What is intelligent automation?
- For one manufacturer, it is processing an increasing number of monthly invoices 90% faster and 100% more accurately than four full-time employees previously accomplished.
- For a life insurance company, it is shortening an hours-long premium calculation process by 92%, so it can now produce as many as 5,000 quotes a day.
- For a healthcare group, it is reducing the number of manual claims processing tasks by 95%, making its payment cycle 80% more efficient.
For most companies, the outcome of intelligent automation is more meaningful than its actual definition. (All of the above results are real—you can read about them here!) But the more you understand what intelligent automation is and how it works, the easier it will be to identify use cases that will produce the most impactful results for you.
Keep reading to learn more about intelligent automation, how it relates to robotic process automation (RPA), and the ways in which companies in all industries are using it to gain a competitive advantage.
A concise intelligent automation definition is:
The application of enhanced technology tools (such as computer vision, machine learning, natural language processing, and others) to a complex process to automate it from beginning to end, for purposes of reducing human effort and increasing efficiency.
To further explain this concept, it helps to examine it in relation to RPA.
Robotic process automation has been around for decades but has become really popular in the last few years. It is essentially a way to automate mundane, repetitive, rule-driven tasks that are normally done by people—tasks you can teach a bot to do instead of a human.
In RPA, automations (sometimes referred to as “bots”) are developed through an easy to use visual design interface that requires knowledge of the business process that will be automated.
The bot can make decisions or follow rules that are based on clear conditions: “If a particular condition (or set of conditions) exists, then do this.” For example, an insurance company would benefit from an RPA bot that automatically copies and pastes data from customer contact forms into various processing systems.
On the surface, that may seem like no big deal; haven’t computers done things like that all along? But the secret sauce of RPA is in how it gets done.
Unlike the creation of typical computer programs, you don’t need skilled programmers who know a variety of programming languages, understand how to build systems from scratch, and grasp how to work with other systems. RPA doesn’t require the involvement of any programmers. You train the bots to do the work the same way humans would do it via the user interface.
If you know how a process works from a human perspective, then you can build the automation. All you need to understand is: How are your people currently doing the work? Then, you teach a bot to do it the same way.
RPA has proven to be enormously successful for many of the companies that have deployed it, particularly in light of the impact of COVID-19. (For some interesting stats on RPA results, take a look here.) But there are only so many tasks you can accomplish by narrowly focusing on automating using RPA bots.
First of all, not all repetitive tasks are straightforward. And repetitive tasks don’t live in isolation—they’re almost always a foundational part of a bigger process that’s crucial to your company’s operations. That’s where intelligent automation comes in.
Intelligent automation, which is sometimes called hyperautomation, digital process automation or intelligent process automation, takes RPA technology (the ability to automate processes simply through the user interface) and layers other technologies onto it to make it more useful. The addition of these other technologies—various forms of artificial intelligence (AI) and business process management tools—combine to make a more intelligent form of automation.
The result? More types of processes can be automated; more integrations with other systems can easily be completed; and more processes can be automated from end to end. It essentially orchestrates and automates the workflow of a process in its entirety, bridging across various systems and includes automated tasks in addition to those completed by humans.
Intelligent Automation & RPA Examples
Check out these examples of AI and intelligent automation as compared to RPA:
- An accounts payable process is made up of a number of steps—extracting data from invoices, entering it into various applications, validating payment requests, and paying bills. RPA can easily automate certain individual tasks within that process, but it doesn’t allow you to automate the complete process, which includes some higher-order decision-making and elements of human intervention (like calling a vendor with questions). Intelligent automation enables automation of the entire process, including the steps that are done by humans.
- Another example that highlights the contrast between RPA and intelligent automation is data extraction. Invoices, for example, have no standard format; every vendor has its own invoice type, making it difficult for a typical RPA bot to extract payment data from the document. Even optical character recognition, or OCR, solutions fall short when it comes to accurately converting a document image into structured data. Intelligent automation layers technology tools like computer vision, natural language processing and machine learning on top of OCR software that make the extraction of structured data much more effective. Not only is more data extracted, but the extracted data itself is higher quality.
What are the benefits of using intelligent automation & RPA?
Nearly every company in every industry suffers from efficiency-related problems. That’s why most of our clients come to us in the first place—because their inefficiencies have started to hamper business performance, and they’re looking for a solution. In most cases, they may not even be able to pinpoint the problem, but they know it exists. (If that’s you, don’t worry—our partner Nividous can help.)
The benefits of eliminating wasteful processes and the associated costs are far-reaching:
- Enhanced productivity: Intelligent automation processes are more productive because they can work 24/7. Meanwhile, the rest of your employees are tackling more pressing issues that are more valuable to your company’s mission and goals.
- Higher employee engagement: Menial, repetitive tasks make for boring work. (Anywhere from 43–53% of the workforce is bored right now!) Boredom leads to disengagement, which leads to turnover, which leads to lost money. When your employees are focused on higher-value tasks, they are more likely to be actively engaged—and more likely to produce their best work.
- Greater accuracy: Most people would agree that data accuracy is important, but they rarely take the time to address the issue in a meaningful way. According to one study, data error rates of approximately 1–5% are common in business databases. Intelligent automation solutions can virtually eliminate the errors associated with manual data entry and help avoid the missed opportunities and faulty decision-making that happen as a result.
- Rapid scalability: RPA and intelligent automation solutions are flexible and can be easily scaled up or down as demand requires. You can deploy more bots quickly with minimal cost, and there’s no additional training required to get more work done.
- Greater insight into your processes: Intelligent automation helps you manage complete processes more efficiently because it provides data around every step. Even if you previously had very little insight around a process, such as where a bottleneck is occurring, intelligent automation enables data gathering to continuously track processes and report on them.
This blog post was originally published by Nividous.