Predictive Analytics

7 secrets to predictive analytics success

Forecast the future with accuracy and confidence. Here are the tools and tactics you need to know to translate data into foresight.

7 secrets to predictive analytics success

Predicting the future has always been a dicey proposition. Fortunately, the arrival of predictive analytics technology, which allows users to project future outcomes based on historical data and analytics techniques, such as statistical modeling and machine learning, has made forecasting results and trends far more reliable than in past years.

Still, as with any emerging technology, predictive analytics can be difficult to use to its full potential. Compounding the challenge is the fact that inaccurate or misleading results caused by poorly developed strategies or the misuse of predictive analytics tools may not become apparent for weeks, months or even years.

Predictive analytics has the potential to revolutionize a wide range of industries and operations, including retail, manufacturing, supply chains, network management, financial services and healthcare. "Deep learning and predictive AI analytics are going to transform all segments of our society on par with this decade’s transformation of the internet and cellular technology," predicts Bob Friday, CTO and co-founder of Mist Systems, an AI network technology company.

Here are seven tips designed to help your organization get the most out of its predictive analytics initiative.

1. Have access to high-quality, well-understood data

To continue reading this article register now

Download CIO's Roadmap Report: Data and analytics at scale