What Works in Boston, Won’t Necessarily Work in Birmingham: 4 Pragmatic Principles for Building Commercialization Capacity in Innovation Ecosystems

Just like crop tops, flannel, and some truly unfortunate JNCO jeans that one of these authors wore in junior high, the trends of the 90’s are upon us again. In the innovation world, this means an outsized focus on tech-based economic development, the hottest new idea in economic development, circa 1995. This takes us back in time to fifteen years after the passage of the Bayh Dole Act, the federal legislation that granted ownership of federally funded research to universities. It was a time when the economy was expanding, dot-com growth was a boom, not a bubble, and we spent more time watching Saved by the Bell than thinking about economic impact. 

After the creation of tech transfer offices across the country and the benefit of time, universities were just starting to understand how much the changes wrought by Bayh-Dole would impact them (or not). A raft of optimistic investments in venture development organizations and state public-private partnerships swept the country, some of which (like Ben Franklin Technology Partners and BioSTL) are still with us today, and some of which (like the Kansas Technology Enterprise Center) have flamed out in spectacular fashion. All of a sudden, research seemed like a process to be harnessed for economic impact. Out of this era came the focus on “technology commercialization” that has captured the economic development imagination to this day. 

Commercialization, in the context of this piece, describes the process through which universities (or national labs) and the private sector collaborate to bring to the market technologies that were developed using federal funding. Unlike sponsored research and development, in which industry engages with universities from the beginning to fund and set a research agenda, commercialization brings in the private sector after the technology has been conceptualized. Successful commercialization efforts have now grown across the country, and we believe they can be described by four practical principles: 

Principle 1: A strong research enterprise is a necessary precondition to building a strong commercialization pipeline.

The first condition necessary to developing a commercialization pipeline is a reasonably advanced research enterprise. While not every region in the U.S. has access to a top-tier research university, there are pockets of excellent research at most major U.S. R1 and R2 institutions. However, because there is natural attrition at each stage of the commercialization process (much like the startup process) a critical mass of novel, leading, and relevant research activity must exist in a given University. If that bar is assumed to be the ability to attract $10 million in research funding (the equivalent of winning 20-25 SBIR Phase 1 grants annually), that limits the number of schools that can run a fruitful commercialization pipeline to approximately 350 institutions, based on data from the NSF NCSES. A metro area should have at least one research institution that meets this bar in order to secure federal funding for the development of lab-to-market programs, though given the co-location of many universities, it is possible for some metro areas to have several such research institutions or none at all.

Principle 2: Commercialization via established businesses creates different economic impacts than commercialization via startups; each pathway requires fundamentally different support.

When talking about commercialization, it is also important to differentiate between whether a new technology is brought to market by a large, incumbent company or start-up. The first half of the commercialization process is the same for both: technology is transferred out of universities, national labs, and other research institutions through the process of registering, patenting, and licensing new intellectual property (IP). Once licensed, though, the commercialization pathway branches into two. 

With an incumbent company, whether or not it successfully brings new technology to the market is largely dependent on the company’s internal goals and willingness to commit resources to commercializing that IP. Often, incumbent companies will license patents as a defensive strategy in order to prevent competition with their existing product lines. As a result, license of a technology by an incumbent company cannot be assumed to represent a guarantee of commercial use or value creation.

The alternative pathway is for universities to license their IP to start-ups, which may be spun out of university labs. Though success is not guaranteed, licensing to these new companies is where new programs and better policies can actually make an impact. Start-ups are dependent upon successful commercialization and require a lot of support to do so. Policies and programs that help meet their core needs can play a significant role in whether or not a start-up succeeds. These core needs include independent space for demonstrating and scaling their product, capital for that work and commercialization activities (e.g. scouting customers and conducting sales), and support through mentorship programs, accelerators, and in-kind help navigating regulatory processes (especially in deep tech fields). 

Principle 3: Local context matters; what works in Boston won’t necessarily work in Birmingham. 

Unfortunately, many universities approach their tech transfer programs with the goal of licensing their technology to large companies almost exclusively. This arises because university technology transfer offices (TTOs) are often understaffed, and it is easier to license multiple technologies to the same large company under an established partnership than to scout new buyers and negotiate new contracts for each patent. The Bayh-Dole Act, which established the current tech transfer system, was never intended to subsidize the R&D expenditures of our nation’s largest and most profitable companies, nor was it intended to allow incumbents to weaponize IP to repel new market entrants. Yet, that is how it is being used today in practical application.

