Assessing product maturity is vital for ensuring quality and reliability in product development, yet the concept of maturity remains ambiguously defined. Traditional maturity rating methods, rely heavily on subjective expert reviews, which can be costly and inconsistent. A possible alternative is a measurement-based approach for maturity rating, which is proposed in this paper to the example of Powertrain Software. By observing overall system behavior through measurement data, the approach eliminates subjective biases inherent in expert reviews. The methodology focuses on three main domains: Functionality, Drivability, and Performance, each requiring distinct evaluation metrics. For drivability, maneuvers are detected using a combination of Euclidean distance and Dynamic Time Warping (DTW), enhancing robustness against data noise and variability. The proposed method successfully identifies maneuvers within larger datasets, providing a reliable similarity measure that can further be used in maturity ratings. This approach reduces coding effort and user interaction while maintaining detection accuracy, offering an additional benefit for maturity rating.