Optimizing Benefits Selection in View of both Member Population and Organizational Preferences

摘要

The present disclosure relates to systems and methods for optimizing benefits plan options offered by an organization through balancing derived population preferences with organizational preferences by analyzing historical selections made by individuals. Census data dividing members of an organization into census divisions may be applied to machine learning algorithm(s) to derive estimated selection preferences of the members. Using selection preferences, costs of various product offering scenarios and overall member satisfaction estimates of the scenarios may be calculated. Product offering scenarios meeting member preference criteria and organizational budget criteria may be presented for review.