Amazon HRIS Data Governance & Workforce Analytics Policy

[Audio] Today I'll be walking you through my HRIS Policy and Proposal for Amazon, with an emphasis on data governance and workforce analytics. I'll be giving an overview of the main parts of my project and explaining how Amazon's HRIS supports the company's overall performance..

[Audio] Amazon is one of the largest global leaders in e-commerce and cloud services, employing well over a million people around the world. With operations spanning fulfillment centers, corporate offices, delivery networks, and AWS facilities, the company depends heavily on HR technology to manage staffing, compliance, and planning. Handling such a massive amount of employee data means Amazon needs an HRIS that is secure, dependable, and capable of supporting quick, informed decisions..

[Audio] For this project, I concentrated on two major pieces of Amazon's HRIS: • Data governance • Workforce analytics Data governance is essential because Amazon manages sensitive personal data across multiple countries with different laws and regulations. Workforce analytics matters just as much because Amazon relies on accurate labor forecasts, productivity information, and scheduling models to keep operations running efficiently. Together, these two areas help ensure the company's HR practices are ethical, secure, and driven by reliable data..

[Audio] Component 1: Data Protection & Privacy The first part of the policy focuses on safeguarding employee information. It outlines expectations for how data is collected, stored, and retained. Key elements include strong encryption, secure data transfers, and clear boundaries on how HR information can be used. The policy also reinforces compliance with laws such as GDPR and CCPA. Given the scale at which Amazon operates, these protections are necessary to limit risk and maintain employee confidence..

[Audio] Component 2: Role-Based Access Control The second component addresses access control within the HRIS. Employee data should only be available to individuals who genuinely need it—such as HR staff, certain managers, or operational leaders. Restricting permissions helps prevent unauthorized access or unintentional misuse of information. The policy also calls for regular reviews of user access to make sure permissions stay appropriate as employees move into new roles..

[Audio] Component 3: Workforce Analytics Standards The third component sets expectations for how workforce analytics should be used. It highlights the importance of ethical practices, transparency around algorithm-based decisions, and routine checks for bias in tools used for hiring, performance evaluation, or scheduling. The HRIS must also have systems in place to verify data accuracy so that analytics produce reliable insights. A good example is Amazon's use of predictive scheduling in fulfillment centers. These tools rely on real-time data to anticipate staffing needs, helping managers control overtime and maintain service efficiency. This shows how a well-managed HRIS can directly improve operational outcomes..

[Audio] The final section offers two recommendations to keep the HRIS strong over time. First, Amazon should broaden its HRIS training efforts. As systems evolve, employees need regular updates on new features, security expectations, and privacy requirements. Second, the company should conduct more frequent audits of data quality and system access. Routine checks help catch errors, confirm accuracy, and strengthen overall security. By following these recommendations, Amazon can continue to use its HRIS in a way that is secure, ethical, and supportive of its long-term goals. Strong data governance and effective analytics translate to better staffing decisions, clearer insights, and improved organizational performance..