Though every other enterprise is attempting something or the other in RPA segment, only about 13% of enterprises have executed a scalable RPA strategy. To scale RPA and to meet the future demands from the market, enterprises will need to combine multiple automation and Artificial Intelligence in business to achieve digital dominance. Success of these dynamic automation initiatives will depend on how well companies scale their talent in this area.
With the fourth industrial revolution hovering on the horizon, the professional world has witnessed the inception and evolution of two major approaches: Robotic Process Automation (RPA) and Artificial Intelligence (AI). While the industries were nearly sure of these two to be functioning at their optimum potential, we are now witnessing the emergence of a third force, stronger and better. ‘Hyper Automation’ is making the heads turn with its rapid reach and effectiveness, to the extent that it is named as ‘The top technology trend’.
Enterprise corporations largely benefited from RPA in the form of reduced costs, fewer operational risks, improved employee engagement, and customer experience. But its dematerialization and automation capabilities were limited to structured business processes. In other words, mere imitations of the human actions and not the analytical reproductions of the same. AI, on the other hand, is a step ahead with its deductive analytics capabilities in stimulating human intelligence using machines. However, AI’s limitations lie in providing precise one-point solutions over resolving the issues end-to-end.
As the next step in enhancing the capabilities of intelligent automation, ‘Hyper Automation’ is out to capture the market. The capabilities of RPA, AI, Machine Learning (ML), Information of Things (IoT) and much more are being assembled to reap exceptional benefits. It requires multiple software, tools, and processes to replicate and replace human work. Hyper Automation, as the future of RPA, does the exact thing by combining the required automation efforts under the same roof. Thus, emerges as the one-stop solution for all business requirements.
Major consumer software corporations such as Amazon and FedEx have adopted Hyper Automation processes. They aim to enhance the consumer experience, intensify recommendation system as well as execute a piece of work related to logistics. Decreased human efforts, reduced risks, elimination of human errors, increased effectiveness and productivity, guaranteed by Hyper Automation is attracting organizations at large. AI-driven decision making, on the other hand, has made enterprise corporations across banking, insurance, healthcare, and retail industries embrace this trend of the decade.
Hyper Automation sure seems like the exact thing that could actualize all our efforts towards building RPA, AI and ML processes. However, it also comes with a demand for better infrastructure and a skilled talent pool. Building an ecosystem for Hyper Automation requires a workforce that constitutes tech talent and non-tech talent working in different fields. From data scientists to RPA developers and testers to SMEs, business analysts and operational executives who can incorporate this approach in their everyday work.
Draup’s talent intelligence helps in accessing real-time data of talent landscape and characteristics but also aids the organizations to hire talents who aid the implementation of Hyper Automation. Draup’s Reskill Navigator, on the other hand, can be instrumental in assisting the organizations to prepare their existing workforce. They are suggested with relevant skills training and development courses to adopt Hyper Automation practices.