To ensure the representativeness of the data, it is imperative for the researcher to collect data from multiple regions, necessitating the involvement of third-party individuals known as enumerators. Due to the researcher's inability to accompany these enumerators in the data collection process, the phenomenon known as the enumerator effect comes into play. This effect can lead to various outcomes such as identical responses, straight lining, or flatlining of data across the indicators of any particular constructs. Subsequently, the utilization of Microsoft Excel becomes crucial for visually detecting instances of straight lining and conducting subsequent kurtosis analyses to further examine the data. Strategies for mitigating the occurrence of straight lining within the data will also be explored and discussed in this context.