Four Models for Corporate Transformative, Open Innovation

January 6, 2023

Abstract

Four models are identified for organizations to pursue simultaneous core growth and transformative innovation leveraging open innovation principles: 1) corporate accelerators —engage with or create autonomous startups; 2) external startup platforms — engage with startups through established third parties, 3) consortia or alliances — leverage resources of peers and emergent players across the innovation ecosystem; and; 4) direct entrepreneurial approach — work from within the organization to develop new units. We identify “innovation maturity” as the key factor to select which model is most appropriate for the organization. Additional considerations include the resources, processes and values of the organization, and the developmental status of the transformative technology. Model choice(s) are dynamic and can evolve over time as the innovation capacity of the organization matures and adapts to change.

Journal of Commercial Biotechnology (2019) 24(4), 23–31. doi: 10.5912/jcb911

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Introduction

As we have argued, transformational innovation is an imperative arena for incumbents – as imperative as routine innovation and improve-ment in the existing business¹. Many organizations include innovation in their stated goals. Principally organizations address innovation through improvements and extensions to current product lines and core competencies.^1,2 While these “sustaining” improvements and extensions are of course important, it’s clear that social, economic and technological dynamics are driving companies down on the Fortune index, or even out of business as they are “disrupted” by others. Those who wish to thrive in this context need to engage intelligently in more transformative innovation that incorporates both new technology and new business models. However, selfdisruption or transformation is easier said than done¹.

Disruptive or transformative innovation in mature corporations poses difficult challenges in resource allocation, processes, and culture as has been demonstrated several decades ago by Christensen and his co-workers^4,5,6. In more mature corporations, creation of a new business model presents all of the same challenges that startups face (e.g., what are the channels, price points, performance parameters appropriate for new markets), as well as other very difficult corporate-specific challenges related to culture and alignment. For example: which budget will provide resources? who will lead the new entity/model? will new customers have to make a choice between the existing and the new business? how will existing customers react to perceived “experiments” with more simplified products? how will shareholders respond? how will existing partners respond? what happens to established employees as the new idea succeeds or fails? How will we exploit the lessons learned from ideas that do not succeed financially? Given all of this complexity, sustained innovation thru current business models is understandably the norm for “traditional organizations.” The transformative path is “the road less traveled”.

Large incumbents must support their existing business while simultaneously innovating. Maintaining while innovating presents a challenge in that maintaining minimizes risk taking, and innovating requires riskmanagement. One important approach is to invite others into the work of innovation by partnering, thereby sharing and diluting the risk. This is the essence of open innovation. Following Chesbrough and Garman, Boni and Moehle summarized many of the best practices of open innovation that have led to success in the evolution of the biotech industry and how those lessons could apply for technology companies in general.^7,8

This article takes a cross-industry perspective that is focused on how to leverage the entire innovation ecosystem to achieve transformative innovation most efficiently — expanding single-company transformation efforts to include novel collaborations with large and small partners. Chesbrough describes these collaborations as “outside-in”, and “inside-out.”⁷We include a more complete description of the benefits of open innovation in later sections of this paper.

Based on our own private sector and academic experiences and additional research, we describe and illustrate four models for transformational innovation and frame them with an approach to model selection.

Models for disruptive or transformative corporate innovation utilizing open innovation in biopharma

The pharmaceutical industry is one that has faced the threat of disruption from the emerging biotechnology industry: The days of the “billion-dollar molecule” to sustain the pharmaceutical industry are over. The industry has responded to this pressure through the formation of open innovation partnerships with emerging biotech companies that specialize in radical new technologies based on genes and proteins. The biotechnology revolution started with VC-backed early stage companies in the 1980’s. These early stage companies were spawning a new industry largely centered in regions with strong academic medical centers and venture capital financial investors, e. g. Boston, San Francisco, San Diego, amongst a few others in the US and worldwide. With academic, investment and corporate resources available, these regions (and others) have generated thriving startup ecosystems. In recent decades, university-driven DNA-based discoveries have spawned biotechnology companies who formed corporate partnerships with big pharma. Many of these companies were ultimately acquired as the pharmaceutical industry sought new protein-based products for their pipelines. That is to say an effective “marriage” between biotech and pharma has created a new industry – the biopharmaceutical industry. This industry is engaged in creating both new underlying technology and new business models. In other words, biopharma is the essence of architectural innovation. Architectural innovation, as described by Pisano and cited in our earlier work on the topic^1,3,generates both new technology and a new business model. This major change has unfolded with at least some of the original incumbent players remaining at the forefront (others have engaged in industry consolidation via M&A). For example, Genentech partnered with Roche and then was fully acquired, as was Foundation Medicine. Other “biotech firms” have continued as independent firm-leading discoveries and drug approvals in select fields like oncology and orphan drugs.

