Data and Analytics with RPA: The digital force simplifying
data and reporting to mine insights!
Early RPA adopters have dabbled with automation of critical processes to derive insights from operational, transaction and master data available with various business functions. Even though data entry and managing workflow have always been a great use case, analyzing the gathered data, preparing the performance metrics, and reporting drive the key value proposition for implementing RPA in this domain.
A considerable amount of effort is spent on “run-the-business” type of reports such as compliance, progress, transactional, and analytical. Besides, high-cost resources are involved in creating and validating the data. Instead, with the automation of these business-critical reports, managers can focus on impactful decision making, due diligence and high-involvement activities enhancing the productivity and value generation of the organization. Some of the key areas where RPA has driven value for data, reporting, and analytics are:
Image capture and OCR
Reporting and insights
Alerts and notifications
With the overwhelming amount of data captured by organizations today, RPA very efficiently manages data validations, cleansing, and veracity. Managers and analysts spend a lot of time just ensuring that the right data is used for accurate analysis, visualization and insight generation for decision-making purposes. Being rule-based and having a well-defined structure, data and reporting become an ideal candidate for RPA implementation ensuring error-free, on-time, hassle-free solutions and services. At ITC Infotech, we have enabled businesses to create and implement effective solutions around reporting, integration, and analytics significantly reducing the rate of exceptions and generating valuable insights for stakeholder decision-making at the right time.
Ensure high-quality data through elimination of possible data errors
Eliminate mundane and repetitive tasks increasing employee productivity
Remain within regulatory norms and adhere to SLAs for critical processes
Eliminate repetitive tasks in aggregation and curation enhancing employee productivity
Replace manual data entry
Avoid the risk of duplication
Reduce error of omission, commission, and oversight
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