Deep business optimization: A platform for automated process optimization

Abstract

The efficient and effective design, execution and adaption of its core processes is vital for the success of most businesses and a major source of competitive advantage. Despite this critical importance, process optimization today largely depends on manual analytics and the ability of business analysts to spot the 'right' designs and areas of improvement. This is because current techniques typically fall short in three areas: they fail to integrate relevant data sources, they do not provide optimal analytical procedures and they leave it up to analysts to identify the best process design. Hence, we propose in this paper a platform that enables (semi-)automated process optimization during the process design, execution and analysis stages, based on insights from specialized analytical procedures running on an integrated warehouse containing both process and operational data. We further detail the analysis stage, as it provides the foundation for all other optimization stages.