Universities are not necessarily to blame for the lack of resources, though. Universities spend on average 0.6% of their research expenditures on their tech transfer programs. However, there is a large difference in research expenditures between top universities that can attract over a billion in research funding and the average research university, and thus a large difference in the staffing and support of TTOs. State government funding for the majority of public research universities have been declining since 2008, though there has been a slight upswing since the pandemic, while R&D funding at top universities continues to increase. Only a small minority of TTOs bring in enough income from licensing in order to be self-sustaining, often from a single “blockbuster” patent, while the majority operate at a loss to the institution. 

To successfully develop innovation capacity in ecosystems around the country through increased commercialization activity, one must recognize that communities have dramatically different levels of resources dedicated to these activities, and thus, “best practices” developed at leading universities are seldom replicable in smaller markets. 

Principle 4: Successful commercialization pipelines include interventions at the individual, institutional, and ecosystem level.

As we’ve discussed at length in our FAS “systems-thinking” blog series, which includes a post on innovation ecosystems, a systems lens is fundamental to how we see the world. Thinking in terms of systems helps us understand the structural changes that are needed to change the conditions that we see playing out around us every day. When thinking about the structure of commercialization processes, we believe that intervention at various structural levels of a system is necessary to create progres on challenges that seem insurmountable at first—such as changing the cultural expectations of “success” that are so influential in the academic systems. Below we have identified some good practices and programs for supporting commercialization at the individual, institutional, and ecosystem level, with an emphasis on pathways to start-ups and entrepreneurship.

Practices and Programs Targeted at Individuals

University tech transfer programs are often reliant on individuals taking the initiative to register new IP with their TTOs. This requires individuals to be both interested enough in commercialization and knowledgeable enough about the commercialization potential of their research to pursue registration. Universities can encourage faculty to be proactive in pursuing commercialization through recognizing entrepreneurial activities in their hiring, promotion and tenure guidelines and encouraging faculty to use their sabbaticals to pursue entrepreneurial activities. An analog to the latter at national laboratories are Entrepreneurial Leave Programs that allow staff scientists to take a leave of up to three years to start or join a start-up before returning to their position at the national lab.

Faculty and staff scientists are not the only source of IP though; graduate students and postdoctoral researchers produce much of the actual research behind new intellectual property. Whether or not these early-career researchers pursue commercialization activities is correlated with whether they have had research advisors who were engaged in commercialization. For this reason, in 2007, the National Research Foundation of Singapore established a joint research center with the Massachusetts Institute of Technology (MIT) such that by working with entrepreneurial MIT faculty members, researchers at major Singaporean universities would also develop a culture of entrepreneurship. Most universities likely can’t establish programs of this scale, but some type of mentorship program for early-career scientists pre-IP generation can help create a broader culture of translational research and technology transfer. Universities should also actively support graduate students and postdoctoral researchers in putting forward IP to their TTO. Some universities have even gone so far as to create funds to buy back the time of graduate students and postdocs from their labs and direct that time to entrepreneurial activities, such as participating in an iCorps program or conducting primary market research.  

Student at work in the NOAA CIGLR Lab at the University of Michigan School for Environment and Sustainability

Some universities have even gone so far as to create funds to buy back the time of graduate students and postdocs from their labs and direct that time to entrepreneurial activities, such as participating in an iCorps program or conducting primary market research.

Once IP has been generated and licensed, many universities offer mentorship programs for new entrepreneurs, such as MIT’s Venture Mentorship Services. Outside of universities, incubators and accelerators provide mentorship along with funding and/or co-working spaces for start-ups to grow their operation. Hardware-focused start-ups especially benefit from having a local incubator or accelerator, since hard-tech start-ups attract significantly less venture capital funding and support than digital technology start-ups, but require larger capital expenditures as they scale. Shared research facilities and testbeds are also crucial for providing hard-tech start-ups with the lab space and equipment to refine and scale their technologies.

