Social and Behavioral Sciences Commons^™

A Quick Guide To Workforce Analytics For Child Welfare Agencies, Quality Improvement Center For Workforce Development

Other QIC-WD Products

Child welfare agencies continue to seek resources to help them better understand their workforce data. The Quality Improvement Center for Workforce Development (QICWD) developed several valuable resources for public child welfare agencies working to build partnerships between child welfare and human resources (HR) professionals to address child welfare workforce challenges. These resources were created for jurisdictions participating in the QIC-WD Child Welfare Workforce Analytics Institutes 1.0 and 2.0 but can be used by any jurisdiction. These resources aim to help agencies build their workforce data analytics capacity and improve practice. Planning When conducting workforce analytics, agencies are encouraged to adopt …

Assessing Your Workforce Needs, Quality Improvement Center For Workforce Development

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You know you have a workforce challenge… but do you know what is causing it? Many child welfare agencies have expanded recruitment efforts through social media, started using telework and flexible work schedules, and even increased wages and provided hazard pay to build and strengthen their child welfare workforce. But sometimes even the best strategies don’t fix the problem because they aren’t aligned with the underlying cause of the problem. When your child welfare workforce is understaffed or overwhelmed it is tempting to want to find an immediate fix because the need to expand the workforce is urgent. However, it …

How Can Child Welfare Agencies Leverage Data To Address Important Workforce Questions?, Quality Improvement Center For Workforce Development

QIC-Tips

Child welfare agencies experience workforce turnover (14-20% annually) that can be costly and result in poorer outcomes for children and families. Although turnover is often acknowledged as a significant problem, it is not one that is easily understood or addressed. The following tips and strategies being implemented by jurisdictions working with the QIC-WD may be helpful for child welfare administrators, legislators, and other policymakers seeking to utilize agency data to answer pertinent child welfare workforce questions.

• Understand what data is collected and stored, and where. Oftentimes, there are multiple systems used by agencies during the employee lifecycle that may contain …

Building Capacity To Effectively Share And Use Data, Robert Blagg

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In child welfare, the need to utilize meaningful data to ensure that the services provided are effective in supporting children and families represents a continuing challenge. There is a large volume of data from sources that are internal and external to child welfare agencies; and it increases almost exponentially on a regular basis. It is difficult for leaders and practitioners to quickly and meaningfully synthesize, make use of, and share new information with colleagues who need it to make sound decisions. Even when data is transformed into knowledge, challenges remain around the preferred method of ensuring information reaches the individuals …

Introduction To Data Dictionaries, Quality Improvement Center For Workforce Development

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Are you interested in exploring how to leverage the data necessary to examine and address child welfare workforce challenges in your agency? If so, you may consider developing and using a human resources data dictionary to help guide your work. A data dictionary is a collection of detailed information about the content and structure of data in one or more databases. This descriptive information is often called metadata (i.e., data about data). Other terms used to describe data dictionaries include data definition matrix, metadata repository, design dictionary, and business glossary. You also might see other variations of these terms, further …

Introduction To Workforce Metrics, Quality Improvement Center For Workforce Development

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It is important for Human Resources (HR) and child welfare leaders to start with a question-based mindset when analyzing workforce data (i.e., being thoughtful about what you and/or your stakeholders want to know), but it is also important to leave room to explore the data as well. This can only be accomplished if you know what is possible. This blog post describes some of what is possible to explore within the realm of workforce metrics as they relate to employee well-being, performance, and retention. In many ways, the concept of workforce metrics is still in its infancy and many things …

Want To Improve Organizational Outcomes? Consider People Analytics, Quality Improvement Center For Workforce Development

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People analytics has been around for more than 20 years. However, it continues to be viewed as an emerging area of study. People analytics shows the contribution that the workforce makes to organizational success and provides insight to maximize that contribution. It is an evidence-based practice that allows human resources (HR) staff to evaluate practice for the purpose of improving outcomes for employees, and to communicate with the workforce the effectiveness of personnel management and HR practice. People data, when used appropriately, may improve trust and transparency within organizations. There is evidence that organizations are not using the people and …

