Policy analysis (PA), as a set of public administration techniques concerned with the evaluation of novel and pre-existing policies, represents a field fraught with human-related risks. When fulfilling their responsibilities, policy analysts should be guided by the principles of concern for others, integrity, and honesty in assessing the policy’s utility. Employing these principles would involve self-criticism and self-correction in one’s approaches to evidence and impartiality.
These principles call for eliminating the risks of policy-related decisions that would eventually bring harm, which explains their importance. Being concerned for the policy’s stakeholders should be a guiding principle for analysts since PA, despite requiring objectivity, needs to examine the affected population’s perspective to comprehend the policy’s effects. Document analysis, which is a common element of PA methodologies, might involve analysts’ access to sensitive personal documents and data (Kayesa & Shung-King, 2021). Thus, demonstrating integrity in the form of truthfulness and the avoidance of manipulations with data should be crucial for PA practitioners. Finally, honesty in utility assessments should represent another guiding principle for analysts since the understatement of policies’ hypothetical negative outcomes would undermine PA’s actual purpose.
When conducting PA, I would employ the identified principles by preventing deviations from higher standards through self-monitoring. In terms of concern for others, I would find the right balance between reliance on objective evidence and visualizing the affected group’s overall perspective of the policy. To employ integrity, I would anatomize my thought processes to avoid the cherry-picking fallacy and the inconsistent application of ethical principles when working with data (Guardia et al., 2021).
In conclusion, honesty in utility assessments would be implemented by using all available evidence and considering its scope to screen for the presence of the policy’s unintended consequences for the key affected group and society in general. Implementing these considerations could be conducive to analytical findings that would effectively predict heterogeneous society’s reactions to the policy.
Guardia, F. H. D. L., Grant, S., & Miguel, E. (2021). A framework for open policy analysis. Science & Public Policy (SPP), 48(2), 154-163.
Kayesa, N. K., & Shung-King, M. (2021). The role of document analysis in health policy analysis studies in low and middle-income countries: Lessons for HPA researchers from a qualitative systematic review. Health Policy Open, 2, 1-13.