For internationally-born entrepreneurs, an additional consideration is visa sponsorship. International graduate students and postdocs that launch start-ups need visa sponsors in order to stay in the United States as they transition out of academia. Universities that participate in the Global Entrepreneur in Residence program help provide H-1B visas for international entrepreneurs to work on their start-ups in affiliation with universities. The university benefits in return by attracting start-ups to their local community that then generate economic opportunities and help create an entrepreneurial ecosystem.

Practices and Programs Targeted at Institutions

As mentioned in the beginning, one of the biggest challenges for university tech transfer programs is understaffed TTOs and small patent budgets. On average, TTOs have only four people on staff, who can each file a handful of patents a year, and budgets for the legal fees on even fewer patents. Fully staffing TTOs can help universities ensure that new IP doesn’t slip through the cracks due to a lack of capacity for patenting or licensing activities. Developing standard term sheets for licensing agreements can also reduce administrative burden and make it easier for TTOs to establish new partnerships.

Instead of TTOs, some universities have established affiliated technology intermediaries, which are organizations that take on the business aspects of technology commercialization. For example, the Wisconsin Alumni Research Foundation (WARF) was launched as an independent, nonprofit corporation to manage the University of Wisconsin–Madison’s vitamin D patents and invest the resulting revenue into future research at the university. Since its inception 90 years ago, WARF has provided $2.3 billion in grants to the university and helped establish 60 start-up companies. 

In general, universities need to be more consistent about collecting and reporting key performance indicators for TTOs outside of the AUTM framework, such as the number of unlicensed patents and the number of products brought to the market using licensed technologies. In particular, universities should disaggregate metrics for licensing and partnerships between companies less than five years old and those greater than five years old so that stakeholders can see whether there is a difference in commercialization outcomes between incumbent and start-up licensees.

Practices and Programs Targeted at Innovation Ecosystems

Innovation ecosystems are made up of researchers, entrepreneurs, corporations, the workforce, government, and sources of capital. Geographic proximity through co-locating universities, corporations, start-ups, government research facilities, and other stakeholder institutions can help foster both formal and informal collaboration and result in significant technology-driven economic growth and benefits. Co-location may arise organically over time or result from the intentional development of research parks, such as the NASA Research Park. When done properly, the work of each stakeholder should advance a shared vision. This can create a virtuous cycle that attracts additional talent and stakeholders to the shared vision and can integrate with more traditional attraction and retention efforts. One such example is the co-location of the National Bio- and Agro-Defense Facility in Manhattan, KS, near the campus of Kansas State University. After securing that national lab, the university made investments in additional BSL-2, 3 and 3+ research facilities including the Biosecurity Research Institute and its Business Development Module. The construction and maintenance of those facilities required the creation of new workforce development programs to train HVAC technicians that manage the independent air handling capabilities of the labs and train biomanufacturing workers, which was then one of the selling points for the successful campaign for the relocation of corporation Scorpius Biologics to the region. At best, all elements of an innovation ecosystem are fueled by a research focus and the commercialization activity that it provides. 

For regions that find themselves short of the talent they need, soft-landing initiatives can help attract domestic and international entrepreneurs, start-ups, and early-stage firms to establish part of their business in a new region or to relocate entirely. This process can be daunting for early-stage companies, so soft-landing initiatives aim to provide the support and resources that will help an early-stage company acclimatize and thrive in a new place. These initiatives help to expand the reach of a community, create a talent base, and foster the conditions for future economic growth and benefits.

Alongside the creation of innovation ecosystems should be the establishment of “scale-up ecosystems” focused on developing and scaling new manufacturing processes necessary to mass produce the new technologies being developed. This is often an overlooked aspect of technology development in the United States, and supply chain shocks over the past few years have shone a light on the need to develop more local manufacturing supply chains. Fostering the growth of manufacturing alongside technology innovation can (1) reduce the time cycling between product and process development in the commercialization process, (2) capture the “learning by doing” benefits from scaling the production of new technologies, and (3) replenish the number of middle-income jobs that have been outsourced over the past few decades. 

Any way you slice it, commercialization capacity is one clear and critical input to a successful innovation ecosystem. However, it’s not the only element that’s important. A strong startup commercialization effort, standing alone, without the corporate, workforce, or government support that it needs to build a vibrant ecosystem around its entrepreneurs, might wane with time or simply be very successful at shipping spinouts off to a coastal hotspot. Building a commercialization pipeline is not, nor has it ever been, a one-size-fits-all solution for ecosystem building. 