Does Your Agency Embrace Evidence -Based Management Practices?, Quality Improvement Center For Workforce Development

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Child welfare agencies are encouraged to use evidencebased practices in all aspects of their work to try to improve outcomes for children and families. The child welfare field has made improvements in using data, research, and evaluation to inform practice and decision-making, but still has a ways to go. The primary goal of the Quality Improvement Center for Workforce Development (QIC-WD) is to build the evidence base regarding strategies to strengthen the child welfare workforce. One means of practicing evidence-based management for improving workforce outcomes is using workforce analytics. As part of the Child Welfare Workforce Analytics Institute, the QIC-WD …

Seal, Social Experiences In Assisted Living: Social Network Analysis Data, Rebecca Mauldin

Social Work Datasets

This dataset is from a longitudinal social network analysis research project that collected survey data on three separate occasions over a 6-month period from residents in a single assisted living facility. It includes psychosocial survey data and social network survey data on acquaintance, companionship, social support, and negative interaction ties among residents of the assisted living facility. === We recommend reading the README.txt and Data Overview - SEAL.pdf files for an orientation to the dataset. ===

Developing Information On Mental Health And Counseling Services, Katherine Bustamante

Capstone Projects and Master's Theses

Taylor Farms Center for Learning (TFCFL) is an afterschool program, which is located in East Salinas, serving primarily 76% of Hispanic and Latino children and families. Providing various programs to break down barriers for children to experience success. Every year in the United States, up to 20% of children and youth experience a mental, emotional, or behavioral disorder but nearly half of all children receive no mental health services. Due to this few agency-sponsored services address this health issue and TFCFL wants to make sure they are offering the right kind of services for their community. This research project will …

Geochemical Data From Angamuco, Michoacán, Mexico, Anna S. Cohen, Daniel E. Pierce

Sociology, Social Work and Anthropology Faculty Publications

Included here are geochemical concentrations (ppm) of ceramic artifacts and clay samples from the archaeological site of Angamuco, Mexico. Additional data include maps and photographs of the ceramic samples. Concentrations were measured via Instrumental Neutron Activation Analysis and are available here asAppendix B. These data complement the discussions and interpretations in “Geochemical Analysis and Spatial Trends of Ceramics and Clay from Angamuco, Michoacán”[1].

Qic-Wd Site Intervention Selection – Fall 2018, Quality Improvement Center For Workforce Development

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The eight QIC-WD sites have worked with the QIC-WD to determined which intervention to implement and evaluate to strengthen their child welfare workforce. These decisions came after a thorough needs assessment through which human resources (HR) data was examined to uncover the root causes of child welfare caseworker turnover. The sites recognize that turnover is not caused by a single issue, so they had to consider which aspect of turnover they could address in partnership with the QIC-WD. The QIC-WD team simultaneously examined available interventions, study designs, and the needs of the broader child welfare field to help each site …

Knowledge Diffusion And Utilization Within A System Of Care Model: Success And Challenges, Betty Walton, Isaac Karikari, Christine Marie Bishop, Erin Tock

Faculty Publications

•Transitioning from required collection & reporting of grant data to routinely using information for planning and quality improvement processes at direct service, program, and system levels •Explores necessary conditions for the successful use of information to plan and monitor progress •Highlights tips •Applying tips to your practice

Unlocking The Potential In Your Workforce Data, Quality Improvement Center For Workforce Development

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Communicating complex ideas to diverse stakeholders is central to reliable decision making. Stakeholders may vary greatly in their interest, familiarity, or expertise with data regarding a policy, program, or practice. Well-designed data visualizations provide a platform for engaging stakeholders in ways that are tailored to their interest, familiarity, and expertise. However, research indicates that visualizations are not always designed effectively to reliably motivate users to understand and ultimately use the data in their decision-making (Evergreen, 2011; Cawthon & Moere, 2007). Thoughtful and engaging visualizations demand the stakeholders’ attention and can facilitate the comprehension of findings (Hillstrom & Yantis, 1994; Treisman, …