Paula Bennett, Minister for Social Development, reveals the critical role data analytics is playing in reducing the number of people on welfare, and deciding which programs to target vulnerable citizens, especially children.
Analytics has helped in investing and using this data for positive action and make a massive influence in the lives of New Zealanders.
“Without using data analytics, we will be throwing a lot of money,” she says in her keynote the SAS User Conference in Wellington. “We will not be getting into the heart of the problem, we will not be putting resources and investment where these are needed,” she says.
“Since 2011, analytics has been at the heart of our welfare reforms,” says Bennett. While cognisant of the criticisms against her when the welfare reforms were announced, she lists the compelling figures on how the government applied analytics to determine funding for programs and beneficiaries.
A key feature used by the government is analytical technical segmentation, she says. This looked at the welfare system at macro level, an overall evaluation, and how much it is costing over a lifetime of the current population.
We spend an average of $22 million dollars a day on welfare, $8 billion a year, she says. The projected lifetime cost for people on benefit was $78 billion.
This baseline valuation of the welfare system is at a level that has not been attempted anywhere in the world, she says. “It is a pretty compelling story on why we want to look at this population to see what we can do,” she says.
The way MSD is using data analysis is gaining attention around the world. The lifetime cost and investment approach is leading edge stuff, and there is a lot of interest from other countries about how NZ is doing it.
This doesn’t necessarily mean spending less in the short term. To the contrary it has often meant spending more to help people into work, as the short-term cost of that assistance is less than the longer term cost of them remaining on welfare.