The ability to innovate with data is clearly tied to having effective data-sharing practices (though to a lesser extent in some — but not all! — heavily regulated industries). (See Figure 7.) Organizations with a high ability to innovate (those that somewhat or strongly agree that analytics helps them innovate) share data both internally and beyond company borders at much higher levels than other organizations: 80% of these organizations report sharing data internally, compared with 53% of other organizations.
Yet, in many organizations, data remains stuck in functional silos or within departments. Nearly half of respondents say that their companies are secretive or somewhat secretive about sharing data (internally and externally). Less than 10% describe their companies as open about sharing data. “It’s a fun topic within our company, because each division has its own data silos,” says Bridgestone’s Moody. “We’re slowly starting to break down those walls and trying to build out an enterprise analytics sandbox, where we can get all the data together so we can do a lot of the more advanced analytics modeling.” Technical barriers to sharing are diminishing with increased reliance on infrastructure such as cloud computing, but organizational barriers are still common impediments to dissolving data silos and creating broad-based access to useful information.4
At W.L. Gore & Associates Inc., systems architect Chris Chen is keenly aware of the need to unlock siloed data to enable innovation. Gore, a manufacturer of advanced materials based in Newark, Delaware, is a research-driven company that is famous for its Gore-Tex waterproof fabric. “We have been running experiments for almost 60 years, but we should be able to do more with the data,” Chen says. “If we could look at all the experiments collectively, would we see that we completely missed some white space in the search? It is hard to answer that if each experiment is a one-off dataset sitting on individual computers.” Sharing is particularly important for catching errors of omission. Without effective data-sharing practices, it’s difficult for an Organization to know whether some analysis has been tried before, with or without success. Processes need to be established to record both successful and unsuccessful results in order to avoid errors. Chen believes that by combining data from all those experiments, the company might “stumble upon” the next Gore-Tex, an innovation that nobody knew was needed but has become essential to outdoor enthusiasts and workers, as well as a huge success for the company. “More importantly, is there a more methodical way to stumble?” he adds. “That’s what data and analytics lets us do.”
Sharing data across silos is necessary, but by itself, data sharing is insufficient to generate valuable insights; companies often need employees with very different skill sets to collaborate in order to unite different views about what the data means. Arabesque Partners, a London-based asset management firm that invests in companies with good environmental, social, and governance (ESG) practices, needs analytics teams and subject-matter experts to work together to weight a variety of data inputs, from board composition information to green supply chains, in order to create the best algorithms. “Our firm is built on two pillars, sustainability research and the quant skill set, using artificial intelligence in order to maximize information out of that,” says CEO Omar Selim. “I look at the head of ESG and the head of quant, and think, ‘Thank goodness they are good friends, because they fight often with each other.’ But the friction is where we generate the value.”
It is possible, of course, for information sharing to undermine the innovation that leads to distinctive products. At Gap Inc., the company’s analytically oriented CEO Art Peck encourages product teams from The Gap and Old Navy to meet regularly to discuss fabric innovations and other issues.
