The minimum energy point of an integrated circuit (IC) is defined as the value of the supply voltage at which the energy per operation of the circuit is minimized. Several factors influence what the value of this voltage can be, including the topology of the circuit itself, the input activity factor, and the process technology in which the circuit is implemented. For application-specific ICs (ASICs), the minimum energy point usually occurs at a subthreshold supply voltage. Advances in subthreshold circuit design now permit correct circuit operation at, or even below, the minimum energy point. Since energy consumption is proportional to the square of the supply voltage, circuit design techniques and process technology choices that reduce the minimum energy point inherently improve the energy efficiency of ICs. Previous research has shown that optimizing process technology for subthreshold operation can improve IC energy efficiency. This, coupled with the energy efficiency advantages offered by fully-depleted silicon-on-insulator (FDSOI) processes, have led to the development of a subthreshold-optimized FDSOI process at MIT Lincoln Laboratory (MITLL) called xLP (Extreme Low Power). However, to date there has not been a quantitative estimate of the energy efficiency benefit of xLP or other analagous technology for complex digital circuits. This paper will show via simulation that the xLP process technology enables energy efficiency improvements that exceed that of process scaling by one generation. Specifically, the process is shown to improve power delay product by 57% vs. the IBM 90nm low power bulk process, and by 9% vs. the IBM 65 nm low power bulk technology at 0.3V.