RPA (Robotic Process Automation)

RPA stands for robotic process automation. These are not physical robots but software — so-called bots — carrying out digital tasks automatically. The bots interact with existing applications through their user interface, just as a human would.

An RPA bot can fill in fields, click buttons, read data out of one application and transfer it to another, or move files. The great advantage: RPA can often be used without deep changes to existing systems, since the bots work on the interface.

RPA bots follow clearly defined rules and processes set in advance. A bot is given a script, as it were: step by step it works through the actions stored. As long as the input is structured and the rules unambiguous, the bot carries out the task reliably and without tiring.

Typical use cases are transferring data between systems, producing recurring reports, reconciling records or handling standardised enquiries. RPA works considerably faster and with fewer errors than manual handling, as long as the processes do not change unexpectedly.

RPA is strong when processes are structured, rule-based and stable — but hits its limits as soon as tasks require unstructured data, interpretation or decisions under uncertainty. A classic RPA bot cannot reliably understand free text in emails or documents, for instance.

RPA bots also react sensitively to change: redesign an application's interface and a bot can grasp at nothing and has to be adjusted. RPA is therefore no substitute for well-considered process design but a tool for clearly delimited, rule-governed tasks. More demanding scenarios need additional technologies.

This is where the combination with artificial intelligence comes in. While RPA handles the rule-based execution, AI adds the ability to process unstructured data, understand content and make decisions. An AI module can capture a document's content for instance, and the RPA bot then enters the extracted data into the target system.

RPA pays off particularly with processes that repeat often, follow structured input, obey clear rules and run on stable systems. Such tasks are found in many areas — in finance, HR administration, customer service or data maintenance for instance.

At Elisabit we examine with you which processes suit RPA and where combining it with AI makes more sense. We thus ensure you go with the automation solution that fits, whether pure RPA for clearly rule-based routines or intelligent automation for more complex, data-driven processes.

A successful introduction of RPA begins with carefully choosing suitable processes. Not every process suits equally: those with high volume, clear rules and stable conditions are particularly worthwhile. Before automating, the process should also be reviewed and where appropriate simplified, since automating an inefficient process merely cements existing weaknesses.

Day-to-day operation matters just as much. RPA bots have to be maintained, since changes to the systems they operate can require adjustments. Companies should therefore set responsibility for maintenance and monitoring from the start. Security and access questions deserve attention too, since bots often work with sensitive data and production systems. With a structured approach, clear responsibilities and a realistic choice of the first use cases, RPA unfolds its full benefit and forms a solid basis for further automation.