The Balanced & Hyper-connected Enterprise, Powered by Intelligent Automation
In an increasingly connected world, what will the enterprise and workforce of tomorrow look like? How will work be performed? In the early stages of their digital transformations, organizations are beginning to leverage automation technologies like robotic process automation (RPA) to replace routine and repetitive tasks. The value proposition inherent in technologies like RPA is extended when organizations take a platform based approach to automation, which means integrating complementary capabilities to realize greater gains in efficiency, productivity and customer satisfaction as driven by automation.
The Untapped Opportunity of Automation
The beginning of any transformation exercise is in defining operations/processes that warrant transformation. Over the last several decades, organizations have resultantly fine-tuned their processes to make them more efficient.
Yet, on its own, optimization won’t be enough for tomorrow’s workforce. That’s because most processes today – even optimized ones – remain largely document-driven and manual. To be more agile and compete more effectively in fast-paced environments, organizations will have to close the gap between manual and automated work.
As it stands currently, that gap is significant. The Forbes survey found that while 60 percent of C-suite executives say they want their processes to be automated or mostly automated, only 38 percent have achieved that benchmark.
These findings indicate there’s a significant – and so far untapped – opportunity to realize gains in productivity, efficiency and quality. This is where adopting a platform-based approach to automation can particularly support a digital transformation initiative. Looking at automation technologies separately can result in problems, such as individual technologies being pushed beyond their respective capabilities. A platform-based approach to automation means leveraging smart capabilities that work together to digitize end-to-end business areas and operations.
According to the Forbes Insights survey, more than three-quarters of respondents said 60 percent of their processes could be automated. In addition, almost one in five said 80 percent of their process work could be automated.
The Ideal Mix of Automation and Manual Work
The goal of this next phase of automation is to integrate automation and people, thus creating a more agile digital workforce that can ‘work like tomorrow’ today.
Even though processes are optimized, they require humans to manually complete the steps. As a result, employees find themselves stuck in roles as “data gatherers.” To deliver higher value to the business, employees instead need to become “data users.”
With intelligent automation, companies shift this dynamic. Bundling capabilities such as cognitive capture, process orchestration, robotic process automation, mobile and advanced analytics, this next-generation technology not only automates steps in a process, but also improves upon them.
The smarter software is, the more it can be used for complex tasks and decision-making. With machine-learning, intelligent automation moves beyond simple capture. It is able to ingest and make sense of large quantities of unstructured text such as emails, images and even voice calls. And since it’s capable of identifying sentiment and tone and learning from past interactions, it can be “taught” to make decisions. Employees have less of a need to intervene, leaving them free to focus on work that delivers strategic benefits, such as higher customer satisfaction and stronger profit margins. In this environment, robots and humans work together as collaborators.
“We shouldn’t call them [cognitive AI agents] robots. We should call them co-bots—because what they’re really doing is collaborating with humans. They cannot do anything without human input and participation,” says Max Cheprasov, chief automation officer at Dentsu Aegis.
Smart businesses don’t need to wait for the future workforce. With intelligent automation, they can work like tomorrow – today.
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