INCREASING EFFICIENCY AND EFFECTIVENESS IN LARGE COMPANIES BY COMBINING SIX SIGMA WITH BPM

The paper underlines the importance in combining the Six Sigma methodology with BPM technology. Companies are just discovering the benefits of combining BPM and Six Sigma. Ideal for enhancing the longterm performance of business processes, the BPM/Six Sigma union helps companies better characterize, understand, and manage entire value chains. It also helps companies improve control and predictability of corporate business processes and generate sustainable enterprise improvements in performance levels.The study starts with the concept of Six Sigma which was powered by principles governed by continuous improvement. In pure terms, Six Sigma helps manufacturing organizations reduce the number of errors or reduce the number of defective products manufactured by them. This is achieved by a regular sharpening of the process and constant monitoring on processes and how they can be improved. This approach had been truly effective in ensuring quality in a manufacturing environment and was later adopted by the services industry during the 90s. However, as the Six Sigma framework relied heavily on the collection and analysis of data of individual processes, synchronizing them between departments was ignored. This resulted in improvement benefits being limited to specific functions only, without taking into consideration the integration with other processes. Another weakness of the Six Sigma methodology is the lack of control used to sustain improvements achieved. This stems from the fact Six Sigma utilizes manual processes to do this, an approach that lacks effectiveness. In this sense, Business Process Management (BPM) initiatives address areas that Six Sigma falls short of, in line with the purpose of achieving excellence in organizations. These two methodologies complement each other to compensate for areas of weaknesses. Although BPM addresses process enhancements and monitoring from a holistic viewpoint, it fails to address the analytical requirements to solve complex issues.