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Hyperautomation is a strategic technology trend that has gained massive adoption with several businesses due to its end-to-end mode of automation. Its approach allows businesses to optimize and integrate processes at larger scales to improve performance and ensure maximum productivity.
According to Gartner’s Top 10 Strategic Technologies in 2020 and 2021, hyperautomation does not only describe a new technology, it also dictates a new form of company growth because it takes a holistic approach of automation that introduces new possibilities into every business department.
Jumpt to:
What is hyperautomation?
Hyperautomation focuses on optimizing business processes through a studied approach by identifying, assessing and automating workflows using an advanced set of technologies. It is based on a framework of tools and technologies, most of which continue to evolve to accommodate enterprise scaling processes. The goal of the scaling process is to continuously optimize automation processes for non- and already existing workflows without future complexities.
SEE: Overhaul your SEO with this automation tool (TechRepublic)
How does hyperautomation work?
Hyperatomation is grouped into three components. These components create a shift from the focus of conventional automation. Instead of creating and maximizing tools through digital process automation (DPA), intelligent process automation and cognitive automation, hyperautomation is process-centered. It considers every automation possibility in a flexible manner to include undocumented processes. The three components of hyperautomation include:
Robotic process automation (RPA)
RPA lays a foundation through process discovery to reveal business processes that can be automated using smaller automation tools and bots. Through a defined sequence, built-in analytics and artificial intelligence (AI) are also used to create an intuitive system from CRM and ERP systems to add more intelligence to automation efforts.
Orchestration and machine learning
This component considers every automation process and creates a synchronized framework that brings all those tools together. The large pool of centralized data drawn from the built-in analytics is used to draw up a framework where every employed tool can work in harmony. Orchestration also considers the impacts of automating processes on value and revenue with the use of data transfer objects.
In some cases, autonomous processes can be created to ensure automation in those processes will not hamper revenue generation. Further, optimization is achieved through conclusions drawn from correlations of large processed data.
Optimization and process mining
This is the final layer of intelligence that is added to ensure seamless integration. By monitoring processes to recognize critical information and complex patterns, the digital traces of business processes can be analyzed to aid decision making.
The orchestration process is also improved further through validations and continuous learning. This helps to determine if the technologies and tools used should be deployed individually or in synergy.
While robotic process automation is at the core of hyperautomation, other sophisticated technologies like AI are integrated to mine and analyze processes. Some of these other tools and technologies include:
- Machine learning
- Low-code and no-code enterprise resource planning (ERP) solutions
- Packaged software
- Integration platform as a service (iPaaS)
- Business process management (BPM) and intelligent business process management suites (iBPMS)
- Event-driven software architecture
SEE: Artificial Intelligence Ethics Policy (TechRepublic Premium)
Benefits of hyperautomation
Synchronized operation
Most companies have implemented automation technologies in different departments. What hyperautomation platforms can help them achieve is to bring together the different interfaces of automation in such a way that they are combined into a system that can work in synchrony. The new coordination in businesses that employ hyperatomation helps to improve productivity and team association through centralized data processing and operation.
Decision making
Decentralized processes in a business can affect decision making due to lack of coherence of data from different automation pools. The margin of error makes management-level decisions difficult and inefficient. But, by taking advantage of AI features and the centralized nature of a hyperautomated system, stakeholders can make predictions from analyzed data history faster and more efficiently.
Ease of expansion and scalability
It becomes easy to expand the operational portfolio of companies without facing management challenges since hyperautomation continuously optimizes its frameworks. New processes are considered quickly and synchronized into already existing ones for a streamlined workflow.
Standardization
With fewer or no errors, operations are standardized at all stages. This is important because of auditing reasons. The standardization creates an audit trail with maintenance records. Hence, businesses are always audit-ready without hassles. Also, the improved synchrony between IT and businesses increases security by reducing the need for shadow IT.
Lower costs
Businesses without automation deal with uncoordinated human capital that slows down growth. For organizations with increasing customer demand, product expansion invites huge costs and diminishing returns especially if expansion is done without proper data analysis and prediction. An optimized system of automation points stakeholders in the right direction of growth with lower costs. It also reduces the amount of labor intensive, repetitive and mundane processes which are time consuming, filled with errors and eat into the revenue of companies in the long run.
Industries that can use hyperautomation
Retail
The COVID-19 pandemic created a surge in the e-commerce industry, making it the main center of order processing. Both back-end and front-end processes as well as customer loyalty systems use hyperautomation to enhance efficiency of placing ads, creating advertising materials, inventory and customer management. Leveraging AI also makes it easy to analyze customer behavior to make better decisions for revenue generation.
Finance and accounting
Finance departments use hyperautomation to improve clerical support, administrative and other purchase processes of companies in the accounts payable department. Other uses also include invoice management, tracking and payment. Generally, companies can increase efficiency while reducing expenses with consistency and reduced error when they employ hyperautomation.
SEE: Will a recession trigger renewed interest in old-fashioned enterprise budgeting and finance software? (TechRepublic)
Healthcare
Hyperautomation is used in healthcare to offer improved patient experience through collection of data that can be analyzed into treatment plans. On the business side of things, billing cycles, staff management and quality control can be centralized into a single hyperautomated platform to ensure regulatory compliance and public reliance.
Supply chain
Delays in the supply chain industries are largely due to increasing demands, low workforce and lack of frameworks to guide workflows in its system. RPA can be used for a number of things; data input, pricing, billing, quotation, inventory management, follow-up, data entry and system maintenance. All these processes are mostly repetitive but can easily be automated to increase efficiency, speed and accuracy.
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