Abstract: For many regions of our nation the “old economy”, which we depended upon for decades, either doesn’t exist anymore, or is rapidly fading away. The new economy, the innovation economy, demands a new approach to economic policy and programs. It requires a higher degree of collaboration between government, academia, and the private sector, and the establishment of regional innovation networks, ecosystems, to generate new jobs and wealth. It requires economic development policies that will facilitate the movement of intellectual property and trained human capital from academia to the private sector, and leverages the inventions of our Federal labs and institutions. Further, this process needs to be sustainable. Thriving in the innovation economy is a journey, not a one-time event. It is the creation of a persistent regional collective intelligence that continuously produces the innovations that are the foundation of our competitiveness.
This white paper demonstrates the value of using Innovation Network Mapping and Innovation Genotype™ analysis to inform economic development efforts. These techniques enable economic developers to identify the technological strengths of academic, commercial, and government organizations within a city, region, or state. They enable identification of important technical domains, specific organizations, and key individuals, which if joined in collaborative networks, create a force to accelerate economic development. Finally, when combined with several network-based mechanisms for economic development, it results in the creation of a larger regional collective intelligence to drive job creation and wealth generation.
The Information Technology & Innovation Foundation (ITIF) is a non-partisan think tank with the mission to “formulate and promote public policies to advance technological innovation and productivity to spur growth, opportunity, and progress”. ITIF’s 2012 report “Innovation in Cities and Innovation by Cities”, by Robert D. Atkinson, notes that for economic development, “industrial manufacturing relocations is a zero-sum game, the gain of one region is the loss of another, while the jobs created through innovation is a non-zero-sum game, both the region and the nation benefit.” Further, “Innovation economics shifts the focus of economic policy toward creating an institutional environment that supports technological change, entrepreneurial drive, and higher skills…regions and states need to recognize that the economic development ‘playbook’ they rely on needs to be updated [to] reflect the new realities of the global innovation race.”
The Brookings Institute 2013 report “Patenting Prosperity: Invention and Economic Performance in the United States and its Metropolitan Areas”, by Jonathan Rothwell et al, supports ITIF’s conclusions and establishes a relationship between patentable inventions and economic performance. The study finds:
- While many innovation dynamics are national and boundary crossing and so require federal nurturing, the fact remains that the innovation process turns out to be intensely localized… the innovation economy has an inherent tendency toward geographical clustering.
- Supporting this they found that 63% of patentable inventions were created by people living in just 20 metro areas that are home to 34 percent of the U.S. population, and the top 100 metro areas are responsible for 92% of all patentable inventions.
- Inventions, embodied in patents, are a major driver of long-term regional economic performance, especially if the patents are of higher quality.
- Patenting is associated with higher metropolitan area productivity… patent growth is strongly correlated with better employment opportunities… [and] significantly lower average unemployment rates.
- Average value of IPOs is 5 times higher in metropolitan areas with above average patents per capita.
- Patents per capita are highest in regions with university graduate programs in science.
- Research universities, a scientifically-educated workforce, and collaboration play an important role in driving metropolitan innovation.
- In regions with existing research universities a critical catalyst for innovation is to speed knowledge transfer out of universities and into the regional private economy through targeted programs that seek to actively reveal new intellectual property; streamline its marketing and licensing; and systematically incentivize universities to maximize outward knowledge flow.
The Brookings study was statistically rigorous and controlled for many variables, and yet, it may seem hard to believe that patenting could correlate with so many economic factors, that is, until you understand what constitutes a patentable invention. Under federal statute, any person who “invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent.” Thus, patentable inventions are the foundation of scalable products and services that create jobs and wealth, hence the correlation with so many economic factors.
The question we are asking is how do we go beyond using patents to characterize a capacity for innovation and use them to guide economic development policies that create jobs and wealth for the region? How could patents be used to speed knowledge transfer from universities and government research facilities into the regional economy, and facilitate collaboration between academia and the private sector to produce economic growth? With these questions in mind, and as a “proof of concept”, we analyzed the Innovation Networks and Innovation Genotypes™ of New Jersey Institute of Technology (NJIT), the state of New Jersey, and the Newark metropolitan area.
