The emergence of big data, machine learning solutions and artificial intelligent (AI) has altered how a business operates and the competitive landscape in a wide range of industries. Their use cases in intelligent automation introduce the adaptive solutions to ever-evolving supply chain situations, customer demands, operational efficiency, all of which play crucial parts in helping business’ growth. This article will walk you through how intelligent process automation impacts business process management and their common use cases, allowing for a step forward in process efficiency.
In many people's minds, automation is considered as AI/ machine learning technologies because AI/machine learning and the robotic process automation both are meant to simplify processes and shorten cycle times. However, once the robotic automation has completed a task, it stops thinking about the task at hand and moves on to the next one.
On the other hand, AI/ machine learning-driven automation can be termed as "intelligent process automation". This refers to the practice of combining the efficiency from automatic mechanism with the power of AI like deep learning and machine learning. In intelligent process automation, the system can be enabled to conduct logic-based, judgment-based, and decision-making activities. When it comes to customer service via chatbot, for example, the smart system learns from the past experience to predict and deliver informed answers, relevant recommendations, all while preserving a friendly, conversational tone. This is how to differentiate intelligent process automation from robotic and rules-based automation.
Better customer experience and operational efficiency are among the primary values that organizations look for as considering investing in any technological solutions for their business. This necessitates leveraging intelligent automation to innovate their current process as this technology can address following inefficiencies in their business workflows.
With about 80% of business data being unstructured, intelligent process automation use cases leverage OCR, NLP, machine learning, and deep learning to effectively glean information from all types of data, making the most out of the business’ resources.
A document's creation, revision, review, and approval are all steps in a company's workflow, which can involve several individuals. Contracts, requests for yearly leave, and cost reports are only few examples. It may not be a big deal in a small company if a document is processed and delivered to the next person in line, and so on. However, in order to scale up, organizations need to automate documentation workflow process to save employees’ time for business-critical tasks and productivity.
Robotic process automation can eliminate the need for human for repetitive and manual tasks like data entry and reconciliation in the billing process. However, it gets more challenging when trying to process invoices in various formats used by different suppliers. This is where intelligent process automation comes in; it uses NLP and machine learning solutions to interpret invoices, extract the relevant information, and format it in a standardized way before sending it back to the ongoing system for further processing.
In today’s competitive market, no company can afford to disregard customer experience and business process optimization. Organizations can satisfy their customers by using the technologies to improve their products and services with better quality and faster service delivery, thus win customer trust and loyalty in their business. Moreover, in today’s competitive markets, consumers have higher and everchanging expectations on the products and services, such as quick responses and resolutions to their inquiries and complaints. Due to human limitations, meeting these needs of such a large customer base can be difficult without the use of automated and smart solutions. With automated customer support solutions powered by AI/machine learning, businesses can overcome such constraints by reducing the response process for customer inquiries to real time, enhancing customer experience and reducing their churn rate.
The AI-driven automation helps to streamline human resources process, including recruitment, hiring, onboarding, offer management, benefits management, and payroll processing. For instance, the HR department can save time and cost with the convenient access to the information they need about the applicants. Intelligent process automation not only eliminates duplicate applications, but it also assists HR in finding the best candidates for open positions.
Time is a powerful factor in measuring service interaction quality, whether with customers, suppliers or any other stakeholders. Assisted by AI/ machine learning solutions, businesses can speed up email handling by having their emails with attachments automatically sent to an intelligent automation system whenever they get one. By using OCR and NLP, intelligent process automation can extract the attached file and "read" it. Additionally, it may glean useful unstructured data, such as invoice numbers, payment conditions, contractual language, etc. Once the data are normalized, they are sent to a subsequent system in the workflow, such as a CRM or ERP.
The potential of intelligent process automation holds the promise of enhanced organizational and workflow agility, flexibility, and efficiency. Organizations can certainly maximize their investment with this technology with enhanced business operation and more profitable opportunities returned.
Schedule a meeting with Adnovum experts today to find out more about the intelligent automation solutions that can be customized for your business.