The internet and digital technology have enabled organisations to decentralise their workforces in various ways, such as remote work. This has also led to the rise of open innovation platforms, which allow organisations to tap into a global pool of talent and democratise problem solving.
In the world of data science, this could mean anyone with data skills, such as researchers, freelancers, students, and hobbyists, can participate in solving business problems by bringing fresh perspectives. Open innovation breaks the echo chamber of internal thinking and fosters diversity in ideas.
Accelerating time-to-solution
While traditional research and development (R&D) can be slow and costly, open innovation platforms offer a powerful alternative by delivering faster and more cost-effective results. Open innovation leverages external expertise and parallel problem-solving to accelerate the innovation cycle, according to a report by StartUs Insights.
Instead of relying on a single team or department, organisations can post challenges to a global network of solvers who work simultaneously and independently. This distributed approach means that multiple ideas are being developed at once, increasing the likelihood of finding a breakthrough quickly.
Furthermore, open innovation platforms often attract domain-specific experts who already have deep knowledge and experience that can be adapted to the problem at hand. This eliminates the need for organisations to start from scratch, which saves months, or even years, of R&D. Rapid problem solving is crucial in responding to market shifts in real time and maintaining a competitive edge. In industries where timing can make or break a product launch or strategic pivot, open innovation platforms are proving to be indispensable tools.
Accessing expertise to solve niche and technical problems
Another strength of open innovation platforms is the ability to solve highly specialised, technical, or niche problems, which often fall outside the expertise of a company’s internal teams. These challenges may be too narrow for in-house R&D to prioritise, or too complex to solve without deep domain knowledge. Open innovation platforms bridge this gap by connecting organisations with a global network of experts who live and breathe these specific problems.
One major success story is NASA’s use of open innovation to predict Solar Particle Events (SPEs), which pose serious radiation risks to astronauts and spacecraft. Traditional methods offered only a two-hour warning window, which was insufficient for mission safety. NASA wanted to extend the prediction window to at least four hours, so it launched the Data-Driven Forecasting of Solar Events Challenge, offering a $30,000 prize. The challenge attracted over 500 solvers from 53 countries, many of whom had never worked with NASA or responded to government RFPs before.
The winner was Bruce Cragin, a retired radio frequency engineer from New Hampshire. His algorithm achieved a 24-hour SPE forecast window with 75% accuracy, far exceeding NASA’s expectations. Cragin applied signal processing techniques from his engineering background to solar data – a classic example of cross-disciplinary innovation.
In this scenario, the value of open innovation was demonstrated in three ways. First, the solution came from outside NASA’s traditional talent pool. Second, the challenge was solved faster and more cost-effectively than internal R&D could manage, and, finally, the result exceeded the original goal, highlighting the value of tapping into diverse expertise.
AI as a catalyst for smarter open innovation
As with many other areas of work, artificial intelligence is rapidly transforming the landscape of open innovation platforms. By automating key processes and enhancing decision-making, AI helps organisations unlock even greater value from crowdsourced problem-solving.
AI can minimise human bias, filter out low-quality entries, and rank solutions based on predefined criteria. AI can also identify patterns or novel approaches that human reviewers might overlook. Because AI is easily scalable, it can solve one of the toughest bottlenecks in open innovation, which is evaluating hundreds or even thousands of submissions. This dramatically reduces the time and effort required for assessment, allowing organisations to focus on the most promising ideas.
Organisations seeking to solve complex, urgent, and niche business problems are now embracing external collaboration through open innovation platforms. This allows businesses to access fresh perspectives, reach solutions faster, and tap into expertise that would otherwise remain out of reach. And, with the integration of AI, these platforms are evolving into intelligent ecosystems that streamline ideation, evaluation, and engagement. Open innovation platforms help organisations become more agile, inclusive, and ready for the challenges of tomorrow.
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