Similarly, observe what is currently happening with the robotics, artificial intelligence and machine learning (AI/ML) technologies that are now emerging from academic research, c.f. centers of excellence located in Boston, Pittsburgh, Silicon Valley, and elsewhere. The automotive industry is taking advantage of these “radical robotic” technology developments with an explosion of venture capital and corporate investment. We are seeing the automotive industry respond by setting up centers in these regions to connect to the traditional automotive industry in Detroit, Europe, Japan, and elsewhere. That saga is still unfolding and transforming the ground transportation industry.

With these examples in mind, and others also under way, the challenge of our present work is to provide a set of models and associated guidelines for the successful pursuit of transformative innovation. Similar challenges exist in other industries as well, and given the challenges involved, we set out to examine and frame approaches for innovation.

Large organizations can work together as consortia, engage with third-party startup-finders, develop their own accelerators, or create transformational innovation directly: The needs of each corporation drive toward different “innovator’s solutions”. Our purpose is to provide a framework to guide the successful selection of the most appropriate path for development and implementation of these transformative innovations through variations on leveraging the collaborative ecosystem through creative use of open innovation principles. The Innovation Dashboard 2.0 is intended to be a guide to the pursuit of these innovations, c. f. Boni and Joseph cited herein¹. We also present various model options for the larger corporations with selections depending on the maturity of their people, processes and problems, as well as the maturity of their innovation cultures.

We propose four models by which companies can engage in open innovation to achieve disruptive or transformational innovation. Corporations live in an ecosystem that includes startups, peers (inside and outside the home industry), universities, 3^rd party innovation platforms, and financial institutions.

This ecosystem invites partnering. In open innovation, the boundaries between the firm and the environment (or innovation ecosystem) are permeable to permit outflow (inside-out), inflow (outside –in) and sharing as appropriate, c. f. Chesbrough and Garman.⁷ Boni and Moehle, in their recent paper titled “Biotechnology Lessons for Robotics: Adapting new Business Models to Accelerate Innovation” have shown that through open innovation (OI) firms can achieve cost-efficient competitive advantage.⁸

Vertical integration (or collaboratively “owning” the entire value chain),
- A lower-cost, lower risk option to commercialization is created by “renting” parts of the value chain from others, e.g. technology, market channels, and customer communication channels,
Leveraging capital-efficient access to resources and processes that are not controlled directly by the firm, including:
- Expertise or skill sets
- Product development and manufacturing capacity
- Clinical development expertise
The firm can gain creative access to “lower cost, value added” capital and expertise, through:
- Partner investments
- Public-private partnerships

The entrepreneurial leadership team minimizes risk and capital to optimize value and build its brand.In developing and validating the business model elements, the firm can leverage the resources and channels of partners across the value chain, and share the value created and delivered with others.

The four models that we describe below, each leverage external players and partners either directly, or indirectly.

We note that companies often think of M & A as an innovation vehicle. For successful transformative innovation that can actually impact the long-term arc of the company, M & A is best approached within one of the models below – acquire smaller companies after a long relationship in an accelerator, consortium or open innovation partnership – in effect a trial marriage (some recent examples include Genentech/Roche, Foundation Medicine/Roche, and ICOS/Lilly).

Each of these four models has its merits – any given corporate might use any or all of them depending on need. Below we describe four models: The peer-based consortium, external startup platforms, corporate accelerators, and direct entrepreneurship from within the large company. See Figure 1 for illustration.

