There’s a popular misconception that a great idea strikes from out of the blue, much like the apple that supposedly fell on Newton’s head. In fact, almost every idea, no matter how groundbreaking or innovative, depends closely on those that came before. “Coming up with an idea is best compared to inventive cooking: combing existing ingredients or modifying a recipe to come up with something new,” says Professor Olivier Toubia, who researches idea generation and social networks.
But is there a way to determine which set or arrangement of ingredients will make a great idea? Toubia together with Professor Oded Netzer sought to answer this question in a recent study that uncovered a schematic link between the various components of an idea and its perceived creativity. It is the first study to quantify how ideas with a particular mix of components that balance between novelty and familiarity are most likely to be seen as creative.
The researchers conducted a series of eight experiments in which participants were asked to generate ideas on a specific topic, such as how to improve a healthcare product. Over 4,000 ideas were generated in this study. These ideas were then evaluated by panels of judges, which in different versions of the study were comprised of consumers, industry experts, and members of an online idea generation community. Each idea received an average rating for its creativity.
“We borrowed techniques from the world of big data, such as text mining, in order to automatically 'read'thousands of ideas and predict ideas that would be perceived as the most creative,” says Netzer, who researches how big data and related tools can be harnessed for business decision making.
In terms of the cooking analogy, each idea could be considered a recipe. Text-mining tools extract the ingredients. Using network analysis, the researchers analyzed the relationship of these ingredients within the baseline network. “If we ask someone to come up with an idea for an omelet, and they say, ‘I’m going to mix eggs and cheese,’ they’re picking a combination that is very common and familiar,” Toubia says. “But if the idea is to mix eggs and mint, that’s a less common and more novel combination.”
By looking at these combinations, researchers could quantify the balance between novelty and familiarity in each idea. “If your omelet has eggs, cheese, and mint, it contains a familiar combination — eggs and cheese — and some novel ones — eggs and mint and also cheese and mint,” Toubia says. The ideas that were seen as the most creative were those that struck an ideal mix between novelty and familiarity. “If an idea is going to be seen as exciting and new, there has to be a twist,” Toubia says. “But at the same time, it has to include something familiar.” In order to determine the optimal mix between novelty and familiarity, the researchers turned to the beauty-in-averageness effect uncovered by psychologists and biologists. Just as human faces with prototypical, commonly-occurring features are judged as more beautiful, the researchers found that ideas with a prototypical mix of novelty and familiarity were judged as more creative.
In their final study, the researchers investigated ways of using these findings to help people solve problems more efficiently and creatively. They asked participants to submit ideas for creative smartphone apps that would help users improve their health. The researchers text mined a baseline of the 500 concepts (from discussions between users of several health apps) that are most frequently associated with health apps and designed a tool that would improve participants’ ideas by bringing them closer to the ideal mix of novelty and familiarity.
For example, if a consumer suggested a smartphone app that included three of the 500 concepts in the baseline, all of which were very common, the tool could suggest an unusual concept to include that would bring the idea closer to that ideal mix of novelty and familiarity. Likewise, if the consumer relied on five concepts, all of which were very unusual, the tool would suggest a familiar element that would help the idea seem more accessible. Ideas that were revised in this way were seen as more creative, the researchers found. “We have all of these big data tools; we can analyze tags and social networks. Most of these tools are just used for targeting and advertising,” Toubia says. “But we can also use them to help people.” Netzer says.
These findings have implications for almost any company or industry that is involved in idea generation. The researchers' hope is that there are many other applications for similar tools. “If you want to be philosophical, this research is saying that good ideas are all about harmony and balance," Toubia says. "And that balance is going to be useful in many areas in life that extend far beyond new product ideas.”
Oded Netzer is associate professor of business in the Marketing Division at Columbia Business School.
Oliver Toubia is the Glaubinger Professor of Business in the Marketing Division at Columbia Business School.
Professor Netzer's research centers on one of the major business challenges of the data-rich environment of the 21st century: developing quantitative methods that leverage data to gain a deeper understanding of customer behavior and guide firms' decisions. He focuses primarily on building statistical and econometric models to measure consumer preferences and understand how customer choices change over time, and across contexts. His research...
Olivier Toubia is the Glaubinger Professor of Business at Columbia Business School. His research focuses on various aspects of innovation (including idea generation, preference measurement, and the diffusion of innovation), social networks and behavioral economics. He teaches a course on Customer-Centric Innovation and the core marketing course, in the MBA and Executive MBA programs. He received his MS in Operations Research and PhD in...
Read the Research
Olivier Toubia, Oded Netzer
"Idea Generation, Creativity, and Prototypicality"