Hyperautomation refers to the use of multiple advanced automation technologies such as artificial intelligence (AI), robotic process automation (RPA), machine learning (ML), low-code, and business process management tools to accomplish end-to-end process automation. Rather than automating a single task, hyperautomation lets you automate multiple tasks within a wider process (and pass work easily between humans and digital workers). Popularized by Gartner, the term and the trend have gained traction with CIOs and IT teams chasing greater levels of speed, agility, and efficiency.
Hyperautomation brings a number of benefits to organizations—including improved efficiency by automating rote tasks, increased innovation by freeing workers up to focus on high-value work, reduced costs by minimizing errors and speeding up processes, and improved accuracy and customer satisfaction.
A strong hyperautomation platform will help you reap these benefits. In evaluating your choices, look not only for advanced technologies but also a platform that smoothly unifies and orchestrates work between tools and handoffs between people and tools. This will help you avoid islands of automation, tech debt, and talent worries. Today, we’ll cover six factors to look for in a modern hyperautomation platform.
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A hyperautomation platform offers several advanced automation capabilities that work together. To choose the right platform for your organization, keep these criteria in mind.
1. Process automation tools that work together well.
Consider how well the platform’s multiple automation tools get the job done together. A hyperautomation platform combines tools including robotic process automation (RPA), artificial intelligence (AI), machine learning (ML), and technology that can orchestrate these technologies into a whole, end-to-end process with humans in the mix. This orchestration layer blends humans and digital workers into a harmonious whole.
Costs also matter of course. Total cost of ownership (TCO) will increase if you have to stitch together AI licenses from one source to RPA bots from another to orchestration capabilities from a third place.
Second, look for a data fabric architecture. Data fabric allows you to connect and use data from across the enterprise regardless of the system of origin. With a data fabric, you work with data in a virtual data layer, rather than working with source data directly. The data may be on-premises or in the cloud model. The data fabric approach allows you to move data quickly without extensive database programming or maintenance—and allows applications to be performant without people needing a lot of database knowledge.
How does this facilitate hyperautomation? The truth is you’ll likely have a conglomeration of IT systems. Without a data fabric, moving data between systems becomes a major chore. You not only have to integrate the data, but you also have to format it, ensure database schemas are up to date, and refactor code for greater performance. And as things change in a software system, you have to keep up. A data fabric’s virtual layer allows you to work with and utilize data without having to deal with the additional troubles maintaining multiple systems entails.
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3.Low-code design and orchestration.
One of the most important things to consider is how you’re going to build automations and applications—and how you’ll adapt them over time. Look for a platform that offers the ability to build out full pro6. Process mining. cesses and applications using low-code via business process management (BPM). These low-code tools not only allow you to build applications fast without heavy amounts of coding, but also make it easy to modify applications or automations as your organizational needs change. This offers flexibility and scalability. If anything changes—whether it’s a modification in process or a change in compliance regulations—low-code allows you to quickly change your processes to adapt to your new needs.
Beyond that, look for an integrated layer that orchestrates automations between humans, digital workers, and systems. This orchestration layer is critical for helping you pass off tasks to the right workers at the right time. Simple automation lacks this orchestration layer, confining any automation to simple tasks. For example, a simple invoicing automation tool using AI-based intelligent document processing might allow you to classify and extract information from a document. With an orchestration layer, you can not only process the invoice, but also route this information to the right people and kick off other automated tasks within the wider process.
4. Integration capabilities.
A good hyperautomation platform makes it easy to integrate with your existing software solutions. Look for one that includes smart API integrations via pre-built connectors to popular software packages as well as easy API development. Plus, when an API isn’t available, you can leverage RPA to bridge the gap by having bots transfer data into a legacy application. This allows you to automate across your existing IT environment without having to buy a lot of replacements.
With hyperautomation, scalability matters greatly. A scalable platform will grow with your organization over time and allow you to expand your automated processes across the organization in new ways. A cloud-based architecture can make a critical difference, too, as they tend to offer greater flexibility and performance. Focusing on scalability ensures you continue seeing returns even years after your initial investments.
6. Process mining.
If you want to optimize and automate your processes, then knowing how they function in real life is critical. Process mining allows you to analyze event logs to view business processes as they occur in reality. You’ll gain insights into inefficiencies, bottlenecks, and governance problems, which lets you continuously improve your processes as you go. Plus, when you combine this with the other capabilities mentioned above, you can adapt your processes faster to meet the moment.
Ultimately, you can go two routes in your automation journey. The first involves implementing small, isolated automation projects to solve individual tasks. However, doing this limits your upside ROI, as the speed and efficiency benefits may stop at the department or team level. Instead, you can choose to improve end-to-end processes organization-wide with a solid hyperautomation platform that scales, now and later. Follow the tips above and you’ll set yourself up for success.
Want to learn more about end-to-end process automation? Download the Process Automation Guide: How to Achieve End-to-End Process Excellence.