1. Consortia or alliances with peers

This value sharing model basically leverages assets of other partners to exploit the value of internal core strengths and capabilities. For example, IBM is taking a leadership position in the Artificial Intelligence/Machine Learning (AI/ML) space based on their early technology investments and leadership position. They have formed a consortium of players to leverage their core AI/ML technology in multiple industries via the IBM Watson and Cloud Platform. Thus, IBM’s industry leadership position is maintained while they collaborate through open innovation partnerships to disrupt through their breakthrough technologies and leverage the assets of their established service organization.

Watson was originally started as a natural language processing program and evolved to be IBM’s cognitive computing platform. The Watson platform has received significant early market penetration over the last few years. Realizing the importance of working with open source software leaders, IBM launched the Watson Data Platform partner ecosystem in 2016. It was the first cloud-based data and analytics platform to support all the key aspects of data engineering, data science, business analytics and application development. Right from the launch, IBM unveiled three major partnerships focused on healthcare with Apple, Johnson and Johnson, and Medtronic. These partnerships and others resulted in the development of products ranging from clinical trial matching tools to clinical decision support systems to meal recommendation and nutrition guidance applications and serve as a great example of how bigtech firms can leverage the partner ecosystem to disrupt major industries.^9,10,11

We have observed an additional emerging collaborative or consortia model for transformative innovation that might be best illustrated by the approaches being taken by larger organizations in the evolving autonomous vehicle (and perhaps electric vehicles) field. For example, Renault, Nissan and Mitsubishi share an innovation center in Silicon Valley. SoftBank recently announced a major investment into GM/Cruise. Another example is the Lyft Level 5 initiative. Chief Strategy Officer Raj Kapoor indicates that Lyft is focusing on creating an entire new transportation ecosystem around ride sharing and autonomous vehicles.¹²Waymo and Fiat Chrysler have announced a recent partnership for self-driving taxis. Clearly collaborative innovation is being pursued pervasively in this emerging field of autonomous vehicles.

The automotive industry has demonstrated an emergent, collaborative innovation ecosystem that leverages the startup communities in Silicon Valley, Boston and Pittsburgh, with a large number of mature auto industry leaders in both the US and internally. Most notable is that there is an ecosystem developing that links “Detroit” (the automotive industry) with the universities, startups, and accelerators where disruptive innovation began under venture capital funding.

2. External startup platforms

3. Corporate accelerators (direct engagement with, or creation of startups)

Corporations face difficult questions about customer expectations, resource allocation and behavior, i.e. entrepreneurial (experimental) response to opportunity. What if they could simply bypass these questions and pursue transformative innovation through direct partnerships with startups? Corporations can create accelerators that stimulate and support breakthrough innovation through collaborations with external startups, or by creating new startups. The Corporate Accelerator Forum was created to develop and share best practices for corporate accelerators. ¹³ External startups can benefit from this arrangement through access to corporate knowledge, tools, space, channels, and systems (as well as, often, working capital). Internal startups can benefit as well.

Collaboration with external startups

Many externally-focused, corporate led accelerators have been launched by larger organizations in the bio space in recent years. Consider JLabs by Johnson & Johnson Innovation, the Bayer CoLaborator for healthcare; and Illumina Accelerator for genomics.

Illumina, for example, follows a classic accelerator model: startups apply to join a cohort with a specific residency opportunity. They receive funding, space and expertise in return for equity. As a corporate accelerator, Illumina is able to provide unique resources not available to other startup incubators, including Illumina-specific tools as well as expert guidance and partnering. Furthermore, because Illumina plays a special role in the ecosystem around genomics innovation, they can provide their startups with introductions and credibility that vastly enhances market access and investment opportunities. At the same time, the accelerator serves its own strategic goals by partnering with startups that bring Illumina into new spaces for genomics.¹⁴

Startup Creation

Google X was created as a unit of Alphabet/Google to generate “moonshots”. Entrepreneurial projects with high impact potential are initiated and then graduate into the Alphabet organization, “fail fast”, or spin off into autonomous units. Astro Teller, “Captain of Moonshots” at X defines moonshots as the intersection of a big problem/opportunity/challenge with a radically different solution and a breakthrough technology that is achievable in the near future – a perfect trifecta. The challenge is to learn quickly and inexpensively. Failures are viewed as learning experiences. Success can emerge from failure by proceeding to something bigger in a market that will support the growth of a market-leading company^15,16,17.