It may even be something we’ve over-indexed on, given the widespread adoption of tech-based economic development strategies. One significant reason for this is the fact that entrepreneurship via commercialization is most open to those who already have access to a great deal of privilege–who have attained, or are on the path to, graduate degrees in STEM fields critical to our national competitiveness. If you’ve already earned a Ph.D. in machine learning, chances are your future is looking pretty bright—with or without entrepreneurial opportunity involved. To truly reap the economic benefits of commercialization activity (and the startups it creates), we need to aggressively implement programs, training, and models that change the demographics of who gets to commercialize technology, not just how they do it. To shape this, we’ll need to change the conditions for success for early-career researchers and reconsider the established model of how we mentor and train the next generation of scientists and engineers–you’ll hear more from us on these topics in future posts!

What Should Come Next for the NSF Innovation Engines Communities? (And What About Those That Just Missed Out?)

The U.S. National Science Foundation (NSF) announced the inaugural NSF Regional Innovation Engines program awards last week, providing an unprecedented opportunity for communities across the United States. The Development awards, also called Type-1 awards, aim to create fertile soil for larger innovation ecosystems to grow. Each team will receive up to $1 million over a two-year period, and the opportunity to apply to become a Type-2 Engine at the end of those two years. Type-2 Engines can receive up to $160 million over ten years. Over 46 states and territories are represented, and Engines are innovating across all the major critical technology areas including:

Read more about them and check out the NSF’s breakdown of awards here.

With the potential to transform the nation’s competitiveness, the NSF Engines program paves the way for future innovation and growth following the vision of the CHIPS and Science Act of 2022. While the bipartisan cluster-building approach of the Engines program is similar to last year’s Build Back Better Regional Challenge and the newly announced Tech Hubs program, there are some key differences. First, the scope of the preliminary awards is much smaller. Second, the focus is on seeding ecosystems that have potential, rather than investing in ecosystems that have already demonstrated unique competitive outcomes. Third, this program specifically focuses its attention on groups new to government funding and on geographically and socially/economically diverse groups.

For teams that won awards

Congratulations!! Your hard work has paid off! This should be the first step on a journey towards growing an innovation ecosystem that will reshape the trajectory of your economic growth and set up emerging, globally competitive industries. This, however, is no time to rest on your laurels–in fact, preparation for your future Type 2 application starts today. Here are three things you can do to ensure your plan has a better chance of turning into reality: 

Celebrate and acknowledge the achievement

This is a significant accomplishment and your community should be proud! Take the time to celebrate your team’s hard work and dedication. Share the news with your organization, partners, and community, spreading the enthusiasm and generating positive momentum. Post it on LinkedIn! Issue a press release! Hold a launch party! In a field in which the work never ends, we seldom take time to celebrate success–this is a great opportunity to pause and acknowledge the work that your partners and collaborators have done to form this coalition! It’s also a great way to get your broader community excited about the work to come. 

Strengthen partnerships and collaborations with other stakeholders

The NSF Engines program emphasizes the power of collaboration and partnerships. Capitalize on your momentum by actively engaging with regional partners, including other research institutions, workforce groups, capital providers, government officials, corporate partners and entrepreneurs. If your Engines coalition leaves out any of the elements illustrated in the diagram below, one of the best ways you can prepare for the challenging work ahead is to broaden your inner circle. By leveraging diverse expertise and resources, you can create an ecosystem that amplifies the impact of your NSF Engine award–turning this from a proposal to build research capacity into a full-ecosystem approach.  

IMAGE: An innovation ecosystem stakeholder model showing the interconnections between entrepreneurs, government, corporations, workforce, capital, and research.
A stakeholder model of innovation ecosystems

Adapted from: Phil Budden and Fiona Murray. “An MIT Approach to Innovation: Ecosystems, Capacities, & Stakeholders.” MIT Lab for Innovation Science and Policy, October 2019.

Type 1 awards are led, for the most part, by universities or non-profits close to the research bench. Some of them incorporate partnerships with local workforce development groups or government engagement, but not all of them. For a development award to grow into a fully-fledged innovation ecosystem, you’ve got to work on building out the connective tissue between the stakeholders that you have yet to engage. 

