Evocative example of stories and flow as elements of problem solving from Town of Cats, a Haruki Murakami story in the New Yorker. Note: emphasis mine.

He had been regarded as a math prodigy from early childhood, and he could solve high-school math problems by the time he was in third grade. Math was, for young Tengo, an effective means of retreat from his life with his father. In the mathematical world, he would walk down a long corridor, opening one numbered door after another. Each time a new spectacle unfolded before him, the ugly traces of the real world would simply disappear. As long as he was actively exploring that realm of infinite consistency, he was free.

While math was like a magnificent imaginary building for Tengo, literature was a vast magical forest. Math stretched infinitely upward toward the heavens, but stories spread out before him, their sturdy roots stretching deep into the earth. In this forest there were no maps, no doorways. As Tengo got older, the forest of story began to exert an even stronger pull on his heart than the world of math. Of course, reading novels was just another form of escape-as soon as he closed the book, he had to come back to the real world. But at some point he noticed that returning to reality from the world of a novel was not as devastating a blow as returning from the world of math. Why was that? After much thought, he reached a conclusion. No matter how clear things might become in the forest of story, there was never a clear-cut solution, as there was in math. The role of a story was, in the broadest terms, to transpose a problem into another form. Depending on the nature and the direction of the problem, a solution might be suggested in the narrative. Tengo would return to the real world with that suggestion in hand. It was like a piece of paper bearing the indecipherable text of a magic spell. It served no immediate practical purpose, but it contained a possibility.

• [from julienorvaisas] This Tech Bubble Is Different [BusinessWeek] – [Mathematicians are behind the ad-driven business-models defined in this article as the next bubble. They're tremendously successful in predicting behavior; a fact I find both intriguing and terrifying.] On Wall Street, math geeks are known as quants. They're the ones who create sophisticated trading algorithms that can ingest vast amounts of market data and then form buy and sell decisions in milliseconds. Hammerbacher was a quant. After about 10 months, he got back in touch with Zuckerberg, who offered him the Facebook job. That's when Hammerbacher redirected his quant proclivities toward consumer technology. He became, as it were, a Want. At social networking companies, Wants may sit among the computer scientists and engineers, but theirs is the central mission: to poke around in data, hunt for trends, figure out formulas that will put the right ad in front of the right person. "The most coveted employee in Silicon Valley today is not a software engineer. It is a mathematician."
• [from steve_portigal] Steve Portigal – You’ve Done All This Research… Now What? [UIE Podcast] – [A 24-minute podcast for your listening pleasure and edification] Conducting research and gathering data are crucial parts in the process of creating great design. But once you have all of the data, what do you do with it? How do you know you’re extracting the right conclusions and not leaving anything important on the table? Steve Portigal of Portigal Consulting uses the methods of synthesis and ideation to approach this crucial next step. During his virtual seminar, Steve explains that synthesis is the process of turning field data into insights and then how you move to ideation to turn insights into solutions. So many questions came up during the seminar that Steve ran out of time to answer them all. He tackles the remaining questions in this podcast.