Hyperautomation is the new buzzword in the IT industry. The term was first coined by Gartner in 2020 and has once again found its place in the research company’s list of strategic technology trends for 2021. In this blog post, we’ll share what is hyperautomation, the difference between automation and hyperautomation and how companies can leverage it.
So, let’s begin.
We begin with a quick understanding of automation and then move to hyperautomation. Automation is the process of leveraging a range of technologies to automatically operate repeatable tasks to minimize or eliminate human intervention. Take for example the case of email automation.
Before automation, people used to send email. If it is a repeatable activity like sending invoices to 20 clients at the end of the month, a person will send 20 emails. Now, this process can be automated through email automation software. You can define the template, create a list of recipients, dates and timing and the emails will be sent automatically every month on the fixed date. You can scale the process to send invoices to thousands and millions of recipients. No human intelligence is required.
Hyperautomation goes beyond the automation of tasks. It deals with leveraging emerging technologies such as Robotic Process Automation (RPA), intelligent business management software like Artificial Intelligence (AI) and Machine Learning (ML) to automate processes and further minimize human involvement. Hyperautomation can integrate and automate a chain of tasks, take decisions and reassess the processes.
One of the basic differences between automation and hyperautomation is in its scope. Automation is a limited process to automate tasks like sending emails, alerts or reminders. Hyperautomation deals with automating the entire processes, such as payment collection that may include multiple tasks, such as creating invoices, sending invoices, calculating balances, payment follow-ups etc.
The second difference between hyperautomation and automation is in the use of technology. Automation deals with one technology to automate tasks whereas hyperautomation deals with multiple emerging technologies.
The third difference between automation and hyperautomation is that the latter requires multiple technologies and an integrated platform whereas the former relies on a single technology and platform.
The last but crucial difference between the two is the benefits that hyperautomation provides to a business. Automation has made things easier for a business by reducing human labor leading to cost-efficiency and an increase in productivity. Hyperautomation will go one level up to help enterprises build smart and intelligent processes that can learn, decide and drive on their own.
As with any emerging technology, building and implementing hyperautomation proocess requires a robust strategy and a toolbox. Gemini Consulting & Services can help you here. We have built strong capabilities in hyperautomation. Our team of engineers, technology experts and data scientists can help you at every step in your hyperautomation journey. In the past, we had partnered with several public and private organizations and helped them build intelligent processes. Contact us to know how we can help you hyperautomate your business processes.
- Start Small: Begin with simple processes that involve a shortened chain of tasks. Set your goals. What you want to achieve.
- Analyze the Process: Get a good understanding of the process. Identify parts that are repeatable and parts where decision-making is involved. Also understand the risks involved.
- Assess and Decide: Assess whether the process really requires hyperautomation, or you can achieve the set goals with some more automation.
- Go for a Technology Partner: Identify the set of technologies you would need to hyperautomate the process. Inquire in the market to find the optimized set of tools for your business. Join hands with a reputed service provider who can help you deploy these tools and get maximum value from them.
- Applying AI & ML: AI and ML are critical for process hyperautomation as it performs key functions like learning from data, training the models and reusing the learning models. Assess how AI and ML will work with other technologies and tools within the process to get your combination perfect.