4. Direct entrepreneurial approach – create transformational innovation from within the organization

Under certain circumstances, corporations can create serial disruptive innovations while sustaining existing business. This means creating and maintaining entrepreneurial behavior within the corporate culture. One could argue that VC-backed organizations like Amazon, Apple, Salesforce and others have disrupted and then sustained innovation repeatedly over the years to become beacons of innovation. Notably, these organizations are led by inspirational founders, i.e., Jeff Bezos, Steve Jobs, and Marc Benioff. Microsoft, Intuit, AirBnB, and Netflix also come to mind as innovative organizations with inspirational founders that have led their industry segments over many years. Such leaders are rare, and even more rare are those who have incorporated others to succeed the inspirational founders.

Other companies have been able to create ongoing innovation with a more distributed, team leadership strategy. One approach is to leverage novel employee or associate ownership models and anchor them into their innovation culture. Examples include Science Applications International Corporation (SAIC) and Gore.

SAIC was founded in 1969 and became the nation’s largest employee-owned research and engineering company, with over $8 billion in annual revenue.¹⁸ SAIC was profitable throughout its history. One of the authors spent a decade as a senior member of the leadership team at SAIC working directly with and under the founding CEO, J. Robert Beyster. During this particularly highgrowth period the company grew 30% per year profitably – and added multiple business units. Key to this success was Beyster’s ability to align the incentives and motivations of the people in the organization. See Boni and Joseph on the Innovation Dashboard in this volume for other elements of SAIC’s approach.

In earlier work, we demonstrated that ownership (both equity and psychological) are key components of successful teams and organizations, c. f. Boni, Weingart and Todorova. ¹⁹ SAIC’s experience reveals how this can work. The company started with a focus on solving problems related to national security for the government; then added new government customers related to national intelligence, space, energy, environment, healthcare; and then transitioned to filling technology-related needs of commercial organizations both nationally and internationally. The company was funded through resources generated from contracts (bootstrapped), not from external, equity financing such as venture capital. An ESOP was formally developed after about the first decade to formalize distribution of shares, and to provide an internal, SEC-regulated market for equity trading to employees (existing, exiting, and new). The company culture during the high-growth era was characterized by principles and behaviors similar to the frameworks in this article.¹⁶

5. Identifying the right model

We have described four models for transformative innovation. Each of these has its merits and tradeoffs. How, then, to choose the right model for any given corporation? The key to this choice is organizational innovation maturity, defined in terms of two factors: 1. Organizational capacity, including resources (e.g., talent, financial), processes (e.g., ideation, customer testing, go to market) and values (e.g., risk tolerance/entrepreneurial behavior, flexibility, field leadership). 2. Transformational innovation capacity (leadership). Change leadership requires the ability to influence others to access the resources and to build a solid platform for transformation. In effect, there are 3 C’s required: communication, collaboration, and commitment.

figure 2: Four Models for Transformative Innovation

A fully mature organization is one where disruptive innovation is embraced: Innovation is fully funded and staffed with long-term commitment, the path from idea to prototype to market to business unit is paved, low-stakes decisions can be made by innovators themselves, lessons feed directly and quickly back into the main business, and “failure” is recognized as a necessary experience in the learning process. Also, open innovation can be pursued where appropriate. For those in the biopharma community, the Eli Lilly/ICOS partnership may be used as an example. Here a joint venture model was employed to commercialize Cialis success to compete with Viagra (even though at the end Lilly acquired the joint venture).

