Two New Technologies Pushing the Boundaries of Business Processes

By Ryan Raiker, Senior Product Marketing Manager at ABBYY Timeline


Ryan Raiker

3 years ago | 4 min read

Today’s advancements in technology offer companies limitless opportunities to improve their processes and operations, turn data insights into engaging customer experiences, and accelerate business outcomes. No doubt, digital transformation is both front and center in these latest efforts by companies to modernize and improve workflows and business processes as well as increase productivity and gain competitive advantage.

Content is king. Isn’t it?

It is also true that, in today’s business environment, data and content are enablers of the digital platforms that generate insights to drive value, efficiency and customer experience. Which is why modern business organizations must pay attention to two interrelated technologies that are stretching the possibilities of digital transformation by augmenting business processes: Content and Process Intelligence (IQ).

Content, especially unstructured content, is the pivot around which business activities revolve. Every business organization receives information through a variety of channels such as mobile devices, email, scanners, and paper. The information contained in such documents is needed by businesses to initiate actions for improving customer service, increasing engagement, enhancing operations and identifying revenue opportunities.

In the past, organizations tackled this problem by deploying capture technology to digitize paper documents, classify, and extract the data contained in them. Today, as systems and business processes become more complex, organizations are turning to robotic process automation (RPA) to optimize operational costs, streamline processes and get rid of repetitive and manual tasks. Unlike manually driven processes, RPA robots (or digital workers) utilize the user interface to capture data and manipulate applications the way humans do.

Why do robots need cognitive skills?

Despite the progress with RPA, a significant technological challenge remains: How can businesses extract and understand the data trapped in content and translate it into actionable insights? This is where Content IQ comes in. Content IQ is a new class of technologies that enables digital workers to understand and create meaning from enterprise content. By combining OCR, machine learning and other AI-enabling technologies, it transforms unstructured content to structured information, opening up a wide range of business processes for intelligent analysis.

What this does is that it equips the RPA digital workforce with advanced cognitive skills, enabling them to perform human-like tasks like reading a document, routing a document, classifying a document or extracting data. This way, technology not only helps digital workers to ‘process’ but also to ‘understand’ content and solve specific business problems as they automatically process both structured and unstructured content.

Streamline and manage workflow with Process Intelligence

While Content IQ technology augments and accelerates process automation, Process Intelligence ensures that your business process is not a black box that keeps you second-guessing your business outcome. With digital transformation becoming a business imperative for all organizations, companies are eager to gain transparency into their processes and operations to see what’s happening and know what action is needed to maintain flow.

Simply put, Process Intelligence technology helps companies analyze every process within their business to identify potential bottlenecks, quantify the impact of inefficient or broken process variations, determine their root causes and how to fix them. As the technology monitors and predicts ongoing performance in real-time, it alerts key staff of any protocol deviations allowing them to understand exactly how their processes execute.

Process Intelligence also helps create a virtual model of business operations and processes that can be leveraged to develop new opportunities and even plan ahead, with the ability to forecast and predict future outcomes. This is typically being referred to as the Process Digital Twin.

It is significant that this technology platform utilizes next-generation intelligent process mining, specialized analytics, automated process monitoring, and artificial intelligence to deliver sustainable, enterprise-wide process excellence. Business operations generate vast quantities of data daily. When properly ingested, merged, and analyzed, this wealth of data can be used to discover patterns and insights that illuminate paths to better customer experiences and new operational efficiencies. By applying advanced artificial intelligence and machine learning, Process Intelligence not only unlocks business value from this data, but it also enables businesses to predict and forecast processes into the future and optimize their operations through real-time monitoring.

Add to that the fact that Process Intelligence uses a fully managed cloud platform approach — which brings with it both flexibility and efficiency — it is not difficult to see why the technology holds real promise for every business organization. The cloud platform approach helps remove operational overhead by handling performance, scalability, availability, security, and compliance needs automatically. Connectors and ETL in the cloud help connect tools and data to existing systems. This both protects and complements existing investments, enabling IT departments to work with tools they already use while expanding on the analysis that others lack.

About the author

Ryan Raiker is an accomplished business consultant with experience working with small and medium enterprises as well as state and local governments. He joined ABBYY in 2019 following its acquisition of TimelinePI, where Ryan managed the company’s Marketing. At ABBYY, Ryan is focused on product marketing, brand management and product development for the ABBYY Timeline product. Ryan studied Business Analytics and Operations Management and later earned his MBA from Widener University in Chester, Pennsylvania.

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