Blog Article

What is Deep Tech?

The term “Depp Tech” was coined by Swati Chaturvedi, co-founder and CEO of investment firm Propel(x).

According to its own definition, these are “companies that are founded on a scientific discovery or a genuine technological innovation” and that, in addition, consider making the world a better place.

However, a company that markets a traditional product or service applying existing technology (such as Uber or Cabify) is not the same as a true technological and scientific advance, with business implications. To distinguish both phenomena, the term ‘deep tech’ has been coined, “Tecnología Profunda” in Spanish.

The ‘deep tech’ promise solutions in fields of all kinds, using techniques such as “big data”, “artificial intelligence” or “deep learning” with a more scientific approach than is customary to see in technology companies that usually dominate the media.

Backed by the rapid growth of high-risk venture capital funding, small companies often win by focusing on solving critical, large-scale problems and exploiting a combination of maturing digital technologies (such as AI and cloud computing) and emerging physical technologies (synthetic biology and architected materials, for example). This convergence is the essence of deep tech innovation.

For incumbents, waiting on the sidelines to see which technologies, or combinations of technologies, develop high-impact applications is not a practical option. They will find themselves playing catchup. Any existing business that has set ambitious goals, such as improving sustainability or building resilience, will need to incorporate one or more deep tech solutions sooner rather than later. This includes companies that produce a physical product or that support a business that produces a physical product, especially if they have made net zero commitments to their customers and shareholders.

But deep tech presents established companies with a twofold challenge. Evaluating the potential of advanced technologies is tough, and finding a winning combination of market need and emerging technology that meets it is harder still. Even the most successful venture capitalists place more losing bets than winning ones.

So, how CEOs can size up the relevance of deep tech for their own organizations.

Identify the Opportunities

A good way to start is by taking a page from the startups and adopting a problem-centric approach. Rather than focusing on the individual technologies themselves, it can be more productive to think about the major needs and problems in business and in the economy that emerging technologies could solve. Venture capital investor Mike Maples calls this “backcasting”: starting from an imagined future state and working backwards to envision how to get there.

The think tank RethinkX has used this approach to illustrate what a global economy based on sustainable energy systems, food production, and mobility could look like in 2035. Its work highlights the idea that technology-driven changes in agriculture or mobility would ripple throughout the global economy, improving sustainability while fundamentally altering value chains and disrupting incumbent systems and players. For example, a switch to proteins manufactured with precision fermentation (a “microbrewery” for cell-based meat) and vertical farming radically changes the requirements for water usage, shipping, and energy.

Sizing the Opportunities

We estimated the total market size of these opportunities in nine relevant economic sectors: transport and logistics, automotive and aerospace, energy, chemicals and basic materials, agriculture and food service, consumer packaged goods and cosmetics, engineering and construction, industrial goods, and fashion and apparel. Since each opportunity area has a different degree of impact in each sector, we used an application-centric view to size the potential value that deep tech can create, integrating the size of the sector, the relevance to sustainability, and the potential for deep tech to resolve (or otherwise alter) tradeoffs in profitability and sustainability. The full potential impact in each sector may not be immediately apparent because systems have interdependencies; a deep tech-catalyzed change in one sector may ripple into many others.

Companies that assess opportunities accurately can jump ahead of the disruption new technologies will cause and become disruptors themselves. Unilever is partnering with food technology company ENOUGH (formerly 3F BIO) to use ENOUGH’s zero-waste fermentation process to expand Unilever’s range of plant-based meat alternatives. Ten major airlines in North America, Europe, and Asia have joined BCG in the Aviation Climate Taskforce, a global coalition that seeks to accelerate breakthroughs in the emerging technologies that can help the industry achieve net-zero emissions. These initiatives share a common approach of deconstructing value chains and rebuilding them around new opportunities enabled by technology.

Unlocking Value with Deep Tech

Each of the nine economic sectors we highlight has big technological, economic, and structural barriers to the adoption of sustainable business practices. Actions in every sector have an impact on other parts of the system, which leads to further constraints that limit the opportunity for sustainable growth and value. For example, product performance and price considerations impede the reduction of emissions and use of sustainable materials all along the value chain, from sourcing to manufacturing to shipping and distribution. Manufacturing processes require unsustainable energy infrastructure and use, and sustainability goals are incompatible with current product or process design.

Some companies are already using converging technologies to remove barriers and open doors to substantial value creation. John Deere, for instance, is applying a combination of sensors, data from the Internet of Things, and AI to improve the performance of its agricultural equipment products, helping cotton farmers save nearly $50 an acre in production costs and reducing herbicide usage with a new data-based business ecosystem. In the process, Deere and others have sparked a revolution in “precision ag.” IBM’s RoboRXN autonomous lab combines AI, robotics, and cloud computing into a new approach for materials discovery.

Four Levels of Deep Tech Ambition

In a series of papers in 2015 and 2016, energy and climate scholar Arnulf Grubler and his coauthors posited four levels of technological change, in order of the complexity of the technologies involved and the ability to scale the solutions they unlock.2 These include tech substitution, system upgrade, system transformation, and system of systems (SoS) transformation.

• Tech Substitution. These changes, drop-in replacements for technologies in an existing system, involve one or more technologies that can scale fast (within a few years) but are generally incremental in terms of impact. Speed to scale depends on technology discovery and maturation.
• System Upgrade. This involves improving an existing system, with moderate potential for change and adding value. Examples include building cars around sensors and software or adding solar panels to houses. This level also involves limited complexity and fairly rapid scaling, which is limited only by capital availability, the ability to integrate, and product release cycles.
• System Transformation. This refers to altering the system with higher potential for value. Examples would be constructing a charging network for EVs or designing a smart grid that includes the capabilities for power storage and local solar. Complexity and time to scale increase at this level; a 5- to 20-year time frame is not uncommon given the need to manage interfaces and build a development stack shared across the ecosystem.
• System of Systems (SoS) Transformation. This level of change entails building an SoS infrastructure. It involves rethinking, redesigning, and then implementing an entirely new approach to a core capability or need, such as electrifying the entire automotive sector and modernizing the power grid at the same time. Institutional and societal adoption require time; historically SoS changes have taken 20 years or more, although digital adoption has moved faster.

How to Start

In forthcoming pieces in this series, we will outline in more detail how traditional companies can play in deep tech and the strategies they’ll need to be successful. For now, forward-looking CEOs should ask themselves the following questions.

• How can we reimagine our future products or services, operations, and supply chain to create great customer experiences and growth sustainably?
• Working backwards from that future, how might emerging technologies overcome constraints or alter the value chain?  
• What are our unique capabilities to define structural incentives, mitigate risks, resolve key frictions, or provide synergistic capability to a partner?
• Which other companies, venture funds, or deep tech startups are actively attacking common constraints to sustainable growth that are similar to the ones I face, and what approaches are they taking? 
• Is our R&D organization and corporate venture arm taking a strategic, knowledge-centric, and systemic perspective to creating and preventing disruption?

Remember that the rapid innovation cycles built around increasingly accessible technologies mean that disruptive capabilities develop more quickly than ever before. This adds urgency to the related question of whether companies want to be the cause or the victim of disruption.

John Paschkewitz, Maxime Courtaux, Vinit Patel, François Candelon, Antoine Gourévitch. (2022). What CEOs Need to Know About Deep Tech. Recuperado 03 de Junio del 2022 de https://www.bcg.com/publications/2022/ceos-need-to-know-about-deep-technologies

BBVA. (2018). ¿Qué es el ‘deep tech’?. Recuperado 03 de Junio del 2022 de https://www.bbva.com/es/que-es-el-deep-tech/