White Paper Supporting Ecosystem Engagement for Sustainable Innovation empowered by IoT and Edge Computing

AIOTI WG Innovation Ecosystems prepared a White Paper Supporting Ecosystem Engagement for Sustainable Innovation empowered by IoT and Edge Computing.

The full document can be found here.

The European industry sector has undergone a drastic development in the last years, following the advent of the digital transformation, green transformation, manufacturing 5.0. Knowledge and technology are now more accessible than it was a decade ago, and this has fostered its interest for looking for applications and business models for those new technologies and knowledge from an industrial and educational perspective.

In the context of the AIOTI Working Group Innovation Ecosystem, we see a strong lever for sustainable innovation empowered by AIOTI through efficient ecosystem engagement and orchestration– with the target to efficiently combine the expertise and resources for increasing the number of innovative solutions being adopted and not only defined. Hence, IoT and Edge Computing innovation ecosystem should connect digitally to the rest of sector and regional innovation ecosystems in Europe from the tech transfer office inside universities to the industry, accelerators networks, universities, research centres, start-ups, SMEs, corporates and public organizations. The innovative and entrepreneurial objectives of the innovation ecosystem will lead to a new line of potential innovation and entrepreneurship activities from universities (as hubs of the ecosystem) into the European industry and society, by establishing and fostering new collaborations and partnerships, providing the necessary tools, methodologies, and activities, and also taking advantage of a digital platform to consolidate innovation ecosystems. To implement this vision, the following recommendations have been identified:

• Open and collaborative innovation with open-minded ecosystem: Innovation requires complementary skills to identify a business idea, create a sound scientific and technological approach, tailor for a specific market need, industrialize and market the solution. The open-minded collaboration from different and complementary experts from a variety of ecosystem actors plays a central role.
• Diversity as key success factor for efficient and inclusive innovation. Gender equality, multi-cultural, multi-disciplinarity are important success factors to avoid bias and introduce new viewpoints inside the projects, concepts and teams. Finally maximizing the probability for a successful innovation – from ideas to business to adoption. KPIs at organizational and ecosystem level are required to monitor progress and results.
• From R&D engineer to entrepreneur: A strong prerequisite for innovation – from idea to adoption– is the evolution of the team throughout this innovation process, being able to provide a continuity in the core competences throughout the different business maturity levels integrating a capacity building approach and a mindset transformation.
• Monitoring Digital transformation – the 6P methodology: Digital transformation is not only the introduction of a digital solution in the company, but rather a disruption at organization level to re-think the core organisational and business processes under the spotlight of digital technologies. This change has strong impacts both at technological and at socio-business level. A quantification and monitoring of this digital transformation is mandatory to monitor and steer this (r)evolution.
• From mature project outcomes to business – the valley of death: Research programs shall address pre-competitive topics and shall not overcome TRL7 to avoid market distortion. The link to follow-up funding mechanisms to maintain the teams and the assets, and investors to create business out of promising project outcomes, should be strengthened.
• Replication strategy – overcoming the “not invented here” syndrome: Outcomes of European programs are likely to be relevant for different contexts after a market-specific customization and industrialization. Instead of re-inventing the solution for each similar problem, an efficient replication strategy is required (a) to expose the outcomes of collaborative programs, (b) to analyse results available versus current needs for potential reuse, (c) to identify mechanisms for efficient asset / team reactivation for technology transfer while taking into account IP management.

List of best practices and recommendations

Open and collaborative innovation with open-minded ecosystem: Innovation requires complementary skills to identify a business idea, create a sound scientific and technological approach, tailor for a specific market need, industrialize and market the solution. The open-minded collaboration from different and complementary experts from a variety of ecosystem actors plays a central role. Often a support (e.g., training, dedicated innovation manager) is required to create the bridges and support efficient and targeted collaboration between the experts, finally creating the link between the first business idea, its technical realization, and the creation of a sustainable business.

Diversity as key success factor for efficient and inclusive innovation. Gender equality, multi-cultural, multi-disciplinarity are important success factors to avoid bias and introduce new viewpoints inside the projects, concepts and teams. Finally maximizing the probability for a successful innovation – from ideas to business to adoption. KPIs at organizational and ecosystem level are required to monitor progress and results.

From R&D engineer to entrepreneur: In order to be successfully deployed, a technology need to reach an appropriate maturity level (Technology Readiness Level, TRL). Similarly, the business model and access to market needs to evolve. A strong prerequisite is thus the evolution of the team throughout this process, being able to provide a continuity in the core competences throughout the different business maturity levels, integrating a capacity building approach and a mindset transformation. The core team shall be provided the possibility to evolve in their competences, environment, responsibilities and duties. From a R&D engineer developing new technologies, toward an entrepreneur able to set-up a legal framework and innovation ecosystem for the commercial uptake of his technologies.

Monitoring Digital transformation – the 6P methodology: Digital transformation is not only the introduction of a digital solution in the company, but rather a disruption at organization level to re-think the core organisational and business processes under the spotlight of digital technologies. This change has strong impacts both at technological and at socio-business level. A quantification and monitoring of this digital transformation is mandatory to monitor and steer this (r)evolution.

From mature project outcomes to business – the valley of death: The European Commission is investing several billions of Euro for R&D programs, targeting to increase competitiveness of European industry and ensuring leadership for specific key technologies. At the same time, research programs shall address pre-competitive topics and shall not overcome a technology maturity above mature prototype demonstrated in operational environment (TRL 7) to avoid distortion of competition. Still, the path from a mature prototype to a successful business is wide, and the risk that the project outcomes are lost (e.g., teams disappearing, lack of follow-up invest for industrialization and exploitation) is high. The link to follow-up funding mechanisms to maintain the teams and the assets, and to investors to create business out of promising project outcomes, should be elaborated. Knowing that the valley of death is a consequence of a lack of user driven innovation and a low level of entrepreneurial ecosystem mindset.

Replication strategy – overcoming the “not invented here” syndrome: Outcomes of European programs have – per definition – a limited technology readiness (up to TRL7). It is likely that the solution is relevant for different contexts, still needs to be further customized (e.g., adaptation to local needs and regulation such as language, branding, specificities) prior deployment in operational environment. Instead of re-inventing the solution for each similar problem, an efficient replication strategy is required (a) to expose the outcomes of collaborative programs, (b) to analyse results available versus current needs for potential reuse, (c) to identify mechanisms for efficient asset / team reactivation for technology transfer while taking into account IP management, rights of commercialization of the IP, rights of use of the IP and IP licensing.