Weather prediction is remarkable ““ so remarkable in fact that it might be useful in the realm of IT. Predicting a hurricane requires a set of highly complex mathematical calculations, as this article by Wally Bahny explains. These calculations factor in historical data as well as current events ““ and as we all know, are more of a “likely scenario” than a rock solid prediction. However, using the data from the past and current findings, the temperature, weather patterns, and even hurricane paths can be determined with much more accuracy than a guess. The question becomes:
So, how can this technology be used in IT? There are software systems available on the market that analyze server and network hardware activity, load, and performance. Many of these systems use regressive and correlative algorithms (to varying degrees of success) to help IT departments predict what could happen based on key triggers, which are in turn based on historical or immediate data “” better systems will use both”¦This type of predictive technology has been tried and tested in many other fields as well, many with greater success than the weather-prediction industry. Some common examples are sales forecasting, drug trials, and insurance risk assessment. In these fields, statistical regression and correlation are used to determine how much product to order, how drugs will affect customers with different symptoms or health attributes, and how risky it is for an individual to own a home or drive a car, respectively.
A proactive analysis system may be the best way to prepare for the unexpected ““ something in IT that perpetually hinder an IT organization. More companies will begin utilizing this sort of predictive forecasting for their own risk management, and more companies will gain a competitive advantage thanks to it.