What is Robotic Process Automation (RPA)?

RPA is a technology that uses software robots or "bots" to automate repetitive and manual tasks traditionally performed by humans. These bots mimic human actions and interact with other systems to execute tasks such as data entry, file updation, customer service queries etc.

Restructuring Business Processes and Relevance of RPA

Why restructuring of business processes is imperative?

• In the ever-changing global market, businesses need to be flexible and adaptive. It's essential to restructure and automate processes to stay competitive.
• To thrive and succeed, today's workplaces need to transition towards digital processes.
• Modern consumers expect tailored, efficient services. To meet these expectations, businesses need to revamp their processes, frequently using digital solutions.

Relevance of RPA

What distinguishes RPA from traditional automation methods is its flexibility, scalability, and compatibility with existing systems. This versatility makes RPA an ideal solution for a variety of business requirements.

Benefits of RPA

RPA streamlines large-scale, repetitive tasks in the back office, transforming operational frameworks, thus fetching below benefits to the organisation:

• Increased Productivity and Efficiency
• Improved Accuracy and Quality of Work
• Cost Reduction & Resource Optimization
• Scalability and Flexibility

Organizations implementing RPA have reported cost savings ranging from 20% to 50% on repetitive tasks and operations. RPA can increase productivity by up to 20% and reduce the time spent on manual and repetitive tasks by 50% to 70%.

Impact of RPA on Organization’s Business Operations

There is a significant role played by RPA in transforming business operations and making them more efficient. Once regular jobs are automated, the freed-up bandwidth can be used on more focused and business-critical activities. It leads to significant cost savings by reducing the need for manual labor in routine tasks. The Return on Investment is evident because operational costs go down, and value goes up since people are moved to more productive tasks.

Impact of RPA on Human Resources

The implementation of RPA transforms job roles within companies, freeing employees from mundane tasks and enabling them to focus on more crucial and strategic work. RPA, thus, guarantees precision in tasks, essential for upholding quality benchmarks.

Industries Transforming with RPA

Let’s look at some of tasks automated in different industries through RPA:

• Finance and Banking: RPA is being used to automate account reconciliation, fraud detection, loan processing, customer onboarding etc.
• Healthcare: RPA is revolutionizing patient data management, appointment scheduling, billing & claims processing, inventory management and telemedicine services.
• Manufacturing and Logistics: Here, RPA is being extensively used to automate inventory management, order processing, supply chain coordination and production scheduling.
• Retail and E-commerce: The activities like order processing, inventory tracking, customer service, pricing optimization and marketing campaign are easily transformed through RPA.
• Human Resources and Recruitment: In this sector, RPA is being used to automate resume screening, candidate sourcing, interview scheduling and payroll processing.
• Telecommunications: RPA is transforming customer service, order provisioning, billing & invoicing, network monitoring and quality assurance testing.
• Hospitality and Travel: RPA helps automate reservation management, customer service inquiries, inventory optimization, loyalty program management and back-office operations.
• Legal and Compliance: RPA is being used to automate contract management, legal document processing, compliance reporting, regulatory filings etc.
• Energy and Utilities: RPA is being used to automate meter reading, billing processes, energy consumption analytics, asset management and maintenance scheduling etc.
• Public Sector and Government: RPA is helping by automating citizen services, permit and license processing, procurement and supply chain management, HR and payroll processing.

Banking, Financial Services, and Insurance (BFSI) sectors are leading in RPA adoption, followed by healthcare, retail, manufacturing, and telecommunications. The most common use cases for RPA include data extraction and processing (45%), customer service (28%), finance and accounting (23%), and human resources (22%).

Technologies and Tools in RPA

Broadly, an organization can opt for one or more of the below to implement RPA:

• RPA Platforms
• Using AI, ML and emerging technologies
• Process Mining and Discovery Tools

Lets take a look at some details on each of these.

RPA Platforms

RPA platforms provide the foundational infrastructure for designing, deploying and managing software robots. Popular RPA platforms include:

• UiPath: a set of tools for automating business processes, managing robots.

• Blue Prism: known for its scalability, security and integration capabilities.

• Automation Anywhere: a platform with a wide range of pre-built automation solutions.

• Pega Robotic Process Automation (RPA): an enterprise-grade RPA

• WorkFusion RPA Express: a free and lightweight platform for SMEs and individual users.

• Microsoft Power Automate: offers integration with MS Office 365, Dynamics 365.

• Jiffy.ai: an AI-driven platform, offers a set of tools for automating business processes.

These RPA platforms offer a range of features, capabilities and deployment options to meet the diverse automation needs of organizations across various industries.

