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October 21, 2011

Predictive Modeling Needs

The world is moving to prediction.  Apple and their Siri application have made  it front and center recently, but even over the past five years this is where the world has been moving.  Whoever can predict their own future more accurately will have the highest degree of control over their own destiny.

In our modern world, the data now exists.  We can tell with extreme detail who interacts with our business, what qualities make a person most likely to purchase, how well our production and service systems are functioning, and how that all translates back to revenue.  The rise of the econometric focused Industrial Engineer is a wonderful thing.  Process meets business back office.

The issue preventing us from this future is our toolkit.  Today, the tools we have available to most enterprises are not effective enough to meet the challenge.  SAP can’t do it.  Oracle can’t do it.  Business Objects can’t do it.  Businesses change quarterly.  What makes a company successful today will not make them successful tomorrow.  If you don’t adapt, you eventually die.  Our IT systems don’t adapt easily.

Most IT systems (like those just listed) are so complex that if they are not setup exactly right the first time then they’ll never be setup right.  Oracle comes the closest to being able to help, but they don’t have the analytic tools yet (and yes, that includes other commercially available platforms that could integrate in).

Until the data structures and tools become as flexible as businesses are they won’t be able to meet our needs.  There are a handful of new database systems out there that have the potential to meet our future predictive modeling needs – usually falling into the Big Data model – but they are still in their infancy and mainly focused on data management for data intense businesses.  Hopefully soon they will evolve into something more.

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