In New Zealand, people are taking a “thinking like a data scientist” approach to optimizing social worker spending and casework prioritization. A related BusinessWeek article titled “A Moneyball Approach to Helping Troubled Kids” (May 11, 2015) highlights the role that scores play in identifying and prioritizing problem areas and deciding what corrective actions to take. Here are a couple of excerpts from the article:
Using data from welfare, education, employment, and the housing agencies and the courts, the government identified the most expensive welfare beneficiaries – kids who have at least one close adult relative who's previously been reported to child safety authorities, been to prison, and spent substantial time on welfare. “There are million-dollar [cost] kids in those families,” Minister of Finance Bill English says. “By the time they are 10, their likelihood of incarceration is 70 percent. You've got to do something about that.”
…one idea is to rate families, giving them a number [score] that could be used to identify who's most at risk in the same way that lenders rely on credit scores to determine creditworthiness. “The way we may use it, it's going to be like it's a FICO score,” says Jennie Feria, Head of Los Angeles' Department of Children and Family Service. The information, she says, could be used both to prioritize cases and to figure out who needs extra services.
In wrapping up the “thinking like a data scientist” process ...