How does the digital workforce effectively progress across industry?
Unlike bots or software robots which are task-centric, a digital workforce is built to augment human workers by performing complete business functions from start to finish and enhancing any job role. Like a human employee, a digital worker can learn and prioritize processes and are pre-built and downloadable with the plug-and-play feature.
Over the past few years, we have witnessed how businesses incorporating robotic process automation (RPA) into their systems have significantly improved their business metrics. RPA and intelligent automation (RPA + AI) have assisted small and large enterprises in building a robust digital workforce and automating various repetitive tasks efficiently.
With the pandemic and ensuing recession, the interest in RPA applications has escalated across industries. Gartner predicts that 90% of large organizations globally will have adopted RPA by 2022 as they look to empower critical business processes digitally. So let’s look at how the RPA digital workforce is helping industries and businesses perform better.
Banking and Finance
Legacy banking and finance processes can be inefficient, but automation is changing the game.
- Accounts payable and closure process: The traditional accounts payable process entails obtaining invoices from suppliers using OCR, confirming the data in the specified fields, and then processing the invoices. RPA automates the entire procedure and automatically credits the amount to the vendor’s account. Additionally, AI sends automatic reminders to customers to submit the required papers and performs account closing operations accurately.
- KYC and compliance: RPA bots are used to manage customer information collection, verification, and processing. With reduced FTEs and 24×7 operational output, the digital workforce can significantly boost the overall compliance procedure.
- Credit verification: By automating background checks and validations as per the established standards and guidelines, IA effectively manages credit certification and streamlines the process for credit card dispatching.
- Mortgage processing: With mortgage processing, banking AI can be deployed to scrutiny checks, such as job and credit history, permanent address, and much more, accelerating the entire process through well-defined algorithms.
- Fraud detection: Through OCR and AI, Banks are identifying fraudulent accounts and flagging them. Banks can then scrutinize these accounts and initiate investigations.
Healthcare
Intelligent automation enables the healthcare industry through effort reduction and faster, more efficient data processing.
- Patient registration: Patient registration enabled by RPA saves time by filling in data and preparing a patient registration form almost instantly.
- Claims management: Patients and hospitals are often involved in managing insurance claims. AI bots can automate claims management using predefined parameters to collect claims data.
- Service interaction: Managing a health plan can get expensive due to functions like claims adjudication, authorizations, and coordination of provider services. RPA platforms can automate these processes and help you bring down costs and improve provider-member interactions.
- Increased throughout with quality: Bots automate processes including maintenance of patient medical records, processing entry-level data, processing insurance claims, and more. NLP clinical documentation frees physicians from the time-consuming manual EHR systems, allowing them to devote more attention to the patient. Along with faster throughput, the digital workforce also brings down the functional cost drastically.
- Predictive Healthcare: Predictive analytics combined with natural language processing can be used to identify high-risk patients and enhance the diagnosis process, moving the healthcare approach from curative to predictive.
Retail
Along with easing up the most basic tasks of the industry, such as product scanning, data analytics, and inventory management, Robotic Process Automation leads to advanced auditability, better customer relationship management, cost reduction, better productivity, and much more.
- Customer support: With RPA, companies can make their customer support more quick and convenient. The software keeps track of orders, sends real-time updates to the customer, and even collects after-sales feedback from the customers.
- Return management: Product returns are a cost to the company, and when done manually, they are time-consuming, further increasing the costs. RPA manages the returns effectively while making the required changes to the inventory database and customer billing.
- Workflow management: From assigning shifts, measuring job time, auditing sales and payroll, to assessing employee work performance, RPA can make personnel processes more productive.
- Marketing and consumer behavior analysis: Adopting RPA delivers reliability and speed to marketing initiatives. In campaign analysis, the bots can help determine campaign goals, ascertain the campaign budget and identify specific channels. The digital workforce also helps with consumer behavior analysis, store planning, new product introduction, customer on-boarding, managing subscriptions, claims processing, and complaint handling.
Manufacturing
Manufacturing organizations have been able to switch their production units to automated software bots thanks to IA. Automation has also significantly reduced operational expenses in the back-end processes like quality control, packing, and product assembly.
- A simpler BOM: The bill of materials with the list of raw materials provides detailed information for new product creation. Leveraging RPA makes product creation faster and ensures accurate and timely creation.
- ERP automation: IA makes resource planning simpler. Generating reports on managing inventory, accounts payable, receivable, and more automatically gives periodic updates leading to better planning.
- Data entry and reconciliation: RPA and OCR can also do a thorough job out of order statement and provisioning and vendor statement reconciliation.
Logistics and Supply Chain
Automation in logistics and warehouse management can solve several critical supply chain challenges.
- Creation of digital supply chains: Today’s supply chain landscape comprises independent silos. Extracting critical data from these silos and older, disparate systems can be challenging. It can require much manual processing and staff to gather this data. Intelligent automation (RPA with AI) can be used to create a digital supply chain, where such processes can be de-siloed, and a data lake/process mining area can be set up for efficiently extracting data.
- Freight management: Intelligent automation provides a fast, agile way to access data and integrate it across systems, saving time and money. IA tools are used for analyzing shipping data, optimizing shipping routes and scheduling orders and deliveries to reduce bottlenecks. They are crucial to reducing repetitive tasks, preventing delays and optimizing available resources.
- Delivery tracking and notifications: You can employ bots to track shipment locations and alert the system when it reaches the desired location. This reduces the time it takes to update the delivery progress. The bots can also automatically update delivery progress and provide stage-wise completion notifications.
The use cases of robotic process automation (RPA reflect its versatility across industries. Owing to its quick deployment cycle time and swift ROI, RPA has become the preferred strategic tool for enabling enterprise-wide digital transformation.
Get in touch with us to know how we tailor-make RPA solutions to help you achieve remarkable process efficiency while driving cost optimization and improving workforce engagement.
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