RPA to CPA: A Journey of Robotic Automation
Published by : Industrial Automation
RPA already enables benefits in the global industrial automation sector and will soon arrive at a plateau, as most decisions in the companies are based on context and with an extra level of intuitiveness and sophistication.
Considering the current market trend, automation witnesses a wide growth in demand from the various companies to expand human potential, along with high productivity, improve accuracy, reduce costs, and increase scalability. In the commercialized market, the RPA based automation process is executed for the computerized repeatable tasks and further identifies new opportunities to expand its capabilities.
Taking a leap from Robotic Process Automation (RPA) to Cognitive Process Automation (CPA)
Considering the benefits, RPA enables macro-level task automation such as repetitive tasks with fixed employee count, while CPA based out on automated technologies such as natural language processing, speech recognition, and machine learning. The latter can automate tasks that are non-standard and involve understanding meaningful information by drawing inferences from reams of data.
Leading the growth maturity curve of automation development, there is wide scope for the demand for CPA. With RPA, the instrumental process assists in addressing without undergoing a complete overhaul, achieving quick and short-term wins. With CPA, the execution of machines enables various abilities such as human-based context, human interaction, decision making, and problem rectification ability. This expected to lead the growth of CPA in the industries to assist companies to formulate cumbersome and multi-task operational processes at more strategic and permanent cost and customer experience benefits. The use of CPA can also benefit the possibility of real-time insights-driven automation, with no human assistance required.
Importance to follow responsible cognitive automation strategy
Effective governance of CPA requires extended collaboration between those governing and people constructing these structures. There has been an increasing name for transparency in automated and robot systems, which stems from worries over the trust, fault identification, and validation. One of the main issues with complex CPA systems is the problem of figuring out responsibility for failures. Narrowing this obligation hole is a crucial legal-ethical issue that wishes to be addressed.
Apart from safety, transparency, complexity, and regulatory factors, at the commercial enterprise level, there are a few operational factors that ought to be considered as a part of an accountable cognitive automation strategy. These include commercial enterprise processes, change management, reengineering, measuring and tracking hazards and compliance, and technology.