Open Innovation Results Summary

Open Innovation Results

Going Beyond the Hype and Getting Down to Business
by Henry Chesbrough 2020 224 pages
4.07
41 ratings

Key Takeaways

1. The Exponential Paradox: Technology advances rapidly while productivity stagnates

It's an Exponential Paradox. Technology is accelerating, while productivity growth and incomes are declining or stagnant. Something is not right.

Knowledge infrastructure is crucial. To resolve this paradox, societies must invest in three key areas:

  • Generation of new knowledge and technologies
  • Dissemination of that knowledge throughout society
  • Absorption and application of knowledge by businesses and individuals

This three-pronged approach is essential for translating technological advances into tangible economic benefits. Without proper dissemination and absorption, even groundbreaking innovations fail to boost overall productivity.

Historical context matters. The post-World War II era saw significant investments in all three areas, leading to robust productivity growth. However, recent decades have witnessed a decline in such investments, particularly in education and infrastructure. This underinvestment helps explain the current disconnect between rapid technological progress and stagnant productivity growth.

2. Open Innovation: Harnessing internal and external knowledge flows

Open Innovation is a distributed innovation process based on purposively managed knowledge flows across organizational boundaries, using pecuniary and non-pecuniary mechanisms in line with the organization's business model.

Two key components:

  • Outside-in: Bringing external ideas and technologies into the organization
  • Inside-out: Allowing unused internal ideas to be used by external partners

Open Innovation recognizes that valuable ideas can come from both inside and outside the organization. It emphasizes the importance of business models in creating and capturing value from innovation.

Benefits of Open Innovation:

  • Faster time to market
  • Reduced costs
  • Shared risks
  • Access to a broader range of ideas and technologies
  • New revenue streams from licensing unused technologies

However, implementing Open Innovation requires overcoming cultural barriers, such as the "Not Invented Here" syndrome, and developing new processes for managing external collaborations.

3. From Open Science to Open Innovation: Bridging the Valley of Death

Great science doesn't automatically translate into great innovation. And the best use of a new technology is often far from obvious.

The Valley of Death is the gap between scientific discoveries and their commercial application. Open Science principles, such as freely sharing research results, are excellent for advancing knowledge but insufficient for translating that knowledge into marketable innovations.

Bridging strategies:

  • Create institutional structures to support commercialization
  • Develop appropriate intellectual property (IP) strategies
  • Provide seed funding for early-stage development
  • Foster collaboration between scientists and industry

Initiatives like CERN's ATTRACT program demonstrate how open science principles can be combined with Open Innovation approaches to accelerate the path from discovery to market application.

4. The Back End of Open Innovation: Overcoming internal barriers

Innovation results depend on what you finish, not on what you start.

Key challenges:

  • Evaluating and prioritizing external ideas
  • Overcoming organizational silos
  • Aligning innovation projects with business unit needs
  • Securing funding for development and scaling

Successful companies like Intel, SAP, and EMC have developed specific practices to address these challenges:

  • Creating dedicated teams to bridge research and business units
  • Establishing innovation funds to support project transitions
  • Seconding innovation team members to business units during transfers
  • Involving business units in defining innovation challenges upfront

These practices help ensure that promising innovations make it through the "Valley of Death" within large organizations and actually reach the market.

5. Lean Startup and Open Innovation: Adapting for large organizations

Just as startups are not tiny versions of large companies, so too are large companies not simply large versions of startups.

Key adaptations for large companies:

  • Balancing experimentation with existing business protection
  • Modifying MVP (Minimum Viable Product) concepts for corporate contexts
  • Navigating internal processes (procurement, legal, etc.)
  • Securing top management support and resources

Telefonica's "Lean Elephants" program demonstrates how Lean Startup principles can be effectively adapted for large organizations:

  • Reducing time-to-market by 260%
  • Lowering costs per project by 48%
  • Increasing innovation projects by 45% within the same budget

Open Innovation complements Lean Startup by providing access to external resources and knowledge, further accelerating the innovation process.

6. Engaging with Startups: Balancing control and influence

Traditionally, large companies have deployed equity-based models of engagement, such as corporate venture capital. CVC has a role to play, but takes significant time and effort to manage. Equity-based models provide control, but don't scale.

Engagement models:

  1. Equity-based:

    • Corporate Venture Capital (CVC)
    • Corporate incubators
  2. Non-equity based:

    • Outside-in programs (e.g., AT&T Foundry)
    • Inside-out platform programs (e.g., SAP Startup Focus)

Non-equity models allow companies to engage with a larger number of startups more quickly and flexibly. They focus on influence rather than control, which can be more effective in rapidly changing markets.

Key considerations:

  • Align startup engagement with strategic goals
  • Develop clear value propositions for startups
  • Create scalable processes for working with multiple startups
  • Balance the need for control with the benefits of broader ecosystem participation

7. Smart Cities and Smart Villages: Applying Open Innovation to urban and rural development

Smart Villages is a promising new initiative for addressing the needs of villagers in poor, underdeveloped rural settings. However, the three dimensions of generation, dissemination, and absorption apply here as well.

Smart Cities challenges:

  • Limited dissemination of technologies beyond pilot projects
  • Lack of killer apps driving widespread adoption
  • Difficulty scaling solutions across different cities

Smart Villages approach:

  • Focuses on empowering rural communities through digital technologies and Open Innovation platforms
  • Attracts private sector investment rather than relying solely on government aid
  • Emphasizes sustainable, market-driven solutions

Key to success in both Smart Cities and Smart Villages initiatives is ensuring not just the generation of innovative solutions, but also their wide dissemination and absorption by the target communities.

8. Open Innovation Best Practices: Lessons from industry leaders

Open Innovation isn't just a set of practices or tactics. It stems from a mindset and belief.

Examples of successful implementations:

  • Procter & Gamble's Connect and Develop program
  • GE's Ecomagination Challenge
  • Enel's Open Innovability approach
  • Bayer's comprehensive pharmaceutical innovation ecosystem

Key principles:

  • Recognize that most smart people work outside your organization
  • Balance internal R&D with external collaborations
  • Leverage IP strategically, both inbound and outbound
  • Focus on building better business models, not just being first to market
  • Make the best use of internal and external ideas

However, even successful Open Innovation programs can falter if not continuously reinforced and adapted. The case of P&G demonstrates how changing leadership and shifting priorities can impact long-term innovation performance.

9. Open Innovation in China: Balancing government guidance and market forces

Xi Jinping thought includes a commitment to the 'decisive role' of market forces in resource allocation, while at the same time insisting that the CCP exercise overall leadership over all areas of endeavor in every part of the country.

Varying industry outcomes:

  • High-speed rail: Successful government-led Open Innovation resulting in global competitiveness
  • Automotive: Mixed results, with foreign brands dominating despite technology transfer efforts
  • Semiconductors: Two-tiered market, with state-owned enterprises lagging behind private and foreign companies

Key tensions:

  • Balancing top-down government guidance with bottom-up market forces
  • Supporting state-owned enterprises vs. fostering innovation in private companies
  • Attracting foreign technology while developing indigenous innovation capabilities

The Chinese approach to Open Innovation demonstrates both the potential and challenges of combining strong government direction with market-driven innovation. Future success may depend on finding the right balance between these forces across different industries.

Last updated:

Report Issue