I've done a lot of this thing called "predictive analytics," and I've found that what works best is machine-aided prognostication. It highlights some things tha

I've done a lot of this thing called "predictive analytics," and I've found that what works best is machine-aided prognostication. It highlights some things that folks aren't aware of, and points to some seasonality that may not be particularly intuitive. I've found it particularly useful in predicting inventory and packaging distributions. For example, if you have a product like soda that you can package a myriad of different ways, predictive analytics is a great way to help determine the ratio and amount you need to put into each type of package. I've seen it used with great success, reducing the amount of excess inventory and increasing sales (because stock-outs don't happen). It's a tool, like any other. It's not a silver bullet that will tell you exactly what the future will hold, but it can give you a good guideline on what to expect, and from there, you can act upon that information.