Robotic Process Automation (RPA) has become a leading technology and is being increasingly adopted by both small and large enterprises. RPA bots performing repetitive, rules-based, and labor-intensive work have increased organizations' productivity and cut down on costs. But, RPA has largely been implemented for specific processes and many other processes are still carried out manually. As businesses start to automate select processes, it's then time to look at the bigger picture. This is where the Hyperautomation approach comes in to scale automation efforts throughout the entire organization.
Why is Hyperautomation Gaining More Attention?
RPA remains the core of hyperautomation, but emerging technologies such as Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Process Mining, etc continue to streamline processes across organizations. Process Mining discovers eligible processes for automation while other advanced technologies create bots to automate them. In short, the process of Hyperautomation "automates automation." Hyperautomation is considered a top trend in Gartner’s Top 10 Strategic Technology Trends for 2021.
Hyperautomation often results in the creation of a digital twin of the organization"
Moreover, the COVID-19 Pandemic forced businesses to prioritize their digital transformation and automation initiatives, which led to increased adoption of hyperautomation. Business operations in most organizations are distributed almost to the point of fragmentation. Automating select processes brings limited gains in terms of speed and accuracy but doesn't contribute much to business decision-making. Furthermore, legacy systems slow down operations considerably. With hyperautomation, every process that can be automated is automated in a streamlined manner that reduces cost and puts the business in a competitive position.
Preparing for Hyperautomation
Shifting from simple task-based automation to hyperautomation is not as straightforward as it may seem. Hyperautomation is a comprehensive transformation initiative that involves technologies such as AI, ML, and RPA and must have a strategic plan in place to ensure success. Here are some steps that can be taken to start your hyperautomation journey.
- Evaluate budget and ensure hyperautomation brings reasonable return on investment (ROI).
- Gain an in-depth understanding of processes, workflows, and systems and use process mining to identify processes that can be automated.
- To identify areas that need improvement, organizations should create a digital twin of the entire ecosystem so that the processes and their performance can be visualized, and insights collected to improve efficiency during hyperautomation.
- How well hyperautomation succeeds is also dependent on the quality of the data involved. Most organizations work with structured and unstructured data. Before starting hyperautomation, it's important to what data will be used.
- Hyperautomation is about using RPA along with several leading technologies such as AI, ML, OCR, NLP, and others for building bots that don't just automate tasks but do so intelligently. Identifying the automation platform, technologies, and tools that best serve the needs of the organization is critical. Tools should be compatible with existing platforms.
- For faster deployment and less dependence on technical expertise, organizations can consider low-code no-code platforms.
Hyperautomation and ServiceNow
ServiceNow’s Now platform already includes support for a lot of technologies. Its latest Quebec release has enhanced the platform’s native AI capabilities and no code low code development capability to augment innovation and productivity. With its acquisition of RPA startup, Intellibot ServiceNow can now offer native RPA capabilities to its customers along with its support for pure-play RPA vendors. ServiceNow is well-positioned to be used as a platform for hyperautomation.