Cronbach’s Alpha is a widely used statistic for assessing the internal consistency of measurement instruments, yet its frequent misapplication and misinterpretation have led to substantial critique. This article revisits the theoretical underpinnings of Alpha, addressing its limitations and common misuses in contexts where essential criteria for objectivity, validity, and reliability are not met. It introduces the Harmonised Validity-Objectivity-Reliability (V-O-R) Framework, a systematic approach that integrates these foundational attributes to enhance reliability evaluation. By incorporating tools such as the test design line, the framework ensures scale validity through a balanced distribution of item difficulties, reducing biases and improving measurement precision. The article also provides theoretical curves that allow for the objective interpretation of Alpha values, based on the number of items distributed according to scale validity principles and the standard deviation of respondents' raw scores. Practical numerical examples illustrate typical, ideal, and problematic cases within the interval of Alpha values, showing how Alpha can be applied effectively within the Harmonised V-O-R Framework, enabling an objective and meaningful assessment of reliability while supporting deeper exploration of multidimensional traits measured by item clusters.