sense. But they have limits.”
A key piece of the limits gets to the heart of our aforementioned “fund people versus projects” divide:
“Grants filter for people who know what the right thing to work on. However, not everybody who could potentially do good work knows the right thing to work on. Especially in a world of increasing specialization people often see problems only through a specific lens or only see one node in a system-level problem.”
We’ll discuss this in much greater detail the next few weeks, but it’s incredibly important in any grant-making system that we clearly identify what behaviors we’re specifically looking to incentivize and structure the grants accordingly.
“Most significantly, grants fail to address one of the biggest impediments to weird new things in the world: the shadow of the future. You get a grant that pays the rent for a few months, perhaps hire a contractor, buy some equipment, or do work that wouldn’t normally be funded in your university. Then what? You need to either land in an institution or get another grant. Either way, you need to tune work that you did on the grant to set you up for your next steps. You haven’t actually escaped institutional incentives at all. This phenomenon constantly looms over the shoulders of those of us who want to see new institutions and games in the world and deserves a much longer treatment.”
The limited timeline offered by each grant, and the current lack of persistence or explicit ties to further grants, is a major contributor to the 10-40% of researcher time spent on grants — as soon as one grant is won, the clock starts ticking until funding runs out, and thus most researchers find themselves on the perpetual hamster wheel of grants. It’s not a great system for our most talented and innovative minds! Reinhardt of course has an answer for us:
“Do tranched funding. Understandably, most people don’t want to give a huge chunk of money to an unproven idea and team. However, the difference between vague noises of support with the potential of money in the future and an extremely clear set of conditions under which a specific amount of money would be available is huge. It not only provides a goal to work for but enables someone to turn around and rally support by saying “if I can just get this much to get to milestone X, I will unlock Y” — it effectively lets them project some fraction of that future money into the present without lying. Many times, a large chunk of clearly-conditioned money in the future can be more valuable than a small chunk of money now. Like so many of these suggestions this one does require work on your part and reduces your optionality. Let’s celebrate people doing work and reducing their optionality to enable awesome things!”
I’ll let this one linger for now, as we’re going to spend more time in the weeds of this type of approach in the future piece dedicated to structures from an investor’s POV.