How can I improve straight-through processing with RPA? How should I enhance my business decisions for optimized automation? These and many similar questions have been answered anecdotally by business automation practitioners for years. Yet, automation capabilities such as workflow, decision, or RPA are usually approached as silos and the use of data science models have been confined within these silos.

However, the democratization of AI is expanding the automation horizons: Machine learning techniques can now be applied reflectively, observing the activities and outcomes of every aspect of a business process, and use them as training data in order to automatically and continuously find ways to improve this process. In this presentation, we will review the key digital business automation capabilities and the type of business events they generate and show how these individual pieces of business insights, collected in a data lake, can be exploited through machine learning to prescribe tangible business process improvements.

Learning Objectives:

• What kind of insights can be gathered from observing business process, decision, bots execution
• How machine learning can be applied to the collected insights
• What kind of impact can be expected on business process improvement