Intelligent Automation In Healthcare, Telecom, And Supply Chain

Intelligent automation (IA) combines robotic process automation (RPA) with advanced technologies such as artificial intelligence (AI), machine learning (ML), deep learning (DL), big data analytics, Internet of Things (IoT), Computer Vision, natural language processing (NLP), optical character recognition (OCR), intelligent character recognition (ICR) , task mining, and process mining to create end-to-end business processes that think, learn, and adapt on their own. Intelligent automation is sometimes referred to as intelligent process automation (IPA) and hyper-automation.

Though IA can be applied across any sector, this paper focuses on its impact and applications across the healthcare and telecom sectors, and the supply chain function.

IA in Healthcare

The healthcare industry has been catapulted into transformation with speed and agility as core drivers. Speed and agility will produce powerful outcomes, including greater patient engagement, enhanced capabilities, and increased care quality in terms of cost efficiency, revenues, and return on capital. Permanent structural changes must be made to sustain speed and agility in ways that will inspire and engage employees and reshape talent.

Healthcare revenue cycle management (RCM) is the financial process used by healthcare facilities to manage the administrative and clinical functions associated with claims processing, payment, and revenue generation. The process consists of identifying, managing, and collecting patient service revenue including the full process of billing and payment that takes place in the healthcare facilities. Some view RCM as the process from patient visits to claims payment. However, the process is far broader than that: RCM begins before the patient is seen and doesn’t end until long after.

Once the basic components of the revenue cycle model are in place, automation can be used in numerous ways to improve upon processes, decrease delays in accounts receivable (A/R), and increase revenue. Healthcare companies are currently leveraging the UiPath platform to increase speed and agility by automating human system navigation and processing to:

Improve a patient’s access to the right provider at the right time and place

Ingest AI-ML engines for predicting health outcomes and improving care delivery

Compress RCM activities to improve cash flow and reduce A/R

Increase productivity and aid in cost savings across patient access, RCM, and contact center operations

Pre-Claim

Fee schedule and pricing
Provider credentialing
EDI/ERA enrollment
Contract negotiation

Pre-Visit

Scheduling and registration
Appointment reminders
Eligibility verification
Pre-treatment authorization and referrals
Plan enrollment

Visit

Patient check-in
Coding and charge capture
Encounter documentation
Co Pay and deductible
Payment arrangement

Claim Submission

Charge entry
Claim scrubbing
Claim submission
Error correction
EDI management

Inbound processing

Mail processing
Scanning and indexing
ERA/EFT processing
Payment posting
Cash reconciliation

Payer

Claim status check
Requests for information
Appeals and resolution
Denials analysis

Patient

Patient statements
Patient refunds
Transition to collections
Patient payment calls

IA in Telecom

The deployment of 5G technology is revolutionizing the telecommunications sector. Telecom companies are adopting end-to-end intelligent process automation (IPA) tools to improve business operations and prepare for the impact of 5G and other networking technologies. Mass-market 5G coverage is expected to increase greatly in 2023. 5G will create significant business opportunities for telecom companies but will also strain their resources and infrastructure. RPA can alleviate this strain in network operations and the call center.

Artificial intelligence (AI) is essential for telecom’s digital transformation and for analyzing data on the network. It can help with automating the network, personalizing information for users, converging systems, and organizing data. An integration with other applications and platforms, including digital assistants and chatbots, provides an opportunity to gain insights into customer preferences for better service and product offerings.

Internet of things (IoT) can help improve the operational efficiency of telecom providers with remote equipment monitoring and management. A majority of telecom providers see IoT as an important driver for expanding services. Intelligent automation can help them see where workflows or processes are underperforming or even broken, and enable them to be proactive about fixing them.

Telecom firms are interested in delivering content directly to consumers. They have been partnering with or buying companies that produce television shows, movies, and live sports events. Intelligent automation solutions can pull data and gather real-time analytics on customer preferences to help them create more targeted content.

