Abstract
Traditional performance appraisal (PA) methods, often reliant on static measures, are increasingly misaligned with the needs of organizations in the complex, continuously evolving, modern work environment. Such methods offer only a snapshot of team performance from a fixed perspective, failing to capture a context-informed scope of performance over time. This limitation restricts engineering managers' ability to make context-informed decisions on resource allocation, potentially misaligning actions or objectives with current or future organizational needs and exacerbating discrepancies between evaluated and actual performance. Consequently, inaccurately assessed employees may feel undervalued or experience decreased motivation and job satisfaction, potentially resulting in higher turnover rates. Addressing these shortcomings requires reevaluating team performance measurement and management. One potential solution for facilitating this approach is adopting mathematical methods that signal changes in team dynamics to leadership and support responsive behavior adjustments based on context-derived insights. Observing patterns in these behaviors, tracking their changes, and leveraging the information they provide becomes a relevant strategy by allowing leaders to monitor the interplay between the team's behaviors and the context in which it operates. This approach enables engineering managers to observe the identification of shifts and disruptions within team dynamics. This paper introduces a novel mathematical appraisal model, incorporating the transdisciplinary principles of systems thinking and categorical sheaf theory to enhance engineering managers' understanding of team performance with context-informed insights.