Robotic process automation (RPA) is a transformative approach to automating business processes to a level that once seemed unattainable by many businesses. "In the past, high cost, excessive implementation time and lack of IT resources were all barriers to RPA implementation for a majority of businesses," says Gerrie Terblanche, CEO of Deltalink Consulting.
Today, software robots can be quickly designed and deployed to automate mundane, repetitive, structured tasks that staff would otherwise be responsible for, such as copying and pasting data between multiple applications. The benefit to business lies in freeing up valuable human resources to perform other, more business-critical, tasks.
As adoption of robotic process automation increases, enterprises are looking for ways to expand the use of these digital workforce robots. A catalyst for rapid RPA adoption is a robot's ability to automate content-centric processes involving various types of data, such as images, documents, text and e-mail. However, the challenge lies in transforming this unstructured content into meaningful, structured information that can be used and integrated into a process.
Terblanche says: "This challenge is being successfully addressed with the use of content intelligence technologies and solutions that are able to turn unstructured content into structured, actionable information. The adoption of content intelligence solutions is helping enterprises digitise their operations, dramatically improve the customer experience, greatly reduce operating costs and increase competitiveness.
"When organisations combine robotic process automation with content intelligence, they are able to automate a wider range of processes and deliver greater business value," he continues.
Content intelligence benefits organisations at all levels of robotic process automation, starting with the most basic automation robots through to designing robots that automate tasks involving more intuition, judgment and problem-solving.
Content intelligence technologies and solutions are complementary to all three digital classes of RPA, according to Terblanche. "CI applies optical character recognition (OCR), machine learning, natural language processing (NLP), and text analytics technologies to identify and classify content and extract data, while continuously learning from human input."
CI can be utilised in many ways with robots, whether the robotic processes are supervised operations initiated by a front-office worker, or automated back-office tasks by an unattended robot. Content intelligence can be the start of any process where content is digitised, documents are classified, data is extracted, and validation is performed. The robot then follows by taking action based on the structured information the CI solution delivers.
Similarly, content intelligence can be inserted as a step in a robotic process to provide deeper insight. With this option, a robot calls one or more of the CI capabilities, such as classification and/or data extraction, and provides results that enable the robot to continue with the process. Staff can also participate in the validation and review of data that the CI solutions deliver to the robot.
There are three levels of automation that impact on business value, listed below:
* Basic RPA: Robots are used to extract and interpret existing applications for the purpose of automating rules-driven transactions.
* Enhanced RPA: Robots are able to understand unstructured content and apply it to process automation.
* Cognitive automation: Robots automate tasks involving intuition, judgment or problem solving; mimic human intelligence and judgment.
Organisations are increasingly identifying business-critical processes that can benefit from the deployment of RPA and the automation of content involving unstructured and structured data. By combining RPA and CI, organisations are able to achieve end-to-end automation for content-centric processes, increase the digital workforce footprint, and support the organisation's digital transformation initiative.
Finance and accounting, logistics, financial services and insurance are just some of the industries where a robot excels at leveraging content intelligence to automate a wide array of content-centric processes.
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