The tasks that robots perform are called automations. An automation is a set of instructions for a robot to perform a manual task that was previously handled by humans. There are two types of automations:
- Robotic Desktop Automation (RDA)
RDA (also called attended automation) is a solution that assists agents in handling simple, repetitive tasks. Agents play a role in triggering and stopping an automation, depending on their workflow.
For example, a call center agent receives a call and needs to retrieve all necessary information that is related to the customer. Instead of having to manually retrieve the data from various applications, the automation assists the agent in gathering this information while the agent is speaking with the customer.
The agent is the one who determines when the robot retrieves the data and what information is gathered by providing an account number to the automation.
- Robotic Process Automation (RPA)
RPA (also called unattended automation) is an operation that does not require human interaction. There are no agents to tell the robot when to collect the information. There are no users interacting with the robot. The design of the automation is entirely self-sustaining.
One of the key benefits of RPA robots is that they can accelerate operational efficiency by automating order fulfillment to keep up with product demand. For example, unattended robots can quickly react to spikes in requests for hand sanitizers, gloves, or protective masks by placing timely orders, so that your company remains compliant with regional health standards.
Tasks that are good candidates for automation
Any routine, rule-driven task or repetitive workflow is a good candidate for automation. For example, RDA robots can help agents automate such tasks as:
- Filling in forms
- Copying and pasting data
- Extracting data from documents
- Moving files and folders
- Synchronizing data through applications
- Monitoring emails
RPA robots can improve your IT operations by aggregating, segregating, sorting, mapping, and distributing large quantities of data.