Reflect on what extra help you need  

One of the innovative aspects of the NSF Engines program lies in just how much information is available about other awardees and the work they propose. Spend some time reviewing the plans your peers have made, and consider what great ideas might inspire your future work. Reflect, outside of the pressure of an application timeline: What aspects of work did you forget to include? Where might you need to make bigger investments to realize your coalition’s potential? Are there competencies or skills that are missing in your leadership team? In short–where do you still need help? A robust network of partners who have been engaged in ecosystem building across different industries and communities are competing right now for the opportunity to help you, as a part of the Engines Builder Platform. Spending some time in reflection now can help you prepare to tap into these resources as soon as they are available–saving time, and ensuring you put your award to its best uses.

For the teams that didn’t win Type 1 awards 

Chances are, you put just as much time and thought into your application as the winners did. In the competitive funding of ecosystem building, what sets great communities apart is the breadth of their outreach, the quality of their commitments, and their ability to sustain a movement in good times and bad. Now is the most important time to show your determination and belief in the ecosystem your city can build! Here are a few things to make sure that all of the work that went into your application doesn’t simply disappear. 

Secure your matching commitments

If you already started to engage funders in your community, now is a great time to schedule a conversation about what the work looks like moving forward. If you were able to raise matching funds or gather organizational commitments in support of your work, circle back to make sure that those commitments still stand. A little bit of perseverance in the face of adversity can do wonders in helping supportive partners feel a sense of confidence in your work–with or without federal funds. 

Rally the troops

Your partners might be discouraged today, but the only thing that has changed in what you proposed is a little bit of federal money. Think of all of the political barriers you moved out of the way, the relationships you built, and the plans you clarified! Your community’s needs and your country’s needs have not changed in the last week. Now is a great time to remind partners of what is at stake–and encourage their continued engagement. 

DON’T recycle your Engines application for Tech Hubs

It might be tempting to look at the work that your community did to support this application and simply find and replace “Engines” with “Tech Hubs.” There’s nothing legally preventing you from doing this, but such an approach is unlikely to be successful. The expectations, activities, and qualifications are fundamentally different between the Engines and Tech Hubs programs. Engines were meant to propose a “from scratch” solution, while the Tech Hubs program is looking for a recipe ready for your next big family BBQ. While your coalition relationships might help you prepare for the next application, you’ll need to think differently about your ecosystem’s strengths and weaknesses to be successful–not just slap a new title on your old word document. 


Whether you did or didn’t win an NSF Engine Type 1 award, your hard work and dedication to your community is to be commended. Simply fielding an application at this scale takes a significant commitment of time, expertise, and partnership. Embrace this transformative journey and unleash the power of innovation within your region.

This is just one of many opportunities to build your regional innovation ecosystem that are yet to come. And in fact, another great opportunity to build your community was announced today, in the Tech Hubs NOFO. While the nature of the work this next opportunity will fund is similar in theme, it is very different in application. As a result, winning this Engine grant doesn’t guarantee you a Tech Hub, and losing it doesn’t have any bearing on your Tech Hub prospects. Whether your work was funded this week, or remains to be funded in the future, announcements like these shouldn’t be seen as either finish lines or stop signs. There is both more work and more possibilities ahead for all communities trying to build a better economic future for themselves and for the country.

What the CRS Report on Regional Innovation Ecosystems Gets Right and Misses

At the beginning of April, the Congressional Research Service (CRS) released a landmark report outlining the scope of federal investments in regional ecosystems, something we have written about at FAS in the past. This CRS report, ‘Regional Innovation: Federal Programs and Issues for Consideration,’ does an excellent job covering the scope and scale of our massive federal investment in innovation ecosystems. It also raises some important questions that legislators would do well to consider. But there are a few places where deeper and more practice-grounded perspectives on innovation ecosystems are needed for Congress to effectively oversee federal programs. Read on to see what highlights and added thoughts we have for lawmakers who wish to invest in regional innovation. 

The recent expansion of federal support for RIS policies may expand the nation’s innovation capacity by helping regional economies address barriers to entrepreneurship and the development and commercialization of certain technology areas. Source.

CRS Highlights

The report connects investment in innovation ecosystems to investments in the critical technologies that will improve our national competitiveness in the long-term.