Innovation Genotype™ Analysis
The concept of an Innovation Genotype™ is based upon a biological metaphor. Just as genes in a genotype express proteins that become organs, which in turn determine an animal’s characteristics, so too, the inventors express inventions that become innovations, which in turn determine the economic and competitive advantage of an organization. By analyzing the genotypes of academic, commercial, and government organizations we are able to identify the organizations that have the intellectual capital and human resource that is the prerequisite for effective collaborations.
Figure 1: NJIT Innovation Genotype (2000-2014)
In Figure 1 the left side of the graph indicates the US Patent & Trademark classes in which NJIT researches have invented during the five year period from 2000 through 2014. The bars on the right indicate the number of patents in the given class. You can quickly see that NJIT has strength in many technical domains with some large concentrations in image analysis, pulse or digital communications, and multiplex communications.
The question becomes, are these strengths relevant to private sector companies of New Jersey? To answer this question we generate the Innovation Genotype of New Jersey and compare it to that of NJIT. See Figure 2 for New Jersey’s genotype.
The state has significantly more patents and they range over a broader spectrum of technical domains, as should be expected given the number of private sectors companies in New Jersey. Because of this we have plotted a single year, the five year period would have generated an unreadable graph.
Figure 2: New Jersey State Innovation Genotype (2014)
Comparison of the state and NJIT genotypes shows there is ample opportunity to find intersections between the universities and private sector companies of New Jersey. We also generated the genotypes of Princeton and Rutgers. As with NJIT there are many intersections between the universities’ genotypes and that of NJ private companies. Finally, we have generated the genotypes of Federal institutions such as NASA and DOE that license their patents and, in some cases, even provide matching funds for the commercialization of their intellectual property. Again there are intersections between these genotypes and those of New Jersey’s private sector companies.
In ITIF’s book “Innovation Economics – The Race for Global Advantage”, by Atkinson and Ezell, they note that a key innovation policy is increasing the flow of knowledge and IP from research universities to regional companies. While this is a laudable objective, the question is which knowledge and what IP should be shared, and with whom to most effectively drive the innovation economy?
Figure 3: New Jersey Class 370 Assignee invention Counts (2010-2014)
To explore this question further out next step was to look for a significant class in the state genotype that was also present in the university genotypes. One such class is 370 “Multiplex communications”. During a five year period 40 New Jersey companies produced 873 inventions from 1,044 inventors in multiplex communications. This is a significant technology domain for New Jersey. The number of multiplex communications inventions per organization is plotted in the figure above.
But we need to go beyond identifying the organizations. While collaborations may be structured contractually at the organizational level, it is the collaboration between individual inventors that produces the collective intelligence. For smaller companies that is relatively straightforward, however for medium and large organizations we need to use Innovation Network Mapping (INM) to identify the critical inventors.
INM uses patentable inventions to reveal the networks of inventors in commercial, academic, and government organizations that are generating the inventions forming the basis of new products and services. INM identifies the inventors that form the “Innovation Backbone™”, that small collection of individuals that drive innovation in their organizations. These are the people that can appreciate new ideas and use them to initiate the creation of new products and services.
Figure 4: Innovation Backbone™ 3 Largest Companies
In Figure 4 we have mapped the multiplex communications innovation networks of the three largest NJ companies. Analyzing these networks we have identified the backbone inventors and highlighted them, and their first degree connections, in red.
In our studies we have found that backbone inventors tend to be either the deep subject matter experts or the internal entrepreneurs that drive the organization’s capacity for innovation. These are the inventors that through collaboration with academia and the state can help create the collective intelligence to ensure a regions success in the innovation economy.
As noted above ITIF finds that a key innovation policy is increasing the flow of knowledge and IP from research universities to regional companies. With genotype analysis and network mapping we have identified the key technical domain in which it would be fruitful to exchange knowledge, i.e. domains of importance to the region’s private sector, the universities and companies that should be involved, and within those organizations the inventors most likely to have a fruitful exchange of knowledge that would fuel more innovation. What we discuss next are four network-based mechanisms to realize the exchange of knowledge and derive value from it.
