New SPSS boss navigates a sea of data

What does the integration of SPSS into IBM mean for buyers and users of SPSS software?
The number one priority that I’ve had for the last seven months is to focus on existing customers. Before we start focusing on acquiring new types of customers we need to protect the base. We’re selling a lot of statistics and data collection to existing customers in academia, in market research, and we’re focusing on them as priority one. Priority two is leveraging the IBM sales channels and services organisations to branch out into other customers where we didn’t have access before.

Customers can expect accelerated innovation in the SPSS product, because we’re reaching into other parts of IBM to see if there are predictive algorithms or capability that we could bring into the SPSS portfolio down the road. We can now tap into the IBM R&D organisation, but wrapped around it we now have services capabilities that SPSS on its own did not have. So we are going to have services expertise on top of the product.

Also now, as part of IBM, we have access to other synergistic products from business intelligence to rule management systems. We’re always going to be open and support other products, but we do now have the ability to develop optimised solutions for customers that we didn’t have before.

What sort of new customers are you planning to target?
We’ve looked at which type of problems customers have been solving over the last several years using SPSS, and instead of doing something radically different, the low-hanging fruit is trying to scale those solutions. We’ve had a lot of customers doing insurance claims management for [detecting] fraud, and now we can scale that because IBM has relationships with every insurance company out there. If you look at telcos doing customer churn, retail companies doing market basket analysis… all these solutions that we’d developed in the past customer by customer, we can now standardise and scale to many, many customers.

How has the acquisition affected employees?
One of the key things with SPSS is that its R&D organisation is its crown jewel – that’s an area where we’re increasing our focus, and adding lots of pre-sales people.

Has SPSS’s headcount gone up or down since the acquisition?
That’s information we don’t disclose. What I spend my days and nights focused on is adding pre-sales people in and outside the organisation as we branch out to some of these other industries.

Do you see your software being used increasingly to analyse consumer-generated media?
Absolutely, because 80% of the data that’s being created out there is unstructured and a lot of it is social media. This whole data collection space is a very strategic one for us. Sometimes people think that all the capabilities we have for text analytics and surveys and whatnot is very much a market-research-only play – what I’ve been telling customers is it’s really not. Yes, we sell a lot of text analytics and survey products to market research companies and they’re a very important segment for us, but the same capabilities are also now being used for commercial customers. Particularly using text analytics to analyse social media and sentiment analysis is absolutely critical to a lot of our customers. Tomorrow we’re giving out an insight award to RTL Netherlands and InSites Consulting for using SPSS to analyse social media conversations to do a better job of their entertainment programming. Just about every company out there now realises the importance of social media and there is very much a growing interest in that space.

What other applications do you see for predictive analytics and data mining in the future?
Right now we’re announcing a product called Decision Management 6.0 which brings data mining and predictive analytics to the business user We now have the ability to take the combination of predictive models and simple business rules to optimise any decision that gets made, so industry by industry we’ve identified a couple of key solution areas: retail market basket analysis and assortment planning, for instance, or telecoms companies are very interested in customer churn and new customer acquisition. With the Decision Management platform we have the ability to take data mining into just about any business process in any industry, so that’s very exciting.