What is hyper-automation?
To put it simply – hyper-automation is going one step further to the existing automation capabilities like RPA and making “the automation” across workflows more intelligent and efficient using technologies like Artificial Intelligence (AI), Natural language processing (NLP), Machine learning (ML), Low-code and more.
Quick statistic: A 2021 Gartner survey shows that the average number of Hyper-automation projects in enterprises ranges from 4-to 10
Moreover, it’s important to note the significance of the pandemic in causing a shift within the market, with companies adopting hyper-automation and putting digital transformation initiatives above all else.
As the business environment is moving towards more complex models and enterprise transformation, hyper-automation is an answer to their expectations, and when the practical limitations of RPA prevent companies from transitioning into GEN 2 automation strategy.
Hyper-automation is rapidly shifting from an option to a condition of survival, ranking “outdated work processes” as the No. 1 workforce issue. – Gartner
GEN 2 automation requires companies to go beyond automating well-defined, time-consuming, repetitive processes and leverage automation for more complex, highly technical areas that often need decision-making and experience.
With hyper-automation alleviating the strain that repetitive processes and legacy infrastructure place on organizations and their resources, we expect to see more of this in the coming years as the desire for automation solutions continues to grow.
Are hyper-automation and intelligent automation the same?
Intelligent automation and hyper-automation are related concepts, but the former is a subset of the latter. Intelligent automation involves RPA, AI, process discovery, and analytics to automate processes; hyper-automation encompasses more advanced technologies such as computer vision and NLP, which are beyond the scope of intelligent automation.
Components of Hyper-automation
Hyper-automation requires an understanding of algorithms, identifying automation opportunities, and creating appropriate automation artifacts, scripts, and workflows using various tools like
- Robotic process automation
- Machine learning
- Cognitive automation
- Artificial Intelligence
- Advanced analytics
- Natural language processing
According to Gartner, “hyper-automation is an unavoidable market state in which organizations must rapidly identify and automate all possible business processes.
The path to Hyper-automation
The goal of hyper-automation is more than just saving money and boosting productivity by automating automation; it’s also about capitalizing on the data collected by digitized processes. Organizations can mine that data for insights that help them make better business decisions in real-time.
Here’s Gartner’s path to Hyper-automation
A hyper-automation initiative involves:
- Identifying which process to automate.
- Choosing the right automation tools.
- Ensuring that the appropriate teams use the automation tools correctly.
- Fostering agile culture by encouraging the automated process reusability.
One way to get hyper-automation initiatives off the ground is to create a center of excellence (CoE) that helps to drive automation efforts.
If you’re getting on the road to onset your hyper-automation journey, here are a few steps that might help:
Benefits of using hyper-automation
You can get the following benefits by employing hyper-automation in your business processes.
Amplifies performance: As we all know, automation can work and perform much faster than humans, which is error-free.
Promotes agility: When it comes to adapting to changes in a business environment, organizations can either be agile or not. If a company makes sure to hyper-automate processes, it won’t be stuck in the same position it was before. It strengthens the company’s agility and ability to scale its business per user’s demands.
Reaps better ROI: Automating tasks can streamline your workflows, reduce turnaround times, and save you time and money. An enterprise-wide transformation can help organizations improve their profitability. And hyper-automation has the potential to boost ROI.
The transition to hyper-automation is no walk in the park. Many companies feel unprepared to tackle automation efforts due to raw or poor-quality data and a lack of resources with technical skills to address it. Organizations can turn to retraining programs combined with a lesson learnt register to help them address their needs and develop a program that works best for them.
In choosing products to offer clients, organizations face a number of challenges. For example, the marketplace for products is growing and evolving so rapidly that it can be hard to keep up. This situation has led to mergers and acquisitions among many companies that offer similar products to make it easier for clients to evaluate potential vendors.
In addition to interoperability among tools, enterprises need to build firewalls to prevent security vulnerabilities of automatically generated apps.
Only about 40% – 60% of the code for automation could be automatically generated using existing tools. – Forrester
Building automated systems at scale often requires a lot of budget and manual work.
Hyper-automation + allied areas | Zuci View
As we know by now, the hype around hyper-automation is real, and that hyper-automation doesn’t operate in a vacuum. It cuts across various areas like RPA, testing, etc.
Let’s see them below
Hyper-automation + RPA
Hyper-automation provides the basic framework for strategic deployment of RPA separately or in tandem augmented by AI/ML. Talking about RPA and hyper-automation, Jyothsna Chandran, Delivery Manager, Digital Engineering at Zuci systems, said,
Gartner expects when RPA is enriched with AI and ML, it forms the enabling technology of hyper-automation. It starts with RPA and expands automation capability with artificial intelligence, process mining, analytics, and other advanced tools like Natural Language Processing, and Optical Character Recognition.
Hyper-automation can make an impact in Insurance (claims), Banking (KYC), HealthCare (preauthorization), Manufacturing (Invoice, receipt), Life Sciences (clinical data processing), and HR (back office).
Think of scenarios that make use of the capabilities below to arrive at use cases.
- OCR: Add machine learning to document extraction with RPA, and businesses can automate many tasks.
- NLP: Customer input understanding like email, document, query
- ML algorithms to classify customer requests and match them to potential actions
- RPA bots or scripts to publish results/ respond back
Hyper-automation benefits include faster data sharing within departments in an organization, thereby providing real-time key insights.
Hyper-automation + Testing
With the advent of hyper-automation, the organizations are going to have their QA amplified further resulting in significant gains on top of the test automation technology.
Scale automation across STLC: Hyper-automation with the help of NLP, ML technology enables organizations to enable automation across the STLC. It includes test activities like automated test generation, script maintenance, defect tracking, and automated status reporting. These help organizations to reimagine their QA and promote a great level of transparency across the testing process.
Intelligent defect detection: Intelligent technology helps to improve the scope of defect detection by evaluating production data and making interpretations to determine which flows are frequently used by real-world users. The collective knowledge helps automatically develop extremely effective automated test scripts.
Broadens the scope for test automation coverage: In contrast to regression testing programs in isolation, Hyper-automation coverage considers the integrated systems and includes all components of a bigger system. By way of doing this, it empowers teams to test a wide range of applications as well as handle complicated flows and dynamic test data requirements.
Increased ROI & Productivity gains: By strengthening the scope of automation, hyper-automation removes bottlenecks that exist in traditional automation and improves productivity. Further, with its advanced AI and analytics capabilities, it can gather and analyze data to understand performance and leverage analytics to monitor the performance and efficiency of its test automation process, course correct in real-time, and save a lot of money in the process.
Hyper-automation is worth the hype!
Hyper-automation, when it turns into reality from being an over-hyped concept can improve operational efficiency multi-fold. It’s going to play an important role in upgrading the organization’s automation game and ensuring that the organizations catch up to the ever-changing demands of the market. In short, it supports the organizations’ goal of digital transformation and making them future ready.
Interested in knowing more about hyper-automation or just want to get started with the basic process automation? Like a POC? Drop us an email at email@example.com and we’ll get back to you in a day.