The forthcoming wave of Web 3.0 goes far beyond the initial use case of cryptocurrencies. Through the richness of interactions now possible and the global scope of counter-parties available, Web 3.0 will cryptographically connect data from individuals, corporations and machines, with efficient machine learning algorithms, leading to the rise of fundamentally new markets and associated business models.
The future impact of Web 3.0 makes undeniable sense, but the question remains, which business models will crack the code to provide lasting and sustainable value in today’s economy?
We will dive into native business models that have been and will be enabled by Web 3.0, while first briefly touching upon the quick-forgotten but often arduous journeys leading to the unexpected & unpredictable successful business models that emerged in Web 2.0.
To set the scene anecdotally for Web 2.0’s business model discovery process, let us not forget the journey that Google went through from their launch in 1998 to 2002 before going public in 2004:
In 1999, while enjoying good traffic, they were clearly struggling with their business model. Their lead investor Mike Moritz (Sequoia Capital) openly stated “we really couldn’t figure out the business model, there was a period where things were looking pretty bleak”.
In 2001, Google was making $85m in revenue while their rival Overture was making $288m in revenue, as CPM based online advertising was falling away post dot-com crash.
In 2002, adopting Overture’s ad model, Google went on to launch AdWords Select: its own pay-per-click, auction-based search-advertising product.
After struggling for 4 years, a single small modification to their business model launched Google into orbit to become one of the worlds most valuable companies.
Looking back at the wave of Web 2.0 Business Models
The earliest iterations of online content merely involved the digitisation of existing newspapers and phone books … and yet, we’ve now seen Roma (Alfonso Cuarón) receive 10 Academy Awards Nominations for a movie distributed via the subscription streaming giant Netflix.
Amazon started as an online bookstore that nobody believed could become profitable … and yet, it is now the behemoth of marketplaces covering anything from gardening equipment to healthy food to cloud infrastructure.
Open Source Software
Open source software development started off with hobbyists and an idealist view that software should be a freely-accessible common good … and yet, the entire internet runs on open source software today, creating $400b of economic value a year and Github was acquired by Microsoft for $7.5b while Red Hat makes $3.4b in yearly revenues providing services for Linux.
In the early days of Web 2.0, it might have been inconceivable that after massively spending on proprietary infrastructure one could deliver business software via a browser and become economically viable … and yet, today the large majority of B2B businesses run on SaaS models.
It was hard to believe that anyone would be willing to climb into a stranger’s car or rent out their couch to travellers … and yet, Uber and AirBnB have become the largest taxi operator and accommodation providers in the world, without owning any cars or properties.
While Google and Facebook might have gone into hyper-growth early on, they didn’t have a clear plan for revenue generation for the first half of their existence … and yet, the advertising model turned out to fit them almost too well, and they now generate 58% of the global digital advertising revenues ($111B in 2018) which has become the dominant business model of Web 2.0.
Emerging Web 3.0 Business Models
Taking a look at Web 3.0 over the past 10 years, initial business models tend not to be repeatable or scalable, or simply try to replicate Web 2.0 models. We are convinced that while there is some scepticism about their viability, the continuous experimentation by some of the smartest builders will lead to incredibly valuable models being built over the coming years.
By exploring both the more established and the more experimental Web 3.0 business models, we aim to understand how some of them will accrue value over the coming years.
Issuing a native asset
Holding the native asset, building the network:
Taxation on speculation (exchanges)
Issuing a native asset:
Bitcoin came first. Proof of Work coupled with Nakamoto Consensus created the first Byzantine Fault Tolerant & fully open peer to peer network. Its intrinsic business model relies on its native asset: BTC — a provable scarce digital token paid out to miners as block rewards. Others, including Ethereum, Monero and ZCash, have followed down this path, issuing ETH, XMR and ZEC.
These native assets are necessary for the functioning of the network and derive their value from the security they provide: by providing a high enough incentive for honest miners to provide hashing power, the cost for malicious actors to perform an attack grows alongside the price of the native asset, and in turn, the added security drives further demand for the currency, further increasing its price and value. The value accrued in these native assets has been analysed & quantified at length.
