@article {10.3844/ajassp.2015.945.951, article_type = {journal}, title = {Quantifying Business Process Optimization using Regression}, author = {Miyambu, Gezani Richman and Seeletse, Solly Matshonisa}, volume = {12}, year = {2015}, month = {Nov}, pages = {945-951}, doi = {10.3844/ajassp.2015.945.951}, url = {https://thescipub.com/abstract/ajassp.2015.945.951}, abstract = {The paper applies regression methods to model Business Process Optimisation (BPO) in order to derive measures for the extent of BPO achievement if efforts to optimise have already started. This will help to identify components of business that still need to be improved if full optimisation has not yet been achieved in a business. Regression methods were used to explain the tentative relationship of BPO with the variables identified as components of BPO. Two models (one with dummy coefficients and another with probabilistic coefficients) were developed. The first one was found to be unsuitable and lacked resources for further development. The second was satisfactory. A measure of BPO progress was then developed. The data used in the experiments were obtained from a private bank in South Africa. A regression model was designed and then fitted, statistically tested and found to be acceptable. Also, an estimate of the measure of BPO attainment level was developed. The study achieved its main goal, but acknowledgment is made to do more experiments with several larger data sets.}, journal = {American Journal of Applied Sciences}, publisher = {Science Publications} }