Hyper-Automation: a transition from Automation

In light of the COVID-19 pandemic, it has become clear that automating further eliminates needless bottlenecks that can affect industries and lives in dangerous ways. Perhaps this pandemic is the wake-up call we need to keep pushing for hyper-automation because it eventually allows policymakers and enterprises to offer more services to their stakeholders.

Robotic process automation (RPA) has gained a lot of coverage in recent years, both positive and negative. Some contend that RPA causes work reductions by automating basic and often tedious tasks that people normally do, whereas others claim that RPA does not eliminate jobs but only makes them easier to do.

Many companies are in the middle of digital change, and many are seeking RPA proofs-of-concept in this sense (PoCs). The right RPA approach will easily drive efficiencies, cost savings, and synergies, which explains why RPA is so common.

RPA is particularly attractive for the logistics side of a market, as it eliminates bottlenecks and increases efficiency. A “bot" (software that takes on the function of a human agent) is much more powerful, accessible, and, essentially, less error-prone than a human.
Organizations are analyzing basic procedures for automation and finding ways to increase customer loyalty, time-to-market, and return on investment with the assistance of IT and business teams. When a proof of concept (PoC) is effective, it is common to want to automate further processes with RPA.

What will be sufficient now that RPA has proven to be successful? The aim is to create a decision-making mechanism that is continuously enabled by artificial intelligence (AI). What distinguishes this from RPA?

RPA usually requires only one software component when designing a use case, while hyper-automation involves the integration of many components. Within the same project, DocDigitizer, for example, would help a technology partner to merge process mining, bots, and the process automation platform. As an API service, we use an “intelligent automation" platform. In this scenario, DocDigitizer entails the use of machine learning in conjunction with an intelligent AI engine to design automated data extraction workflows that provide (near)  100% accurate results. This way, we can give clients more leverage over their data systems.

As a result, hyper-automation entails combining emerging technology such as RPA, AI, deep learning, and process mining to simplify operations in a way that far outperforms traditional automation. In addition to hyper-automation, other buzzwords for this term include automated process automation and intelligent process automation. Simply stated, hyper-automation is the combination of automation systems to increase human capacities and reduce error rates.

Since data and observations are accessible more easily and can be used for quicker and more accurate decision-making, hyper-automation provides an enterprise with more flexible business management. Correlations in the captured data can be detected and converted into observations using algorithms.

In addition, there are certain special issues to consider, such as legal criteria. Nonetheless, synergies will be realized by streamlining and taking a systematic approach to operations in order to find suitable options for meeting these criteria.

Throughout the pandemic, DocDigitizer has worked tirelessly to assist organizations in their automation initiatives. For example, we partially automated credit deferral processes for a major Portuguese bank to assist in dealing with a massive surge in demand. As a result, the bank's end customers benefited from faster turnaround times, the reduced effort required to use the service, and a more reliable overall operation. We have streamlined financial relief services for a large Portuguese bank in order to reduce costs and improve customer service, as well as loan servicing for a Portuguese bank through the Paycheck Protection Scheme.

Hyper-automation presents new obstacles to the IT industry by combining several elements as an overall term. Organizations would also rely on technologies that can communicate with one another. Interoperability, or the simplicity with which software components can interact with one another, is more critical than ever before.

This also implies that potential technological implementations should be not only user-friendly and modular but also capable of being implemented into the hyper-automation structure. So-called “plug and play" solutions that collect data from different sources and use APIs become critical because the more data I can effectively analyze, the more competitive advantage I can generate. Despite these problems, the benefits of hyper-automation are numerous.

In unpredictable periods such as the pandemic, it is vital to respond quickly to obstacles and make sound decisions. This is made possible by companies engaging in hyper-automation and efficiently handling their data and processes. Today, technology is an essential component of the supply chains of both public and private organizations. The pandemic emphasizes the significance of the technology supply chain in meeting modern demands. Harmonization of products such as hyper-automation solutions, cloud technologies, managed networks, and comprehensive cybersecurity is all part of an efficient technology supply chain.

As organizations seek to rebound and reinvent through the challenges caused by the pandemic, strengthening the technology supply chain is a win-win situation for all parties involved. End customers can be served more quickly, new customer and product strategies can be developed, and higher productivity can be achieved at lower operational costs. DocDigitizer helps system integrators and other technology partners to advise its customers in exactly these areas.