HBR: Do ‘lean startup’ methods work for deep tech?

The rise of deep-tech innovation: Over the past decade, deep-tech innovation has emerged as a powerful force in the technology sector, delivering groundbreaking advancements and attracting significant investment.

• Deep-tech innovation harnesses cutting-edge scientific understanding to create previously inconceivable technologies, as exemplified by companies like SpaceX and products such as mRNA vaccines.
• Emerging deep-tech companies are tackling global challenges, with examples including MIT researchers’ discovery of “halicin” to combat antibiotic resistance, Terrapower’s pursuit of sustainable nuclear energy, and Quandela’s advancements in quantum computing.
• These deep-tech innovations have the potential to transform industries, economies, and individual lives on a global scale.

Unique challenges of deep-tech ventures: Deep-tech projects face distinct obstacles that set them apart from traditional tech startups, requiring a different approach to development and investment.

• Deep-tech ventures often involve prolonged research and development periods, necessitating patience and sustained funding from investors.
• High upfront costs are typical in deep-tech projects due to the need for specialized equipment, facilities, and highly skilled personnel.
• Stringent regulatory landscapes present additional hurdles for deep-tech companies, particularly in sectors like healthcare and energy.

Limitations of traditional startup methodologies: Applying conventional startup approaches, such as the lean startup method, to deep-tech ventures can lead to unexpected pitfalls and may not adequately address the unique challenges of the field.

• While traditional tech startups focus on refining existing technologies and reducing market uncertainty, deep-tech startups must primarily mitigate technological uncertainty.
• The lean startup approach, which emphasizes rapid iteration and customer feedback, may not be directly applicable to deep-tech projects that involve developing entirely new technologies.

Adapting startup methodologies for deep tech: Although traditional startup methodologies cannot be directly transferred to deep-tech ventures, certain aspects can be adapted to suit the unique needs of these innovative projects.

• Deep-tech startups should prioritize demonstrating proof of concept to validate their technological breakthroughs and attract investor interest.
• Defining clear milestones supported by compelling data is crucial for tracking progress and maintaining investor confidence in long-term deep-tech projects.
• Forming strategic partnerships with established companies, research institutions, and government agencies can provide deep-tech startups with valuable resources and expertise.

Navigating the regulatory landscape: Deep-tech companies must develop strategies to effectively navigate complex regulatory environments, particularly in highly regulated industries.

• Early engagement with regulatory bodies can help deep-tech startups anticipate and address potential compliance issues.
• Building relationships with policymakers and industry associations can provide valuable insights into evolving regulatory frameworks.

Embracing “learning by thinking” and leveraging AI: Deep-tech startups can benefit from adopting innovative approaches to problem-solving and utilizing cutting-edge tools to accelerate their development processes.

• The concept of “learning by thinking” encourages deep-tech teams to engage in rigorous theoretical analysis and thought experiments before committing to costly experiments or prototypes.
• Artificial intelligence and digital tools can be leveraged to simulate complex scenarios, optimize experimental designs, and analyze vast amounts of data, potentially reducing development time and costs.

Fostering a culture of truth: Creating an environment that values honesty and open communication is essential for the success of deep-tech ventures.

• Encouraging team members to openly discuss challenges, setbacks, and uncertainties can lead to more effective problem-solving and risk mitigation.
• Maintaining transparency with investors and stakeholders about the inherent risks and potential timelines of deep-tech projects can help manage expectations and build trust.

Broader implications for the innovation ecosystem: The growth of deep-tech innovation presents both opportunities and challenges for the broader technology and investment landscape.

• As deep-tech ventures continue to attract increased attention and funding, traditional tech investors and companies may need to adapt their strategies and develop new expertise to effectively engage with this sector.
• The success of deep-tech innovations could lead to a shift in focus towards more transformative and scientifically grounded technological advancements, potentially reshaping the priorities of the tech industry as a whole.