Intelligent Process Discovery: Article 2 of a series of articles on Hyperautomation By Aditya Abeysinghe

Intelligent Process Discovery: Article 2 of a series of articles on Hyperautomation

By Aditya Abeysinghe

Is tracked data changing consumer behavior? By Aditya Abeysinghe

In the last article I wrote about Robotic Process Automation (RPA – automating processes using robots or automated bots), its advantages and drawbacks of using RPA. However, users who use RPA should know which processes need to be automated and should separate processes which are more useful compared to others in business processes. This task is handled by intelligent process discovery where it “intelligently” discovers processes that could be automated.


Why do we need software to discover processes?

As such, one might ask if business processes are created, handled and maintained by humans, why is it necessary to use software to discover which processes need to be automated. One of the main reasons for using software is that the flow of tasks in a software is consistent. Software is also considered as not being biased towards mental, social and physical limitations. They could work given the required input and sufficient hardware support round the clock. Their output and throughput is consistent and there are few errors in comparison to those made by humans.

Another key area is that using software outperforms humans in discovering processes with the use of dashboards for analytics. If the same were done by humans, then each data found should be fed to an analytics platform and then information should be obtained. Hence, knowledge should be gained by identifying relationships between this information. Several analytics tools need to be used, data should be stored in some place and then analytics should be stored for later use. This is a lengthy process and requires several humans and software. The cost is high and each process needs to be accurate for the other to succeed. However, if a software is used, it can analyze existing processes, gather data and display analytics on dashboards or flows within less time as well as cost. The margin of error is also less and is easily reproducible given newer inputs.

Continuous monitoring is another area where software outperforms humans in process discovery. Software could run in the background and can continuously monitor which processes need to be automated for more efficiency. As they run in the background, there is less performance issues on employees who need to be specially assigned for monitoring. Therefore, management can focus on other strategic tasks and have less focus on RPA and improve productivity of their internal tasks.

Information security is another area that process discovery tools provide benefits over humans. With such a tool, it can be monitored “who is authorized to view, what information could be restricted” at a higher level. Transmitting data between humans and between humans and software is minimized. This causes lesser opportunities for attackers to steal information when they are available to a limited group.


How does Intelligent Process Discovery work?

Intelligent process discovery identifies day-to-day business processes through its integrations to the business’s systems. It creates a top-down hierarchy map of all processes and then uses business process analysis from the bottom-up to identify which processes are most relevant to the business.

Data from each event is identified from machines and servers used by users, and then are tabulated into its database in a structured way for analysis. Then using AI and other intelligent algorithms, it periodically analyses these captured data and then finds how much processes have a relationship with each other.

Image courtesy:


Comments are closed.