Holding the native asset, building the network:
Some of the earliest companies that formed around crypto networks had a single mission: make their respective networks more successful & valuable. Their resultant business model can be condensed to “increase their native asset treasury; build the ecosystem”. Blockstream, acting as one of the largest maintainers of Bitcoin Core, relies on creating value from its balance sheet of BTC. Equally, ConsenSys has grown to a thousand employees building critical infrastructure for the Ethereum ecosystem, with the purpose of increasing the value of the ETH it holds.
While this perfectly aligns the companies with the networks, the model is hard to replicate beyond the first handful of companies: amassing a meaningful enough balance of native assets becomes impossible after a while … and the blood, toil, tears and sweat of launching & sustaining a company cannot be justified without a large enough stake for exponential returns. As an illustration, it wouldn’t be rational for any business other than a central bank — i.e. a US remittance provider — to base their business purely on holding large sums of USD while working on making the US economy more successful.
Taxing the Speculative Nature of these Native Assets:
The subsequent generation of business models focused on building the financial infrastructure for these native assets: exchanges, custodians & derivatives providers. They were all built with a simple business objective — providing services for users interested in speculating on these volatile assets. While the likes of Coinbase, Bitstamp & Bitmex have grown into billion-dollar companies, they do not have a fully monopolistic nature: they provide convenience & enhance the value of their underlying networks. The open & permissionless nature of the underlying networks makes it impossible for companies to lock in a monopolistic position by virtue of providing “exclusive access”, but their liquidity and brands provide defensible moats over time.
With The Rise of the Token Sale, a new wave of projects in the blockchain space based their business models on payment tokens within networks: often creating two sided marketplaces, and enforcing the use of a native token for any payments made. The assumptions are that as the network’s economy would grow, the demand for the limited native payment token would increase, which would lead to an increase in value of the token. While the value accrual of such a token model is debated, the increased friction for the user is clear — what could have been paid in ETH or DAI, now requires additional exchanges on both sides of a transaction. While this model was widely used during the 2017 token mania, its friction-inducing characteristics have rapidly removed it from the forefront of development over the past 9 months.
Revenue generating communities, companies and projects with a token might not always be able to pass the profits on to the token holders in a direct manner. A model that garnered a lot of interest as one of the characteristics of the Binance (BNB) and MakerDAO (MKR) tokens was the idea of buybacks / token burns. As revenues flow into the project (from trading fees for Binance and from stability fees for MakerDAO), native tokens are bought back from the public market and burned, resulting in a decrease of the supply of tokens, which should lead to an increase in price. It’s worth exploring Arjun Balaji’s evaluation (The Block), in which he argues the Binance token burning mechanism doesn’t actually result in the equivalent of an equity buyback: as there are no dividends paid out at all, the “earning per token” remains at $0.
One of the business models for crypto-networks that we are seeing ‘hold water’ is the work token: a model that focuses exclusively on the revenue generating supply side of a network in order to reduce friction for users. Some good examples include Augur’s REP and Keep Network’s KEEP tokens. A work token model operates similarly to classic taxi medallions, as it requires service providers to stake / bond a certain amount of native tokens in exchange for the right to provide profitable work to the network. One of the most powerful aspects of the work token model is the ability to incentivise actors with both carrot (rewards for the work) & stick (stake that can be slashed). Beyond providing security to the network by incentivising the service providers to execute honest work (as they have locked skin in the game denominated in the work token), they can also be evaluated by predictable future cash-flows to the collective of service providers (we have previously explored the benefits and valuation methods for such tokens in this blog). In brief, such tokens should be valued based of the future expected cash flows attributable to all the service providers in the network, which can be modelled out based on assumptions on pricing and usage of the network.
A wide array of other models are being explored and worth touching upon:
Dual token model such as MKR/DAI & SPANK/BOOTY where one asset absorbs the volatile up- & down-side of usage and the other asset is kept stable for optimal transacting.
