Assignment:
Discussion 1
The Office of Alumni Affairs is looking to evaluate if they are meeting the goal of increasing pledge fulfillment rate by 4% annually. Based on the quantitative data provided form 2011-2013 they had not seen an increase in pledge fulfillment. In fact, they actually saw a decrease in pledges by 2.63% overall. Additional data has been collected again over a two-year period, 2013-2015, to analyze whether there has been an increase of 4% annually. There are several steps to analyze this data to determine the success of meeting this goal.
The first step
(1) to analyze the data is to calculate the overall outcomes for pledge fulfillment rates each year, 2013-2015.
(2) The second step will be to compare the yearly pledge fulfillment rates to that of previous years. For example, was an increase or decrease seen from 2013 to 2014 and then again from 2014 to 2015.
(3)The third step is to compare the yearly pledge fulfillment data increase of decrease seen to that of the Office of Alumni Affairs goal of a 4% increase annually overall (The Urban Institute, 2004).
(4) If similar data is available through the Association of Private College and University Alumni Directors (PCUAD), the data can then also be compared and shared among previously established benchmarks (Redder, 2007).
To analyze further,
(5) the next step would be to look at the data breakdown based on demographics. For example, Age group is a demographic that can be analyzed to see if there continues to be a decrease in the 55+ age group and increase in under 30 and 30-55 years age group.
(6) The Native American Studies Alumni who are hypothesized to have seen an increase in donations due to the pilot program and blog is another outcome characteristic that can be compared.
(7) This data is then compared to previous annual pledge rates in the next step to determine if these differential groups specifically may have an effect collectively on the 4% increase.
(8) A closer look at the attendance to baseball games, archeological digs or participation in the blog are potential outcome indicators to analyze to determine possible reasons for successful or unsuccessful pledge rates.
(9) Where there are significant findings within the data such as increases above 4% or significant decreases among an age group, this should be highlighted.
(10) Based on the data analysis and any significant findings, the evaluation can help explain the success of the Office of Alumni Affairs programming and rates of increase or decrease among demographics annually (The Urban Institute, 2004).
Redder, K. (2007). Easy as Pie.
The Urban Institute (2004). Analyzing Outcome Information: Getting the Most from Data.
Discussion 2
The Office of Alumni Affairs at Binchley College set a goal of increasing the pledge fulfillment rate by 4% annually. According to the previous quantitative data gathered from 2011 to 2013, Binchley did not achieve the goal in 2012 or 2013. The data shows an overall decrease in the pledge fulfillment rate over the years rather than increase. Through additional data gathered from 2013 to 2015, Binchley can determine if the trend of decreasing overall pledge fulfillment continued or if the goal was still attainable. For the program to be properly evaluated to understand why there was either success failure, there are ten steps to follow.
The first step
(1) is to summarize the overall outcomes for the pledge fulfillment rates from 2013 to 2015. Typically, it is best to organize using tables, enabling the data to be easily analyzed together.
(2) is to compare the annual pledge fulfillment rates with previous years, such as 2011 to 2013. The comparison provides better context to properly interpret the data and will provide different benchmarks as indicators in the program (The Urban Institute, 2004).
(3) is to compare the outcome of the pledge fulfillment rate to the set goal of an annual increase of 4%. The comparison will provide proof of how well the program is doing. Upon the analysis, I can determine if the program needs to change or if it is meeting the goal.
(4) is to compare the outcome from Binchley's program with that of similar programs. Such programs, for example, can be provided through the Association of Private College and University Alumni Directors or PCUAD. PCUAD shares benchmark information to colleges to improve alumni programs (Redder, 2007). The comparison can show me what other institutions are doing right in the program to develop successful results.
After gathering the basic data,
(5) is to compare the outcomes of the programs according to demographic group. For example, in the 2011 to 2013 years of the program, the data was divided into different categories including three age groups of alumni. Using the data provided for 2013-2015, I would following the same age groups established the previous years, under 30, 30-55, and over 55.
(6) is to compare outcomes by service characteristics and I would utilize the academic majors. The student intern supervisor inferred that the Native American program developed by the associate director had a positive influence on pledge fulfillment (Hackling, 2019). Analyzing the data by academic major will indicate if her inference has merit to it.
(7) is to compare the outcomes by age group and service group from 2013-2015 with the previous years of 2011-2013. The first data set, 2011-2013, was showing an increasing trend in both age groups of under 30 and 30-55 while there was a decrease in age 55 and over (Hackling, 2019). The comparison by age will show how the trend matures and the success of the program through the years.
(8) is to examine findings across all available outcome indicators. I would utilize the data on participation and attendance at the multiple reunions, baseballs games, contributions to the blog, and archeological digs as potential indicators. Development of relationships with alumni and donors has produced positive results on pledge fulfillment rates in the Native American program, so participation in events like baseball games can foster the same feeling, indicating possible reasons for successful pledge rates.
After analyzing and compiling all the data, specific data can be highlighted that provides the most helpful information for my purposes. For example, I would focus on significant increases or decrease in the pledge fulfillment rate that impact the success of the program heavily. With the goal of an annual increase of 4%. Any unusual or unexpected numbers would be highlighted. I would highlight areas with increases or decreases of that percentage. Lastly,
(9) I would look for answers to why the program is a success or failure. Through an analysis of the significant data, I can determine what factors led to the result of the program. For example, the external factor of aging alumni over 55 years old leading to passing away or retirement and the limited funds preventing additional pilot programs similar to the Native American program could explain the decreases in the annual overall pledge fulfillment rate. Following a full analysis, I can find explanations and the findings would be communicated to the Office of Alumni Affairs to lead to improvement of the program.
References
Hackling, K. (2019). Milestone Two- Draft of Data Presentation. Unpublished paper, Southern New Hampshire University.
Redder, K. (2007). Easy as Pie.
The Urban Institute (2004). Analyzing Outcome Information: Getting the Most from Data.