Thought Leader Interview

Jim Davis, Senior Vice President and Chief Marketing Officer for SAS, is responsible for providing strategic direction for SAS products, solutions and services and presenting the SAS brand worldwide.

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. It was in this role that he began to develop the model for continuous communication among engineers, marketing experts and customers that he champions today. From there he was promoted to Director of Product Strategy and then vice president of Worldwide Marketing before assuming his current role.

Denis Pombriant: Jim, analytics has been an important topic for large and small enterprises for decades, but today the subject is taking on extra significance. What's driving the renewed interest?

Jim Davis: I believe a number of factors. I think we're all aware of the data volumes that are out there today, and some estimates have data doubling every 18 months. Some people say it's doubling every two years. We can debate that all we want, but I think the fact of the matter is there's just a tremendous amount of data out there, and people understand that if they can make sense of that information, it can give them not only the ability to just remain competitive in the markets, but also help them float through the down markets as well. So that's one piece.

I also think, if there has been a silver lining in the dark economic cloud that we've been dealing with the past couple of years, it's been the need to be more efficient, be more fact-based in our decision making. I think that silver lining in the cloud has been analytics, and creating an awareness of what analytics can do for an organization, taking it into the enterprise well beyond where it might have been in the past. I think it's going mainstream.

High-end analytics used to require expensive computing power. I think, when we look at storage and computing power now, it's cheap compared with where it's been in the past, so more people can use it. If we look at the last couple of years, not only have businesses become smarter but consumers have become smarter as well. So the way in which we deal with consumers of our products has to be much more targeted.

And then, there's also the issue of transparency in an organization, particularly in financial institutions and measuring risk, based on some of the issues and problems that we've had in the past few years with financial institutions. Nobody wants to go through that again. So there's a lot of demand for calculation of risk, making sure that something like we've experienced doesn't happen again.

DP: Could we drill into that a little bit more? You mentioned the financial industry, and that's a great example, and I've seen some of your videos on the different areas that analytics plays a role in, and I wonder if you could drill into some of the other areas of the enterprise where analytics processing is making a difference, that some people may not be aware of yet.

JD: Well, I think that historically people have looked at analytics as reserved for a few select tasks in an organization, whether it be forecasting inventory levels, or doing some segmentation around customers to present them with a particular offer. I think now what we find is that analytics spreads across the enterprise, regardless of industry. So it's very prevalent in marketing, not only for customer segmentation, but now we're dealing with things like social network analysis.

We talked about the volumes of data that are out there today. I think we all realize that the majority of data in the world today is unstructured. But most of our analysis to date has been based on structured databases. So when we look at marketing, for instance, they now have a responsibility to really look at the effect of social networks on brands, products, and customers.

There's also fraud, risk and customer profitability. We no longer do want to keep really large customer and prospect databases. They're too expensive to service and keep current. We want to be able to deal with customer profitability and narrow our target, to increase margins. There are things like warranty analysis in manufacturing. And in human capital management, dealing with employee churn, making sure you can maintain your talent. And the list goes on. Retail's a hot market right now.

DP: I was actually impressed that there's a role for analytics in new drug development, too.

JD: Yes and it's actually an area that we’ve been involved with almost since our beginning. We have a number of regional user meetings but we have one international users group meeting in the spring each year that draws between three and four thousand people. But if I look at the makeup of that audience, it’s probably one of our largest segments, if not the largest segment.

When you think about all the data that is generated from the clinical trials process to bring a drug to market, anything that a drug company can do to reduce the time it takes to go from R and D to actually getting the product on a drug store or pharmacy shelf, it represents a lot of savings. We all know the R and D process is expensive. These guys need to get drugs to market as quickly and as safely as possible, and that's where our drug development platform comes into play.

DP: All right, so when I think about analytics, simplicity and user acceptance always drive things in a lot of cases of new technologies, or simplicity drives user acceptance of new technologies. And for many years, analytics had an image of being hard to work with, which limited its use. What's changing right now in terms of the user, and in terms of the products that vendors like SAS are bringing to market?

JD: So a couple of things are making it easier for people to deal with analytics. The first is, if you look at the businesspeople who are coming out of school today, they understand much better than those that came before them what analytics can do to help in business. There are a lot of programs out there. We founded a program at NC State that gives people a master's in advanced analytics. And the people that are taking the curriculum are not math majors and statistics majors. They are businesspeople. They are people that are focused in on solving problems.

