Robotic Process Automation
Effective and sustainable approach to business process automation
There are more and more companies resorting to automatisms with Robotic Process Automation, RPA technologies.
The advantages are clear:
- The use of "bots" increases process speed and throughput.
- Eliminates human error risk.
- Frees staff from the frustration of low-added-value repetitive tasks.
Many processes, such as finance back-office can draw significant benefits. Yet, the use of RPA only for process automation also presents a series of risks, such as maintainability and exception management to be taken into account and mitigated. To exploit the potential of these tools to the fullest, avoiding the inconveniences arising from their unchecked use, Irion has designed an approach based on its EDM, Enterprise Data Management platform and an operational and implementation framework called SAMS.
"With practical RPA application, we realized that these tools are integrated into an overall process automation architecture, with data and workflow management capabilities built with tools that manage them natively." Choosing Irion, which we already knew and liked, was the natural outcome.
- Umberto Colli, Creval Chief Operating Officer
Define and apply criteria for evaluating the eligibility of a process for automation.
Implement process automation solutions using the RPA for automation tasks for interaction with IT applications. A complete Process Automation architecture must include other key components such as an EDM, Enterprise Data Management solution.
Define and apply a production, management and maintenance model for Process Automation solutions.
Implement automation solutions following guidelines and implementation and management agreements common to all.
The role of EDM in Process Automation
The Enterprise Data Management component determines and applies rules based on data that guides the articulation process in the Process Automation architecture guaranteeing:
- Access to information sources.
- Required data collection from sources to:
- Evaluate process feasibility in every step.
- Calculate required information for process completion through transformation, aggregation and enrichment tasks.
- Data-driven process rule management and related applicability conditions.
- Operational reporting generation.
- Data process "auditability" and traceability.
- Process performance reporting and dashboard generation.