Governance tokens which provide the ability to influence parameters such as fees and development prioritisation and can be valued from the perspective of an insurance against a fork.
Tokenised securities as digital representations of existing assets (shares, commodities, invoices or real estate) which are valued based on the underlying asset with a potential premium for divisibility & borderless liquidity.
Transaction fees for features such as the models BloXroute & Aztec Protocol have been exploring with a treasury that takes a small transaction fee in exchange for its enhancements (e.g. scalability & privacy respectively).
Tech 4 Tokens as proposed by the Starkware team who wish to provide their technology as an investment in exchange for tokens — effectively building a treasury of all the projects they work with.
Providing UX/UI for protocols, such as Veil & Guesser are doing for Augur and Balance is doing for the MakerDAO ecosystem, relying on small fees or referrals & commissions.
Network specific services which currently include staking providers (e.g. Staked.us), CDP managers (e.g. topping off MakerDAO CDPs before they become undercollateralised) or marketplace management services such as OB1 on OpenBazaar which can charge traditional fees (subscription or as a % of revenues)
Liquidity providers operating in applications that don’t have revenue generating business models. For example, Uniswap is an automated market maker, in which the only route to generating revenues is providing liquidity pairs.
With this wealth of new business models arising and being explored, it becomes clear that while there is still room for traditional venture capital, the role of the investor and of capital itself is evolving. The capital itself morphs into a native asset within the network which has a specific role to fulfil. From passive network participation to bootstrap networks post financial investment (e.g. computational work or liquidity provision) to direct injections of subjective work into the networks (e.g. governance or CDP risk evaluation), investors will have to reposition themselves for this new organisational mode driven by trust minimised decentralised networks.
When looking back, we realise Web 1.0 & Web 2.0 took exhaustive experimentation to find the appropriate business models, which have created the tech titans of today. We are not ignoring the fact that Web 3.0 will have to go on an equally arduous journey of iterations, but once we find adequate business models, they will be incredibly powerful: in trust minimised settings, both individuals and enterprises will be enabled to interact on a whole new scale without relying on rent-seeking intermediaries.
Today we see 1000s of incredibly talented teams pushing forward implementations of some of these models or discovering completely new viable business models. As the models might not fit the traditional frameworks, investors might have to adapt by taking on new roles and provide work and capital (a journey we have already started at Fabric Ventures), but as long as we can see predictable and rational value accrual, it makes sense to double down, as every day the execution risk is getting smaller and smaller
Technology Transfer is defined as “the process of transferring technology from its origination to a wider distribution among more people and places.” Various communities such as business, academia and government are routinely involved in these initiatives including across international borders, both formally and informally.
The primary desire is to share expertise, knowledge, technologies, methodologies, facilities, and capabilities among governments or universitiesand other institutions to ensure that scientific and technological developments are accessible to users who can then pursue development, robustification, design for manufacturability and exploit the technology into new products, processes, applications, materials or services. There are several types of returns. First, for the stakeholder’s investment in the research itself. Second, for creation of new job opportunities. Lastly, for a new product or service that is likely to impact the health and viability on a global scale.
The U.S. government invests some $135B each year to advance science and technology (S&T) as the basis for breakthrough knowledge development and new innovations, of which around 20 to 30 percent is invested in successful Technology Transfer. The federal S&T budget is a sizeable sum. In fact, the federal laboratory ecosystem provides a home to several hundred thousand scientists and engineers working to solve some of the most significant scientific challenges on a national and global scale. The national laboratories alone annually produce 11,000 peer reviewed publications and over 1,700 reported inventions and 6,000 active technology license agreements. However, the primary mission of the federal laboratory ecosystem is to perform basic research for scientific discovery to, support national defense and other missions, and to perform research and development in spaces where industry is not yet ready to lead.
Unlike both public and private commercial companies, the federal laboratories perform R&D with neither specific products nor services directly in mind. Most work in the public interest, and are often trusted advisors of the government. They understand the mission space, the requirements, and the gaps that need to be closed to improve safety and security of the nation.
