In the era of digital transformation, automation is essential. This is because it can maximize work efficiency and improve corporate productivity by providing an environment where you can focus more on core tasks instead of simple repetitive tasks.
In recent years, RPA (Robotic Process Automation), the most common automation methodology, has grown explosively with great interest from companies. However, RPA only works on structured data, so it is not useful for anything other than limited tasks such as finance and accounting, so there are limits to its expansion. Due to these limitations, digital technology has developed rapidly and people’s expectations for work automation have increased, but it has become difficult to meet these expectations.
The concept that emerged as a solution to this problem is Hyper automationIt is called an ‘advanced automation system’. We introduce the core technologies, advantages, and steps for introduction of hyperautomation, which will replace existing automation systems.
Hyperautomation goals and core technologies
Hyperautomation is a concept that complements existing automation methodologies such as RPA. In 2019, global IT research institute Gartner defined the term ‘hyperautomation’ as follows.
“Hyperautomation is an approach that goes beyond the task- and process-oriented automation concept represented by RPA and focuses on quickly identifying, verifying, and automating as many business and IT processes as possible by placing the organization’s business itself at the center of thinking. ”
In other words, RPA is a ‘task’ automation method that focuses on individual or unit tasks, but hyperautomation automates the so-called ‘end to end’ work process from the beginning to the end of the process. Therefore, hyperautomation includes robotic process automation (RPA), artificial intelligence (AI), machine learning (ML), natural language processing (NLP), data mining, and software as a service (SaaS). It can be said to be a concept that is an integrated set of various technologies, tools, and platforms such as Service) and also includes a problem-solving method to perform higher-level tasks by identifying and learning patterns based on data.
The main technologies of hyperautomation, which are effective in business innovation because they promote rapid expansion and expansion of automation through the combination of technologies and handle unstructured data, can be summarized as follows.
Advantages of using hyperautomation
Hyperautomation maximizes business operational efficiency by streamlining core processes across the organization. By seamlessly integrating diverse technologies, processes, and data sources across the organization, companies can improve cross-departmental collaboration and information flow to make better decisions and build a connected, responsive business ecosystem. This allows companies to quickly adapt to market changes, expand their business scope, and sustain growth while minimizing cost increases.
Additionally, organizations can more closely monitor and analyze a variety of data during automation. In other words, you can collect data with intelligent automation tools to build a ‘digital twin’ of your organization, reduce human errors, and increase work accuracy and efficiency. At this time, by securing insights and predictive statistics to help with decision-making, you can run your business based on more detailed and accurate data and reduce risks due to uncertainty. As digitized, automated operations expand, technologies such as data encryption, access control, and audit trails can be applied to more processes to enhance security across the enterprise and protect data by applying end-to-end protection to mission-critical parts. You can stay safer.
On the revenue side, reducing human resource input through automation can increase work speed and workload while reducing unnecessary operating costs. Additionally, by focusing only on necessary tasks, employees can spend time on more creative and productive tasks and develop their capabilities. And this leads to improved operational efficiency and increased profits for the company.
In fact, Gartner, a global IT research institute, predicted that companies will be able to reduce operating costs by 30% by 2024 by introducing hyperautomation and redesigning business processes. Deloitte, a global accounting firm, also predicted in its ‘Intelligent Automation’1 report that companies will be able to improve employee capabilities by 27% over three years by introducing hyperautomation. This is equivalent to a workforce of 2.4 million full-time employees across the 523 companies that participated in the survey.
Hyperautomation application examples
Representative examples of how companies utilize hyperautomation include signing contracts with new customers, managing personal information, and automating accounting tasks. For example, when signing a new contract, you can set it to automatically fill out parts similar to existing contract content and register customer information in the database to minimize the information creation process when signing additional contracts with the same customer. In addition, when personal information management and accounting work is carried out using the existing processing method, there must be no errors in information input, updates are required when new information is generated, and although it is a simple information work, errors can cause major problems to companies. It’s similar. When hyperautomation is used for this task, errors can be reduced and work efficiency increased by automatically collecting, analyzing, and updating data.
