At IP.com, we talk a lot about innovation. In fact, we don’t just talk about it, we live it! Innovation is the lifeblood of most businesses and it’s our purpose to help drive innovation with reliable, easy-to-use products. With the power of IP.com’s AI-based tools in your hands, you’ll move more quickly to your next patentable idea.
There are many steps from idea to innovation but the connective tissue is insight. It is key to driving innovation of the highest value, utility, and novelty. Every so often, it’s good to step back and take a bird’s-eye view of what innovation really is and where it comes from within an individual or organization.
What is insight?
There are four kinds of innovation, ordered from least to most impactful. They are: incremental, architectural, radical, and disruptive. Insight plays a different role in each. At the incremental side of the scale, insight leads to a small but meaningful innovation in an existing method or technology. Innovations that are disruptive are revolutionary and, in time, will change how entire industries operate. Both are important and useful to your business, and innovation at one end of the scale can feed into another.
Businesses are always looking for ways to systematically generate insights, ranging from the incremental to the disruptive, aiming to set a new standard in the marketplace with game-changing technology. This puts the day-to-day operations of an engineering team and their use of AI tools to generate insights at the heart of progress.
Insights that drive innovation occur along several dimensions. They could reflect feedback regarding a problem a customer is having. Or they could happen while examining a competitor’s patent. It could even happen spontaneously with an “aha” moment while watching the news. What do these scenarios have in common? They are backed by data. Whether it’s a dataset of 1 or 1 million, you need data to fuel insights.
And while much ink has been spilled over how vast compilations of data can be distilled into useful insights by the latest predictive tools, many can be costly and impractical for smaller teams. Many don’t have the time and resources to collect, compile, and manage the data internally.
What you need is a straightforward and reliable machine learning-based AI tool that works to analyze and interpret qualitative and quantitative data, with the power to visualize it in a concise and meaningful way. This puts the power in your hands to make observations to uncover your next insight. Whether they are dramatic leaps in innovation or simply beating your closest competitors, these insights have the power to improve customer experiences and therefore your business.
Data can be gleaned from real-world or digital sources through observation, direct consumer feedback like surveys or online behavior. It can also be compiled from domestic and international online databases as is the case with IP.com’s intellectual property search tools. Insights are then derived from that data through deeper analysis to make business decisions.
Sources of Insight
It is important to understand various sources of data to better take advantage of them. Insights tend to follow the source they originate from. Many data sources and ways to generate insight were borrowed from the scientific method and applied to business problems. After all, what is business but the science of commercial innovation?
Those sources of data are:
- Direct customer feedback
- Consumer sentiment
- Third-party data
- Conventional online metrics
- Predictive models based on Big Data and AI
- Full-text prior art databases featuring academic, legal, and commercial literature
It is from here that you and your team can capture needed insights.
How IP.com’s InnovationQ Plus Delivers Insights
IP.com’s premier product, InnovationQ Plus®, uses advanced AI to help you uncover multiple data points needed to drive your next insight and innovation. With millions of results from databases all over the world, InnovationQ Plus combines the practicality of semantic, natural language AI search tools with the precision of manual Boolean search filters.
From there, you’ll be able to combine insights from national patent databases like the European Patent Office (EPO) to help understand the legal, economic, and IP lifecycle environments. With these more comprehensive data points, you’ll have a better chance to take your next innovation to the next level.