Robotic Process Automaton (“RPA”) can complement overall data analytics in multiple ways from data creation (data entry to reports & dashboard). In this article we will focus on essentially 2 critical function from data management standpoint.
Create Meta Data. As BOTs executes and complete task(s), it creates can create logs or records for audit, analytical and/or diagnostic purposes. This meta data is used for several other purposes to embark next level journey
Data enablement in Legacy Systems. Legacy system where data integration is still a challenge in some cases. RPA technologies are making is feasible and making data accessible by means of data collection using screen scrapping, data entry automation.
As bird eye view bots do not essentially improve analytics capabilities but aid in data collection. Underlining that core benefit of RPA is in data federation; the capability to collect data from many different sources and aggregate it in an easy-to-analyze format.
Data federation in large enterprises is a major concern as legacy systems historically held large companies back in terms of easy access to data. Now with access to granular data about processes, large companies can see two important benefits:
Process Optimization through Process Mining. Granular data about processes can help identify bottlenecks and inefficiencies, enabling corporations to increase both speed and efficiency of the process. Furthermore, it makes propagation of best practices easier. Since process flows can easily be visualized with the help of data, process flows in different regions can be compared to find the best processes for the whole company.
Process Simulation. In a manual and complex business process, it can be very difficult to work out the consequences of even small changes. So, businesses often rely on gut feeling when making process changes. This frequently leads to new and unexpected process issues, for example bottlenecks in downstream tasks. Because bots will execute processes strictly on the basis of predefined rules and faithfully record every activity, a simulation model developed with RPA data takes the guesswork out of process change decisions. Process simulation on the basis of RPA data makes it easier and less risky to implement the changes that count.
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