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The term Robotic Process Automation (RPA) has been around since 2005. Regardless of industry or market, one of the best ways to make business efficient is adopting Robotic Process Automation into business functions.
The advent of RPA aims to revolutionize the pharmaceutical industry by applying the "robots" to perform high-volume, repeatable tasks, which are presently handled by humans.
A tireless digital robotic workforce that puts in work 24/7 can bring companies' return on investment up to 600% to 800% in three years, according to the London school of economics.
Embracing RPA is even more critical in today’s era of rapid change. Pharmaceutical companies are under pressure to either improve the success rates of their Research & Development investments or lessen the cost of failure. In the meantime, the digital economy is shifting the expectations of providers and patients alike. Companies need to create relationships with integrated health care systems such as key stakeholders and hospital management teams, as the point of contact in a value environment shifts away from individual physicians.
For example, a rogue chatbot can do actual damage to patients by offering false advice, in addition to hurting a company’s reputation. Thus, companies must plan for possible challenges and establish a well-defined roadmap. These steps will help companies efficiently implement bots and realize substantial, company-wide benefits from RPA solutions.
Here are some reasons as to why pharma companies should embrace RPA:
This change won’t happen overnight. To understand the opportunities essential in RPA adoption, companies should commence to assess which low-complexity tasks are best suited for the technology.
Aress (www.aress.ai) helps such companies by consulting and strategic recommendations to augment their digital transformation initiatives and optimize returns on investment in new-age digital technologies. Reach us at firstname.lastname@example.org for more details.
Category: Analytics, Artificial Intelligence, Big Data and BI