What's Different Now?

"We wouldn't even be talking about big data if it wasn't a problem. If we had it all figured out, there would be no need to discuss it. But we ARE talking about it because there are obstacles to harvesting it and putting it to good use."

I'm talking with Jim Davis, who is a senior VP at SAS, and acts as its chief marketing officer. Jim has unique—possibly revolutionary—perspectives on the interrelated subjects of business intelligence ("old school, but necessary"); business analytics ("actually creates value from information"); and the now-trending subject of big data ("not necessarily what you think it is.")

Let's start with that last one first. "There is no pat definition for big data," says Jim. "In fact, big data can be relatively small, but represents a difficult processing-time issue. Basically, you've got big data whenever you exceed the capacity of a conventional relational database management system to handle it."

So it's more about complexity than size? I ask. "Often both," Jim answers.

We've arrived at this odd juncture, Jim thinks, because we've moved from simple old-school BI—"run a report on last year's sales figures"—toward "greater fact-based decisioning cultures," in his words. "These require not only more data, but more complex things regarding the processing of the data. It's no longer a matter of a select group of people doing modeling, but it's about people tackling tough analytic problems that can make or break the business," he says. "And we've probably come to this point because of a tough economy. That has led to a greater sensitivity at the executive level of what analytics can truly mean to an organization."

Running in parallel with this trend is the other buzzworthy phenomenon—social media. "Social media is having an enormous impact, particularly in the area of customer relationship management and all the analytics required for that. Which is a lot! The companies that are not succeeding with social media view it as something ‘new and different,' Jim continues. "Those that are succeeding see it as simply another data source they need to integrate with their existing decision-support environment. If you see social media as something that can supplement the information you already have, then you increase the value of your data.

"The real value of social media comes from listening to it," Jim says. "It has to do with determining the sentiment from the phraseology about the topic, whether it's your executive team or your brand or your product. There's enormous value in understanding how people feel about those things. It's the new focus group!" he laughs. "In effect you use social media to supplement your status with a constituent or customer. If you're monitoring the social network, you can do that immediately. That is not exactly prevalent yet," Jim admits, "but it's growing, especially in financial institutions and online retailers. If you pick up someone who's not happy and you can get to them quickly with some offer to rectify the problem, you can turn sentiment that's red into green."

What's Different Now

"There's a gap in many organizations," Jim claims. "They have line-of-business people over here, and over there they have analysts that deal with predictive modeling and regression and high-end analytics. What has been lacking historically is someone to manage the communication between those two organizations. I call that a data scientist." Jim admits that when he first heard the term, "I thought it was kind of Frankenstein-ish." But it's a real and growing discipline, he insists.

"These people don't need to be experts, but they need enough knowledge in mathematics, statistics and computer science to at least know what's possible. We've been working with universities to create programs to pump out these data scientists. These are usually people who have business backgrounds who go back to school to get exposed to what's available in predictive analytics, operations research, forecasting... What graduates out of those programs are people who bridge the gap between the Ph.D. statistician and the businessperson. There's a high demand for that type of people right now," Jim says. And he predicts it will only become greater.

"Anything that involves big data needs to be quantified and have some value attached to it. This is the difference between business intelligence and business analytics. Applying analytics will, in a very short period of time, have a difference on the top line, bottom line or both. Whether it's customer acquisition and retention, or fraud detection, if you can prove the case that it's worth $50 million... suddenly the resources become readily available," Jim insists.

"We're moving away from buying product, to creating an environment that supports the entire decisioning process. That may entail gathering BI data from business processes, then passing it through an analytics process, the results of which then have to be distributed to a large number of people so everyone's working off the same information. That is not a single tool or operation; it's an environment of integrated tools and processes. THAT's what's different now." 

Jim Davis, senior vice president and chief marketing officer, is responsible for providing strategic direction for SAS products, solutions and services. Davis helped lead the transformation of SAS from a tools provider to the software solutions provider it is today. Davis joined SAS in 1994 as an enterprise computing strategist focused on IT issues. He later served as program manager for data warehousing, one of SAS' first global projects to incorporate customer feedback in the development process. From there he was promoted to director of product strategy and then vice president of worldwide marketing before assuming his current role.  

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