This paper presents an industrial-grade hardware-in-the-loop (HIL) validation method for a wide-area monitoring system designed to detect electromechanical oscillations in power systems. The proposed method leverages dynamic mode decomposition (DMD) to extract spatiotemporal patterns from synchronized phasor measurements, enabling accurate identification of oscillation modes. Traditional methods are widely used but face limitations in accurately capturing complex system dynamics. Despite the improved processing capabilities of modern controllers, advanced data-driven methods such as DMD remain underutilized due to concerns about computational cost and implementation complexity. This paper demonstrates the feasibility of integrating DMD into industrial-grade controllers by employing efficient algorithms such as singular value decomposition and QR decomposition. A comparative analysis with the Prony method across multiple test systems, along with industrial-grade hardware-in-the-loop validation, confirms the accuracy and computational efficiency of DMD for real-time applications. Results show that DMD reliably identifies local modes, inter-area oscillations, multimodal behavior, and mode shapes. These findings support the integration of spatiotemporal methods into industrial-grade controllers to improve the performance of real-time monitoring on power system stability.