Jeff Erickson | Technology Content Strategist | May 5, 2023
For years now, businesses have been collecting data on their daily operations, measuring manufacturing lines, healthcare interactions, shipping logistics, financial transactions, and countless other critical details. There has long been a market for business process software that uses that data to better understand those operations and simplify, standardize, and automate where possible. Now there’s a new opportunity: Take all this valuable operational data and business process expertise and use it to train artificial intelligence and use AI-backed applications to better anticipate and then react to business ups and downs. Doing so successfully could deliver a powerfully disruptive business advantage, which analysts at Gartner have dubbed hyperautomation.
Hyperautomation is a business technique for wringing more speed, efficiency, and accuracy out of daily work operations. It is related to another trend: intelligent automation, which is the technical process of combining robotic automations with artificial intelligence (AI) and machine learning (ML) to mimic human interactions and automate complex processes. Hyperautomation is the business discipline built around intelligent automation, helping organizations tap into their storehouse of operational data to identify and automate more business and IT processes.
Unlike typical automation, hyperautomation gives businesspeople a way to access operational data, integrate data sources, and use AI services to automate complex, nuanced business process. These can include customer service interactions, document routing, shipping logistics, business analytics, and many other processes. With data-backed capabilities, such as artificial intelligence, natural language generation, computer vision, and anomaly detection, hyperautomation seeks to orchestrate a business process that requires interpreting human language, advising best options, and even analyzing a series of steps and incorporating bots to automate them. The goal is to deliver the best business outcomes with the least cost while improving the accuracy and speed of business operations.
Organizations use hyperautomation to squeeze maximum efficiency from daily operations and get the best results. Although its goal is simplicity for the business user, hyperautomation involves a complex orchestration of multiple technologies, tools, and platforms. According to analysts at Gartner who coined the term, hyperautomation involves: artificial intelligence (AI), machine learning (ML), event-driven software architecture, robotic process automation (RPA), business process management (BPM) and intelligent business process management suites (iBPMS), integration platform as a service (iPaaS), low-code/no-code tools, packaged software, and other types of decision, process, and task automation tools.
A hyperautomation practice is a way for a business to get more value from its industry expertise and the mass of operating data it collects every day. By integrating data flows and training AI, businesses can increase efficiency in their day-to-day operations and support more effective interactions between employees, customers, and partners.
As you can see, hyperautomation requires combining many disciplines and deep expertise in the operation being automated. The result, however, can provide a new level of efficiency in customer and partner interactions that can lead to cost savings and competitive advantages.
A hyperautomation project involves identifying workflows that would benefit from automation, sourcing, and integrating the right operational data, choosing the appropriate automation tools, reusing proven automations where possible, and extending their capabilities with various forms of AI and machine learning, such as anomaly detection, computer vision, or natural language processing.
The goal of hyperautomation is to mimic the way clients or employees would interact with applications and blend into the process. For example, by recording how people perform a task, a bot can be created that automates that action; with AI, that action can include understanding intent in a client’s natural language and making decision on next steps in a workflow. Over time, the data from these digitized operations can be analyzed to find hidden opportunities for improvement in the business process. As tasks get more complex and the speed and accuracy of business operations improves, you’ve moved from automation to hyperautomation.
Robotic process automation (RPA) is a system that allows people in an organization to create computer bots to replace human interactions and take away mundane, repetitive tasks in their work. If someone is regularly copying and pasting text or constantly moving documents from one file to another, a computer bot can be generated to take on those steps while the employee moves on to other tasks.
Hyperautomation is, effectively, the orchestration and enhancement of RPA to accomplish broader and more complicated goals. To automate tasks and later build more complex hyperautomations, the IT team provides standardized repositories of operational data and APIs for integrating data from multiple sources. Businesspeople get a low-code or no-code platform to drag and drop data and integrations to build an automated workflow. Organizations often govern the process with an automation center of excellence that vets ideas, coaches the participants, and provides support.
Hyperautomation adds a layer of artificial intelligence that is trained on and informed by the large volume of historical and near real-time operational data. The use of AI enables automations to interact with customers, partners, and employees in ways that can, for example, understand intent, quickly source accurate information, take the appropriate response, and communicate in natural language.
Hyperautomation is an application of sophisticated AI that has the potential to revolutionize business. It opens opportunities to give businesses a competitive advantage by offering new levels of efficiency. Hyperautomation helps companies make better use of all the operating data they collect and store; it lets them take a smarter action in the moment by using event-driven software, rather than just using data to look back and analyze the past. For example, a port can track and move containers faster and more accurately by using computer vision to automatically identify and measure a container as it enters a port. Or an insurance firm can expedite a claim using intelligent character recognition to look at the text of a document and then automate a document flow, flagging only a small number for review by an employee. Likewise, finance, healthcare, manufacturing, and online retail can all be made more efficient by enabling faster, more accurate interactions with customers, patients, and suppliers by using business automations that also reach into a supply chain to foresee needs, order goods, fill out documents, and suggest next steps to clients or employees. In all these areas, hyperautomation is a competitive advantage that reduces the burden of repetitive tasks, lowers cost, improves accuracy, and leads to innovations.
As hyperautomation takes hold in businesses, they’re seeing benefits in numerous areas.
Hyperautomation promises much, but it takes thorough planning and a commitment to data management to make sure the right data is used to drive responses. Without these, it can become a burden instead of an asset. Potential challenges include:
Across industries, hyperautomation is proving it’s worth by helping organizations cut costs, improve service levels, and lower risks. Here are five real-world examples:
For a business process to go from manual to hyperautomated takes the commitment of many people, as well as a whole lot of data and other technology. Here’s a breakdown of the high-level steps involved in hyperautomation.
When it’s time to bring hyperautomation to your organization, you’ll want trusted tools for process automation, IoT, data management, and AI services. A good place to start your effort is Oracle Cloud Infrastructure Process Automation, which helps developers and business experts automate approval workflows that span ERP, HCM, and CX systems. To pull in all the data you need to fuel this hyperautomation, you’ll need an integration service, such as Oracle Cloud Infrastructure integration services, that’s capable of connecting any application or data source. Regardless of your industry or use cases, OCI gives you the tools needed to simplify repetitive tasks with reusable business rules, prebuilt integrations, and low-code designs.
Why implement hyperautomation?
Hyperautomation is a business strategy that delivers new value from operational data. It combines process automation and data integration expertise with AI and ML capabilities to achieve greater speed, efficiency, and accuracy in daily work operations. It does this by automating complex workflows, such as document management, customer service interactions, and many other processes to deliver a competitive advantage.
How is hyperautomation achieved?
Hyperautomation involves orchestration of multiple technologies, tools, or platforms. It combines business process automation platforms with technologies such as robotic process automation (RPA) and advanced AI and ML technologies.
How can I get started with hyperautomation?
Hyperautomation is an extension of business process engineering. Look for a partner who knows process engineering and offers the AI and ML services and integration tools you’ll need to move from automating tasks to hyperautomating whole business processes.
What are some best practices for hyperautomation?
Best practices for establishing hyperautomation in your organization include identifying workflows that might be automated, choosing the appropriate automation tools, reusing proven automations where possible, and extending their capabilities with various forms of AI and machine learning. You’ll also want a feedback loop to verify that automations are achieving their goals and are improved over time.
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