A Quantitative Assessment of Data Accuracy and Operational Efficiency in Digital Service Platforms

Abstract

This study presented a quantitative assessment of the relationship between data accuracy and operational efficiency in digital service platforms, with a focus on measuring how data quality dimensions influenced system performance outcomes. A cross-sectional explanatory research design was adopted, utilizing a dataset of 210 observations derived from system-generated records and structured questionnaire responses. Key variables included data accuracy dimensions such as validity, consistency, and completeness, alongside operational efficiency indicators including processing time, response latency, throughput, and workflow completion rate. Descriptive analysis revealed that data validity (M = 3.94, SD = 0.62), consistency (M = 3.88, SD = 0.67), and completeness (M = 3.91, SD = 0.59) exhibited moderate variability, while operational efficiency measures such as throughput (M = 145.3 transactions per minute) and workflow completion rate (M = 91.6%) indicated relatively stable performance levels across platforms. Inferential analysis demonstrated statistically significant relationships between data accuracy and operational efficiency. Correlation coefficients ranged from 0.41 to 0.68, indicating moderate to strong associations, with data consistency showing the strongest relationship with workflow completion rate (r = 0.68). Multiple regression analysis revealed that data accuracy variables collectively explained 57% of the variance in operational efficiency (Adjusted R² = 0.57, p < 0.001). Among predictors, data consistency (β = 0.42) and completeness (β = 0.36) exhibited the highest influence, while validity (β = 0.29) also contributed significantly. Effect size analysis further confirmed the practical importance of these relationships, with an overall large effect size (f² = 0.28). Subgroup analysis indicated that high-volume platforms exhibited stronger relationships between data accuracy and efficiency, while systems with advanced validation mechanisms achieved higher performance levels (M = 4.35). The findings established that data accuracy is a critical determinant of operational efficiency, with both statistical and practical significance, providing a robust empirical foundation for understanding performance optimization in digital service platforms.