Lithium ion battery (LIB) degradation originates from complex mechanisms, usually interacting simultaneously in various degrees of intensity. Due to its complexity, to date, identifying battery aging mechanisms remains challenging. Recent improvements in battery degradation identification have been developed, including validated, in-situ incremental capacity (IC) and peak area (PA) analysis. Due to their in-situ and non-destructive nature, IC and PA implementation is feasible in on-board battery management systems (BMS). Despite their advantages, the understanding and applicability of IC and PA techniques is not straightforward, as it requires both electrochemical and material science backgrounds. However, BMS design teams are mainly integrated by electrical engineers and may not include battery scientists. Aiming to bridge gaps in knowledge between electrical engineering and battery science towards battery degradation identification, here we present a systematic approach consisting in a set of look-up tables generated from IC and PA techniques. The look-up tables provide a simple, yet reliable tool for the evaluation of LIB degradation modes. Various real-life examples of cell degradation are also presented to illustrate and validate the use of the proposed approach. This study exemplifies the use of look-up tables providing a simple, fast, and accurate automated estimation of LIB degradation modes to be implemented in BMSs.