Many super funds are investing heavily in data profiling and predictive analytics solutions that promise to unlock a tidal wave of insights, often geared toward improving “member engagement”. But mostly, these analytics solutions are just providing more data—not insights—and it is no wonder. Standard data and risk profiling generally focuses on basic member and financial data, such as age and account balance. Predictive analytics often requires complex models and is focused on classifying likely outcomes across a segment rather than an individual member. While these can provide important information to develop product strategies, there are additional levels of data that...