Why big data is suddenly sexy

Jul 15, 2011

FORTUNE -- Software maker SAS gets a lot of love for its laid-back corporate culture (it ranked No. 1 on Fortune’s Best Companies to Work For list in both 2010 and 2011). But no amount of on-site massages, car washes and Zumba classes can alleviate the increasing pressure the North Carolina-based company is feeling from heavyweights like IBM (ibm), Oracle (orcl) and SAP (sap).

SAS’s analytics software was designed to analyze agricultural data back in 1976. Today a wide range of industries, from retail to financial services, use the company’s tools to make sense of massive volumes of information. But the recent explosion in “big data” has been both good and bad for SAS. As demand for business intelligence and analytics software increases, so does SAS’s competition. IBM in particular has been on a tear, snapping up data players like Cognos, SPSS and Netezza in recent years and encroaching on SAS’s territory.

SAS isn’t sitting still. Earlier this week the company unveiled a new version of its software that it claims will help “enable faster, better decision making by improving analysis of vast and growing amounts of data.” SAS remains the largest privately-held software company (and growing), but some critics say the company is doing too little too late to fight off IBM and overcome other challenges, like free, open-source alternatives and the proliferation of tablets and other devices in the workplace. Fortune recently caught up with Jim Goodnight, SAS’s 68-year-old co-founder and CEO, to talk about the growing opportunities—and competition—in big data.

Why is big data such a hot area?

We’ve been around for 35 years, and big data is suddenly sexy. Now we’re having to deal with larger and larger amounts of information. There are many industries who want to use this data to optimize. For example, we are working with Macy’s for markdown optimization. They have millions of items and they try to sell everything they can before the end of the season. This activity used to be done by hand, but now we can use data to forecast every item in every store and how much it should be marked down. We’re seeing a lot of growth in the financial sector too. We do risk computations for credit risk and market risk, these are things that all the banks are now taking another look at.

Are you seeing a lot of growth in your software-as-a-service [as opposed to on-premise] deployments?

Cloud computing is not that new. Back in the early days of computing when mainframes cost several million dollars a piece companies rented time on the machines. Back in the 60s that was called timesharing, and now it’s called cloud computing. Virtualization has been around since the 70s at least so it’s been around. Cloud computing is just taking very cheap computers and sticking them together. But we support it. A lot of companies find that virtualization is a good way to cut down on cost. They can run different operating systems. There are a lot of companies that prefer to get the entire solution handled for them especially in these days of tight budgets.

Looking out over the next five years, what big challenges do you anticipate for SAS?

We stopped looking at five years out a while ago because we need to be able to respond to the competition and to new devices faster than that. So we now look at two years. Now we’re having to respond to the iPad which wasn’t even around two years ago. Before we didn’t have to worry about mobile BI [business intelligence] but now that the iPad and Android machines and the PlayBook from RIM (rimm) are out suddenly the world is being swamped with these things and we have to respond. We’re also trying to take advantage of social media, taking a look at all the tweets and blogs and pulling them together.

What about challenges from competitors like IBM?

Let’s put it this way, we have been competing with Oracle, IBM, and SAP for at least 30 years or more. We don’t find a lot of differences now than before.

What about newer competition from free, open-source alternatives like R [a programming language for data analysis]?

R at this point doesn’t scale to bigger problems like we’re doing. We’re doing some very large-scale computational problems. R is predominantly for statistical analysis. R and SPSS [which IBM bought for $1.2 billion in 2009] are tools. We make tools but we also make a large number of solutions designed to help customers solve problems.

 Is your corporate culture sustainable or do you anticipate you will have to make any changes or cuts?

I don’t see any changes. Of course our medical costs keep going up, and something needs to be done about these runaway medical costs. But we are looking at about 10% growth this year and a little more than that the year after. We’ve hired over 400 people so far this year and we need to get revenues up a little more. We spend a lot on R&D—about 22% of yearly revenues go into R&D. My tendency is to favor R&D more so than sales and marketing.

Do you have a succession plan in place?

I feel like I’m still very capable of running the company. I am quite healthy and I still think I’m the best to run the company. When I start to think otherwise I’ll get someone else to do it. Companies rarely talk about succession plans. I don’t know any company that makes a big deal about the successor until they need one.

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