One of the important aspects of a State of Health (SOH) estimation algorithm is to not only give a measure of the cell capacity but also to provide information on degradation of individual electrodes. In this paper, individual electrode capacity and utilization window are proposed as parameters related to individual electrode degradation. These parameters are then identified using the Open Circuit Voltage (OCV) and their identifiability is studied for different operating windows. The windows are motivated by practical limitations in the availability of data for deep discharged and full charged states in real-world battery applications. The identifiability analysis here is based on the condition number of the normalized sensitivity matrix with respect to the data window size and location. This classical metric is then used to tie the identifiability of the electrode parameters with data acquired around phase transitions of the electrode material. It is shown that having data at phase transitions provides better identifiability of the individual electrode parameters. It is noted that the results agree with the long-established method, Differential Voltage Analysis (DVA), used by electrochemists. In DVA, the terminal voltage data across phase transitions is used to compute shifts in the peak locations in the dV/dQ curve and relate to electrode capacity.