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Today, transparency is imperative to succeed, and many funding sources will require that your proposal contain an evaluation section.

In your recommended resources there are two examples of logic models to assist you in understanding the assessment process. “The logic model it displays the sequence of actions that describe what the program is and will do – how investments link to results” (Taylor-Powell, Steele, & Douglah, 1996). We include five core components in this depiction of the program action:

• INPUTS: Resources, contributions, and investments that go into the program.
• OUTPUTS: Activities, services, events, and products that reach people who participate or who are targeted.
• OUTCOMES: Results or changes for individuals, groups, communities, organizations, communities, or systems.
• Assumptions: The beliefs we have about the program, the people involved, and the context and the way we think the program will work.

External Factors: The environment in which the program exists includes a variety of external factors that interact with and influence the program action? (University of Wisconsin Extension, 2014).

• Please read the case study of a local fire department prevention program below and consider how the fire department will determine the objective to be met, data to be gathered, specific measure, and data collection procedure.

Example:
A local fire department plans to expand its fire prevention program. The objective is to reduce losses to persons and property by reducing the number of fires in the community. More specifically, the department wishes to reduce the number of preventable fires by increasing the frequency of fire department inspections of residences and businesses. In the past, there has been no satisfactory method of separating the impact of some major fire prevention programs, such as pre-fire inspections, from effects of other factors. It has been hard to determine whether increased resources devoted to inspection would indeed reduce the rate of fires. The procedure that will be introduced in this program is the collection of data on the percentage and rate of fires deemed relatively preventable by inspection.

As the department plans its evaluation process, it considers the number of fires that are relatively preventable by inspection, per 1,000 occupancies, or 1,000 residencies. Changes in this rate over time may indicate the impact of their inspections; a decrease would presumably demonstrate their value.

The program’s benefits might also be demonstrated by the number of fires deemed preventable by inspection and a reduction in the number of fires in homes and businesses that have been inspected, compared to those that were not inspected.

The department is also concerned about process. For example, the ability to identify relatively preventable fires depends on the fire-cause categories used and the reliability of inspectors in identifying and recording those causes. Identifying preventable fires would be easier if fire-cause categories were defined with that purpose in mind. For example, rather than reporting only that a mechanical defect caused a fire, as is typically done, it would be useful to know whether the defect was one that could be seen or otherwise easily-detected during an inspection (Kiritz, 1979, para 1-5) .

In this way, the department fashions both its product and process evaluation. The department then produces a chart listing the aspects of the problem to be examined, the perspective measures to be employed, and the means to be used in gathering data:

Objective	Data to be Gathered	Specific Measure	Data Collection Procedure
Reducing the number of fires	Reported fire incidence rate	Number of reported fires per 1,000 population, total and by type of residential occupancy	Evaluator obtains data generally available from department records.
	Reported building fire incidence rate	Number of building fires per 1,000 occupancy types (e.g. single-family dwellings, duplexes, apartments, mobile homes, small stores) and by fire size	Number of occupancies by type may be estimated from planning department data(for residencies) or from pre-fire inspection records for commercial/industrial occupancies; fires size estimated by fire officer at the scene
	Reported plus unreported building fire incident rate	Number of unreported plus reported building fires per 1,000 households )or businesses), by type of occupancy	Evaluator surveys a representative sample of citizens and fire incident reports, reasons for underreporting would also be solicited
	Preventability of fire	Percentage and rate of fires that are relatively preventable by inspection or education	Intended for internal fire department analysis based on judgments as to the relative preventability of various types of fires
	Pre-fire inspection effectiveness	Rate of fires in inspected vs. uninspected (or frequently inspected vs. infrequently inspected occupancies, by type of occupancy and risk class	Data obtained by linking fire incident reports to fire inspection files

(Kiritz, 1979, para 6).