Data

From 2004 through 2006 the Clark County Family and Children First Council in partnership with the Clark County Funders Forum participated in a community wide strategic planning process using a model developed by the Ohio State University Center for Learning Excellence and called Partnerships for Success (PfS).

PfS is a comprehensive planning and implementation

model based on a set of guiding principles that have been articulated in the literature on the effective prevention and reduction of youth problem behaviors and the promotion of positive youth development.  That set of guiding principles includes Making Data-Informed Decisions.  This guiding principle requires that communities continually review data in order to define priorities and make decisions related to program implementation.

Four levels of data informed decisions are involved in PfS:

  • First, data are used to determine the magnitude of problem behaviors in a community and prioritize efforts to respond to them.
  • Second, data are used to identify levels of risk, protection, and assets that exist within the community to help target potentially effective strategies.
  • Third, data are used to determine best practices related to implementation decisions for new programs. Programs with highly feasible approaches based on sound scientific evaluations are preferred.
  • Finally, data are used to continually evaluate the progress of the PfS Initiative within the community.


Clark County’s PfS Strategic Initiatives Report in 2006 included the recommendation for a central data base with standardized data collection and regular trend analysis.  Throughout the PfS process it was clear that a consistent data collection mechanism does not exist in Clark County. Data collection and retention vary from organization to organization and from field to field. Data, when found, vary in depth, dependability, and format. This situation leaves leaders and funders unable to consistently reference uniform statistical information or cross-reference evidence from program to program. Establishing data-informed, “big-picture” priorities and engaging in data-informed decision making is difficult in most instances.