Finding collaboration between large companies and startups can be tricky. These are the weird couples in the business world. However, great challenges may require bold solutions as organizations strive to define the best path to improve processes. Successful companies develop innovation models and systems that are suited to their circumstances and reflect their business strategies. They design a mandate for innovation programs, ensuring clear communication of the goals, direction and parameters of these efforts.

This process includes the definition of innovation objectives, the necessary resources, the establishment of a work profile for privileged partners and the guarantee of subjects on which the company’s R&D efforts are clearly defined. Over the past few years, some suggestions have emerged that we are at the start of a new cycle that could carry R&D for the next two to three generations or that we can move from the end of a cycle to a ‘roll out’ phase. – which mainly consisted of creating applications based on existing information and communication technologies – until the start of an “installation” phase during which new technological infrastructures are built.

For this transition to be successful, organizations must understand how to partner effectively with startups to understand the challenges and opportunities that deep technologies can offer. Startups are uniquely positioned to explore areas such as biotechnology, artificial intelligence (AI), and quantum computing because they are designed to be nimble, agile, and creative. But translating that value into a pragmatic corporate giant requires a happy marriage that understands and appreciates each other’s worth. To illustrate this point, consider the three basic attributes that define deep technology in a business context: impact, time and scale, and investment.

Innovations based on in-depth technology can generate enormous economic value, but their ultimate impact extends far beyond the financial realm to a wide range of areas, such as human well-being, sustainability and infrastructure. Deep technology also takes time to move from basic science to an applied solution for real use cases. The time can vary widely depending on the technology, although it is almost always longer than the time needed to develop an innovation based on widely available technology (think a new mobile app). Finally, the financing needs of deep technology companies vary considerably depending on the technology available. Several factors complicate this investment, including market risk and technology risk. Deep tech investors have little or no key performance indicators with which to gauge market traction and potential. Moreover, obtaining the required expertise and the continued adoption of the skills can be a huge obstacle depending on the specialization of the required knowledge.

Before partnerships with startups begin, companies need to think about how they plan to interact with startups, where the decision-making power lies, if they can act and react as quickly as startups expect and where. ‘require, and what types of KPIs would be applied to assess progress. However, adapting the “hard” side of the organization – governance, processes and key performance indicators – is not enough. The values, cultures and goals of companies and startups are different. Legal entities assigned to working with startups may need their own immersion in entrepreneurial cultures in order to better understand what startups are trying to do and the challenges they face. In this way, company representatives will be able to see startups as valuable partners to be championed throughout the organization.

Deep technologies have the potential to make dramatic improvements over the technologies currently in use. But massive investments and considerable effort will be required to bring these technologies from the laboratory to the market. Almost $ 60 billion was invested in the fastest growing deep tech sectors in 2018. Of this figure, $ 18.6 billion went to biotechnology, $ 14.5 billion was invested in AI, $ 11.2 billion for photonics and electronics, $ 8.0 billion for robotics, $ 5.5 billion for advanced materials science, $ 839 million for blockchain and 123 M $ to quantum computing. About 4,000 deep tech startups in the United States accounted for about half of that total investment, but other countries are quickly catching up. Between 2015 and 2018, the compound annual growth rate of private investment in deep technology was 10% in the United States, 47% in the United Kingdom, 73% in Germany, 81% in China, 103% in Korea from South. Worldwide, private investment for the same period had a CAGR of 22%.

There are six steps companies can take to play a leading role in shaping deep tech ecosystems:

1) Cooperate to compete: think beyond the immediate objectives of the company; commit to a long-term vision for the development of the ecosystem as a whole;
2) Identify the capabilities that add value: define what the company can offer to nurture the ecosystem and bring cutting-edge technologies to market – not only money, but also access to customers, data, networks, mentors and technical experts;
3) Do not choose the winners in advance: Deep tech sectors are changing rapidly. Continuously monitor the ecosystem to identify successful startups, applications and business models as they emerge;
4) Blur the lines with partners: Make it easy to navigate deep technology partners into your business system. Define a clear role for them in your innovation strategy, ensure the sponsorship of managers and engage key professions;
5) Streamline decision making and governance: Success depends on a more agile partnership with rapidly evolving startups. Adopt agile working methods;
6) Find what you are not looking for: Develop revolutionary solutions by combining the expertise of previously unconnected fields or industries. Pay attention to game-changing opportunities that offer both economic and social value.

Collaboration can seem like a difficult act, especially if you plan to outsource some of your software development. Yet the opposite is true. Cross-border collaboration in itself presents a great opportunity to experience managing cross-functional teams. Why? Because you can augment your internal staff with the missing expertise – software engineers. By engaging different roles on your end (e.g. product management and sales), you can create a more complete list of requirements for the project, ensure a more even distribution of the workload, prioritize the difference tasks, facilitate knowledge sharing, avoid bottlenecks due to extended approval and speed up the transition for any new team member.

Scientists and entrepreneurs working in the deep tech arena aren’t turned off by big problems – or the time and effort it takes to solve them. Indeed, for many, these problems are part of the attraction. Mitigating climate change, feeding eight billion hungry mouths, and maintaining an aging population in good health are challenges that seem to be worth a career – and big markets that are getting a lot of attention from startups, investors. and businesses.



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