This CRS report lays out clearly and in detail, for the first time that we’ve seen, the connection between the legislative intent of a national technology competitiveness strategy (expressed via the CHIPS and Science Act) and regional innovation ecosystems. It also lists the ten identified critical technology areas in the same place. Did you feel a breeze? It’s a collective sigh of relief from ecosystem builders across the country who now have a simple guide to the technologies that they ought to consider building an ecosystem around. The report lists those as:

There you have it, folks. Wise ecosystem builders would do well to consider whether the cluster they’ve been working to build advances one of these key technology areas, and where their competitive advantage lies within these. It’s important, however, that the report explicitly says this list  is a guide and not a requirement, and that communities will likely choose the clusters that they build for many reasons–some more closely tied to local economic conditions and assets. 

What is more, the report recognizes that, “‘regional economic development is often a long-term process,” and thus Congress needs to consider the long view when it comes to funding periods and appropriating money for programs to advance Regional Innovation Strategies (RIS). Such patience is necessary to see world-class clusters develop to their full potential.

We have now seen the writing on the wall–the federal government has invested in regional innovation ecosystems because leaders see them as a path to improving national competitiveness, which they define in terms of these ten critical technologies. The only question left to answer is: how does your region’s work support this vision? If what you’re building isn’t on this list of ten technologies, you’d better have a darn good reason. 

The report sets up a stakeholder framework as a basis for understanding and evaluating innovation ecosystems. 

The report defines regional innovation ecosystems using a stakeholder model. This is very similar to the FAS view–that innovation ecosystems are made up of different stakeholder groups, working together in a complex, adaptive system to advance a shared vision. In fact, that philosophy is at the core of the comments we made to help inform the Tech Hubs and Recompetes programs. The stakeholder groups that CRS identifies don’t fully align with our understanding of successful ecosystems, especially with regards to distinguishing between small and large firms within ‘private industry.’ But the basic idea is important; definitionally, regional innovation ecosystems are groups of people. 

The report rightly calls out the fact that innovation ecosystems aren’t always accessible or inclusive–and that they sometimes create more prosperity for those who are already very privileged. 

As the report outlines considerations for Congress, it rightly acknowledges that traditionally, innovation ecosystems have not been forces for equity and inclusion. Building inclusive Tech-Based Economic Development (TBED) movements requires navigating many layers of systemic wrongs, including (but not limited to) racism, sexism, and their intersectional impacts. The majority of past TBED efforts have failed to produce equitable outcomes for left behind groups. Over the years, too many have written these challenges off as “pipeline problems” without also investing the time and effort necessary to understand the work that equity would require.  

This is why CRS should not frame RIS as just ‘a place-based form of TBED.” This regards the current regional innovation programs as more or less contiguous with past TBED efforts, and fails to fully envision how RIS programs could look different. Modern innovation ecosystems are about much more than just helping those with a Ph.D. in biology roll the next pharmaceutical innovation out of an R1 university lab.

The report questions how agencies might coordinate to ensure that all federally-funded regional innovation ecosystem programs work together to promote innovation everywhere. 

Another aspect of this report that should be lauded is its call for interagency collaboration. Federal agencies should work together to advance a shared vision of renewed national competitiveness. This method of alignment is often called “collective impact.” There are clear steps that agency leaders can and should take, inspired by this framework, to align around shared strategies: they should agree on a common agenda (both Congress and the Executive branch have a role here); they should agree to a shared system of measurement and evaluation; they should consider how to best design the programs they manage to be mutually reinforcing; they should be empowered to engage in continuous, expedited communication that is unburdened by bureaucracy; and they need a “backbone organization” or at the very least, a forum, that can be used to hold all federal stakeholders accountable to this shared plan. 

Additional considerations for Congress

The underlying purpose of innovation ecosystems is to make it easier for new companies to enter a market; entrepreneurship is not an incidental benefit, it is the entire point.

One casualty of the broad political acceptance of cluster development as economic development is that we have lost touch with the reason we build clusters to begin with. We don’t build clusters because more clusters are good. We don’t build clusters because they create jobs (although the productivity increases that they enable often result in job growth). We build clusters because they fundamentally change the dynamics of an industry on a local scale, giving one geographic place the ability to build specialized capabilities to support the growth of companies in a specific industry. Because it is often difficult for those specialized capabilities to be replicated without great expense, that place then has a sustainable advantage in supporting companies in an industry. As they say in the business school world, that place has ‘built a moat,’ that will protect its unique regional assets from the globally competitive hordes. This ‘moat’ is effective because “new entrants” (startups) find it much easier to enter the market when they have access to these specialized capabilities–and they would find it much more difficult and expensive to start the same business in a community without those resources. 

