Reducing costs, burden, and risk of human error in large scale survey data collection and Scope of Work reporting using Automation

Abstract

Ongoing activities involving multiple stages or partner organizations–such as tracking survey participants or program subcontractor activities–can result in time-consuming and expensive data collection processes that are at risk of human error. The examples provided are from 1) a survey reaching 4,000+ college students across 10 institutions, and 2) a reporting workflow collecting scope of work data from 50+ subcontractors. In both cases, a series of R scripts were used to automate processes along the entire project pipeline. The scripts replaced or streamlined connections between data collection tools like Google Forms, Excel, and Qualtrics and reduced the risk of mistakes at critical points such as survey eligibility. We saw a 90% reduction of personnel costs associated with survey administration (800hr/30wk) and a 98% reduction for funder reporting (2048hr/yr). Using scripts to minimize manual survey collection tasks allowed for an expanded recruitment at effectively the same cost. Likewise, automating the collection and processing of funder-required evaluation data allowed for more time to be spent on program implementation and eased the reporting burden on the subcontractors.