How can you find time to drive efficiency across your organization when there is so much digital work to be done? This is one area where hyperautomation and digital transformation initiatives intersect. Yet, just like other technology trends, our understanding of hyperautomation and its value has become convoluted.
Let’s demystify some of the gray areas surrounding what hyperautomation technologies and tools can help you accomplish as you shape automation strategy and select tools.
[ Which emerging automation trends deserve your attention now? Get the Gartner® Emerging Technologies and Trends Impact Radar: Hyperautomation report. ]
Hyperautomation tools are a set of technologies used to automate complex workflows and augment human capabilities, leading to improved efficiency and decision making. What merits the “hyper” designation? Hyperautomation uses more than one specific type of automation technology to automate work, and it helps organizations automate entire business processes end to end, not just discrete tasks.
Robotic process automation (RPA), intelligent document processing (IDP), artificial intelligence (AI), and business process management (BPM) are all automation capabilities that make up hyperautomation technology and can be implemented throughout your organization to improve business processes.
The benefits of hyperautomation include increased efficiency, employee performance, cost savings, and compliance. Process automation platforms often include low-code/no-code tools in their hyperautomation technology stacks that help you grow and scale your automation initiatives.
Even after you have an established automation strategy, you should always continue to search for new automation opportunities in your organization. As you continue your journey and implement hyperautomation technologies, keep these key facts in mind.
Often left out of automation frameworks and strategies is how to orchestrate these tools across business processes. It is essential to your success that you map out where each automation tool is being used and how work is being handed off between people, bots, and systems.
Look at the broad automation opportunities from an end-to-end perspective to capture a holistic view of the process flow, identify areas of improvement, and understand total process journeys. Take a business-driven, disciplined approach to learning when, where, and how automation efforts are being executed.
Not every hyperautomation tool is right for every scenario, no matter how shiny and exciting it seems. To ensure ROI on hyperautomation, make sure to understand how each automation tool is intended to be used in the actual workflow.
Remember why you started your hyperautomation projects in the first place. If you’re trying to alleviate boring tasks for knowledge workers, don't throw AI into a situation where it needs to make complex decisions based on contextual information. Likewise, if you have a frontline worker in accounts payable who needs to see data in real time, don’t stick RPA with the job of copy-pasting data in an environment that has an API.
Each tool was designed to do a specific task and should be used to improve employee productivity, not cause more headaches.
[ Get the eBook: More than 200 ideas for how to use RPA and IDP, with use cases for additional functions and industries. ]
The quality of input determines the quality of output. These tools and technologies can improve operational efficiencies, but they can only work with the data and information they have. If your organization doesn't have the right information in forms due to poor data architecture, hyperautomation can’t reconcile this.
This is where a process automation platform with data fabric capabilities can play a significant role in hyperautomation success. (Process automation and hyperautomation, by the way, refer to the same thing: automating entire business processes end to end using multiple automation technologies.) A data fabric connects data across your organization’s disparate software systems, whether they’re on-premises or in the cloud, using a virtualized data layer that sits on top of your systems. Users interact with the fabric view; the data stays put.
Among other things, this means your data architecture will help rather than hinder automation progress. Also, data fabric centralizes data management for stronger security and compliance, a must-have as you scale automation efforts.
[ Want to learn more about how data fabric helps organizations with automation strategy? Get the eBook: The Data Fabric Advantage. ]
Remember, hyperautomation initiatives aren’t a golden ticket for solving all your business operation issues. Consider the people, process, and technology framework when going through any digital transformation initiative. People and processes are just as, if not more, important than technology in achieving your business goals.
Automation technologies can either free your teams from manual, repetitive tasks and drive operational excellence or shackle them to additional digital labor. The outcome depends on your strategy and approach to automation.
Hyperautomation tools and technology are a big piece of the puzzle, but you must ensure that you can streamline your efforts with automation, use the right tools for the right use cases, and optimize across all facets of your organizational processes.
Learn how to successfully implement end-to-end process automation strategies. Get the Process Automation Guide.