In the context of today’s regional innovation ecosystems, a community’s ‘moat’ might look like a shared, subsidized lab space that allows biotech companies to reduce the cost of developing a technology and completing clinical trials by sharing the burden of building expensive Bio Security Level – 2 labs. BioSTL’s lab facility in St. Louis is one example which reduces local companies’ barriers to entry in the biotech market. It might also look like the innovation matchmaking programs conducted by the Milwaukee Water Council, which connect startups with the Council’s 250 member companies like Molson Coors and Culligan–an advantage that you’d probably put in the “five forces” category of customer power. It might look like the work being done to repurpose Wichita’s legacy aerospace manufacturing capabilities for a new smart manufacturing era through broad worker training, building a new ‘supplier power’ in terms of the supply of labor. Each of these interventions makes it easier for “new market entrants” to succeed and grow. Startups are, fundamentally, new market entrants.

We have forgotten that job creation is an incidental output of the act of starting a business, not the other way around. This is an important distinction, because it leads to the mistaken logic that any job ‘created’ in a place that has a cluster is the same as any other. This logic lumps together startups and larger, older companies as ‘the private sector.’ This is irresponsible because new, small businesses really are the engines here. Research suggests that all net new job creation in the U.S. is attributable to new companies, even to the point that they offset job losses from older companies. This is not to say that larger and older companies do not have important roles in innovation ecosystems—they do. More established companies serve as customers, investors, and acquirers of startups. They often take cues from disruptive startup competitors that lead to improvements in their own productivity and profitability. They employ lots of people by virtue of their size. But to mistake their role as that of generators, and not consumers, of innovation can be very, very expensive

Lumping together the interests of large companies and startups as “the private sector” jeopardizes the effectiveness of our investments in innovation ecosystems, and therefore American competitiveness, altogether. In the future, the CRS should consider revising their stakeholder model to recognize the meaningfully different role of startups as other models do.

Domestic cluster selection decisions are not made in an analytical vacuum. They are organic and social decision making processes that are also path dependent.

The point of federal program evaluation is not to assess whether communities have made the ‘right’ decision, but to assess whether the federal government’s support is making a difference in a given community’s growth trajectory. In its discussion of the need for better evaluation and measurement of federal regional innovation ecosystem programs, the CRS cites a bevy of academic studies published in peer-reviewed journals that speak to how communities ought to choose clusters in the context of a variety of statistical frameworks and analyses. But they reflect academic understanding of the observable factors of an ecosystem, not the day-to-day reality of ecosystem builders working to build coalitions through a consensus process. That renders them incomplete as an analytical tool. 

This is why: Imagine yourself in the shoes of an ecosystem builder. You are likely managing a number of direct support programs for entrepreneurs, attending a bevy of community meetings and working groups on topics ranging from regional economic development to neighborhood disputes, all while trying to maintain a broad professional network, adjuncting a class at your local university, and representing the voice of entrepreneurs in your state legislature with no funding or help (after all, Foundations can’t fund lobbying activity and entrepreneurs are busy running their businesses). When the EDA announces the next grant opportunity (and that your application is due in 60 days), your first thought is likely along the lines of, “Well, I guess I am going to have to fit that into my 1-3 a.m. email answering time.” 

The reality is that many communities and the ecosystem builders that lead them–especially those that do not already have a functioning cluster with rich local support–begin thinking about their plans to build a cluster shortly after they hear about opportunities to fund that work. Their analyses of what cluster to build are not informed by carefully replicated statistical models, pulling from the methodology sections of the papers cited in this report. Should communities be thinking more proactively about these opportunities? Certainly. Do resources and tools exist to support them as they do that work? They do not. The best-supported communities can count on philanthropic funding of consultants from McKinsey, Deloitte, and Brookings to support them as they assemble their plans. Those communities have already won EDA Build Back Better and Good Jobs Challenge and are well on their way to winning an NSF Engine award. Those that remain have won nothing, and have already invested time in two to three failed efforts. Insanity, it is said, is doing the same thing over and over and expecting a different result. 

