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RPA and Cognitive Automation: Deciding the Best Automation Technology

Meenu EG

Business enterprises should invest their time and money in understanding technologies to ensure optimal automation methods

Businesses across the globe are going through rapid digital transformation and automation. Cutting-edge technologies like AI, robotics, and IoT are enabling this transformation by enhancing business efficiency and agility. Robotic Process Automation (RPA) and Cognitive Automation are two components of redefining and automating industry-wide business operations. According to a Statista report, the expenditure on Cognitive Robotic Process Automation is expected to reach about 3.62 billion USD globally at a CAGR of 60.9% from 2017 to 2026.

What are RPA and Cognitive Automation?

Robotic Process Automation (RPA) enables the automation of mundane and repetitive tasks in an organization with maximum accuracy and minimum labour. Implementing RPA reduces the workload on human workers thus allowing them to focus on high-priority tasks that need high-level skills. All business processes consist of boring routine tasks like data processing, calculations, answering queries, etc. RPA is process-oriented and takes up rule-based tasks that do not demand advanced analytics or rational thinking.

RPA leverages basic technologies like workflow automation, macro scripts, screen mapping, and others that require minimal or no coding. RPA demands human intervention in case of exceptions since they can only work with structured and trained data sets.

If RPA represents the initial part of automation, cognitive automation acts as the supporting pillar for RPA to enhance its capabilities using advanced technologies. Cognitive automation uses disruptive technologies like AI, machine learning, NLP, and advanced data analytics to automate business processes. Unlike RPA, cognitive automation can build its own rules and establish correlations between data sets to provide business insights. Cognitive automation augments human intelligence to simplify complex business operations and its intelligent decision-making abilities ensure better performance analysis.

While RPA demands less cost and short-term benefits, adopting cognitive automation can be a bit expensive and has a long-term impact. Cognitive automation enables RPA to continuously learn and interpret data without compromising on accuracy and quality. For example in customer interactions, RPA can answer similar, repetitive questions or the ones that the system is already trained to answer. But, RPA with cognitive automation will enhance this process by enabling human-like interaction, engaging conversations, finding new answers, and incorporating emotional intelligence into the interaction.

Which is the Right Technology for your Business?

Choosing the right one might not be the right strategy. Since these two technologies are interrelated, it is better to understand their uses and then adapt accordingly. Acquiring basic RPA models can be beneficial for the short-term purpose of automating basic tasks. Although if an enterprise needs advanced benefits then it might be effective to combine RPA with cognitive automation. Cognitive automation will enable beating many challenges posed by the RPA systems like limited application and compromise in the quality of results.

The incorporation of cognitive automation into RPA systems will increase efficiency and business intelligence. A company should identify the right amount of RPA and cognitive automation considering the business goals and demands. Implementing cognitive automation can take time since it requires learning and simulating human behavior and intelligence and hence, might not provide an immediate ROI like RPA. The best possible way would be working with a digital software expert and understanding the journey of automation and optimal mix of these technologies. A company needs to invest in quality research to gain better knowledge about automating end-to-end business operations and this will ensure better utilization of finances and technologies.

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