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[Blog] The Expansion of Predictive Analytics

When you think about using data to predict future behavior or outcomes, industries like marketing or supply chain may come to mind. Marketers collect consumer data to retain customers and target new individuals. Data is used in supply chain to manage inventory and avoid erroneous costs. This use of data, better know as predictive analytics, has continued its expansion into other fields. IBM describes predictive analytics as “a branch of advanced analytics that makes predictions about future outcomes using historical data combined with statistical modeling, data mining techniques and machine learning.” Predictive analytics help organizations avoid risks and improve overall outcomes.

Predictive analytics has made its way into industries like healthcare and human resources, helping healthcare professionals determine trends in diagnosis and treatment and HR professionals hire the best talent. Recently, predictive analytics has made an impact on a somewhat unlikely field – child welfare/juvenile care. Agencies are hoping to use predictive analytics to improve treatment plans and create better outcomes for children and families. Predictive analytics can also help agencies save time and money, allowing them to allocate resources in a more beneficial manner. Major considerations for the success of this tool in child welfare and juvenile care center on the amount of clean data, though, which is critical to the accuracy of predictions.

In order to improve the effectiveness of predictive analytics, many organizations are partnering with vendors who can help them improve data collection and analysis. It’s also important to note that predictive analytics alone will not solve all treatment issues within child welfare. Other quantitative and qualitative methods will be necessary. Still, it’s interesting to imagine the opportunities available as these agencies embrace technological advancements that have benefited other industries for years.

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