A team of researchers that includes Stanford Graduate School of Business professor Amit Seru has developed an innovative strategy that applies big data computing to several million patent documents to rank the innovative importance of almost every U.S. patent over the past 200 years. The basic idea behind the new approach is simple: An important invention is one that both differs greatly from what came before and greatly influences what comes later. This is the classic definition of a “paradigm change.”
Amit and his team’s computing challenge was immense. The team had to identify important terms in 9 million patents, each of which contains thousands of words. Then they had to analyze how frequently those terms showed up in each of the patents during previous and subsequent years. This large “correlation matrix” is what made the task computationally intensive. In the end, the ratio between “that differs greatly from what came before and greatly influenced what comes later” became the gauge of a patent’s importance. In other words, real innovation is a paradigm changer.
The team found that their top-ranked patents based on paradigm change synced up very well with the assessments of historians on the key historical innovations.
Seru says, “the big news is that the new way of ranking important inventions (paradigm change) appears to be accurate and sets the stage for deeper understanding of the conditions in which real innovation can thrive.”
For more info see: “Big Data Settles A Debate About Innovation,” Edmund L. Andrews, Stanford Business Catalyst, Summer 2018, page 34.
The Outside the Box column will continue to focus on “paradigm change” as the true definition of real innovation.
What do you think?