Regulatory affairs and regulatory operations departments handle huge volumes of admin. Robotic process automation (RPA) is increasingly helping with the more routine tasks, saving time and reducing human error while freeing up people to apply their expertise and add value. Now that life sciences organizations have seen for themselves the tangible benefits of RPA, they are beginning to think about where they could take the technology next.
RPA is a great place to start for regulatory affairs functions looking to work in smarter ways and reduce risk and time to market. In regulatory affairs and regulatory operations departments, there is a broad range of highly-structured, ruled-defined processes and tasks that lend themselves to process automation. These include the kinds of tasks once routinely outsourced to third-party service providers in pursuit of greater cost-efficiency.
Operational Use Cases
RPA is already used for automated data entry; extracting data for upload, importing documents, or archiving them; checking data or document quality; or parsing emails. RPA tools can help with creating or verifying hyperlinks between related data in documents too. Often, as multiple documents are readied for submission, collating the links that are needed to aid reader navigation is left until the end of the process. At this stage, the task can be overwhelming, potentially requiring tens of thousands of hyperlinks to be added.
Another strong use case for RPA is extracting standard data from routine documents such as standard agency approval letters. Here, AI-enhanced RPA can boost a tool’s potential. AI-enabled RPA allows tools to cope with unstructured scenarios as well as fully standardized, highly-structured contexts where the parameters remain consistent and predictable. As agency approval letters can vary by country, an RPA tool with some degree of machine intelligence could help by first determining which country the letter has come from, and therefore where to look to extract the required information and how to interpret it before uploading the results into a regulatory system.
Some companies are looking to use RPA as an agile, interim solution to deliver quick wins in parallel to larger-scale transformations of regulatory information management (RIM). Targeted RPA applications help to highlight what’s possible, inspiring investigation into more advanced use cases – and reassuring teams that automation isn’t a threat to their jobs, but rather the key to making working life more interesting. These applications—turned around quickly and affordably—can readily demonstrate their worth and reaffirm the business case for regulatory digitalization. A blended approach of RPA-extracted data and human insights can help build a powerful regulatory intelligence database with wide-reaching benefits in accelerating and improving the quality and success rates of global submissions.
Building Confidence in RPA
Determining and communicating strong targeted use cases for RPA will help to build credibility and confidence in the technology and break down fears about technology taking people’s jobs. As RPA use cases grow, companies are increasingly considering whether to develop and run their own RPA capabilities, or turn to third parties to create and operate the tools for them. Some process automation tools will remove the need to rely so heavily on external services to improve operational cost-efficiency.
It will increasingly be the case that the use of RPA—or standard systems offering the same capabilities for such automation—will become a pre-requisite when choosing service providers. There will be a reasonable assumption that third parties that have invested in next-generation processes can be expected to be operating at a level of superior economic advantage over rivals.
Maximizing the Potential of Intelligent RPA
As organizations survey and scope the potential for RPA, the key is to identify the pain points, where tasks are executed according to check lists, or the most resource-draining or inefficient outsourcing relationships, and use this as the steer for RPA development. RPA bots are relatively easy to code; the bigger challenge is harmonizing processes and channels and shoring up data quality so that automation can be applied easily and reliably. To maximize the opportunities for harnessing RPA technology, standardizing the capture, recording and management data is a critical foundation.
Process optimization is an important first step when it comes to getting to grips with the benefits of RPA. Beyond that, RPA technology can increasingly support process transformation with systems that use artificial intelligence that supports human insight into how to optimize processes and drive efficiency.