What people need and what they say they need isn’t always the same thing. This is an especially apparent truth in product development, where researchers and decision makers are often dependent on feedback captured via surveys or interviews where people may be biased, guarded, embarrassed, inarticulate or even forgetful. Regardless of industry, people in the business of product development can agree: This information gap can be a roadblock to introducing solutions that professionals and consumers across the board are clamoring for.

On the other side of the spectrum, incredible new ingredients and technologies — from robotics to voice recognition to sensors — are popping up across industries at breakneck speeds. In the rush to create the latest “it” product, developers often find themselves starting with a material and asking: “How can we use this?” When you’re trying to introduce a solution that people truly want or need, that’s a tough question to start with.

Somewhere between these two factors — what people really need and don’t have on one end, and what technologies can make a meaningful impact on the other — lies the sweet spot where the next breakthrough product is waiting. And as some leading companies have started to discover, open source data can lead you straight to it. Most recently I witnessed this play out with a company in medical device development — although the learnings from their experience are applicable across industries. Here’s why:

Discover what’s truly missing

Traditionally, when we think of big data and product development, the discussion is about internal data: feedback on existing users, products, sales gleaned from proprietary databases. But it’s when companies turn their attention outward to the masses of unstructured data that they can understand not just what already exists, but what ought to be.

If you’ve had even the most limited exposure to Facebook or Twitter, you’ve probably noticed that people love to complain on social media. While that’s not always the best thing for your newsfeed, it’s led to a hotbed of data that product development teams have never seen before — and many are still unsure how to use.

It’s easy to see how healthcare as an industry stands to benefit from unfiltered access to people’s biggest questions, concerns and needs in real time. I saw this firsthand when researchers at a well-known medical supplies company were on the search for solutions to help stroke patients with rehabilitation and turned to social intelligence for insights.

Exactly what solution was most needed was still unclear, and it’s misleading to believe social networks alone translate accurately into consumer insights. However, when they delved into the most specific forums and blogs and message boards where patients, caretakers, and healthcare professionals speak freely about their problems or even communicate with physicians, they noticed what appeared to be a gap in the market. Despite — or perhaps because of — the fact that most of the stroke rehabilitation products in the market address the upper body, arms and back, most of the patients were actually complaining about the lack of products dealing with the legs. And as far as they could tell, no one else was solving for that.

Make sure you’re first

While social intelligence is great for tapping into consumer opinion and unmet needs, it can’t confirm why those needs are unmet. This is critical intelligence. Product development — especially in the medical device field — is an expensive and risky endeavor with a high chance of failure, and product managers can’t afford to invest in developing a product that already exists.

When you cross-compare with other forms of open source data, you can get a good idea of not only what products already exist, but what your competitors are working on. Floating around in the vast open Internet are mass amounts of bite-sized data like competitor launch schedules, new hires, and IP filings that individually are of little value. Once collected and connected, however, this data can paint a very clear picture of the market and trends. In fact, you can even discover competitor product and innovation strategies: what they’re investing in, developing, and bringing to market. For the research team exploring the idea of stroke rehabilitation products focused primarily on legs, this intelligence confirmed that not only were there no existing products like that on the market, but there weren’t likely to be any coming soon.

Find the perfect partner

Open source data can not only answer the “what” and “why,” but also the “how.” This is where product teams can finally connect the dots between gaps in the market and technologies that can solve for them. By gleaning and cross-comparing data from sources like patent databases, academic sources, and technology forums, data scientists are able to help decision makers narrow in on which hot new ingredient or technologies in development could actually solve those unmet consumer needs. In the case of stroke patients, this data turned researchers toward robotics that could address the leg and the lower body parts’ rehabilitation. Not only that, but it also provided a shortlist of the leading experts and niche startup companies that would be the best fit to make that happen — and helped bring this much-needed medical device that much closer to reality for the people who need it.

It wasn’t long ago that the reality of distilling meaning from the overwhelming amount of information available just wasn’t possible. Thanks to technology that can now collect, analyze, and integrate vast amounts of information regardless of the source, unified data and decision models are now a reality.  From healthcare and pharmaceuticals to consumer packaged goods, and food and beverage, open source data is now a rich resource for product development teams working towards the next big thing.

Gil SadehGil Sadeh is CEO of Signals Group, an Israel-based tech company that has developed an analytics platform for new product development innovation. Gil has extensive experience in research and intelligence with more than 15 years of work as an intelligence officer in varied business and governmental frameworks.