Analytics maturity doesn't just happen by accident

One way to think of "advanced analytics" might be as "complex analytics," the kind that go beyond the traditional analytics employed to produce business intelligence. However, there is another meaning that is certainly apropos in the context of anticipating circumstances, predicting trends, and prescribing actions. In such future-facing scenarios, "advanced analytics" might suitably be thought of as "analytics in advance." This is where the analytics maturity model starts to make sense.

David Sweenor, Statistica product marketing manager in Quest's Information Management Group, provides a practical summary of this maturity model in his post, "5 ways to boost your business IQ." It is worth noting that the model he touts is layered like a pyramid, with each layer built upon the solid foundation of previous layers. There is no skipping ahead when it come to maturity: every level of analytical maturity must be earned and learned in sequence.

Accordingly, Sweenor helpfully provides a quick overview of five advanced analytics techniques that should be evaluated by any organization seeking to build up its maturity: segmentation, decision trees, predictive models, text analytics, and optimization/simulation. And he describes some helpful Statistica case studies that prove the value of advanced analytics in real-world scenarios. Read David's post and see where you are in the model. You can also find more Statistica case studies under the "Resources" tab here.