It’s no surprise that Cognitive Business Automation has commanded the spotlight as of late. After all, it has single-handedly become the greatest driving factor of innovation for business in history—primarily due to the influx, nature and need of process-driven applications. But what does it really mean?
Setting aside the over-used technical jargon that seems to get thrown into the mix, the reality is that process-driven applications were and continue to be the cornerstone of the business-to-customer relationship. However, as the human race continues to evolve through data and technology, companies must learn how to leverage customer data as a whole and embrace new ways of thinking to make every aspect of their product/service unique for each customer.
As such, Cognitive Business Automation is the field that enables us to connect customer and services through data to deliver a far better and more personalized customer experience for every individual, while maintaining optimal operational efficiency.
It’s a revolutionary step forward as it pertains to business process that has pulled the collective world squarely into the new era of Artificial Intelligence and Robotic Process Automation. Process-driven applications empowered by AI and supported by RPA lead to further automation, increasing operational efficiency whether through decision automation, unstructured data processing, or task automation, and will enable organizations to provide a more personalized and engaging customer experience.
But what does all of this AI and business process mean in the long term for human interaction? Do machines become the rulers of the world? No . . . in fact, we are still very much needed. In a global survey of 300 executives, Forbes Insights uncovered a fascinating indicator of the state of automation: While respondents are happy with their process automation initiatives so far, they acknowledge that manual intervention and human orchestration are still the rule rather than the exception.
A brief lesson in history . . . in order to look to the future.
Process-driven applications have been at the heart of Digital Transformation initiatives for many organizations for well over a decade. For instance, some of the simplest use cases of process-driven applications could be pricing an insurance claim, applying for a mortgage account, on-boarding a new customer, or fulfilling a retail order. In all of these cases, the process is largely the same: a collection of structured activities triggered by other system events or user actions (Process Inputs), governed by business rules (Decisions), set by a system or a user (Process Controls), and enabled through data services and system integration points (Process Enablers) to produce a specific Output such as a business goal.
Traditionally, process engineers and solution architects relied heavily on Business Process Management (BPM) methods and tools to optimize these process-driven applications; these methods and tools helped organizations methodically identify and implement improvement opportunities to cut operational costs, reduce processing time, increase revenue and enhance the customer experience.
However, traditional BPM systems fell short of supporting the innovation needed to address modern world complexities, the need for a more personalized customer experience, and the speed at which organizations wanted to achieve that innovation. These systems heavily relied on humans to perform cognitive tasks, leading to increased human errors and operational costs.
Which brings us to the bright and very exciting future. Now, with next generation process-driven applications, organizations have begun to incorporate AI and RPA to gain greater operational efficiency and create more engaging user experiences.
Artificial Intelligence, for example, is being leveraged to enrich business processes in a multitude of ways. For instance, Decision Automation through Machine Learning is being used to spot patterns or pattern deviations that can create insight that a business process can leverage to automate decisions handled by humans in the past (e.g. assessing the risk of a new mortgage application, automating pended claims adjudication, detecting fraudulent transactions).
It’s also being used to create more well-rounded customer experiences through text analysis and natural language processing to extrapolate process action from natural language such as email, text messages, chatbots, etc. And it must be able to instantly provide the customer with a more personalized and engaging experience. As per the previously mentioned examples, companies can now enable such things as adding a dependant under an insurance policy through a chatbot or a personal voice assistant, analyze customer sentiment or frustration by translating an email and proactively reaching out, and so much more—again, all addressing the greater picture of personalization.
Then of course there is the Robotic Process Automation aspect of the equation—one that presents organizations with an entirely new set of opportunities.
For example, organizations can leverage RPA to automate lengthy and time-consuming repetitive user tasks. The prime use case for that is customer service groups within any organization. Customer service agents usually need to repeat the same task for different customers. When these tasks are automated with bots, it can dramatically reduce processing time and operational costs.
But far beyond that, there is also the ability to leverage RPA to perform non-invasive integrations. Most mission-critical enterprise systems are still legacy systems that are inaccessible outside a user-interface or command line and require lengthy modernization initiatives to become accessible. RPA enables organizations to take a non-invasive approach by mimicking human steps and eliminating the need to modernize large monolithic systems.
In all, Cognitive Business Automation is changing the world as we know it. As process-driven applications empowered by AI insights, Natural Language Processing and Robotic Process Automation take hold. The results are already countless. From expanded automation possibilities within any business process (whether through decision automation, unstructured data processing, or task/system automation) to reduced operational costs, cycle time and errors due to minimal human intervention, organizations of all types are saving money while becoming more efficient.
And though traditionally business process management tools have in some cases negatively impacted the end-user/consumer experience, cognitive business automation has vastly reversed that old-school notion. In fact, these same technologies that are saving companies time and money are also making the customer experience better. From enhanced customer experience due to the prompt and personalized responses, to newly created services and products all thanks to the intersection of workflow automation, artificial intelligence, and robotic process automation—the possibilities are seemingly endless.
The only question now becomes one of possibilities and imagination.