Data Analysis

Data Analysis

Data analysis provides us with the "tools" and information to make critical decisions about best practices, monitor for any disparate treatment, advocate for additional funding or flexibility to meet the needs of the children, youth and families served, assess the best use of our resources (both internal and external) and help us to plan strategically. Data analysis includes various sub processes, e.g., generating data reports, extracting reports from existing databases and interpretation. Information obtained from data analysis helps inform the broader community about the needs of children, youth and families and encourages them to invest in their future.

 

Data analysis allows us to understand the population being served by the organization and the issues confronting it. It allows for an assessment of the impact of services that have been provided to children, youth and families. Methods used to analyze the data should be dictated by the underlying objective of the analysis (i.e., the question) and could involve simple descriptive statistics (counts) to more complicated statistical analysis designed to offer an understanding of association (regression and other techniques). Additional methods include qualitative analysis and mixed-use methods.

 

Data analysis includes additional processes such as generating data reports and the interpretation of these reports through the lens of the public child welfare system. Statistical manipulation of data is not the sole source of analysis. Reasoning skills also allow meaningful interpretation of the statistical findings and data analysis.

 

Quality decisions result from a careful and thorough evaluation (analysis) of relevant information. These analyses will complement the decision-making skills for staff at all levels within the organization and advance the use of these methods as a decision support tool. Data analysis that focuses on generating reports from existing sources should include the following as a basis for using reports to improve decision-making:

  • Measure performance in the target areas.
  • Create sub categories of reports based on user requirements.
  • Support data clean up and report development and maintenance efforts. Distribute reports to appropriate stakeholders.

Core competencies of professionals responsible for analyzing data include:

  • Quantitative reasoning skills in decision-making.
  • Using quantitative findings to support decision-making.
  • Ability to use various software to generate appropriate statistical findings. Meaningful interpretation of management reports.
  • ssment skills to test the validity of the statistical findings.
  • Interactive skills with statistical analysis.





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