Evaluation and Data Use

These tips and strategies may be helpful for child welfare administrators, legislators, and other policymakers seeking to utilize agency data to answer pertinent child welfare workforce questions.

High-quality data is necessary to support data-driven decision making about the workforce. This blog post, video, and resource provide guidance on how to assess data quality and improve it to make it useful to support decision making.

This resource highlights 9 criteria that are relevant for workforce data, suggests ways to assess data quality, provides information on how to correct data and improve the quality of future incoming data, and links to other resources and tools.

Data visualization can communicate data in a clear, concise, and engaging way – this blog post presents strategies to help you visualize your workforce data.

This blog post highlights why and how child welfare agencies can build capacity to share and use data through visualization.

This brief highlights strategies that evaluators can use to improve the utilization of child welfare workforce research, based on the experience of the QIC-WD.

This blog post describes how data dictionaries can position child welfare agencies to leverage their human resources data for workforce development.

This blog post describes two primary workforce outcomes—performance and retention—and how agencies can use workforce metrics to measure them.

Multi-site, multi-intervention, multi-design evaluations are complicated. This post summarizes key evaluation challenges and the QIC-WD's solutions to addressing complex issues inherent in child welfare workforce research.

The QIC-WD is using an assessment tool to help Institute participants determine if they practice evidence-based management.