The primary customers of the output from federal laboratory research and development efforts are often the federal agencies directly funding the work, since commercial transfer brings private funds to bear to bring products to market with government funded intellectual property inside. It is also an expectation as part of the charter of federal laboratories in 1986 that successful commercial outcomes are resultant benefits of the high-performance research programs.
What are the perceived barriers of Technology Transfer?
There are several constructs that impact success of Technology Transfer, and not least the uniqueness of the Intellectual Property (IP) involved, for example:
Is it leading-edge and breakthrough?
Is it disruptive?
Is it easily “copied”?
Are there competing technologies?
Is there a work-around?
All these factors contribute to the ultimate value positioning opportunity for transfer. In addition, federal laboratories are not evaluated directly by their sponsors on the commercial impacts of their research initiatives, and are in many cases discouraged from “picking winners and losers” in their effort to remain the unbiased and trusted advisors of the government. Due to the nature of their funding, federal laboratory research outputs are atypically complete product solutions and are most often in the early stage of development. Companies to which the outcomes are transitioned must provide additional resources to develop research results into commercial, robust, sustainable products and services, and in the case of any environmental or medical technologies, seek appropriate regulatory approvals and often conduct clinical trials, if necessary.
These additional steps consume further investment dollars, can dilute internal company efforts, and seriously hinder the attractiveness of the transfer opportunity. Furthermore, most successful products combine multiple innovations from a variety of sources to meet customer needs. A single technology license rarely provides a complete solution. These circumstances are especially true for the output from federal programs. The ability to deliver a final product is rare, and outputs are routinely seen as components ready for embedding into other more complex offerings.
Other issues that present barriers, in the case of federal R&D, is that the initiatives emanating from the federal laboratories are perceived to be difficult for companies to access. This is due largely because researchers must obtain funding for all their labor hours, and relatively few resources are available to support sustained collaborations with companies unless they are negotiated within the license agreement itself. Frequently, early stage companies pursuing technology transfer opportunities require assistance and mentorship not available at federal laboratories.
The hope is that some of the newly created and established accelerators and incubators with associated mentoring and guidance make for a more seamless transition route. Often good ideas resulting from the discovery phase at the federal labs are touted as moments away from widespread distribution, yet it rarely turns out to be the case. There is still a good deal of additional development, robustification, design for manufacturability, and even market positioning necessary before an “idea” evolves into a fully-fledged commercial opportunity. To streamline this process, encouraging entrepreneurs, investors and IP licensors to communicate a more perfect set of requirements necessary for “go-to-market” opportunities would eliminate the mismatch of expectations between the research and the commercial communities.
Many existing reports, white papers and articles outline the barriers to successful Technology Transfer, and they inevitably focus on the existence of the “valley of death” defined as the phase directly after discovery yet before commercialization. Many articles describe the “push” perspective as the process by which technology moves from research to commercialization. However, the Technology Scouts, now a common formal position in many established companies, spend most of their time searching for technology in a market “pull” process to enhance and supplement a competitive, long-term company business strategy.
Photo Credit: The MITRE Corporation
Conditions for success
There are three conditions that must be met for successful Technology Transfer. Perhaps it would be insightful to list these “pull” conditions, so that those frustrated by perceived barriers on the “push” side reassess approaches to improve and increase yields for successful transfers. The conditions are as follows:
Alignment of Mission: The technology must enhance, simplify, and supplement the mission and the strategy being pursued by the “scout.” It must be the answer to a problem that the scout is charged with solving by his or her stakeholders. When technology “pushers” try to convince scouts that they should be solving a different problem, the pushers, and the deal, will fail!
Resources and Time to Market: The cost to innovate is immediate and certain, yet the value of the innovation is future and uncertain. There is an entire industry dedicated to predicting the value of future innovation, yet it is not an exact science and the elusiveness of the return and when it will be seen can be a killer!
