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.
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Hyperautomation technology and tools, explained.
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.
- Robotic process automation (RPA): Software bots to automate repetitive processes, such as copying data from one system to another.
- Intelligent document processing (IDP): Tools to automatically pull and categorize information from forms and turn it into structured, digital data.
- Artificial intelligence (AI): Applications that use machine learning and natural language processing (NLP) to make simple, cognitive decisions without people needing to be involved.
- Business process management (BPM): Graphical notation tools for modeling and specifying complex 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.
3 things to know as you select hyperautomation tools and shape strategy.
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.
1. Ensure technology is connected throughout your workflow.
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.
2. Give the right job to the right person (or bot).
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.
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3. Garbage in, garbage out: Data architecture matters.
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.
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Hyperautomation tool takeaways.
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.
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