How To Improve Efficiency and Reduce Costs in Your Business Through Hyperautomation
- What is Hyperautomation?
- The Difference Between Automation and Hyperautomation
- Hyperautomation: Advantages and Disadvantages
- Hyperautomation Tools
- Hyperautomation: Examples
- Hyperautomation Services
Hyperautomation is a concept that we have seen for several years in a row in Gartner’s forecasts on the technological trends that will mark the future of business. Its advantages are endless when it comes to improving productivity and reducing costs in a company, so we tell you what it is, its advantages, and how you can implement it in your company.
What is Hyperautomation?
Hyperautomation brings together several components of process automation and integrates tools and technologies that amplify the ability to automate a company’s work. It includes artificial intelligence, machine learning, robotic process automation (RPA), business process management, low-code/no-code tools, and integrated platforms as a service (iPaas). Their goal is to promote better employee engagement and give them more competence and a better return on invested capital. There is no single automation tool that covers human work processes. Therefore, hyperautomation combines multiple technologies to help organizations visualize their operations, analyze key points and give more value to their processes. In fact, we can find two types of processes in which to take advantage of hyperautomation:
- Those triggered by incoming documents or emails: unstructured or semi-structured data that can be validated with machine learning models.
- Fully digital: some processes are triggered by structured customer data or internal company processes, which will already be automated or easy to implement.
The Difference Between Automation and Hyperautomation
It can be difficult to distinguish between process automation and hyperautomation, but the main difference lies in the scale at which they are implemented. Automation refers to performing a repetitive task without manual intervention, but it is typically applied on a smaller scale, with solutions designed to address individual tasks. For example, automating tasks within a specific workflow. Hyperautomation, on the other hand, uses multiple automation tools to achieve an intelligent solution and scale the tasks to which it is applied. It facilitates the incorporation of artificial intelligence and machine learning capabilities, thereby further reducing manual effort.
Hyperautomation: Advantages and Disadvantages
Hyperautomation transforms companies by streamlining business processes by eliminating repetitive tasks and automating manual ones. This translates into benefits such as:
- Completing tasks with consistency, accuracy, and speed.
- Cost reduction.
- Improved customer experience.
- Increased productivity.
- Capitalization of data collected and generated by digitized processes.
- Improved business decision-making (better and more timely).
- Improved adoption of AI and ML in business processes.
- Helps prioritize future automation efforts.
For all these reasons, we are witnessing a moment of great growth, thanks to its ease of use and intuitive nature.
Hyperautomation is fairly new, although its development is very scalable and efficient. Thanks to RPA, 2016 saw the beginning of a new paradigm in automating repetitive and tedious processes that had only been possible under human supervision. With the advent of technologies such as low-code and AI, they have been integrated into the process until reaching the current concept of hyperautomation. Technologies such as intelligent business process management suites (iBPMS), process mining, natural language processing (NPL), optical character recognition (OCR), and digital twins are also coming into play. Furthermore, this will continue to grow thanks to the increased implementation of these technologies, the trend towards apification (selling data via APIs), and the integration of Web 3.0, which will mean smarter and more connected websites in the perfect environment for hyperautomation.
As mentioned above, hyperautomation has only recently become part of business strategies, but it is already having a major impact on many industries and on process improvement. We have compiled some of the most important ones.
Hyperautomation in Banking
The banking sector is one of the sectors with the greatest potential for implementing hyperautomation in its processes. It can be applied in regulatory reporting, marketing, sales and distribution, payment or lending operations, business support, etc. Intelligent automation systems driven by artificial intelligence calculations can filter transaction exchanges and proactively recognize fraudulent and malicious exercises. As a result, numerous banks and financial organizations have begun to use advanced analytics in application selection for prognostics and prevention and reduce the likelihood of non-performing assets in the future.
El sector bancario es uno de los que más potencial tiene a la hora de implementar la hiperautomatización en sus procesos. Se puede aplicar en informes regulatorios, marketing, ventas y distribución, operaciones de pago o préstamos, soporte empresarial, etc. Los sistemas de automatización inteligente impulsados por cálculos de inteligencia artificial pueden filtrar los intercambios de transacciones y reconocer de forma proactiva los ejercicios fraudulentos y maliciosos. Por ello, numerosos bancos y organizaciones financieras han comenzado a utilizar análisis avanzados en la selección de aplicaciones para el pronóstico y la prevención, además de para reducir la probabilidad de activos improductivos en el futuro.
Hyperautomation in Healthcare
Studies show that, in the United States, the healthcare industry spends $2.1 billion a year on poorly performed and error-prone manual tasks in provider data management alone. That’s why improving operational efficiency in tedious administrative tasks is so important. Automation can empower smart invoicing by examining invoice details for each division and matching them without manual mediation. This saves a lot of time and helps optimize insurance and claims organizations in clinics. AI recognizes inclusion and policy terms; a bot could submit bills with important documentation. On the other hand, advanced analytics are assembled with easy-to-use dashboards using real-time, free-flowing data, allowing effective treatments to be sent based on best practices and best outcomes.
Hyperautomation in Insurance
Hyperautomation can help Insurtechs in the insurance claims process, where this technology approves and organizes data from various sources to verify and collate customer certifications. All of this is effortless, more accurate, and much faster than human processes. Advanced analytics can also be used to gain meaningful insights from the information collected by sensors, handheld devices, surveying, etc. This helps insurers calculate risk factors and policy premiums for a specific customer segment.
Hyperautomation in Retail
The way products are purchased has made a radical shift to a much more digital and e-commerce model, so upgrading the business to this format and improving the traditional one is crucial to stay relevant to buyers. Hyperautomation helps to mechanize processes, such as order management, payments, transportation, warehousing and inventory, supplier management, data control, etc. Customer loyalty is also significant in the retail sector, and AI-driven facial recognition techniques can be precious in recognizing a regular customer on the premises of a store, thereby making offers tailored to their preferences.
Hyperautomation in Manufacturing
Hyperautomation can be a handy tool in manufacturing processes to assist employees in their tasks. The manufacturing of a part can be automated to allow workers to intervene and monitor the intelligent workflow with real-time analytics. Automated predictive maintenance is used to collect data from machinery to understand the factors that create failures and schedule maintenance before it stops working and creates major problems.
Hyperautomation in Recruiting
The process of hiring an employee is lengthy and involves numerous phases, but hyperautomation eases the workflow. For example, AI-based solutions and ML capabilities can understand candidate experience data to select the most appropriate profiles in much shorter timeframes. Chatbots are also set up to send automated responses to set up interviews or communicate that they are no longer in the process. A simple process results in a better experience for candidates and a better brand image for the company.
Hyperautomation provides organizations with a framework to scale, integrate and optimize business automation. It focuses on adding more intelligence and applying a broader approach to automation to scale efforts. Still, the right balance must be struck between traditional manual efforts and optimizing complex processes. This is why it is so important to have a professional in place to lead the automation process. At Plain Concepts, we help you implement the strategy that best suits your needs to achieve your goals. Contact us!