Summit Series on the NAE Grand Challenges

Four years ago, a banker in Singapore asked Jim Goodnight, CEO of SAS, for help. His risk computations were taking 18 hours and he wondered if SAS could streamline the process. “That one question has generated four years’ worth of total transformation and reinvention of our software,” Goodnight said, while speaking at a conference dedicated to promoting partnerships among industry, academia, and government while addressing issues in advanced manufacturing.

Goodnight explained how SAS software was redesigned to take advantage of a new generation of computer chip that allows massively parallel computing. The bottom line? The banker’s 18-hour process now takes 12 minutes. “When you run into computational problems, I think we’ll have a solution for you,” Goodnight concluded.

Gene Gsell, senior vice president of the manufacturing business unit at SAS, also spoke at the conference. Gsell pointed out that innovation is essential for advanced manufacturing and for meeting the Grand Challenges for Engineering. He explained how SAS analytics create innovations that improve manufacturing processes for SAS customers. 

For example, the South Korean company POSCO, the fifth largest steel manufacturer in the world, wanted to reduce scrap, improve quality, and incorporate Six Sigma, a process improvement strategy. Using SAS analytics, the company reduced lead time by 50%, reduced inventory by 60%, and has so far saved more than $450 million dollars. Gsell shared a quote from a manager at POSCO, who said that SAS analytics helped uncover nonlinear relationships that did not come to light with traditional methods.
Both Goodnight and Gsell emphasized the urgent need for more people who can analyze data. Goodnight described how SAS partnered with North Carolina State University to create a Master’s of Science in Analytics. Eighty students graduated in 2013, with most of them having at least three offers of employment. “Demand for data analysts is huge,” Goodnight said. “All big corporations are seeking these people out."

Gsell agreed, saying, “We need to prepare students to become CAOs—chief analytics officers.”

As for Big Data, the phrase that seems to be on everyone’s lips, Gsell offered his definition: “more data than you can handle.” He said, “It’s been around a long time. What’s different now is the big computers. Processes that used to take days or weeks now take minutes or hours. We’re able to eliminate the need for sampling. Now you can hit the entire data set—it’s a huge breakthrough.”
Other examples Gsell shared were helping Caterpillar predict when their machines would need maintenance, helping an auto parts store predict demand for different parts in different stores, and using data management to improve the interactions between different parts or silos of a company, such as research, production, sales, IT, and finance. “Too often we overinvest in the silos and underinvest in the data management that allows them to work together,” he said. “Data integration is crucial to link the silos and create value.”

The New Engineering Frontier: Manufacturing for the Grand Challenges, a National Academy of Engineering Grand Challenges summit, was organized by the Research Convergence Accelerator in consultation with the NAE, and sponsored by SAS Institute (premier sponsor), Lord Corporation, and Cray, Inc. The Research Convergence Accelerator is a consortium of Duke University, North Carolina A&T State University, North Carolina State University, RTI International, University of North Carolina-Chapel Hill, and Wake Forest University. The conference was held October 31-November 1, 2013, at the Umstead Hotel and Spa on the SAS Institute campus in Cary, North Carolina.