Hyperautomation is a strategy used to boost automation of processes by an organisation via a variety of advanced technologies, systems, and tools. These can include AI, robotic process automation (RPA), and machine learning (ML). With these, businesses can better automate, discover, and operate a range of divers processes.
Rather than automating one task or process at a time, hyperautomation looks at the larger picture in an entire enterprise. It combines a range of automated responses so they work together in a cohesive manner. It transforms disconnected, separate routines into a single ecosystem.
Implementation strategies
To ensure a rapid expansion in a business, hyperautomation uses multiple technologies together. Research firm Gartner says AI and automation platforms designed for enterprises are key drivers behind successful hyperautomation. Companies can now automate tasks and processes that may have been un-viable previously, particularly around tasks that depend on unstructured data – that is, information not already organised in databases.
Although there are numerous benefits to hyperautomation, implementation presents some challenges.
Process discovery is a crucial first step, used to capture an overall view of operations and to identify potential bottlenecks. From here, businesses can assess where automation might provide the greatest value, according to possible gaps or weaknesses in current operations.
Hyperautomation selects appropriate technologies, including generative AI, RPA, intelligent document processing (IDP), integration technologies (APIs, iPaaS), AI agents, and no-code/low-code platforms. Once the right technologies and tools have been identified, hyperautomation adopts a mix-and-match approach, combining and selecting technologies to complete business-wide automation.
Change management is a common challenge when implementing hyperautomation. Organisations should be prepared to change work practices when transitioning to hyperautomation, ready employees for new workflows, and guiding the people in the business shift between automated and manual tasks.
Hyperautomation brings ethical considerations too, creating concern about job losses and displacement. Bias in AI algorithms may also need addressing so that unfair outcomes or discrimination are avoided.
At the core of a business’ responsibilities is the consideration of the possible impact that automation may have on a business’ workforce, customers, and, in a broader sense, society. Ultimately, the use of hyperautomation must align with ethical standards and corporate regulations.
Hyperautomation success stories – case studies
One of the biggest hyperautomation success stories comes from Heineken, the multinational brewing company. The brewer implemented an ambitious hyperautomation program, saving 14,000 hours of work per month, with an estimated 1,000,000 hours to be saved by the end of 2025.
The radical transformation was the result of a team and framework created and led by Lucy Todorovska, the company’s global hyperautomation product manager. The team set up “Toolkit,” a group of technologies and teams bringing together what was termed “a highly diversified tech stack – intelligent automation, document processing, low-code development, chatbot development, toolchains, test automation, and digital integration.”
Heineken adopted a federated delivery model, letting regional and functional teams use automation alongside business and IT stakeholders. Governance, training, and support were provided, and the company was careful to retain a degree of local flexibility.
Heineken’s hyperautomation approach resulted in a scaling set of automated processes in the enterprise and a substantial operational improvements, achieved without disruption or the ‘bottlenecking’ of initiatives by the central team.
Another hyperautomation success story comes from Bank of America, which used RPA with AI to improve customer service operations. AI-powered chatbots now handle routine inquiries and help deliver faster, more accurate responses for customers. RPA automated back-end tasks like account management and transaction processing. The bank was able to handle increasing volumes of customer interactions without the need for additional staff.
Summary
It’s widely agreed that in multiple industries that hyperautomation is the future of enterprise transformation, blending advanced technologies to create automation in many facets of operations. The path to successful hyperautomation is not linear, but a strong culture of adaptability and collaboration gives businesses the best chances to achieve hyperautomation goals.
The arrival of agentic automation means hyperautomation strategies will accelerate change, and hyperautomation in a real sense has only just begun.
(Image source: “Time Machine Clockwork” by Pierre J. is licensed under CC BY-NC-SA 2.0.)
