The data collection process has various steps that require expertise in formulation and implementation and this is done best by properly trained data collectors. Regardless of the preference for defining data whether qualitative or quantitative, accurate data collection is important to ensure that the integrity of the research is maintained.
Data collection by improperly trained data collectors leads to the inability to accurately answer the research questions, distorted findings therefore wasted resources, inability to validate or repeat the study, compromising decision in regard to public policy, misleading of other researchers pursuing the same or related research topic and causes harm to the participating agents. Improperly trained data collectors lead to poor results and if the results are used to support recommendations of public policy, it will cause disproportionate harm. Improperly trained data collectors will not comply to the research questions and may collect data that is not a true reflection of the natural situation.
The goal of a research is to help improve a situation or come up with amicable solutions to a problem. This involves accurate data collection and carrying out a relevant data analysis through careful planning and thorough thoughts (Bedi, Bhatti , Gine, Galasso, Goldstein and Legovini, 2006). Collection of sub standard information and data implies that the evaluator will arrive at the wrong conclusion and that the wrong recommendations will be implemented. Outcome evaluation seeks to establish the effectiveness of the research, reaching at an accurate conclusion from the collected data and making recommendations. Thus if the data collected is inaccurate, the analysis and conclusion will be wrong.
To overcome these problems, the evaluator is required to design the needs of the data collectors especially where there are multiple data collectors. The evaluator