Collective Intelligence Clusters (CIC)
Collective Intelligence Clusters are all about connecting creative people based on similarities and generating new knowledge based upon differences. The structure of the CIC mechanism is shown in the figure below. The Hub (large blue circle) represents a “neutral” organization, for example a university, not-for-profit, or government organization that has expertise, and intellectual property in relevant technical domains X, Y, and Z. The smaller white circles represent commercial entities, large and small, who may, or may not be competitors, that also have expertise and intellectual property in one or more domains X, Y, and Z.
Figure 5: Collective Intelligence Clusters
Connecting them on similarities creates a cluster (dotted lines/circles) generating a greater collective intelligence for the region and driving invention in that domain.
The 2013 “Report on the MIT Taskforce Innovation and Production” the authors noted the importance of risk pooling and risk sharing. The clusters accomplish this by facilitating the dialogue between the inventors of a domain on the challenges, opportunities, and future direction in that domain.
This is analogous to the structure of the semiconductor industry’s SEMATECH, but with the university or government lab taking the action to pull the commercial entities together. Like SEMATECH these clusters would create knowledge and IP on the common platforms that all competitors in X, Y, or Z need to compete but that no one entity can easily fund on their own. For example the SEMATECH consortium conducts research and development to advance chip manufacturing by jointly solving problems related to new materials, processes, and equipment for semiconductor manufacturing, which all members need to compete in the industry. This is the risk pooling identified as important to innovation by the MIT study.
The CIC structure might vary in terms of formality, ranging from something akin to a community of interest to a formal legal structure such as SEMATEC. A CIC might start out as a Hub facilitated community of interest, that as trust grows, and competition demands, morphs into a more formal legal entity focused on increasing the region’s competitiveness in a given domain. The green box represents the other ecosystem elements required for success, e.g. a link to the financial, venture capital, and private equity communities, legal support, incubators, licensing of university or other IP, etc.
The CIC may even decide to create a common pool of intellectual property to which all members have some rights, or to jointly fund basic research that has potential benefit to all members. It could be an important resource in generating regional innovation roadmaps and identifying the policies and practices that either support or inhibit innovation. The key is to create the collective intelligence that could be used to benefit the region resulting in higher competitiveness, job growth, and wealth.
Innovation at the Intersections (IATI)
The CIC structure also enables the Hub to facilitate finding the often breakthrough, or even disruptive innovations at the intersections. In the figure below the yellow arrows between clusters represent the opportunities for innovation at the intersections.
Figure 2 Innovation at the Intersections
In this example we have labeled the clusters as “Healthcare”, “Nanotechnology” and “Sensors”, three domains that are ripe for innovation at the intersections, however, it could be any collection of domains. The role of the Hub is to facilitate members of the CIC to search for, identify, and then engage in interdisciplinary innovation.
In the example at left advances in nanotechnology might lead to new sensors capable of collecting additional data that could advance healthcare, or nanotechnology might be used to more effectively deliver medications and drive the need for novel sensors to monitor application of the medication and the patient’s progress.
In either the CIC or IATI structures a key role of the Hub is to establish a neutral ground and practice the behaviors that will generate trust between all members. This will include establishing the policies, practices, legal and contractual formalisms, and acceptable behavior patterns that everyone can agree to. It also means that the Hub has to provide leadership by walking the walk.
Co-Development Teams (CDT)
The third mechanism is an adaptation Nike’s successful Co-Development Team model. This mechanism is aimed squarely at commercial innovation and the rapid collaborative creation of jobs and wealth.
Figure 7: Co-Development Teams
In this adaptation of the Nike co-development model, Nike is replaced by any large regional original equipment manufacturer (OEM large blue circle). With the help of the Hub, or from the OEM having participated in the CIC and/or IATI mechanisms, a team of “suppliers” A, B, and C is formed called the Co-Development Team (CDT). The OEM communicates the challenge, which is likely to be proprietary, to the CDT. The CDT agrees to confidentiality with the OEM and further agrees to collaborate to find a solution acceptable to the OEM. In exchange for A, B, and C sharing their knowledge and creating a solution, the OEM offers them the first right of refusal for the OEM’s orders for the solution. The CDT also agrees that if they cannot fulfill all of the OEM’s orders, the OEM can then reach out to other suppliers to have them fulfill the excess orders.