So how are decisions made in these cities that are not among the shining few? How do they choose what cluster to build, when to pivot and when to stop trying and put their time and effort elsewhere? FAS is working to interview a cohort of the cities that have as yet, been left out of federal funding for innovation ecosystems. We’ll soon publish a series of blogs telling their stories, and drawing insights from their shared experiences. In the meantime, our early returns show that these decisions are more likely to be made behind closed doors in a Chamber of Commerce board room than in consultation with statistical models. It is our hope that this effort can help to inform programs still to come, especially the Recompetes program created in the CHIPS and Science Act. The success of federal investments should be judged on the basis of how much they improve the capacity of a region’s innovation ecosystem, via the capacity of its stakeholders.

Place-based TBED is not sufficient to build an inclusive innovation ecosystem. 

Page 3 of the CRS report explicitly says, “The RIS approach is a place-based form of TBED.” While that might have been true when Congress first began funding the Regional Innovation Strategies Program in 2014, times have changed. Today, building innovation ecosystems that advance American competitiveness and provide opportunity for all requires a much broader approach–one that includes but is not limited to TBED strategies. Ten years ago, many regional innovation ecosystem movements were primarily focused on the effective and speedy commercialization of university technology. That approach and its single-minded focus on the most highly educated, well-credentialed people with entrepreneurial potential has led us to a place where many don’t believe that innovation ecosystems can be inclusive. But there is another way of building inclusive access to innovation for those who have been more often impacted by it. 

Today, workforce development and broad entrepreneurship support are commonly understood to be important added elements of ecosystem building strategies. These are aspects of ecosystem building that are not always well-supported by a TBED approach. But these two strategies are not enough, because alone they create, essentially, two classes of innovation ecosystem participant: one that has the education and support necessary to become “an innovator” and benefit from the opportunity for massive wealth creation, and another, less well-resourced class of ecosystem participant who can be part of “the workforce,” limiting their options for wealth creation. In some ways, this responds to the reality that we see across our country–that access to generational wealth, and thus access to the capital needed to start an innovation-led enterprise, is deeply inequitable. It also reflects deep and systemic inequities in access to educational opportunity, to networks, and even in the group of model entrepreneurs that one can look up to as an example. Given these inequities, building systems that produce more equitable outcomes will be challenging. But it is not impossible and for the good of all of us, we should try.    

This moment, and the emerging thinking around cluster development as a tool to advance not just economic development, but also industrial policy, may just provide us an opportunity to think differently (and more inclusively) about regional innovation ecosystems. What is the primary difference between TBED strategies focused on university commercialization and industrial policy, focused on producing semiconductors, biotechnology, and advanced manufacturing capabilities? It is supply chains–which often include small and midsize enterprises with the potential for high growth and broad wealth creation. It is also commonly understood that these supply chains don’t exist today in the way that they need to. To us, that sounds like a call for the creation of a generation of growth-capable small businesses, grounded in skills like process manufacturing, bench science, and component assembly–skills that are much more broadly distributed across our country than Ph.D. credentials. 

The inclusive innovation ecosystems of the future will require diverse pipelines of university innovators, and workforce development that trains people for good jobs in these critical technology industries. It will also require adequately supporting opportunities to start and grow new small businesses in critical technology industries, inclusive and locally preferential supplier pipelines, and new markets for main street businesses that are an important part of making places vibrant as they attract “the workforce” needed to grow (and in that, new pathways to provide amnesty for, formalize, and grow the informal businesses that are common in systemically disinvested communities). It will require small armies of sole proprietors that support and provide affordable expertise to help companies–whether small businesses or startups–grow, like graphic designers, communications advisors, manufacturing consultants, CPAs, lawyers, tax preparers, and wealth advisors.  

Most importantly, the inclusive innovation ecosystem of the future will require opportunities for people who have traditionally been disenfranchised, experimented on, priced out of their own homes, and left behind in the name of growth and innovation. In order to have truly equitable impacts, in fact, we must prioritize this kind of restitution via wealth creation. New models are emerging from the grassroots, like community wealth-building trusts and requirements for small business opportunities in first-floor retail. Entire innovation districts are being built explicitly around the needs of Black innovators, such as the Sankofa Innovation District in Omaha. Does this sound like TBED to you? Because to us, it sounds like something much richer, more inclusive, more equitable, and more liberating.