Will the Use of "Predictive BI" Add More Value to Decision Management?

I would offer a resounding "Yes!". The combination of reflective data (which helps uncover the patterns of what has already occurred) that comes from classic reporting and analysis systems (dashboards based on ROLAP data, interactive charts and reports, etc.) with predictive data (which help project that pattern smartly into the future) that comes from sophisticated, correlative models can help more decision makers genuinely compete more effectively. This is a great step toward putting analytics to work in almost any organization. The next step is making this kind of insight simple and affordable enough for a much larger market than we've seen in the past.

I have to say that I cannot add much to Brian's answer, except to say that adding the predictive layer to business intelligence applications is where organizations will begin to see the full value of what BI can bring to the organization. Luckily, with the influx of mid-market solutions, we are starting to see these applications move downstream - it just becomes a matter of time for us to see the full benefits and full applications of predictive analytics across a broader market.

If predictive BI delivers actionable results, then automation can deliver real value to a company. For example, recurring revenue is becoming a bigger part of many business models. These business models are critically dependent on revenue retention. The ability to predict where churn can occur and then automatically target education and incentives via online channels, is a case in point where predictive BI can drive automation. The same could be said for predicting areas of up-sell and driving a 1:1 campaign. The value of predictive BI is whether the results are actionable and whether the results are tied to automation. If predictive BI creates more questions for decision makers to ponder, the value is questionable.