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GCN Home > 07/25/05 issue

Jim Goodnight | Intelligence apps look to future

Interview with Jim Goodnight, CEO of SAS Institute Inc.

By Joab Jackson, GCN Staff

It’s no surprise that SAS Institute Inc., the world’s largest privately held software company, makes its home in Cary, N.C. With headquarters so near three of the state’s top universities—Duke University, North Carolina State University in Raleigh and the University of North Carolina at Chapel Hill—the company has its pick of math and computer science graduates. Such a wellspring of talent helps the company stay ahead of the game in analytic software, which the company has offered since 1976.

Unlike many CEOs, SAS headman Jim Goodnight has programming experience. He has actually done a considerable amount of coding for the company and occasionally still leads projects. He also knows his stats. He holds both bachelor’s and master’s degrees as well as a doctorate in statistics from N.C. State. Before working at SAS, he was an N.C. State faculty member, and he continues to serve as an adjunct professor.

GCN associate writer Joab Jackson interviewed Goodnight at SAS’ annual Government Executive Event in Washington.

GCN: Do you see customers shifting their interest from data analysis to data forecasting?

Goodnight: It certainly has been a trend at some cutting-edge organizations. In the past, enterprise resource planning systems basically gave you information about what has gone on before. They didn’t really try to help you forecast what will happen in the future. Now we’re seeing a trend of, say, retailers forecasting demand for goods so they can ... optimize prices to maximize profit. We have a lot of work going on in optimization.

GCN: Is SAS preparing for the new crop of multicore processors about to be released by Advanced Micro Devices Inc. and Intel Corp.?

Goodnight: We’ve done quite a lot in making the SAS software multithreaded. If you have a single-threaded software, it doesn’t matter how many processor cores you have, the application will only use one of them. For our 9.1 release, we threaded a number of the data-mining procedures that operate on large amounts of data. We will continue over the next few years to multithread everything we have. Some of our core summarization routines and sorting routines can quickly be threaded.

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