One of the things that they learn is that various analytic routines like a regression, can do to help business. But they also understand that what we're developing is more of an analytics supply chain within an enterprise. So you have people that are experts. They might be Ph.D.s in statistics in your organization, and they may be doing some of the heavy lifting in terms of the modeling exercise. But the results of those modeling exercises then is shared, or pushed down throughout the organization, in a way in which it makes sense for particular users.

Also user interfaces have come a very long way. We're no longer, obviously, in the era of 3270 terminals. We've got laptops, we've got iPhones, we've got iPads. People can get information delivered to them.

There's also much more automated discovery taking place in organizations. Many models are being placed in operational systems as well. So we might call that "smart analytics," so again that’s heavy lifting being done somewhere in the organization, but everybody is benefitting from it when some of these models are placed into the operational environment.

DP: And we've already touched on social media, but the avalanche of data that social media applications are providing seems to be one of the important driving forces that is causing a lot of people to say, well, I might not have needed analytics before, but I think I do now. Is that your feeling?

JD: Yes, I think social media is certainly driving the adoption of analytics in some organizations. I think it's interesting. As businesses, we have moved from looking at social media as simply something that's fun, where you can tell people what restaurant you went to last night, or what you thought of a particular movie, to understanding that there is enormous business benefit in social media.

One of the fastest-growing areas of SAS is around social media analytics, where you measure sentiment around particular topics within the organization, whether it be your brand and what people think it, or what people think of a particular product, or how you're perceived in the community.

I think about an example that was out there last fall, and I'm sure you've heard about this. You know, the Gap clothing store, they had a situation where they had a logo for the Gap that's been around 20 years. And they were thinking about changing it. And they went ahead and changed it. They went through the creative process, and they pushed that logo out onto a website, showed it to some people. And people didn't like it. People didn't like it at all. And within a matter of days, the Gap turned around and went back to their old logo.

Now, prior to social media, you would not have had that benefit. What would have happened is, you would have hired a creative agency. You would have developed a new logo or brand. You would have launched it into the marketplace, and then you would have had focus groups over the next six to 12 months. And then, in six to 12 months, you would have found out that it wasn't hitting the mark. But what's the damage that was done in that six to 12 months? Social media gives you an immediate read into what people think about you're doing in the marketplace, and allows you to adjust.

DP: Sounds like the difference between Coke and New Coke or the Gap would be a real interesting business school case study.

JD: Yeah, I hadn't thought about that, but I would agree with you a hundred percent. It took a while for the folks at Coca-Cola to realize what had happened. So we need to figure out how to harness this. What we need to be careful of, though, is to recognize that the data from social media is not something we need to look at in an isolated fashion. This data is another data source that we can marry with some of the traditional data sources within our organization.

So it's not just looking at what people think of you. It's also looking at factors within the organization, and overlaying those factors on sentiment to see what the correlation between some traditional activities within the organization, and traditional metrics, might be having on sentiment in the marketplace.

I think it’s a multiple step progression. First, everybody's going to look in the mirror, and they're going to say, okay, I see what people think of me. The next step is, I would like people to think differently of me. That's when traditional analytic activity begins to take place. Things like social network analysis, where we look at rings of influencers. We need to understand who is affecting the perception of our products and our services. And so we begin to do something about it.

DP: Was that the basis of the study you did with Harvard Business Review?

JD: Yes, at a very high level. Everybody thinks it's important to create a social media strategy in the organization, yet the majority are also struggling with what that means and how to get started. The big piece that needs to be put into place initially in organizations is some form of measurement capability so that they all have a starting point.

DP: Since I saw the study, I've started thinking about analytics as the killer application for social media.  

JD: I think it is certainly a killer application. But, I think we have to be very careful, too. I have this fear that, as businesses, we’ll blow it before we get it right. And what I mean by that is, there will be a lot of excitement over the number of people who are participating in social media, and some are going to want to just do blatant marketing to those people. But if they won't know what they’re getting into because social media populations, are self-policing. And some brands, some companies, will run the risk of taking a pretty hard hit if they blatantly try to abuse the medium. And I think there are going to be some lessons learned.

So if I look at what would be a nice talk at a social media conference in about six months, it'll be case studies on how tried-and-true brands didn't understand the community, abused it by trying to do outbound marketing into it, not recognizing that social media is not something you do outbound marketing to. It is a two-way communication vehicle. I think we'll eventually get it right, but we have to be very respectful of the community.

DP: You are speaking to the choir. I've seen this kind of thing happening for years, and it's refreshing to hear somebody point all this out.