The co-development model is subject to “free-riding”, the state in which one member of the CDT does not contribute. The co-development model allows the other CDT members to turn the free-rider into the OEM who then acts as the judge and jury. If the OEM determines that one member of the team is a free-rider then the free-rider becomes the last supplier to get orders from the OEM, and in fact risks getting no orders at all. This provides a strong motivation to collaborate.
The Hub has many important roles. First, assuming the co-development model will be exercised with many different OEMs and many “suppliers” there is a need for a standard set of policies, practices, contracts, etc. similar to what Nike has developed, but that the OEMs may not have. To facilitate formation of multiple co-development networks the Hub would create a standard package, and the training, for members of the co-development network to understand their obligations under this mechanism.
Another role of the Hub could be to provide the neutral facilities for the CDT members to collaborate in. If subject matter experts from the hub participated in the collaboration they would be in a position to act as “expert witnesses” should a free-rider challenge arises. They would also be in a position to act as a mediator and prevent the free-rider challenge. This could be a valuable service offering of the Hub.
Finally, the Hub could provide links to the other ecosystem elements like venture capital, private equity and banking, and provide the tools and training to successfully run a co-development collaboration.
Technology Enhanced Manufacturing
The fourth mechanism seeks to create jobs and wealth by synergistic collaborations between startups and mature small to medium size manufacturers.
Figure 8: Technology Enhanced Manufacturing
Many small to medium size manufacturers lack R&D and new product development capabilities. Conversely, many startups have creative technologies but lack the ability to manufacture, market, distribute, and service the potential products based on them. The objective is to connect a small to medium size manufacturer with a technology startup to create a synergistic new product or service that takes advantages of each members’ strengths.
This “connection” might be as minimal as an agreement to collaborate in creation of the product or service and to share in the costs, revenues, and profits. Conversely it could be a merger that creates a whole new entity. In this latter case it might involve a venture capitalist or private equity group with a controlling investment in the startup that uses a leveraged buyout of the manufacturer to create the new entity. The point is, there is a large range of potential relationships that might allow the parties to “walk together” before they “run together” thus increasing the probability of success.
Technology Enhanced Manufacturing (TEM) could increase the probability of startups successfully traversing the “valley of death”, thus reducing the risk of investments in them. It would also help to revitalize small to medium size manufacturers who tend to get locked into a single product and end up being disrupted by changes in the industry.
The TEM model can be generalized to link any “innovator” with any “producer”. An example of this is Apple’s App Store where the innovator could be a lone programmer in the garage and the producer is the App Store. In short, it is linking those with ideas to those that can create value from them.
Again there are many possible roles for the Hub to play. The Hub could actively identify the potential manufacturer + startup combinations, and convene them to explore the opportunities. The Hub could again create a standard package of policies, practices, legal agreements and contract forms to facilitate the union. The hub could contribute facilities, researchers and intellectual property in exchange for a piece of the pie.
Regional versus Domain Centric Economic Development
While the examples used above focused on NJIT and the private sector of New Jersey it should be understood that these methods and mechanisms can be applied to any geographically defined region and any combination of private, academic, and government organizations. For example, the analysis can be restricted to a metropolitan area, county, or otherwise defined geographic region. Alternatively, if we assume that certain technical or industrial domains are important to a state’s economic future, for example cybersecurity or genetic medicine, then these methods and mechanisms can be applied at a state level to create a statewide innovation network.
In summary we have demonstrated how an innovation network approach to private economic development creates new opportunities beyond the traditional models, and fosters regional job and wealth creation in a sustainable, systematic, and proactive manner by creating a regional collective intelligence involving the private sector, academia, and the government.
For more information please contact Gary Markovits at firstname.lastname@example.org.
A PDF copy of this post can be found at: Innovation Network based Economic Development – White Paper
 “Medici Effect: What You Can Learn from Elephants and Epidemics”, by Frans Johansson
 See “Managed by the Markets: How Finance Re-Shaped America” by Gerald F. Davis. In the post industrial economy Davis defines the “corporation” as a “nexus of contracts” distinctly different from the vertically integrated corporation as typified by Ford Motor Company of the past. TEM is essentially a nexus of contracts to varying degrees.