Lately, whenever I hold a whiteboard discussion on collective intelligence, customers, prospects, analysts and even my fellow team members give me their full attention. Now, people have talked about collective intelligence for ages, but I think what drives the point home now more than ever before is the success we’re seeing with crowdfunding and crowdsourcing.
There’s an important lesson from crowdsourcing that data scientists need to learn: there’s greater value in your information if you can share it more readily with more people. The collective intelligence you can gather will be far richer than if it had stayed within the confines of the corporate walls.
Let’s face it, intelligence is not evenly distributed in this world. But there are lots of folks who are very good at building models and want to make them available for the greater good. By tapping into this shared, group intelligence, companies of all kinds can make better business decisions. Perhaps that’s why I get similar levels of excitement whether I’m talking to a Silicon Valley start-up, healthcare organization, energy company or high-tech manufacturer.
After all, why rely on four or five data scientists in your own organization when you can turn to data scientists around the world for insight and perspective? This is the winning approach taken by Apervita, a leading health analytics community and soon-to-be partner, which empowers health professionals and enterprises to capture and share health knowledge. They’re smart about facilitating collective intelligence by simplifying how people author, publish and use health analytics, including algorithms, quality and safety measures, pathways and protocols.
In February, the Mayo Clinic joined the Apervita community to share its extensive portfolio of algorithms covering specialties, such as cardiovascular, pulmonology and oncology. The goal: To make it easy for physicians to sift through all the Mayo Clinic’s cardiovascular data, for instance, so they can automatically identify patients at risk for sudden cardiac arrest, which is the leading cause of death among adults over the age of 40.
In May, the Cleveland Clinic joined the Apervita community to share its advanced prediction models and wealth of medical knowledge with a broader audience. By liberating all this data and putting the collective knowledge to work, these organizations and Apervita are making it much easier for health researchers and practitioners worldwide to have a positive global impact on health.
The beauty of Apervita’s cloud-based approach is in the simplicity and openness of its platform, which enables anyone, anywhere to create and subscribe to analytics and then easily integrate them into their workflows. This is the same approach taken by Algorithmia, which launched in 2013 with the goal of advancing the art of algorithm development, discovery and use.
Dublin, Ireland-based ExpertModels is another innovative group with an open, online platform for sharing data insights as well as building, requesting or marketing data sets, analytical models and data science expertise. The openness of these data markets and communities is what makes them an ideal conduit for collective intelligence. That’s also what truly differentiates Statistica because the sheer openness of its architecture makes it possible to blend the best of these models through a common repository.
By opening our platform to other environments, Statistica has empowered organizations to take models from Algorithmia, Azure ML, ExpertModels, etc., and knit them together in new workflows to increase interaction and collaboration. It’s a great example of how we’re helping customers get smarter about collective intelligence—and we’re the only company that can deliver this level of integration.
It’s one of the reasons Borden Chemical initially chose Statistica as an analysis platform at over 30 sites worldwide. A leading supplier of high-performance resins, adhesives, coatings and basic chemicals to a broad range of industries and thousands of end-use applications, Borden integrated Statistica with its SAP and Laboratory Information Management System (LIMS). By taking advantage of Statistica’s open, distributed architecture, the company easily empowered more than 150 researchers, quality control engineers and technical consultants to combine their collective intelligence worldwide to simplify complex data analyses and reporting.
I’m confident this collective intelligence message will continue to resonate, especially as we share more examples of all the amazing things we can accomplish with distributed intelligence. After all, we’ve always known that “two heads are better than one,” so think of what can be done when you amplify that with hundreds of thousands of smart people and interactive models.