Power states in power-scalable systems are managed to maximize performance and reduce energy waste. Power-scalable processor capabilities (e.g., Intel Turbo Boost) embrace a "faster is better" approach to power management. While these technologies can vastly improve performance and energy efficiency, there is a growing body of evidence that "faster is not always better". For example, in some I/O intensive benchmarks, we observe up to 47% performance loss when running codes at faster (higher power) frequencies versus slower (lower power) frequencies. To the best of our knowledge, this is the first work to systematically and accurately pinpoint the root cause of these types of slowdowns. The lack of such studies is likely due to three challenges we overcome in this work: 1) high runtime system variance, 2) bottleneck isolation across user- and system-space boundaries, and 3) non-determinism in parallel codes. Our analytical model-driven approach isolates resource contention as the root cause of slowdowns at higher processor speeds and suggests solutions we test empirically. We propose and evaluate the use of a power-aware that can increase performance more than 3-fold over the default Linux kernel while maintaining comparable reliability in the I/O subsystem. Our work motivates the need for more studies that potentially reconsider the "faster is better" design paradigm.