Robotics and cognitive automation in HR Deloitte US

Deloitte Insights and our research centers deliver proprietary research designed to help organizations turn their aspirations into action. Louis; Tom Reuner of Horses for Sources; Alex Lyashok of WorkFusion; Alex Bentley, Mary-Beth Provencal, and Kevin Whittingham of Blue Prism; and Guy Kirkwood of UiPath. Our global Deloitte firm has a large and growing capability, with a range of thought leaders. For more information within the United States, please contact Peter Lowes at For more information within the UK and Europe, please contact John Middlemiss at Deloitte Insights and our research centers deliver proprietary research designed to help organizations turn their aspirations into action.

Brookings recognizes that the value it provides is in its absolute commitment to quality, independence, and impact. 2 min read – By acquiring Apptio Inc., IBM has empowered clients to unlock additional value through the seamless integration of Apptio and IBM. Watch the case study video to learn about automation and the future of work at Pearson. “Cognitive automation, however, unlocks many of these constraints by being able to more fully automate and integrate across an entire value chain, and in doing so broaden the value realization that can be achieved,” Matcher said.

Structured vs. unstructured

High employee turnovers, especially in shared services or offshore centers, make these costs even more critical. Compared to that, robots provide you with stable and scalable capacity 24x7x365 without vacation, sick leave or any other diversion. All this for roughly a ninth of the cost for onshore labor time or a third of the cost for offshore labor time.

You can think of RPA as “doing” tasks, while AI and ML encompass more of the “thinking” and “learning,” respectively. It trains algorithms using data so that the software can perform tasks in a quicker, more efficient way. RPA is best for straight through processing activities that follow a more deterministic logic. In contrast, cognitive automation excels at automating more complex and less rules-based tasks. One concern when weighing the pros and cons of RPA vs. cognitive automation is that more complex ecosystems may increase the likelihood that systems will behave unpredictably.

Impacts to the insurance operating model: Technology

This is a multi-disciplinary science that draws on research in adaptive robotics as well as cognitive science and artificial intelligence, and often exploits models based on biological cognition. The integration of these components to create a solution that powers business and technology transformation. Without sufficient scale, it may seem difficult for the benefits from R&CA to justify the effort and investment. Yet all too often, firms find themselves stuck in experimental mode—held back by resource and knowledge limitations, or overwhelmed by the complexity of technologies and processes. Avoid common pitfalls by setting the right expectations with appropriate preparation and diligence. Traditional RPA usually has challenges with scaling and can break down under certain circumstances, such as when processes change.

IA employs OCR (Optical Character Recognition) to gather and analyze data from multiple inputs in different formats and uses data analytics to compare vendor capabilities, reliability and compare pricing. Digital is here to stay, and in a few years, “being digital” will likely no longer be a competitive advantage for companies, but necessary for survival. With the dropping costs and rising adoption of R&CA, companies could easily be faced with applying these technologies everywhere, regardless of industry, function, or even company size. The integration of these three components creates a transformative solution that streamlines processes and simplifies workflows to ultimately improve the customer experience. It’s an AI-driven RPA solution that helps you automate more business and IT processes at scale with the ease and speed of traditional RPA. Faster processes and shorter customer wait times—that’s the brilliance of AI-powered automation.

It develops rules for processing paperwork and has a series of “if/then” decisionmaking that handles tasks based on those guidelines. When key conditions are satisfied, the tool can pay invoices, process claims, or complete financial transactions. Robotics & Cognitive Automation release this employee potential by taking over repetitive, rule-based work and mimicking human decisions in data-driven environments. Another viewpoint lies in thinking about how both approaches complement process improvement initiatives, said James Matcher, partner in the technology consulting practice at EY, a multinational professional services network. Process automation remains the foundational premise of both RPA and cognitive automation, by which tasks and processes executed by humans are now executed by digital workers. However, cognitive automation extends the functional boundaries of what is automated well beyond what is feasible through RPA alone.

This ensures a fast and positive return on investment that can go far beyond traditional automation solutions. The success of Robotics & Cognitive Automation depends on a dedicated sponsor and the engagement of business as well as IT. Those stakeholders can be brought together in a Center of Excellence, establishing in-house automation capabilities that provide sponsorship, process expertise as well as IT and operational support. While there are different models for a Center of Excellence, Robotics & Cognitive Automation should be considered an operational asset that is driven by business.

Down the road, these kinds of improvements could lead to autonomous operations that combine process intelligence and tribal knowledge with AI to improve over time, said Nagarajan Chakravarthy, chief digital officer at IOpex, a business solutions provider. He suggested CIOs start to think about how to break up their service delivery experience into the appropriate pieces to automate using existing technology. The automation footprint could scale up with improvements in cognitive automation components. A holistic view of automation capabilities can help organize and galvanize a team to avoid the common robotics and cognitive automation pitfalls and ultimately achieve scale.

Over the next 10 years, automation is expected to displace 22.7 million existing jobs and create 13.6 million new jobs in the US economy, resulting in a net job loss of 9.1 million jobs (or 7 percent of jobs in the United States). A significant portion of this impact would be felt across the insurance industry, given that 51 percent of financial jobs are projected to be transformed by automation by 20192. For example, substantial time is often spent reading, manipulating, or abstracting paper or digital documents for relevant information.

Implementing R&CA for efficiency

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• RPA effortlessly integrates into any enterprise architecture, negating the need for process or technology re-engineering, by introducing tireless virtual workers that add value to your organization.
• It no longer is sufficient to get a college degree and not take any further courses or certificate programs.
• The main challenge faced in such a function is ensuring the processing happens quickly because failing to do so can have many negative consequences.
• Cognitive automation requires more in-depth training and may need updating as the characteristics of the data set evolve.
• RE companies should consider two more factors, which look beyond financial considerations.
• Those stakeholders can be brought together in a Center of Excellence, establishing in-house automation capabilities that provide sponsorship, process expertise as well as IT and operational support.