JD: Yes, it's frustrating, because I don't think a lot of people get it. I see a lot of people, particularly in consumer packaged goods, that say, oh my God, what a source of data, I'm going to go after it. And they're going to shoot themselves in the foot if they're not careful.

DP: Has marketing changed in your opinion?

JD: I don't know that everybody realizes it yet, but yes. Marketing historically has been about creating messages and doing a lot of outbound campaigns, segmenting your audience. Marketers have to listen. And it's two-way communication now. The consumer is much smarter today, and has great tools available to communicate around experiences. You know, they go to a restaurant, and they have a bad experience. It used to be that they could tell somebody, and 10 people knew. And as the HBR report points out, now your opinion is immediately heard by 10 million people.

DP: That's pretty amazing. Let me change gears here for a sec. I know your company's been putting out some really interesting and powerful cloud computing applications. There's a lot of discussion about the merits of cloud computing versus on-premises computing versus hybrid solutions. Is there a single best approach?

JD: No, I don't think so. I believe the approach should be one of recognizing that as you look at what you need to do from a computing standpoint, seen as process, it's not a point application. So particularly in the world of analytics, if you look at an analytic application dealing with something like marketing to customers, you know, everybody's doing that. You can break that down into data acquisition, data cleansing. Then you have segmentation. Then you have offer optimization, and then you have monitoring of the results of the campaign. So right there I just named five steps.

I think an organization then needs to look at those five steps and say, what are we good at and what resources, both hardware and personnel, do we have to deal with those five issues today? And maybe we're good at three of them. So then we need to look at, well, how can we get best-of-class in the other two? Well, one way is to spend a lot of time, acquire the personnel, acquire the knowledge, and build it over time. But you can't do that any more. Markets are moving too quickly. So you immediately think in terms of, can I find this capability in the cloud? Can I find this capability in a hosted environment?

Maybe I'm doing data quality outside the firewall. Maybe I'm doing some segmentation outside the firewall, but taking advantage of resources in a cloud, and/or individuals who are processing the cloud, who can do that work for me. So I think there has to be a strategy and an understanding of what direction you're taking. The cloud is not just for small organizations. It's changed the way in which large organizations approach new projects.

Retail is a great example. Retailers want to really do whatever they can to increase their margins. It's very, very difficult. And when we look at things like price optimization or markdown optimization, what does that take? It takes some people that understand a bit about analytics, operations research. It takes computing power, and it takes the ability to present the information back.

Well, retailers all know they need to do that, but if they can start in the cloud, and not deal with the capital expenditure associated with the infrastructure, and not have to bring the people in immediately, they can get going. They can see what it's going to take. They can then make a decision over time, do I continue to operate this in the cloud, or do I bring it in house.

A lot of industries are approaching it that way. Start in the cloud to see what our results are, with the idea in the back of our head you might bring it back in. I don't think the majority of them are going to bring it back in. I think they're going to realize it's working really well, and we're just going to leave it out there.

DP: Now, individually we've talked about social media, we've talked about analytics, we've talked about cloud. It seems like there are three major technologies, that would include mobility, social media, and analytics, kind of coming together at this point in time. They've all been around for a while, but it seems like we're reaching critical mass with them, and driving what some people are calling the evolution of cloud two. Would you say that each concept is at the same level of acceptance and market penetration today? Do you see the convergence as something that's important to the future, and why?

JD: I would agree that a convergence is taking place. I would say that they are at different stages of maturity. I think there's a difference between maturity and acceptance here. I think that all are accepted. I think just about everybody agrees that these things are not going away, so they are going to converge in some fashion.

Mobility is probably ahead of the curve in terms of adoption from a corporate perspective, from a business perspective. I think social media has a high acceptance level, but in terms of the mature strategies, it's probably lagging in terms of mobility. It's easier to deploy a device than it is to determine what you're going to do with the data on it.

I've always believed that the iPhone is a great device. I've always believed that the Blackberry is a great device. But I think the form factor on something like an iPad and some of these other tablets really has business application and business benefit. So I think that is probably one of the biggest drivers in bringing these three things together.

DP: That's a very good point, and of course the larger form factor is a perfect solution to eye strain for aging baby boomers like me.

JD: Personally, I love the iPad. I use it for e-mail. The majority of travel I do now, I don't take a laptop with me any more. I take an iPad with me. And it's interesting. You see some of the studies out there right now, or the facts out there right now, about our declining desktop PC purchases, what's the future of the laptop, and you look at the explosion of tablets in the marketplace. I can get by with an iPad on most trips these days.

DP: Well this has been very interesting. Thanks for your time.

JD: My pleasure.