Implementing Big Data Analysis Platform and Risk Management Resilience in A Manufacturing Industry in Beijing, China

This study examined the implementation of Big Data Analysis Platforms and the level of Risk Management Resilience among employees in manufacturing companies in China. Using a quantitative descriptive-correlational research design, data were gathered from 256 employee-respondents through a structured questionnaire measured on a four-point Likert scale. The respondents were mostly staff, employees with 1 to 3 years of service, and those assigned to the Production Department. Findings revealed that the implementation of the Big Data Analysis Platform was evident, with an overall mean of 3.04. Among its dimensions, Business Alignment and Value Framing obtained the highest mean of 3.12, while Storage and Modeling obtained the lowest mean of 2.91, suggesting that data infrastructure and modeling systems may still require improvement. Risk Management Resilience was likewise assessed as evident, with an overall mean of 3.10. Exposure and Vulnerability Baseline received the highest mean of 3.15, while Absorptive Capacity and Continuity Performance obtained the lowest mean of 3.05. ANOVA results showed no significant differences in the assessments when grouped according to position. However, significant differences were found according to length of service in selected dimensions of both Big Data Analysis Platform implementation and Risk Management Resilience. Departmental differences were observed only in Business Alignment and Value Framing. Correlation analysis revealed a very strong positive and significant relationship between Big Data Analysis Platform implementation and Risk Management Resilience, with r = 0.85 and p < .001. The findings suggest that stronger data platform implementation is closely associated with better organizational resilience. The study recommends improving data storage and modeling, strengthening business continuity systems, enhancing employee data literacy, and