TIBCO Rolls Out Spotfire 3.1 with Spotlight on Predictive Analytics

In a move to mainstream predictive analytics, TIBCO Software this week rolled out the latest version of its Spotfire platform.

Dubbed Spotfire 3.1, the latest iteration promises a natural language statistical experience. Spotfire 3.1 aims to help anyone in an organization get fact-based answers to questions that help drive revenue.

The company says its software is not just for analytics gurus but also marketing professionals, business development managers and others who need forward-looking business intelligence in a hurry.

"Unlike traditional business intelligence tools, which for the most part aggregate historical trends only, Spotfire 3.1 projects them forward with what-if scenarios," says Mark Lorion, vice president of marketing for TIBCO Spotfire. "Anyone in the company can ask questions on demand and our analytics will provide future predictions based on behind-the-scenes data-driven methods. Users don't have to understand the methods. They just have to ask the questions – and they get answers instantly rather than waiting days like you would with today's business intelligence (BI) tools."

Spotfire 3.1 in action

Let’s say you’re trying to promote a new product in the consumer goods market. Spotfire 3.1 lets you choose input variables based on what you suspect might be driving the advertisement response, such as price, discounts, packaged offers, age of the respondent or length of time as a customer. You would then press a button that asks, "Are these related?"

After you push that button, Spotfire 3.1 works behind the scenes to run predictive models, using analytics and statistics to compile sensitivity analysis and correlations, then return a colorful graph that shows the response rate and which factors are most closely correlated to people clicking on your advertisement.

The software's multiple scale bar charts and combination bar and line plots offer analysis of unstructured, ‘free-dimensional’ data to identify key outliers and trends amongst the data.
While BI gives you historical data, the predictive analytics aspect of Spotfire 3.1 offers insights into what could happen next time you run a similar promotion. It can also help you fine-tune your promotions by targeting the customers that clicked on your ad, or offering different promotions to different audiences – and it does it almost instantly.

Unlike traditional BI or static spreadsheets, Lorion says Spotfire 3.1 also includes conditional coloring and lasso and axis marking that allow for better data analysis of patterns, clusters and correlations among sets of variables. The software's multiple scale bar charts and combination bar and line plots offer analysis of unstructured, "free-dimensional" data to identify key outliers and trends amongst the data.

“IT organization and statistician groups aren’t able to respond quickly enough to the many questions that arise from business users, so they go to their gut,” Lorion says. “Spotfire lets you make fact-based decisions rather than gut-based decisions.”

Spotfire 3.1 works in tandem with Spotfire Application Data Services to let companies analyze data from various sources, including SAP NetWeaver BI, SAP ERP, Salesforce.com, Siebel eBusiness Applications, and the Oracle E-Business Suite.

Of course, predictive analytics software is not a new concept, and Lorion admits that the predictions are only as good as the quality and breadth of the available data. But predictive analytics is gaining momentum in the enterprise marketplace. The economic downturn has been good for the analytics space because customers need to make reductions and predictions – but they need to be smart about it.

IBM bought predictive analytics firm SPSS last July for $1.2 billion. And IDC predicts the $1.4 billion market for advanced analytics, of which predictive analytics is a subset, will grow 10 percent annually through 2011. Despite tight IT budgets, Lorion is optimistic about the space and the company’s offering.

“The economic downturn has been good for the analytics space because customers need to make reductions and predictions – but they need to be smart about it,” Lorion says. “Companies don’t want to hire PhDs to make sense of their statistics. But we need to drive awareness of our product and educate the market that the power of predictive analytics isn’t in the hands of only a couple of statisticians.”