The prompt tells us we know the root cause, so that’s helpful. The temptation here is to jump right to a solution, to select a strategy and implement it, or worse, to “just call the clerk.” But good change management is more measured than that. The next step after identifying the root cause(s) is to articulate how you intend to address the root cause(s) by drafting a theory of change.

Here, your theory of change should provide a step-by-step chain of logic describing how you think addressing the clerk’s scheduling procedures will result in a reduction in time to adoption.

For example:

The clerk will schedule adoption finalization hearings quicker, so that the time from petitioner’s hearing request and the adoption hearing decreases, so that there is less time between the filing and the hearing, so that the adoption hearing happens sooner, so that the adoption finalization happens sooner, so that children eligible for adoption have their adoption finalized, so that the number of children in foster care eligible for adoption but not yet adopted decreases.

You don’t need to collect more data on the root cause if you have enough data to make a reasonable inference about it. At some point the data is “good enough” and you can take action. But of course, once you implement an intervention you should continue to collect data to see whether or not it’s working.