What pain points cognitive automation solves for businesses 

Cognitive automation, also known as intelligent automation, applies artificial intelligence technologies such as machine learning and natural language processing to automate enterprise processes. This technology goes beyond robotic process automation (RPA), which uses a set of predefined rules to execute processes. 

RPA requires human intervention when it encounters a case with no response instructions. The system does not learn from data. On the other hand, cognitive automation learns the context from the data using patterns. It analyzes and predicts the following action. Over time, the system can eliminate the need for human intervention and can function independently, just like a human does. 

What makes cognitive automation powerful

We already have some process automation technologies, such as digital process automation and robotic process automation. But what does make cognitive automation powerful? It’s the ability to leverage data to its full potential.  

Data is the bedrock of cognitive automation. Unlike robotic process automation (RPA), cognitive automation leverages data for contextual learning and cognitive decision-making. The machine learning algorithms used in cognitive automation create patterns that could be undetectable for intuition-based human intelligence. 

Another dimension of how cognitive automation leverages data is tribal knowledge. Enterprises generally rely on the tribal knowledge of their employees that have been in the trade for a long time. Tribal knowledge is acquired over experience and remains in the brains of employees but is not recorded in any shareable format. For example, a work manual or a training video. Companies face two challenges with tribal knowledge. One, when the experienced employees leave, their tribal knowledge will also leave the organization. Two, the tribal knowledge might go outdated as the processes get updated. Because no one can check and validate the tribal knowledge, this might give inefficient results when used. 

Cognitive automation solves these two tribal knowledge problems and makes the best use of your enterprise data. When an automation system learns a new thing, it doesn’t forget it. The system stores the information in the knowledge repository. It uses the knowledge when it comes across the same case again. The system makes the information accessible to other stakeholders in the environment for better decision-making. Thus, cognitive automation has become a more efficient and powerful automation solution than other automation solutions. 

What pain points cognitive automation solves

Cognitive automation technology offers numerous benefits to organizations by addressing some critical pain points. By automating repetitive and mundane tasks, this automation technology can free up employees to focus on more strategic and creative work. Additionally, by leveraging machine learning and other AI technologies, cognitive automation can improve decision-making processes and provide insights that humans may be unable to discern independently. Here are some potential business case benefits.

Process efficiency gains

By automating tasks such as data entry, invoice processing, and customer service, cognitive automation can help organizations to streamline workflows and reduce the amount of time and effort required to complete routine tasks. This can help to improve overall efficiency and productivity, allowing employees to focus on more strategic and high-value activities. 

For example, the federal agency General Services Administration (GSA) built an automation system called Truman. By pre-populating information from vendor packages and conducting compliance checks with external databases, Truman helped the agency save over 5000 work hours. GSA stated that the automation system allowed their employees to focus on market research and customer engagement.  

Improved accuracy

Cognitive automation can reduce errors and improve accuracy by leveraging machine learning algorithms to identify patterns and anomalies in data. This helps ensure that decisions are based on accurate and reliable data, reducing the risk of costly errors and mistakes. 

Optimizing operating costs

By automating routine tasks, organizations can reduce the need for manual labor, which can lead to cost savings in terms of labor costs. Additionally, organizations can reduce the costs associated with errors, rework, and other inefficiencies by improving efficiency and accuracy. In his Forbes article, KPMG’s David Kirk estimates that companies can save 40 to 75 percent of costs using intelligent automation.

Enabling informed decision-making

A couple of decades ago, businesses made decisions based on human intuition. Later, they started relying on data from a variety of sources in different formats, structured and unstructured. So, they were not fully utilizing their data in their decision-making process. By leveraging machine learning algorithms, cognitive automation can provide insights and analysis that humans may be unable to discern independently. This can help organizations to make better decisions and identify opportunities for growth and innovation. An HBR article says, “To fully leverage the value contained in data, companies need to bring artificial intelligence (AI) into their workflows and, sometimes, get us humans out of the way. We need to evolve from data-driven to AI-driven workflows.” 

For example, a financial institution could use automation to analyze customer data and identify trends in spending habits, leading to the development of new financial products and services. 

Enhanced customer experience

Customer experience is the new battlefront. In a Gartner survey, 81% of marketers agreed their companies compete entirely based on customer experience. Cognitive automation can help organizations to provide faster and more efficient customer service, reducing wait times and improving overall satisfaction. Additionally, by leveraging machine learning and natural language processing, organizations can provide personalized and tailored customer experiences, improving engagement and loyalty. This can translate into new revenue opportunities through repeat business and positive word-of-mouth recommendations. For example, a retailer could use chatbots to handle customer inquiries and provide personalized recommendations based on customer preferences, increasing sales and revenue. 

By leveraging cognitive automation technologies, organizations can improve efficiency, accuracy, and decision-making processes, leading to cost savings and enhanced customer experiences. The business case for intelligent automation is strong, and organizations investing in these technologies will likely see significant productivity, profitability, and competitive advantage benefits. 

To learn more about cognitive automation, read our ebook Unleashing the Power of Cognitive Automation. 

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