Company Exclusivity: Technology companies (and their owners) scale quickly when they have a superior value proposition and a sustainable competitive advantage. IP is a critical element in building a sustainable competitive advantage. For technology providers, this exclusivity model is not always good business since investment in IP has a return if and only when an exclusive partner successfully commercializes and scales; if it does not occur, the upfront costs for innovation are not recovered.
What needs to change to improve Technology Transfer outcomes?
Important in the process of Technology Transfer is the need for companies and the federal laboratory scientists to have a shared understanding of the resources provided by federal laboratories. The federal laboratories are tremendous sources of innovation and technical expertise, yet they cannot provide everything a company will need to develop and commercialize a product or technology offering.
Both programs require companies to invest private resources, either as in-kind contributions to collaborations or as direct project funding.
One overarching opportunity, then, is for increased federal investment in collaborations with private sector partners to make the laboratories more accessible to companies with limited financial resources. The Argonne National Laboratory, for example, has supported a realization of this situation by implementing their Executive in Residence Program, where a company employed scientists working in close proximity at the federal lab during the later stages of technical development. The opportunity is then readily positioned for “spinning off” into its own entity—or to support future strategic initiatives in a well-established company.
Additionally, there are other programs that offer extension or expansion pilot programs to support Technology Transfer, such as the Small Business Voucher Program (SBV), the Technology Commercialization Fund (TCF) and the various Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) programs. These programs target collaborations with federal laboratories that enable increased access to the laboratories and facilitate joint projects that can result in new products and subsequently the creation of new jobs. Expansion of other programs, such as the DOE Energy Investor Center and the DHS Transition to Practice (TTP) program, increase the visibility of the innovations and capabilities of the federal laboratories. At the same time, they help raise awareness of the commercialization opportunities that exist in the federal laboratories.
Photo Credit: The MITRE Corporation
Viewing the start-up realistically
If a project is pitched as perfection but delivers great, the project fails. If the project is pitched as good but delivers great, the project succeeds. Start-ups need to reign in how much perfection-pitching they perform. Investors, partners and acquirers need to view start-ups more realistically than their perception of a start-up’s ability to make overnight transformations.
Aligning definitions of success and support at the stages of technology progression is critical to achieving positive outcomes. Mission alignment needs to continually improve. An increasing amount of research is being performed by universities and government so, as a result, there needs to be a protocol developed upfront to allow for alignment with established companies and any start-ups that ultimately commercialize the technology and discover marketing positioning for an output product.
Terms and agreements are also critical components for Technology Transfer because with investment in research, costs occur immediately yet revenue is future and uncertain. Any licensing terms need to share this inevitable risk, and provide the freedom for the licensor to pursue other licensees in cases where a commercialization effort does not meet certain financial goals.
What kind of regulatory/mandatory changes need to take place?
Federal laboratory scientists are often willing to help companies adopt their technologies, as evidenced by the success of the Argonne Laboratory’s Executive in Residence Program, as well as MITRE’s first-hand experience of partnering with them to develop and nurture opportunities. It takes a team to deliver Technology Transfer successfully.
However, federal labs have limited funding available to support engagements with private sector companies unless incorporated directly into the license itself. Mandating availability of increased funding of this kind, as well as reducing the administrative burden associated with accessing those funds, would drive greater private sector engagement with the federal laboratories, and thereby increase the commercial impacts of federal laboratory research and development.
In terms of mandatory changes to facilitate the delivery of and derive benefits from new innovative products in healthcare, for example, supported by a connected Digital IT architecture, investment in a standard interoperability framework would be highly significant. Currently, the landscape is diverse, and pointedly so in healthcare, where hospitals each operate individually with different system installations that limit the ability to interface seamlessly across institutions. Under these circumstances, it is impossible for any new innovations to be easily accessible by all points of the domain due to lack of an interoperability mindset. In addition, encouraging a more patient-centered architecture would lead to an increasingly robust innovation environment for healthcare. In fact, it has been shown that having patients involved in their healthcare improves results and lowers costs.
