NOTE: The following blog was written by Luke Spooner who was one of two recipients of the CESBCY Student Bursary Award.  Luke is a graduate student in the Faculty of Pharmacy at The University of British Columbia and a Research Assistant at Broadleaf Consulting. The second recipient was Jacob Helliwell who is pursuing an MPA at University of Victoria.  See Jacob’s blog titled: Three Reasons you Should Attend c2017: Student Edition.

This past year, working as an evaluator, has been an amazing new learning experience for me.  As an evaluation researcher, I have focused on evaluating programs through various quantitative and qualitative methods. Through the use of these methods, I have been able to determine if a program has been effective in achieving its targeted outcomes. However, sometimes it is challenging to determine how different aspects of a program contribute to the program’s overall impact. I’ve learned that if program evaluation can lead to a better understanding and optimization of contributing parts of a program, that program will be in a better position to  use limited resources effectively and efficiently.

It is fascinating to see first-hand how different aspects of a program coalesce and uniquely contribute to outcomes. My experience has also made me reflect and ask: Can we improve how we collect data to evaluate all these different program aspects?  The collection of data can be time consuming, difficult, and sometimes a low priority for program leaders as they often are primarily focused on program implementation rather than the evaluation. These factors can all lead to incomplete and insufficient data, which makes it difficult to make good planning decisions.

To improve the quality of the evaluations we conduct, it is important for evaluators to ask these three questions: What data is necessary for evaluation of this program, what is the simplest way we can collect this data, and how can we best simplify data collection? One approach that I have found useful in improving data collection is to create and provide data collection tools. Data collection tools that are easy to use and provide visual feedback, such as a graph or bar chart, are simple and effective ways of reducing the burden of data collection and improving the quality of data collected. Another approach is to reduce the amount of data collected. Using simpler methods to measure program outcomes allows for less data to be collected,  and this data is often more complete and accurate. Ultimately, there are many possible approaches to improve how we collect data in our evaluations. Considering questions of need and simplicity will improve the quality of data collected, and will lead to better evaluations and future program planning.

Key words: Reflection, Big Data, Data Quality, Evaluation

Twitter account: @LSpooner2