Driving Business Transformation with Cognitive Automation

We live in an era of digital acceleration, wherein our life is deeply embedded into digital infrastructure and smart technologies. The digital penetration is so deep that in a single day we produce around 3.5 quintillion bytes of data. That’s a striking figure! The rate at which data is produced clearly indicates the rising demand for a digital economy. Businesses around the world are looking for multi-dimensional cognitive frameworks to create a digitally-connected and intelligently driven business ecosystem.

When technology has become a defining factor, having a breakthrough business idea is not enough. Being agile, customer-centric, and synergizing disruptive business models, can only take you so far. You need a smart engine to drive you forward, propel you in the right direction, reduce cost and optimize critical processes, mull trillions of data in real time, and make smart decisions in split seconds. Making cognitive process automation is the best logical option, the next big leap toward business transformation.

Fast - Forward - Futuristic

Digital fluency is becoming a must to survive. Organizations are on a committed lap to creating an autonomous digital enterprise (ADE), trying to put competitors in the slipstream. Automation has become a necessity, not a luxury, and embedding AI into RPA will make it a super-powerful option.

When there is a huge volume of data flow from multiple touchpoints, you need an agile system to sagaciously verify, process, map, and manage the data sets. Process automation was introduced to manage mundane repetitive tasks, now it has evolved as a critical enabler in optimizing cost across business verticals.

The Never Ending Stream of Technology Outburst

The digital saga has clearly given us a glimpse of what the future beholds. The increasing digital demand calls forth the dire necessity to combine smart technologies and create contextualized intelligence in order to meet day-to-day critical requirements. When heading towards an artificial general intelligence-dominated business ecosystem, tech-centered organizations are destined to get the best out of this transition. Robotic process automation plays a critical role in this transition, often acting as a digital catalyst in achieving significant operation efficiency.

Cognitive Automation: A Centerpiece in Digital Transformation

Automation is a major piece in solving the digitalization puzzle, be it shifting work roles or creating business impact.

Robotic process automation has helped businesses improve process efficiency, reduce operation costs, and impact quality standards across the organization. In the early stages. The prime suspects were monotonous and labor-intensive tasks. By integrating intelligence into RPA, businesses are taking it to the next big league, enabling an ecosystem of end-to-end digital transformation at scale.

Cognitive automation uses modern technologies such as contextual analysis, data mining, optical character recognition, opinion mining, and pattern recognition to make intuitive and informed judgments. With intelligent automation, businesses will be able to mine through huge streams of structured and unstructured data, plotting patterns, mapping datasets, and finding similarities pertaining to specific business processes. They then move on to converting these signals into actionable insights, enabling the system to emulate human intelligence.

What Makes Cognitive Automation So Special

When you mix intelligence with technology it opens up a realm of opportunities for businesses to leverage the benefits.

• Optimize workflows and automate more than 70% of repetitive tasks
• Increase scalability and process optimization
• Keep a digital trail on tasks, processes, and workflows
• Scalable beyond headcount. A single bot equals 6 FTEs
• Early detection and recommendation on operational challenges
• Analyze data and find opportunities for continuous process improvements
• Minimal supervision zero bias

Cognitive Automation Use Cases

Prescriptive Maintenance Using Cognitive Systems

Real-time prescriptive maintenance has been a pipe dream for factory managers. Any unplanned breakdowns in the manufacturing sector can lead to cumbersome experiences, followed by a downstream of compliance issues and quality compromises. With technology, factories and product lines are becoming more instrumental and interconnected. Manufacturing units must enable cognitive capability from the shop-floor level, bringing together sensor data, information analytics, data warehousing, and dynamic case management to improve collaboration between manufacturing units, predict/prevent mechanical breakdown, prevent incident events, and so on.

Combining cognitive computing and the industrial Internet of Things (IIoT) can significantly influence global performance, and quality of production, as well as identify root causes and offer optimized maintenance plans. By leveraging cognitive technologies businesses will be able to continuously monitor the overall equipment effectiveness (OEE) of plant machinery and use the data insights to predict the statistical probability of equipment failures, process failures, and line slowdowns.

Bringing an Edge to Trade Finance Using Intelligent Automation

When increasing international trade, it becomes enormously important to bring in a machine-first approach to optimize financial operations across business verticals to ensure seamless and error-free transactions on a global scale. Considering the huge volume of customer requests and inquiries generated on a daily basis, it's important to have a smart engine to process the data intelligently and make decisions in split seconds. Prescriptive analytics is one such technique widely used in the financial sector to understand payment patterns, overdue payments, credit risks, etc, and spontaneously generate queues.

Trade finance is followed by an intensive paper-driven process, considering the surge in digital payments and the complex nature of bilateral transactions. The end-to-end fulfillment of each and every trade finance case is very time-consuming and tedious. Delays in payment processing can have a negative influence on customers. The need for an agile smart engine to process each and every trade finance case with speed and accuracy seems critical.

Cognitive Automation: a Soothing Remedy in Healthcare

The modern healthcare system is fueled by data to make smart decisions and deliver decisive patient care. Digitizing patient information and embedding it with a cognitive system will help critical healthcare professionals to diagnose the patient's conditions and create a personalized treatment/ healthcare plan without causing any delay.

While maintaining a repository of electronic health records helps ensure compliance, prevent loss of data, and continuous monitoring to keep tabs on patient status, bringing in intelligence systems can free up your healthcare staff to make quick data-driven decisions. Giving enough wiggle room for healthcare employees to prioritize patient care over manual paperwork.

Emerging regulatory frameworks in the healthcare sector enable technology to read through patient medical history, get information on prescribed medications, and quickly run medical tests to find the right prognosis with a high success ratio. When done manually these processes can cause delays, spike human errors, high backlogs, and cost creeps.

Cut Through Clutter & Deliver Safe-Personalized Experience @35000 ft

With technology advancements, more instruments, more checklists, more speed, more protocols, and more stress, are introduced into the cockpit. Too much going in a small pod. It becomes a necessity to introduce automation, by keeping humans in the loop.

Aviation is one pioneering sector that embraced automation from its initial stages. For decades the aviation industry has been using automation to improve operational efficiency. With cognitive technologies, airlines are redefining safety measures and rigorously trying to push boundaries to deliver unique and personalized customer experiences.

Creating a neural network of integrated systems will enhance situational awareness, enabling an aircraft to quickly respond to critical situations, and plot a safe path with the data available. Considering the flight patterns, and co-relating them with the flight parameters and data, the cognitive system can predict near occurrences (heading towards a stall point, decreased rate of climb, collision path, etc).

The cut-throat competition in the airline industry bids for contextualized customer experience and continuous engagement. An unplanned flight cancellation can cause widespread commotion among customers. Using cognitive technologies the airline can initiate a customized mass messaging with alternate travel options, process refunds, and help the customer find an alternative flight/ rebooking, etc. Making sure a course of action is initiated to support customer concerns.

While cruising at 35000 ft cognitive technologies provide tailwinds to flight operations, whereas AI is plotting plans to make you a frequent flier for the airline.

A Nutshell View

Technology transformation with artificial intelligence (AI) will continue to automate discrete functionalities. Cognitive automation has evolved into an advanced system that learns at scale, reads through different patterns and signals to reason with, mimics human intelligence and interactions. Businesses that adopted cognitive automation were able to achieve market resilience and develop cutting-edge business models.