Organizations like SAIC, Google, Intuit, Amazon & AirBnB are fully mature and fully invested in ongoing transformative innovation. Some of these have been discussed in more detail in our companion paper (c. f. Boni and Joseph, “Aligning the Corporation for Transformational Innovation: Introducing Innovation Dashboard 2.0 – see paper in this volume of JCB)They use direct entrepreneurial behavior. This model is fastest at bringing new transformative innovations to life, with greatest impact, and with greatest ownership of the value chain.

For companies earlier on their innovation journeys, in spite of the obvious benefits, direct entrepreneurship requires too much investment, risk tolerance and cost. Less mature organizations can “rent” parts of their innovation processes as a strategy for developing maturity and minimizing risk, albeit while losing profitability as a cost of “rental”. In order to grow to the direct entrepreneurship stage, companies can mature through more mixed forms of innovation, proceeding through the models in order over a time period consistent with the evolution and validation of the underlying technology.

Companies just beginning their innovation journey may have limited ability to engage dedicated resources, innovation processes and a cultural appreciation for risk. Leaders may not yet have the social capital to argue for investment in experiments that could result in true transformation. Such companies can begin with model 1 above: A consortium or alliance. This arrangement leverages their existing incremental innovation practice and extends it through low-risk collaboration. The work of collaborating with peer organizations serves as a learning experience – employees and leaders learn to take advantage of the knowledge, relationships and practices of diverse peers. Costs are shared across members of the consortium or alliance. Innovation reaches farther out from the core business than it would in the absence of the collaboration, but may have limits due to IP considerations, low risk-tolerance and a desire to keep costs low.

As the company matures its disruptive innovation practices, it needs and can tolerate innovation that is farther out along the disruptive path. A company that understands collaboration and is ready to invest more consistently can add Model 2: third-party (external) innovation platforms. Here, investment is specific and limited, the corporation gets to see the work of many different startups representing many different experiments relevant to the corporation’s interest, and the labor of growing and communicating those experiments is handed off to the third party. This allows the corporation to expand its view into innovation opportunity space while keeping risks relatively low. Through connecting with many startups, the corporation can refine its language and strategy regarding innovation whitespace. Costs for platform participation can be higher than consortium participation, but remain low relative to other models because additional employees are not required.

Eventually a maturing company needs deeper access to a more specific group of experiments in the space(s) of interest. Corporate acceleration, allows the organization to create its own bespoke approach to learning and innovation, through engaging (or creating, see Google X example above) independent startups. This requires staff, a strong strategic position on what hypotheses to address, and the organizational maturity to wait patiently for the time required for a new idea to reach the market and drive outcomes. While costs are high relative to consortia or third-party platforms, they remain extremely low relative to typical product development or R & D departments – a small staff can manage multiple cohorts of startups and their associated ideas annually.

At each developmental step, risk tolerance and ability to respond to information increase. The organization can add higher-risk, higher-learning and higher-reward innovation practices to its toolkit. Ultimately a company that is very mature, both in terms of organizational capacity and in terms of leadership, spread their transformational innovation resources across multiple models. The Model 4 companies named above engage in direct entrepreneurial practice, and also in startup acceleration, industry consortia, etc.

Conclusion

We claim that transformative innovation is an imperative for established firms. At the same time, transformative innovation is slowed by the very practices that allow such firms to become established. We have proposed four models that allow companies to engage in transformative innovation at an appropriate level given organizational and leadership capacity.

With this approach, organizations can begin by “dipping a careful toe into the water”, use early experiences to increase their capacity, and progress toward greater and greater innovation opportunity. As the experiments advance, organizations learn more about industry considerations, the state of relevant technologies, how to capture value and how to minimize risk. Our advice is to learn by doing, and to take one step at a time. Our recommendations are supported by study of cross-industry innovations over recent decades.

Consider as an example the evolution of the pharmaceutical industry from the time of the biotechnology revolution that started in the 1980’s with the well-known and transformative Cohen-Boyer discovery, invention of recombinant DNA, and formation of Genentech for commercialization. Pharmaceutical companies (traditionally based on small molecule technology) watched and partnered with emerging biotechnology companies (including Genentech and Amgen) since the pharma companies did not have entrepreneurial cultures and were unfamiliar with the evolving science underlying biotechnology. Biotech companies emerged in 1980’s and were funded by VCs to demonstrate technology safety and efficacy. This approach reduced technological risk through the formation of drug specific partnerships and licensing agreements.

