Using advanced process analytics, our Digital Workforce can determine the bottlenecks and variances that are present in existing process execution. This is important for process automation decisions, as well as process redesign and optimisation.
Our process analytics toolkit automates the discovery phase by leveraging machine learning algorithms to identify the processes that are most suitable for automation. Instead of spending a large amount of manual effort in collecting data and understanding the process flow, our toolkit can automatically discover the problem.
The toolkit can automatically create process diagrams and summarize process data statistic reducing time spent on analysing processes significantly.
How long was it running?
How many tasks were handled?
How many different variants of the process are there?
What kind of decisions are being made during processing?
By collecting and analysing the data automatically what is happening inside the process is made visible. This allows automation decisions or process development actions to be based on facts instead of estimates.