Paper Title :Predicting KPI Performance

Author :Manuel G. Cadongonan Jr.

Article Citation :Manuel G. Cadongonan Jr. , (2019 ) " Predicting KPI Performance " , International Journal of Management and Applied Science (IJMAS) , pp. 50-55, Volume-5,Issue-9

Abstract : This study proposed algorithms to predict the KPI performance of an organization. The Key Performance Most Fit Line algorithm finds the slope and y-intercept equation as fitting most of the KPI achievement reports submitted in weeks. The produced equation will serve as the minimum or maximum prediction KPI performance value against the values produced from the best-fit line equation of the Least Square algorithm. The KPMFL algorithm requires the output of the Key Performance Equivalence algorithm. The KPE algorithm computes the equivalent value of the percentage of KPI report per submission. The KPE algorithm includes factors such as degree of difficulty of attaining certain KPI and the time it takes to submit achievement for that KPI. These proposed algorithms were validated by six Information Technology and Quality Assurance Management experts from the Royal Commission Yanbu Colleges and Institutes in Saudi Arabia. Keywords - Key Performance Indicator, Performance Prediction Algorithm, Performance Measurement, Performance Most Fit Line

Type : Research paper

Published : Volume-5,Issue-9

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