What can government agencies do to enhance opportunities?
Federal laboratories are ultimately driven by the goals and objectives of their funding agencies and offices, and they remain the bedrock for delivering outcomes for national defense as well as national safety and security. Technology Transfer Offices can help companies access the innovations and capabilities of the federal laboratories by increasing the programmatic value they place on such engagements, and actively encourage or support the interactions. In effect, this approach will benefit their needs, too, by making a product or service readily available, in a robust way, at economically viable price points.
There are also more likely to be further and future advancements of the technology available in due course driven by the product development efforts of the commercial company. This outcome would undoubtedly reduce sustainability costs for the agency as their needs would continue to be serviced directly from private funds. As noted earlier, extending and expanding programs such as SBV and TCF would likely increase private sector engagement with the federal laboratories.
Government agencies also can help with mission alignment. A good example of this approach was the space race in the 1960s. There are also several other examples where the government has been the catalyst for successful technologies that generate commercial breakthrough opportunities. Agencies should be setting goals and metrics and providing financial incentives for academia, federal labs, and the private sector to work together to meet these goals. Nevertheless, the government needs to avoid picking winners and losers because only the market can determine the future value of any technology. Once the “macro” level goals are set for alignment, individuals (scientists, innovators and engineers) need to be trained on the behavioral science of how better to understand the “micro”’ level needs of the others in the chain.
The NSF (National Science Foundation) I-Corps and the Fed-Tech program deliver value by helping innovators and entrepreneurs understand product market fit through experiential training in discovering needs. Similar programs, designed to align fundamental research to commercialization, would go a long way towards improving the situation. The Innovation Research Interchange (formerly known as the Industrial Research Institute) is helping to support match-making initiatives through its Federal Laboratory Activity Group (FLAG). Specific areas of focus are: Energy/Sustainability, Advanced Materials/Manufacturing, Cyber Security/Data Analytics and Robotics/Automation.
The government makes a good partner because it is a natural convener of new discoveries, can sustain much longer term strategies compared with industry, and is not under the demands of shareholders. Rather, it is often neutral and can enable even typically competitive organizations to collaborate for the greater good of society. While governments are not expected to over-regulate, their ambiguous guidelines can sometimes lead to fragmentation if the industry does not reach consensus, as evidenced by the lack of interoperability in the healthcare segment. If the government actively engages industry, then further fragmentation would be avoided and the associated longer term problems likely minimized.
What can and how can we help entrepreneurs to aid the process to success?
To support the entrepreneurial process, federal laboratories are encouraged to focus on some new approaches, namely:
Increase visibility of their capabilities and ensure innovations are readily available
Provide clearer guidance on what the laboratories can provide and, equally important, what they cannot provide
Host a series of technology focused workshops to raise awareness of available programs and opportunities
Award grants to entrepreneurs to support their programs
Create more opportunities for innovation bridges, so that challenges are solved together from the onset
Supporting entrepreneurs to quickly achieve a “Yes/Go” or “No/Go” pitch to future investment is critical. For example, a start-up entity often has 12 to 18 months of runway, during which time it needs to quickly succeed or fail (and pivot, if appropriate). With limited resources, the team is unable to spread itself thinly and therefore must remain focused on its target goal. A “maybe” response is a killer; it results in burning resources and does not help entrepreneurs to understand clearly if their product is providing true value. Being harsh but factually quantitative enables a better outcome for all.
Entrepreneurs themselves fall into distinct groups as determined by their efforts. Entrepreneurs focus on target-market fit and sustainable advantages of their products to attract investors. They need exclusivity yet have limited funds for licensing. For many start-ups, future equity is their only currency, so they need financial resources to help solve the problem.
What can well-established companies do to improve interaction, integration and chances of success?
Investing time with the federal laboratories to learn more about ongoing research activities and outputs is one way to improve outcomes. Most research results are complex and are “works in progress.” While it is relatively rare to find a nearly commercially-ready technology solution in the laboratories, the laboratories have deep expertise and capabilities and can help companies quickly solve complex challenges.
