This is a summary of a presentation shared during KrASIA’s Magnify China 2021 on July 6 and 7. Check out other segments’ recaps here. If you have any inquiries regarding this event, feel free to reach us at email@example.com.
“Open Innovation,” as a 21st century model of adapting to changing business environments, calls for companies to involve partners, customers, and stakeholders to acquire knowledge and ideas that exist outside the organization. These external resources help companies create new products, save costs by outsourcing, and stay ahead of the competition. Unsurprisingly, the talents and technologies in China’s ecosystem have become an attractive resource to corporates.
This presentation examines three main vehicles that have proven to be successful corporate open innovation initiatives in China. Robyn Tan, managing director of KrASIA, discussed the mechanics of innovation teams, accelerators, and corporate venture capital (CVC), using Unilever, Intel, and Daimler as case studies.
First, Unilever Foundry is Unilever’s dedicated innovation arm that works with business units to search and screen for solutions to existing business problems. Through Chinese partners and agencies, the foundry can match with startups and assess them on criteria that typically include technological strengths, the applicability of their solutions, and fundraising history.
In terms of implementation, Unilever’s different business units will then embark on a proof of concept, or POC, with the startups and decide if they can be scaled up in the future and if they are applicable to other Unilever brands or markets worldwide. Through such projects, Whale, a Chinese AI and IoT startup, provided a content management display system that digitized the shelves in Unilever’s offline retail channels. Their technology helped Unilever’s brands stand out from competitors, attract foot traffic, improve customers’ interactive experience, and convince customers to spend more time in front of Unilever’s shelves to achieve sales conversion, all while collecting consumer behavior data.
Second, Intel established Intel Capital as a farsighted program that builds strong connections between Intel and the startup community. This allowed the company to explore new business areas beyond microprocessors by funding these startups and observing experimental businesses and products. Since 1998, Intel has invested more than USD 2.1 billion in China through seven different funds across AI, autonomous driving, acceleration technology, 5G, and more. One of their recent investments was in KFBIO, a company that uses big data, cloud computing, and AI to scan and digitize images that help pathologists make diagnoses in a fast and reliable manner.
Finally, Daimler has its accelerator program, Startup Autobahn. The program operates in four main stages: a 100-day scouting phase to evaluate and filter startups relevant to set topics, a pilot project stage that facilitates prototyping and pilot tests between the top 30 startups and Daimler’s partners, an expo day to showcase the results from each project, and then POCs for pilot projects that can be applied at scale in the partner company. GeeFish Technology was one of the startups that successfully emerged through Startup Autobahn and developed a car entertainment system that combined AI technology with gestures and biometric recognition.
To round out the presentation, the team compared three different open innovation models, noting that each has its pros and cons. Running an innovation arm could demand fewer resources and deliver quicker results compared to the other two models. Accelerator programs, while requiring a longer time frame, facilitate closer collaboration between the corporation and the participating startups. CVC could allow for a wider scope of interest, but it is capital-heavy and would face stronger demands for proven returns from the corporation’s investment department.
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