New SPSS boss navigates a sea of data

What does the integration of SPSS into IBM mean for buyers and users of SPSS software?

---

Date:

research-live, 18 May 2010 | By Robert Bain

IBM's Deepak Advani took over as CEO of survey and analytics software maker SPSS following its acquisition by the computer giant last year. The firm is now studiously referred to by its spokespeople as "SPSS an IBM company" and its products and services are being integrated with other IBM offerings. We spoke to Advani yesterday about what the future holds for the firm's predictive analytics and data mining services.

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.

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.

...

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.

Read more.