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Home > Public Risk Management > Managing Risk in Workers’ Comp: The Value of Predictive Analytics
Podcast: Public Risk Management
Episode:

Managing Risk in Workers’ Comp: The Value of Predictive Analytics
Category: Government & Organizations
Duration: 00:12:37
Publish Date: 2017-01-02 16:43:31
Description: Today’s guest, Michelle Despres shares with us what predictive analytics is all about, its importance, why it is trending in organizations today, claims management and how predictive analytics tackles it. She also enlightens us on the benefits of predictive analytics as regards to claims management and how to measure its success. Predictive analytics is the branch of advanced analytics which makes predictions about unknown future events. It uses many techniques to analyze data point to make future predictions. Its importance cannot be overemphasized as workers complain and make a lot of compensation claims. The predictive analytics then makes organizations become proactive, forward-looking and anticipating outcomes and behaviors of employees/workers. It also allows resources to be allocated and helps management reduce the incidence of exploding claims as claims have become trendy and expensive. Predictive Analytics helps organizations with issues such as obesities, aging, injuries, etc. to their workers reduce costs and help manage their outcomes. For example, a lot of professionals know when a claim can become costly but don't have the data to identify these claims as bad claims. Predictive analytics helps with the data that makes, stops or manage these claims from exploding to bad claims or getting very expensive hence saving costs. Benefits of Predictive Analytic Programs The benefits collecting data and P.A programs help organizations in the following ways: # Knowing the most objective way to allow for better management of claims # It helps organizations know what is happening, what is causing an event and the best way to manage it. # It allows organizations to make substantial savings, calculations and outcome measurements. # It gives companies the opportunity to apply the right resources at the right time. # Helps companies get in front of claims pro-actively. The data gotten from P.A helps reduce the risk of re-injury for employees returning to work as it improves the return to work outcome, control rising costs, and allows for tighter claims management. The gotten data also helps organizations get in front of claims before they become bad and also help give these organizations efficient medical management approach. An example of P.A and a bad claim is a situation whereby a certain department or category of workers in a certain company turned up with hand and wrist injuries. The predictive analytics data helped determined the cause of the injuries, why it was happening and the best approach to managing the situation to prevent further reoccurrences. Tips for Organizations that want to begin P.A # Start with the end in mind: Here the objective of the P.A should be ascertained before you delve into it. # Beware of data leakage. # When you have a claims management dilemma, start with the most expensive and frequent claims. # Determine what action would be taken on identified cases in time. How to Measure a Successful P.A Program A critical factor for a successful development of predictive analysis project is a well-defined set of business performance metrics specific to the organization business objectives. For this case they include # An increase in return to work outcome. # A decrease in overall claims by employees. #Reduction in hidden claims. # Cost reduction as regards injuries etc.
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