Automation, at the scale and velocity of business
Gartner observes that modern business, while progressively embracing automation as an enabler, lacks a well-defined culture to scale it with their tactical and strategic goals. It recommends ‘end-to-end automation beyond RPA’, assimilating complementary technologies for profound business impact. Indeed, in the closely contested marketplace that characterizes the New Economy, a piecemeal approach to process automation may leave much to be desired. It is a vulnerability that can only be mitigated by adopting a broader take on automation: Hyperautomation.
Conceptually, Hyperautomation entails automating every possible process across your institutional matrix and streamlining outcomes by ironing out exceptions, inconsistencies, and vestiges of manual interventions. It involves a vast collection of technologies, including Artificial Intelligence, Machine Learning, and Robotic Process Automation (RPA), to transform legacy workflows, helping you attain tremendous cost and resource efficiencies.
Hyperautomation is essentially the next step in the automation maturity curve. Adopting a more homogeneous approach, it seeks to amplify the implications of conventional RPA deployments by elevating performance at the scale and velocity of your business. It is an advantage that Gartner considers to be a ‘condition of survival’ for modern organizations.
Maximizing value for your automated enterprise
Hyperautomating repetitive, mundane, and low-value task loads eliminate the toil across your enterprise ecosystem, allowing your employees to focus on what they do best. Besides, Hyperautomation investments also put your organization at several strategic advantages, including:
Hyperautomating, a considerable share of the enterprise task loads, empowers your employees to attain more within the finite hours and resources available to them. It also frees up the human capital for high-value roles like innovation and corporate planning.
Automating systems and processes homogeneously across the supply chain ensures that data is consumed more efficiently in your operations, and products and services are delivered with greater reliability, improving time-to-market.
Citizen-led development underscored by the emergence of the low-code culture implies that automation is no longer reliant solely on IT. Using enterprise low-code platforms, your employees can upskill and hyper-automate processes on-demand, democratizing their benefits.
With Hyperautomation, it is possible to integrate your legacy technology and data-system landscapes, allowing them to communicate seamlessly by putting all periodic infrastructure maintenance workloads on self-drive.
Hyperautomation amalgamates a diverse range of technologies, fostering a digital-first culture for your organization. It enables you to rapidly update, change, or adapt to the evolving business realities using digital agility and flexibility at scale.
The end-to-end automation permits the use of analytics to monitor your business
KPIs, continuously correlating expenses with the returns over specific time horizons.
How does Hyperautomation work?
As a concept postulated by Gartner, Hyperautomation expands the idea of RPA by bringing business process management tools, AI, and Machine learning capabilities into the mix. This workflow processing framework consistently pushes the decisioning workloads towards cognitive technologies while consistently capturing operational data in real-time, even unstructured ones, thus automating those processes that were not possible before. Hyperautomation essentially opens up the scope to calibrate businesses responses based on continuous changes in the environment and decisioning at speed by the AI algorithms. Its development traces the following cycle:
Making Hyperautomation possible
The best possible Hyperautomation outcomes are achieved at the intersection of the following technologies:
Robotic Process Automation (RPA)
As the cornerstone of the Hyperautomation proposal, RPA technology puts your interfaces, applications, and workflows on self-drive that otherwise engage an outsized proportion of your workforce bandwidth, delivering suboptimal results.
Process Mining connects the dots by analyzing the continuity of your business processes, pinpointing anomalies in runtime, and evaluating throughput to ensure the best possible outcomes at any given instance.
Whether it is data at rest or in motion, the Ingestion Engine tracks data dependencies across your enterprise ecosystem and facilitates their consumption into Process Mining, Decision Modelling or iBPMS
Integration Platform as a Service (iPaaS)
iPaaS is a cloud-native suite for automated execution and management of integrations between your processes, services, applications, and data, deployed across different environments.
Advanced Analytics delivers deep insights into your business ecosystem and forecast outcomes, allowing you to inculcate an informed and pragmatic decision-making culture.
An intuitive and enabling UX interface stands between the hyper automated business functions and your end-users, allowing them to effortlessly extract the most out of the human-machine interactions.