A perceptive forecast made by an analyst recently is that by 2018, 20% of business content will be authored by machines1 . In the Enterprise Content Management (ECM) space, this spells relief. The volume and velocity of business data has reached chaotic proportions; fortunately, cognitive technologies are shining a light on the solution.
The solution comes with its fair share of questions for content-intensive industries like banking, manufacturing and retail: How is content (types, sources, utility, and half-life) evolving? What are the alternative approaches to content automation? What are the distinctions between these approaches? What is the technological implication in terms of change management and investments? And what do we need to do today so that we can seamlessly integrate as-yet-unknown processes and technologies in the future?
The flavours of automation
There are three fundamental types of automation that are of interest to content-centric businesses (see Figure 1 for details):
Robotic Process Automation (RPA)
Think of this as the automation of clerical processes that display rigid patterns and limited boundary conditions such as quote-to-cash and loan processing. For these processes, RPA delivers substantial improvement in employee productivity, impacts cost and shows a dramatic reduction in error rates. This improves customer satisfaction and eliminates the time and cost associated with rework.
Imagine analytics as a catalyst for intelligence when added to RPA. Analytics can discern patterns in structured and unstructured content (emails, chat records, voice files, images and video). Analytics can uncover fraud like fake medical claims, deliver fresh insights to aid decision-making, and provide visibility into content being consumed and its ROI. These influence future investments in the type of content to store and analyze.
Cognitive Process Automation (CPA)
Visualize a system based on a loose set of instructions that is in a constant state of evolution propelled by Machine Learning. The system dynamically adjusts rules to curate and generate complex content. As examples, this would include the automatic creation of financial reporting, legal submissions and regulatory compliance. The key advance here is the acceleration of complex content creation and the ability of the system to answer complex questions (e.g., which customer contract is the best?).