The telecom industry has reached a significant technology milestone. Instead of depending on human workers to run business processes, providers are implementing a new form of collaboration, pairing employees with intelligent process automation—a combination of RPA, AI-ML, and IoT to automate telecom processes end-to-end.

Operations and Maintenance

Alarms data extraction and correlation
Intervention report
Field engineer dispatching
Site management
Incident management

Supply Chain

Inventory levels (demand planning)
Stock/store reconciliation
Lead time optimization
Transportation selection
Distribution center planning

Sales and Marketing

CRM and BSS data quality and updates
Loyalty and churn management
Campaign management and effectiveness
Sales reporting and forecasting
New order booking and processing
Advertising placement

Customer Care

Self service demands
Omnichannel contact center
Field service management
Workforce management

Store Operations

Inventory management
Recruiting, onboarding, and staff engagement
POS opening and closing activities
In-store order, billing, and complaint management
New store opening
Stock and store reconciliation

IA in Supply Chain Management

In an ever-evolving and technologically advanced world, businesses are faced with meeting changing consumer preferences and environmental uncertainties. As the market place develops, processes and procedures within the enterprise must adapt to changing market demands. Many of the adaptations that help businesses stay competitive fall under the supply chain and operations function. Modern supply chains help improve living standards by enabling consumers to buy essential, quality products at lower cost. This is because an effective supply chain streamlines the process of getting products to market faster and cheaper

Intelligent supply chain solutions, based on the digital enablers such as process mining, task mining, RPA, intelligent document capture (IDP), (IoT), AI-ML, and big data analytics create the foundation for a high-performing, lowcost supply chain by addressing the following businesses challenges:

Increasing complexity in supply chains due to globalization, restructuring, and acquisitions

Inability to see a unified view of shipments, orders, and invoices with relevant details and statuses

High volume of exceptions due to upstream process inefficiencies

Lack of integrations across channel partners and customers

Legacy business processes and systems resulting in sub-optimal supply chain performance

Planning

Sales and operations planning
Sales forecasting
Demand planning
Supply/capacity planning
Inventory planning
Stock/store reconciliation
Lead time optimization

Sourcing

RFX management
Buying channel enablement
Requisitions management
Buying execution
Spend management
Vendor management
Master data management

Logistics

Goods receipts management
Inventory management
Bill of Lading (BOL) processing
Inquiry and quotes
Shipment tracking
Carrier RFX management
Logistics administration

Aftermarket

Reverse logistics
Service contract management
Warranty management
Customer service
Spare parts management
Preventive maintenance

Reduced costs

Automation in transaction processing results in cost reduction
Fewer FTEs needed to complete high-volume repetitive tasks

Higher productivity

Decoupling of business volume from workforce capacity
Higher efficiency in process and reduction of non-value-added activities
Increased productivity with the potential to operate 24/7
Up to 60% reduction in average handling times

Consistent quality

Reduced transactional and human errors due to transaction level automation
Consistent quality delivered as human error is eliminated
Customer experience enhanced with reduced cycle time and improved reliability

Improved auditability

Greater visibility and auditability of transactions, leading to better control over end-to end process
Ability to mine enormous volumes of data
Greater adherence to audit and regulatory compliance

Staff satisfaction

Higher employee satisfaction with eradication of monotonous tasks allowing individuals to focus on higher value work
Paves the way for new talent, raises capability of workforce with upgrades to more skilled tasks
Digital workforce in place to drive transactional and repeatable tasks

About Cyient

Cyient (Estd: 1991, NSE: CYIENT) is a consulting-led, industry-centric Global Technology Solutions company. We enable our customers to apply technology imaginatively across their value chain to solve problems that matter. We are committed to designing tomorrow with our stakeholders and being a culturally inclusive, socially responsible, and environmentally sustainable organization.

For more information, please visit www.cyient.com
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Intelligent Automation in Healthcare, Telecom, and Supply Chain IA centers of excellence can drive operational efficiencies, productivity, and cost savings.

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