Additionally, there is the need to resist the urge to negotiate the terms and conditions of collaboration agreements with federal laboratories. Most laboratories can quickly implement standard agreements, yet must seek multiple levels of federal approval for non-standard agreements, significantly increasing the time required to put an agreement in place. Furthermore, federal laws and policies limit the extent to which partnering agreements can be substantively changed, so that lengthy negotiations rarely result in significant changes in agreement terms.
Defining success at the stages of discovery, development, deployment and distribution are key to having projects reach positive outcomes. Without this expectation setting, project timing will be misaligned and it will be challenging to realign the stage-appropriate support to achieve real business value.
Again, the three conditions associated with barriers to success apply—namely, alignment of mission, resource needs and time to market, together with company exclusivity. However, where a start-up may be heavily dependent on IP as a sustainable competitive advantage, large companies have other factors contributing to that competitive advantage, for example, brand, supply chain, scale, and channels. Large corporations will tend to “engineer” around patents in their commercialization process. Acquisition of IP will occur through licensing if it is core and foundational, and they cannot overcome the barrier. They will also only buy/license IP in times of disruption or transition. Generally, this outcome is achieved by acquiring a start-up that has commercialized a proven product market fit. In effect, established corporations are looking for products, not research, when they need technology.
How can the VC communities and start-ups take advantage of outcomes from federally funded programs?
Interactions between venture capital (VC) communities and start-ups present several areas for improvement. For example, enabling them to interface and work routinely with universities and other programs would increase their familiarity and comfort level with federally funded initiatives. However, it is also important to note that writing a successful grant application is very different than preparing a strong business pitch deck.
Encouraging portfolio companies to visit and engage with the federal laboratories to learn about available technologies and collaboration opportunities would certainly drive enhanced relationships leading to technology transfer. Allied Minds is one such company that routinely interfaces with several federal entities with the primary objective of accessing and gaining exposure to early stage IP. In the main, Technology Transfer offices are always happy to coordinate visits from prospective collaborators.
VCs are essentially risk managers and are unlikely to accept more risk to increase the flow of IP. VCs need to see their investments explode—or fail fast. Return on investment from Technology Transfer extracted from federal labs would undoubtedly increase if the lab can define the path to commercialization, even if they cannot execute that path due to their mission. Quantified data linking research to customer will attract VCs. As such, NSF I-Corps, Fed-Corp and DHS TTP initiatives are helpful programs. If technology has an assessed product market fit through a customer discovery process using scientific methods, in addition to the science of the invention, there is less risk. VCs will take advantage of this type of program in their investment decisions.
There is currently a mass of untapped technical potential and IP sitting on shelves within the federal laboratory ecosystem that has been funded by federal agencies. We know that those concepts which do make it to market, such as laser technology from the 1960s, have compelling impacts, solve national and global problems, provide a catalyst for greater success by industry alone, and drive the economy and GDP of the country. The laser is only one such technology, the Internet is another—it started life at the Stanford Research Institute (SRI). And there are also many technologies we rely on today that emanated from the space race.
The results of all these programs are generally clearly visible, as compared with private investment where only those making the investment typically benefit and the outcomes are less visible to society. The advancement and discoveries of industry, therefore, have only limited impact as a result, compared with when the outcomes are delivered from government funded programs. Recommendations to further support unlocking the potential from federally funded R&D are as follows:
Increase funding to support the transition of technology to entrepreneurs
Enable federal laboratories to better understand business world needs
Engage teams with market positioning early on so that modifications can be built in accordingly
Create more programs like DHS and TPP to showcase early, impactful technologies
Encourage and find ways to showcase opportunities at all of the federal labs
With these modifications and implemented changes, there will likely be:
Increased technology transition to entrepreneurial and well-established companies
New opportunities generated for discoveries that make an impact on the national and global landscape
Economical and viable options delivered to support widespread government use of a technology
Technology advancement at private expense that will be available to government
A return on the initial investment by enabling economic development from growth of a new industry