We know of the impact that Robotic Process Automation (RPA) has made on multiple industries. However, RPA in itself is undergoing a transformation that is set to bring a wave of unprecedented change. This transformation is known as Intelligent Process Automation (IPA).
Intelligent Process Automation is the coming together of Artificial Intelligence with new age technologies such as Natural Language Processing, Machine Learning, Computer Vision, Robotic Process Automation, Cognitive Automation and more. IPA is set to become the core of next generation operating models. Mckinsey has revealed that companies across industries that are still in experimental stages with IPA have already experienced automation of 50-70% of tasks, with ROI growth in triple-digit percentages.
We have known RPA to robotize repetitive tasks. IPA, in addition, throws in fundamental process redesign into RPA and machine learning; and improves upon the robotic activities. The result is simple and effective – improved customer journeys, which is a byproduct of fewer operational risks, better response time, simplified interactions and speedy processes. The deep learning, cognitive technology of IPA gives it decision-making capabilities that makes the difference in the long run.
The Future of IPA
According to Cognilytica, an analyst firm that covers the market on artificial intelligence, machine learning, and cognitive technologies, the total market for IPA solutions will grow to over $8.3 billion by the end of 2023. That said, the question on most minds is whether IPA has reached its pinnacle yet, and does this ring the death knell for RPA.
The answer to both these questions is a “NO’.
While it is true that with IPA getting smarter it is likely to supersede RPA, it is also true that such levels of superior cognitive technology is yet to materialize.
Cognilytica, based on their research and experience in the cognitive technology, have created a scale that measures the capabilities of IPA systems, and have set up four yardsticks for assessment. At Level 0 stand RPA systems that have not been embedded with AI; Level 1 systems have language and context awareness; Level 2 are powered with intelligent process awareness; and finally, Level 3 – the most powerful among them all – offer autonomous process automation. Cognilytica reveals that reaching Level 3 is still a distant dream for RPA vendors, and only a few are at the fringes of Level 2.
However, this development does not mean that RPA itself is on its way out. What is important to understand is that with passing time, cognitive advancement will naturally get embedded into automated processes. RPA and AI are meant to go hand-in-hand and are not to be seen as competitive technologies; rather as enhancements.
Real-life application of IPA
Case 1:Hollard, a leading insurance company in South Africa implemented iRPA (Intelligent Robotic Process Automation) with the goal to understand and solve complex customer-centric solution objectives. The company added virtual assistants/robots into their end-to-end processes to streamline their operations. The robots were particularly needed to process the high volume of email received from the broker base and other parties, ensuring that they are compliant with the regulatory and statutory provisions at all times. The insurance firm has, over a period of under two years, saved approximately 2000 hours per month in processing time, and reduced cost per transaction by 91% and mean time to execute by 600%, among multiple other benefits. Read the whole iRPA case study here.
Case 2: Kiva Systems, which was recently acquired by Amazon for about $800 million, developed a “mobile-robotic fulfillment system” to automate retail distribution centers for companies such as Crate & Barrel and Walgreens. The robots go back and forth the distribution center, without collision, and transport shelving units loaded with products to workers who are preparing customer orders for shipment. The bots have helped improve worker productivity by a factor of two, compared with its next-most automated facility. After the Amazon acquisition, over 130,000 of these goods-to-worker bots have been put to work in Amazon warehouses and Dcs.
Case 3: Credit Suisse, a Swiss multinational investment bank and financial services company, uses the IPA technology to analyze millions of data points on thousands of companies and automatically write English research reports that assess company expectations, upside and risk. These reports help analysts, bankers and investors make long-term investment decisions. According to Credit Suisse, in comparison with analyst-written reports, the bots have tripled the volume of reports produced, while improving their quality and consistency.
The Beginning of Intelligent Automation
The future of automation is suggestive of cognitive systems that will self-learn and handle processes better, improving the overall workflow, making necessary modifications and optimizing processes in a world where there will be more semi-structured or unstructured data. With RPA’s transformation into IPA comes a smarter system that can handle a wide range of complex enterprise activities unlike ever before. From just simplistic automation of rote jobs and the focus on improving productivity and cutting costs, the emphasis will move to intelligent automation and insightful decision-making that will truly intensify customer experience.
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