Robotic process automation, or the use of software with artificial intelligence (AI) and machine learning (ML) features to automate repetitive tasks, has been a key driver in the ongoing digital transformation of business processes. Chatbots, a common form of RPA, have already begun to revolutionize how businesses streamline work processes, improve productivity, and better utilize their most important resource: their employees.
In 2019, Gartner identified the next step of RPA as hyperautomation, which uses advanced automation technologies, business processes, and AI to more effectively employ human intelligence. Hyperautomation’s goal is to provide more robust analytics and insights that will allow organizations, from small businesses right up to enterprises, to make better decisions for their workforce and their bottomline.
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How Hyperautomation Works
Gartner has named hyperautomation the leading technology trend of 2021, and with good reason. The ongoing pandemic has shifted how we all work and has been a catalyst in how businesses structure their workforce and workflows. RPA has been and continues to be a good point of entry for companies looking to introduce basic, task-driven automation into their business, but its rules-based functionality is not enough for companies looking to automate more complex and disparate forms of data.
Hyperautomation takes RPA and marries it AI, ML, business process management (BPM), and advanced analytics to drive automation of not just low-level tasks, but entire business processes. This complex automation issues data and insights that will, in turn, inform and influence how humans in the organization make decisions. Gartner has taken pains to make this point in its definition of hyperautomation as a way of alleviating fears of automation replacing or devaluing human work; the process is actually used to bring humans into the data-driven, decision-making process.
Here is how each aspect of hyperautomation works together to streamline business processes.
RPA’s key function is to perform repetitive, high-volume, rules-based tasks. For example, RPA can be used to automate various aspects of a company’s customer service via a chatbot. While RPA can establish efficiencies and free up employees to do more complex tasks, RPA is incapable of learning and understanding context beyond the task at hand, making evolution of processes impossible. RPA is also incapable of processing unstructured data, meaning it can’t understand and process videos, images, audio, and text-heavy items (i.e., social media posts).
Organizations have found RPA beneficial to their operations and finances, but many eventually outgrow its limited feature set and lack of functional scalability. However, in a hyperautomation context, RPA is the foundation on which more complex automated processes can be built.
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Business process management is another term for software that provides workflow management. BPM software provides a high-level view of a business by providing data and analytics that can help business leaders refine the organization’s goals and strategies. It tests new workflows for efficacy, which helps organizations avoid implementing potentially destructive processes that can hamper their business.
In a hyperautomation context, BPM software can be used to manage an organization's hyperautomation strategies and initiatives, effectively refining processes that are the best fit for reaching company targets and goals.
AI and ML
At the heart of the continuous development and improvement of automation is AI and machine learning. AI introduces intelligent processes alongside machine learning that enables software to identify natural language patterns (NLP), data patterns, and optical character recognition (ORC).
AI and ML are not cheap and require careful consideration and planning before they are implemented, including if they will integrate well with existing technologies and processes.
Advanced analytics helps organizations gain deeper insights into their content and data by using tools and techniques like Tableau and Google’s Data Studio. Wielding advanced analytics, organizations can make predictive models to strengthen their strategies and plans for future growth by generating recommendations and forecasting outcomes.
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Benefits of Hyperautomation
The excitement around hyperautomation business models is justified for all the reasons companies turn to new processes:
- Increased productivity. Employees can move past time-consuming, repetitive tasks to do more meaningful, productive work that uses less resources and brings more value to the organization’s workflow.
- Advanced technology integration. Companies that have started their digital transformation with RPA can now move toward complex automation to develop more flexible, agile operations and upgrade legacy systems with advanced interoperable technologies.
- ROI. Organizations can track their return on investment using key powerful analytics to measure money saved weekly, monthly and yearly after deploying hyperautomation. These metrics can be used to better optimize further deployment and resources.
Hyperautomation’s moving parts may seem out of the scope for SMBs in the market to expand their automated processes, but the investment is ultimately worth it. Small to medium-size businesses looking to make this transition should assess their company’s needs and select areas where automation makes the most sense. For example, sales and marketing departments are especially conducive to automation as processes such as email campaigns, budget management, and sales leads can be automated. By incrementally investing in areas where automation is most beneficial, SMBs will be able to scale their intelligent automated system as they grow.
To quell fears about job security in the presence of automation, companies should also bring employees into the loop through open discussions about how the automation process works as well as train employees in using the system. This all-hands-on-deck approach as well as open communication about the transformation will underscore that the automation investment and goal is to refine workflows and free employees to be more creative and innovative in their own work.
Building a Future Automation Foundation
Hyperautomation is a buzzword for an elegant automation process that is quickly catching on. Its complex architecture is in service to making workflow and tasks more efficient while remaining invested in the human input and production of that work.
Of course, the ultimate stated goal — to free workers to do more meaningful, engaging work — comes with challenges, including finding the right, interoperable tools to building a complex automation system that plays well with current and future technologies and the learning curve for employees across the board.
Yet, the benefits to both business and the workforce are so appealing that hyperautomation is swiftly moving from concept to reality as companies seek to raise the bar on implementing transformative digital technologies — doing so to lay the groundwork for a future that is already in plain view.
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