A statistical system management method to tackle data uncertainty when using key performance indicators of the balanced scorecard

[EN] This work is focused on the development of a graphical method using statistical non-parametric tests for randomness and parametric tests to detect significant trends and shifts in key performance indicators from balanced scorecards. It provides managers and executives with a tool to determine if processes are improving or decaying. The method tackles the hitherto unresolved problem of data uncertainty due to sample size for key performance indicators on scorecards. The method has been developed and applied in a multinational manufacturing company using scorecard data from two complete years as a case study approach to test validity and effectiveness. Sánchez-Márquez, R.; Albarracín Guillem, JM.; Vicens Salort, E.; Jabaloyes Vivas, JM. (2018). A statistical system management method to tackle data uncertainty when using key performance indicators of the balanced scorecard. Journal of Manufacturing Systems. 48:166-179. https://doi.org/10.1016/j.jmsy.2018.07.010