Despite our dire need for more solutions that are fundamentally transformational, advancing technologies beyond the lab can be a daunting transition for any scientist-entrepreneur.
In this two-part session, we introduce an overarching reference framework for deep tech ventures, contemplate the characteristics that make for a robust ecosystem around them, and dive into the journey that have taken our two start-up Finalists from our Hello Tomorrow Asia Pacific Challenge 2021, Takachar and AgroMorph, from advanced technology to productisation.
Here are some highlights from the session that we hope you’ll find useful!
Deep Tech: Commercialising Science and Engineering
From Research to Solutions
Validating the business requires securing investors and corporate partnerships. It’s hardly measured by customer response or sales, because the research seldom makes it to market for at least a couple years.
The commercialisation of research depends on smoothly functioning innovation ecosystems—combinations of individuals, companies, infrastructure, and policy linked through formal and informal networks.
This is underpinned by the concept of open innovation, where collaborations are crucial.
Go-to-Market Challenges Faced by Deep-Tech Start-Ups (vs Tech Start-Ups)
Time-to-market: Long development cycles are a result of high R&D intensity (among others), often spanning several years before an initial product is ready (vs. a few months for a startup developing software). Since the technology is novel, training partners and determining modes of distribution can be challenging.
Financing: Capital-intensive from early on and for an extended period, (vs. funding needs in growth stage for customer acquisition, e.g. Uber) especially because infrastructure is expensive.
Industrialisation: Complex turning experimental POCs into industrialisable product (vs. needing just additional servers/ users to scale). Technology risk and complexity arise because technologies applied are often at low technology readiness levels.
Characteristics of Successful Deep-Tech Ventures
They focus on solving fundamental issues rather than on optimising or incrementally improving existing innovations. They are problem-oriented rather than technology-driven.
They leverage the convergence of disruptive technologies (96% mobilise at least two). This isn’t intentionally engineered, but is a result of the technologies being developed as being the best possible solution among all possible solutions for the problem they are trying to solve.
They develop mainly physical or hybrid products and not just software or marketplace platforms. They are shifting the innovation equation from bits-only (digital) to “bits & atoms” (physical). They build on the ongoing digital transformation and the power of data and computation to mostly develop physical products, rather than software.
Their growth model is based on central positioning within ecosystems (research, governments, investors and corporates) rather than growth based solely on massive investor funding.
Key Milestones From Research to Market
Traits of a Deep Tech Ecosystem
It is a multi-entity association. They involve more types of players from more diverse sources, both public and private, and each with their own needs and priorities.
Characterised by dynamic structures and relationships, where participants come and go, creating new kinds of relationships that are not always formal.
Rely less on a central orchestrator and more on multifaceted interactions among participants.
Money is not the primary currency of exchange. Knowledge, data, skills, expertise, contacts, and market access are also currencies that link ecosystem players.
Evolving Needs and Priorities
As startups mature towards commercialisation, they tend to need expertise and lab and testing facilities less, and talent, visibility, and access to the market more.
While corporations and investors seek financial returns, in the early phases of technology development, they might have other more strategic priorities, such as access to knowledge in a particular technology or the desire to have a stake in the game in case things start to take off. And then when the prospects for commercialisation become more concrete, the focus shifts to financial goals.
Because of these evolving needs and priorities, the nature of collaboration also changes, and companies deploy different tools and models for their ecosystem participation.
Science Entrepreneurship: From Lab to Market
Your customers/ users are your best mentors. Talk to them early, and keep them close throughout your development cycle - build their feedback into your iterations.
Focus on understanding the customer and getting their insights. It will help you narrow down your functional requirements and be the basis for technical questions like: What does technical performance of our machine mean? What should be the parameters against which our equipment should be judged? How should we plan out a product development cycle over the next five to 10 years?
Develop empathy for your customer and use it as your driving force
Embrace customers that push you beyond your comfort zone. Even if you don’t win their business in the end, you will always learn something new about the problem/ solution/ product.
Advice for New Startups
Find the core strength of your business, but don’t be afraid to branch out.
At the earliest stages, focus on building fast rather than perfectly. You don’t have to have a fully functioning prototype before approaching your customers. Identify aspects of your product your customers value the most, and test those subcomponents first.
Reference/ benchmark against a peer/ competitor, if any, that is leading in your field.
It doesn’t hurt being a second mover as long as you substantially value-add to your customers in a more-than-slightly-incremental fashion.
Harness a good sense of your production cost, at pilot and at scale.
Consider low hanging fruit opportunities even if that isn’t the biggest/ ideal market you’d be targeting later. Enter the market faster and test your product in real-world conditions to gain time to address much of the technical and business risks associated with other applications that you may want to target in future.
Solicit mentors who can share objective advice, and who perhaps offer different perspectives than you.
Failure is a great teacher - don’t fear it!
Sources of Funding
Impact investors (e.g. CDC group in UK, and Delphos Group in the US). Just understand that you will need a network to get in and the lead times are long.
Grants (e.g. government grants, R&D grants)
Competitions (e.g. Hello Tomorrow Challenges)
Pre-finance from large corporates
Families and friends
Grow to be what you seek in the ecosystem
Startups who’ve made it (or have battle scars and stories to tell) have so much to offer to the ecosystem. Be a mentor to new, budding deep-tech entrepreneurs - it’s a precious, yet under-supported community!
Special thanks to our speakers:
Whether you managed to attend this session or not, let us know how we fared and the changes you'll like to see around here. Give us some candid feedback here.