What is hyperautomation?
Robotics has always served to perform routine tasks that don't require much intelligence but high speed and accuracy, which take humans years and years of practice. However, now business processes are increasingly not following stable and predictable scenarios. It created a need for a new type of automation. Hyperautomation (the term coined by Gartner), also known as Intelligent or Digital Process Automation, is a trend on everyone's lips. The new approach is not restricted to manufacturing only and creates added value across many industries - medicine, retail, insurance, software development, etc. According to Gartner, forward-thinking businesses should think of building a hyper-automation strategy to keep up with the times and stay competitive. So, what is it? In simple words, it is a synergy of technologies and state-of-the-art tools to automate all processes that can be automated. It has robotic process automation (RPA) as its core with a layer of Artificial Intelligence. Therefore, it is also referred to as RPAAI or "unassisted RPA." The RPA market is predicted to reach $2.9 billion in 2021, whereas companies will spend almost $100 billion on AI by 2023. Accenture provides interesting insights on how humans and machines will interact in the future in the form of collaborative intelligence. The main idea is not to outflank human employees but free them of low-value repetitive tasks and equip them with tools that will considerably improve business outcomes.
Components - RPA, AI, process mining, etc.
RPA emulates human actions when dealing with a system or a device through a UI interface. It is task-specific, works with structured data, and differently from hyper-automation, which requires a whole ecosystem, can be done from a single platform. RPA makes no changes to the legacy systems. It has a wide adoption now and established best practices.
Decision-making and processing unstructured, ambiguous data are what Artificial Intelligence is good at. It helps to automate entire workflows, not just specific tasks. Through certain algorithms, Machine Learning as part of AI ensures constant improvement of processes based on previous experience. ML was invented in the 1950s and has been used for forecasts, fraud detection, to name just a few.
Natural Language Processing (NLP) is AI's ability to "understand" and respond to human language. A vivid example of this is Siri from Apple.
Optical Character Recognition (OCR) converts any format of text into machine-readable. It automates the process of capturing visual data and interpreting them to perform the required task.
Process Mining is another crucial element. Software systems identify business processes that have efficiency and compliance problems and thus accelerate automation. The result is creating the Digital Twin of an Organization - a virtual clone of a process to test a range of scenarios to find the optimum one and then control if automation runs as expected.
Below, you can find several examples of how this approach works in different domains.
Hyperautomation has a wide range of applications in the banking industry, from marketing to payment operations. Prevention of fraud and money laundering is possible with the help of ML-based predictive modeling. Advanced Analytics assesses borrowers and minimizes risks for the bank, and considerably shortens the decision time for the client.
In insurance, there are many manual operations, such as dealing with claims. Intelligent automation allows validating information and ensuring compliance with high accuracy and speed, round the clock. Processing a plethora of scanned and digital documents and selecting the optimum insurance product for clients are just a few tasks that can be streamlined with the digital workforce.
In retail, digitalization encompasses all core operations: handling orders, logistics, supplies, procurement, etc. AI enables dynamic pricing through real-time analysis of competitor websites and other factors, such as user sentiments, e.g., through social media trends.
AI-based chatbots are becoming a convenient alternative to customer support teams. Instead of only providing pre-defined responses to queries, a new generation of chatbots analyzes response satisfaction rates and user behavior on the website to provide more relevant information. The system behind it also automatically generates smart analytics. It also can handle such tasks as locating data and automatic follow-up on leads.
In healthcare, automation works wonders with smart billing, processing insurance, and claims documentation - tasks that take up thousands of valuable manhours. Doctors do not have to spend time filling in electronic health records manually, thanks to ML-based voice-recognition transcribing systems. Sophisticated AI bots can interact with patients at home, analyze symptoms, and direct them to hospitals if necessary.
Benefits of hyperautomation
Let's sum up the main benefits this technology can create for a company:
- Incomparably (to humans) faster and error-free performance.
- The absence of mundane tasks contributes to employee satisfaction.
- Advanced analytics for better decision-making. AI helps not only to retrieve data from business processes but provides valuable insights and potential action plans.
- End-to-end automation of sophisticated processes and workflows with various datasets.
- Improved customer experience and ultra-personalization.
- Higher profitability by considerably augmenting process efficiency.
- Continuity of improvement thanks to ML.
- Scalability. Smart automation spares time and resources for growth.
Although hyper-automation is still in its very early stages of development, it is inevitable in almost all spheres. "Faster, better, safer"- these words have always been the motto for successful businesses all over the world, and now there is another one - "digital." The Covid-19 pandemic has demonstrated how volatile the world is, and economic conditions, as well as user behavior, can change in the blink of an eye. In this light, intelligent automation seems to be a must, as it offers the key not only to survival but higher ROI thanks to cost-cutting and flexibility. However, its implementation requires meticulous planning, building a viable strategy, and identifying the right tools.
Blackthorn Vision has been in the automation market for more than a decade. We have created business solutions for such industry giants as Sensia. It is what makes us a trustworthy partner for a digital transformation of your business. If you feel the need to streamline your company and do not know where to start, our Discovery Phase will draw a comprehensive automation map for you. Contact us now to get your customized solution.