According to a McKinsey study, cognitive automation tools empower businesses by enabling them to automate 50-70 percent of tasks. And because this technology gets smarter over time, the number of tasks that can be automated is growing.
Businesses can automate invoice processing, sales order processing, onboarding, exception handling, and many other document-based tasks to make them faster and more accurate than ever before. The days of waiting around for approval are over thanks to cognitive automation.
Cognitive automation is a concept that describes the use of machine learning technologies to automate processes that humans would normally perform. There are various degrees of cognitive automation, from simple to extremely complex, and it can be implemented as part of a software package or content management platform.
When it comes to cognitive automation, focusing on the result is oftentimes easier than focusing on the technology itself. For example, if you purchase a content management system with automation capabilities, you should focus on the following:
Cognitive automation is more advanced than regular automation technologies because it doesn’t just take on repeatable tasks, it also makes processes faster and more efficient by connecting the dots in a way that only a robotic mind can. As it learns the ins and outs of your processes, it uses advanced logic to further streamline them, giving it a decided advantage over traditional automation software.
Cognitive automation isn’t just another buzzword for process automation. There have been a lot of those over the last several years, with Robotic Process Automation (RPA) taking the lead. For now, let’s set all of that aside and focus on the potential of this technology within an enterprise-class organization.
First and foremost, it’s important to understand that this technology is already being implemented in countless organizations. In fact, a 2019 global business survey by Statista claims that nearly 40 percent of businesses are already incorporating some form of cognitive automation to improve processes. Although the way these businesses are using it varies greatly by industry, it speaks to the importance of this burgeoning technology. Soon, the majority of companies will be leveraging this advanced form of automation to work smarter — not harder.
How do you unlock the potential of this technology for your organization? It starts by defining and mapping the processes you want to automate. Document your processes step-by-step and talk to an automation expert to see how (or if) they can be automated. Cognitive automation is not a one-size-fits-all solution and it can’t be purchased as a standalone product. It must be integrated into software or incorporated into a digital platform. Furthermore, it must be integrated with your core technologies (i.e., ERP, business applications) to provide safe, reliable functionality.
Comparing and contrasting the various types of automation is a challenge for even the most knowledgeable automation enthusiast. From machine learning to artificial intelligence and the aforementioned RPA, it seems like new automation-related terms are constantly being invented. Since these technologies are oftentimes incorporated into software suites and platforms, it makes it that much more difficult to compare and contrast which type is best for a particular business.
As we mentioned previously, cognitive automation can’t be pegged to one specific product or type of automation. It’s best viewed through a wide lens focusing on the “completeness” of its automation capabilities. Essentially, it is designed to automate tasks from beginning to end with as few hiccups as possible.
For example, RPA shines with repetitive processes that are performed the same way over and over again. When something unexpected happens, RPA lacks the ability to analyze context and adjust the way it works. While reliable, RPA is also rigid, relying on if/then logic rather than actual human perception and response. Therefore, RPA has trouble automating certain processes that are prone to “exceptions” and unstructured data, such as invoice processing.
The main difference between these two types of automation is the manner in which they handle structured and unstructured data. Traditional automation thrives with structured data but falters when it comes to unstructured data.
Conversely, cognitive automation can easily process structured data and many instances of unstructured data. Although it can’t guarantee straight-through processing for all data, it can learn to handle many “exceptions” (i.e., mismatched part numbers, unit of measure discrepancies, duplicate invoices, and other instances that generally require human intervention).
Here’s how traditional automation works:
Now, let’s take a look at cognitive automation:
With traditional automation, the process comes to a grinding halt once unstructured data is introduced, restricting your organization’s ability to unlock truly “touchless” processing. In a traditional automation environment, humans and machines work together to speed up processes. In a cognitive automation environment, humans and machines still work together, but machines handle more tasks at a faster clip. Human ingenuity is only required to handle the most confounding outliers.
Remember, automation is not a product in and of itself. Your organization’s ideal automation solution will be packaged into a software suite designed to help your business tackle one or multiple challenges.
While some high-end point solutions designed to handle one particular task or department may incorporate cognitive automation, it’s more likely that you will find it housed within a robust Enterprise Content Management solution, such as IntelliChief.
Therefore, you need to consider your budget, implementation timeframe, and processes before moving forward with a cognitive automation solution. Once you have collected this information, you can consult an expert to see whether or not this advanced technology is right for you.
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