Let’s look at examples of how hyperautomation is applied in each industry sector. first financial industryThis is the area where the greatest impact is seen through the automation of contract conclusion, personal information management, and accounting tasks, as in the three examples above. In addition, automated processes are introduced in the ‘customer service’ aspect, which can have a direct impact on customer and employee experience, such as asset management, loan approval process, and insurance payment, to shorten business processing time and save human resources.
manufacturingBy collecting and analyzing IoT sensor data inside the factory, you can optimize the production line and automatically inspect products, automating the operation and management of the production line, and production planning. medical fieldBy collecting and analyzing patient data, you can predict diseases, develop prevention and treatment methods, and automatically monitor patient conditions. public institutionIn order to reduce costs and shorten work processing time, you can automate the collection and analysis of public data and manuals for responding to emergency situations. retailHyperautomation can be applied to all tasks required for store management, including customer data collection to provide customized services, order processing, inventory management, and accounting.
GS Caltex is not satisfied with its existing capabilities of importing, refining, and selling crude oil, but is establishing and executing a digital transformation strategy to change the organization’s DNA with the intention of spreading DX (Digital Transformation) across the entire value chain. The Yeosu plant is the best example of GS Caltex’s unique hyperautomation in the company-wide digital transformation process. The Yeosu plant reduced blind spots and strengthened efficient internal security and protection through 164 AI CCTVs. In addition, the Yeosu plant is the world’s fourth largest single oil refinery, and requires systematic management as more than 800,000 devices, instruments, and piping facilities are organically connected. In particular, there are a total of 1,665 combustion facilities inside the 84 furnaces in the factory, and previously, about 600 production operators managed the facilities relying on their eyes and experience. To address the limitations of visual observation during the digital transformation process, we introduced smart sensor technology that verifies optimal combustion conditions with laser equipment. The real-time monitoring function makes it possible to achieve goals such as eliminating on-site inconveniences and saving energy by managing combustion facilities with minimal investment costs. This is a case of optimizing production based on data, which not only improves profitability by increasing productivity, but also serves as a good example of forming a consensus within the company during the future digital transformation process.
Steps for successful hyperautomation adoption
In order to successfully introduce hyperautomation, you must first comprehensively reexamine and organize the organization’s processes and then apply them step by step. In particular, the size of data is getting bigger day by day, and data infrastructure is being distributed to the cloud or on-premise environment, so hyperautomation will not be very useful if the data management system is not properly established.
The detailed plan for establishing a hypoautomation system is generally 4 steps: foundation building, roadmap establishment, execution, and expansionIt proceeds as follows. First, in the ‘foundation building’ phase, a core team is formed or a Center of Excellence (CoE) is operated. We organize work processes so that automation can be introduced efficiently, and check whether all processes and work steps are in line with the company’s strategic goals. Through this, the vision and goals of hyperautomation must be defined and a consensus within the company must be formed.
The second step is ‘establishing a roadmap’. Before introducing hyperautomation, you must first establish a hybrid integrated environment. Only then can you bridge the gap between multiple environments, including on-premise mainframes, cloud data lakes, and API management solutions. Therefore, it is necessary to assess the organization’s readiness, including evaluating existing technologies and understanding the current level of automation maturity, to select high-priority applications and align them with organizational goals.
The next step is the ‘execution’ phase, where priorities are set according to strategic importance and success metrics are defined. We then implement the automation solution and continue to improve efficiency based on actual operational results, including operation, performance evaluation, and optimization of the automation process.
The final step is ‘scaling’ hyperautomation. This phase will focus on scaling automation initiatives across the organization. Effectively define strategic priorities and opportunities, integrate automated processes across the business to maximize the impact and benefits of hyperautomation, and optimize workflows between each process.
As global supply chain problems arose due to difficulties in production, distribution, and sales due to COVID-19, companies began to pay attention to hyperautomation, which can increase resilience. Since then, many companies have introduced hyperautomation to innovate business processes using various technologies, but it is undeniable that they are facing difficulties due to realistic barriers such as complexity of technology integration, data security, and initial investment costs.
Nevertheless, hyperautomation can ultimately be seen as the overall methodology itself that can implement and spread work automation suitable for business goals, so it is a trend that most organizations have no choice but to accept in the face of the irreversible changes of the era called digital transformation. If we can’t avoid it, shouldn’t we start efforts to introduce ‘hyperautomation’ suited to our organization so that we can maintain competitiveness and achieve sustainable growth by proactively responding to the changing environment? Ultimately, these efforts will strengthen the organization’s competitiveness and become a catalyst for innovation.
1Justin Watson et al., 『Intelligent Automation: Rethinking Organizations in the Together Era』 (Deloitte, 2019), P5.