Early licensing agreements (which created awareness)and then partnerships (for more in – depth consideration) emerged for technology and clinical development with funding by Pharma companies (including corporate VC, VC, and eventually IPOs). Selected acquisitions were made at Phase II a & b and beyond for pipeline portfolio development for the pharma market channels – thus entering the “choicephase”. Over several decades, the industries consolidated as both technology and business models evolved. This experimental and progressive form of adoption of new technologies can lead to full adoption of the new approaches over time. For example, Genentech is now effectively Roche’s R&D arm leading the development of a stream of new drugs. Since integration of companies thru M&A is so difficult, this mode of adoption is worth further study and also extrapolation into other industries beyond biopharma.

Beyond biotech, we have noted the emergence of Consortia & Alliances in the autonomous vehicle arena driven by robotics, AI/ML. The “big automotive players” (e. g. Detroit), much like their pharma analogs decades earlier are experimenting to gain expertise and to explore these emerging, “radical” technologies. We are now observing serious collaboration and consolidation in the autonomous automotive sector. Note that the early stages of investment are driven by VC (including corporate VC) investments into startups (a form of risk minimization for the “big players”. As the technology advances, automotive companies have been setting up operations and collaborations in Silicon Valley, Pittsburgh, etc. to be close to the sources of technology and the expertise around that – cluster emergence in the tech space.

This paper is designed to go hand-in-hand with another paper in this volume, “Aligning the Corporation for Transformational Innovation: Introducing Innovation Dashboard 2.0 by Boni and Joseph. Users may use the dashboard/innovation canvas introduced in the companion paper to outline the strategic and tactical character of any given company’s innovation goals.

We have laid out 4 models for companies to consider for adoption based on their own needs, culture, and innovation maturity. The choice of models to be employed should be examined and used as appropriate by each organization. Each experiment drives learning that can go on to transform culture, processes, people and choice of problems to drive long term success.

