Other parts of this series:
The COVID-19 outbreak has led to a marked drop in the volume of child protection reports. Calls are down coast to coast. We don’t know precisely why that has happened, with possible explanations ranging from the obvious (closed schools mean teachers aren’t seeing children in person) to the provocative (perhaps the decline is evidence that too many families are reported, anyway). What we DO know is that as the economy and public life reopen, the volume of cases will grow.
Most child welfare leaders are anticipating a rapid, significant spike – a caseload tsunami that child welfare agencies will be unable to outswim. Many are worried that they won’t have enough case workers. Not enough foster parents. Not enough cars. In short, not enough resources to care for these kids.
Plenty has been written about this with understandable angst and anxiety. Today I want to write about a way forward – some clear steps leaders can take to outmaneuver uncertainty. By better understanding the actual challenges ahead, child welfare leaders can begin to devise workable solutions.
Let’s agree that it’s time for less fear, more forecasting.
You see, other industries have long used quantitative approaches to make predictions about things like sales, inventory, customer behavior and profits. Child welfare, as an industry, is different in hundreds of ways. But that does not mean we cannot also be the beneficiaries of an approach of this nature.
Now is the time to use an analytic approach to understand this coming “tsunami.” How much will cases go up? Where will the volume increase? When you know that, you can map out how best to deploy the resources you have and you can plan for the resources you need, if any.
With the right support, forecasting can be surprisingly simple. Start with actual caseload numbers from July 2019. Setting aside the lull in recent months, assume that the caseload in July 2020 would be identical. With that as a baseline, incorporate data related to other drivers of child welfare cases. Three of the best examples are calls for domestic disturbances by police departments, applications for food stamps, and increases in substance use (which can be quantified with something as simple as alcohol sales). If there are measurable increases in factors like these, analytic calculations can help project the resulting impact on child welfare cases.
Imagine being able to forecast needs in a particular jurisdiction, with project caseloads delineated by best-case to moderate to worst-case scenario. Will these numbers be 100 percent ironclad? Not necessarily. But they will provide tangible guidance to help quiet the anxiety and rev the engine for an effective response.
These forecasts will also provide hard numbers should child welfare need to preserve existing funding or request additional resources. While most states have understandably focused flattening the curve for the healthcare system, this kind of forecasting can help “flatten the curve” for family and children’s services.
Above all, forecasting delivers the power of knowledge – empowering leaders to plan based on facts, not fear.
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