Notes and references

Arthur A. Boni, Special Edition Editor. (2018). “The Business of Commercialization and Innovation”, Journal of Commercial Biotechnology, Vol. 24, No. 1, January 2018. Also refer to Boni and Joseph, “Aligning the
- Corporation for Transformative Innovation: Introducing Innovation Dashboard 2.0 included in this volume.
For example, a recent industry paper “Benchmarking
- Innovation Impact”, describes self-reports from US Fortune 1000 companies. Respondents dedicate 20% of innovation effort to transformational innovation, while the remainder is dedicated to incremental, sustained innovation, and adjacent markets. KPMG, Innovation Leader: Benchmarking Innovation Impact 2018. Retrieved from https://www.innovationleader.com/ benchmarking2018/
In addition to the terms “disruptive,” radical”, and “transformational,” Pisano suggests “architectural innovation” to designate innovations that seek to create new meaning (and incorporate new technology and new business models). Gary P. Pisano (2015), “You Need an Innovation Strategy”, Harvard Business Review, R1506B, June.
Clayton M. Christensen. (1997). The innovator’s dilemma: when new technologies cause great firms to fail. Boston, Mass.: Harvard Business School Press.
Clayton M. Christensen and Michael E. Raynor M. E. (2003). The innovator’s solution: creating and sustaining successful growth. Boston, Mass.: Harvard Business School Press.
Clayton M. Christensen, Scott D. Anthony and Erik A. Roth. (2004). Seeing what’s next: using the theories of innovation to predict industry change. Boston: Harvard Business School Press.
Henry W. Chesbrough, and Andrew R. Garman (2009), “How Open Innovation Can Help You Cope in Lean Times”, Harvard Business Review, Dec. 2009.
Arthur A. Boni and Christopher Moehle. (2014). “Biotechnology Lessons for Robotics: Adapting new business models to accelerate innovation”. J. Com. Biotechnology. 2014.
Steve Lohr, (October 17, 2016). IBM is Counting on Its Bet on Watson, and Paying Big Money for It. Retrieved from https://www.nytimes.com/2016/10/17/technology/ ibm-is-counting-on-its-bet-on-watson-and-paying-big money-for-it.html
David, H. Freedman (June 27, 2017). A Reality Check for IBM’s AI Ambitions. Retrieved from https://www.technologyreview.com/s/607965/a-reality-check-for-ibms-ai-ambitions/
Laura Lorenzetti (2016). Here’s how IBM Watson Health is Transforming the Health Care Industry. Fortune. Retrieved from http://fortune.com/ ibm-watson-health-business-strategy/
Bloomberg Business Week (2018), “Lyft’s Strategist Wants Self-Driving Electric Vehicles to Save the World”, April 16.
Corporate Accelerator Forum. (2018). Retrieved from http://www.corporateacceleratorforum.com
Illumina Accelerator. (2018). Retrieved from https:// www.illumina.com/science/accelerator.html
This strategy has resulted in a number of Alphabet subsidiaries, including include Waymo, Verily, Capital G, Google Ventures, Google Fiber, Sidewalk Labs, and DeepMind Technologies. These initiatives span the entire spectrum of technologies from robotics, to autonomous vehicles and drones, to wind technology, to biotechnology, to medical devices, to satellites, to artificial intelligence, to urban renewal. All meet the criteria listed as Moonshots, and have been developed with the strategy of “failing fast and cheap” by de-risking the enabling, breakthrough technology and radical solution quickly – the market and business model will then follow. According to Teller, one project (Google Brain, now called the Neural Network Project) has produced enough value for Google to more than cover the total costs of X. Dougherty, C. (2015). Astro Teller, Google’s ‘Captain of Moonshots,’ on Making Profits at Google X. Retrieved from https://bits.blogs.nytimes. com/2015/02/16/googles-captain-of-moonshots-on making-profits-at-google-x/
X Company Website. (2018). Retrieved from https://x.company
Eric Schmidt and Jonathan Rosenberg (2017), “How Google Works”, Grand Central Publishing.
J. Robert Beyster and Peter Economy (2014). “The SAIC Solution: Built by Employee Owners”, 2nd Edition, La Jolla, CA, The Foundation for Enterprise Development.
- Specifically, Beyster and Economy described 8 principles —
  1. Build and sustain a “people-first” culture. Beyster maintained a poster at the entrance to his suite that stated as a constant reminder, “all of us are smarter than any of us”
  1. Support employee freedom, but with high ethical standards. This allowed employees to move quickly and aggressively to identify and pursue opportunities
- Build and maintain exceptional science and engineering core skills within the company iv. Employee ownership at all levels to link reward to contribution
  - Experiment constantly with management structure and with new business investments that are opportunity driven. At the same time, avoid strict adherence to formal plans given the likelihood of unexpected change. Adjust the organization to best address customer need quickly vi. Build a Board of Directors and external advisors who adhere to company principles and to provide independent connections, advice and guidance to the organization thru its growth stages. Connected networks are a key to innovation vii. Create a network of diverse, entrepreneurial leaders and innovators, organized into business units that operate autonomously and are located strategically close to customers, suppliers, subcontractors and stockholders. Together, the CEO, Board of Directors, external advisors and business unit leaders comprise the guiding coalition that drives the vision. viii. Balance investment with reasonable profit to support sustainable, accelerating growth. Profitability and diversity drive success and independence
Boni, Arthur A., Laurie M. Weingart, and Gergana Todorova. (2014). Chapter 7, “Building, Managing, and Motivating Great Teams”, in Biotechnology Entrepreneurship (Ed. Shimasaki, 2014, Elsevier).
Kuang, C. (2016, 8/2/16). An Exclusive Look at Airbnb’s First Foray into Urban Planning. Retrieved from https:// www.fastcompany.com/3062246/an-exclusive-look-at airbnbs-first-foray-into-urban-planning
Open Homes Webpage. (2018). Retrieved from https:// www.airbnb.com/openhomes