AI, Machine Learning and Emerging Technologies in RPA

Emerging technologies (AI, ML, NLP, OCR, Computer Vision, IoT etc) can be integrated with RPA platforms to automate complex tasks and handle unstructured data:

• AI-powered Intelligent Automation and RPA
  AI and ML enable RPA platforms to perform intelligent automation by learning from data, identifying patterns and making decisions based on historical data and real-time information.
  

  Examples: Tools like DataRobot, H2O.ai are being used to build machine learning models for fraud detection and improving security measures for the financial institutes. Retail companies use Dialogflow, Microsoft Bot Framework and IBM Watson Assistant to build chatbots for customer service automation. Insurance companies use ABBYY FineReader, Tesseract OCR etc to automate document processing and data extraction tasks.

• Cognitive Processing with NLP and RPA
  Cognitive processing capabilities provided by AI and NLP technologies enable RPA platforms to understand, interpret and process unstructured data such as text, images and voice inputs.
  

  Examples: Healthcare companies are using Google Cloud Natural Language Processing, IBM Watson Natural Language Understanding and NLTK (Natural Language Toolkit) to process and analyze textual data, reduce manual effort and minimize errors.

• ML-based Predictive Analytics and RPA
  AI and machine learning technologies enable RPA platforms to perform predictive analytics by analyzing historical data, identifying trends and forecasting future outcomes.
  

  Examples: Amazon Forecast, TensorFlow and scikit-learn etc are helping the Retail and e-commerce industry by developing predictive models for sales forecasting, optimizing inventory levels and enhancing revenue generation.

• Computer Vision and RPA in Manufacturing and Logistics
  Computer vision is being integrated with RPA platforms to automate visual inspection, quality control and inventory management tasks in the manufacturing and logistics sector.
  

  Examples: Tools like OpenCV, TensorFlow Object Detection API and Microsoft Azure Computer Vision use Computer Vision algorithms for analysing images and videos of products, identify defects and automate quality control processes.

• RPA in IoT and Smart Automation
  RPA platforms are also being integrated with Internet of Things (IoT) technologies to enable smart automation and process orchestration across interconnected devices and systems.
  

  Examples: UiPath IoT, Automation Anywhere IoT and Pega Infinity are integrating with IoT technologies to improve system performance in IoT-enabled environments.

Process Mining and Discovery Tools

Process mining and discovery tools analyze event logs from different information systems to provide a visual representation of processes and provide insights into process bottlenecks, inefficiencies and opportunities for automation. Some examples of standard tools are:

• Celonis
• UiPath Process Mining
• Minit (acquired by Microsoft)
• Fluxicon Disco

Essentially, these tools help organizations prioritize automation initiatives.

A dilemma: industry-standard tools or custom development?

Many times, organizations are at a crossroads whether to use industry-standard tools or opt to develop custom automation tools. Here are considerations to make an informed decision:

Industry-standard RPA Tools vs Custom Development

If you require a reliable, scalable and feature-rich solution with comprehensive support and a vibrant community, industry-standard RPA tools may be the best choice.

If you have unique requirements, specialized business processes and the necessary technical expertise and resources, custom development of RPA tools may provide greater flexibility, customization and control, potentially leading to a competitive advantage.

Ultimately, the decision should be based on a thorough analysis, cost-benefit evaluation and alignment with the organization's objectives.

Key Challenges & Concerns in RPA Deployment

Around 30% to 50% of initial RPA projects fail due to various reasons, including lack of proper planning, inadequate understanding of RPA capabilities and resistance to change. Here are key challenges faced during RPA deployment:

• Implementation Complexity: RPA implementation can be complex, requiring a deep understanding of the existing processes, systems, and workflows

• Scalability and Maintenance: RPA solutions must be able to scale to accommodate growing volumes of data and transactions, and be easy to maintain, update and manage.

• Integration with Legacy Systems: Ensuring seamless integration, data synchronization, and interoperability between RPA bots and legacy systems is crucial to avoid disruptions, data inconsistencies, and compatibility issues.

• Skilled Workforce: There is a growing demand for skilled RPA developers and professionals. However, there is a shortage of talent with the required RPA skills and expertise in the market.

Steps for RPA Adoption

• Engage the stakeholders involved.
• Define clear objectives and set measurable KPIs
• Assess current processes and identify ones suitable for automation
• Evaluate and choose right RPA tools and technologies; train the team on these
• Prepare a detailed implementation plan
• Monitor and measure the performance against the target KPI’s;
• Regularly review and optimize in view of future needs.

Conclusion

Robotic Process Automation (RPA) is a powerful technology that holds promising advancements in future. Improvements in the cognitive abilities are expected with advancements in RPA technologies. Also, combining RPA with new technologies will result in Hyperautomation and is likely to create more compelling automation solutions. RPA promotes adherence to laws and regulations, ensuring businesses maintain compliance and uphold integrity, thereby fostering transparency and trustworthiness within the company.

Meritech is fully equipped with experienced team in integrating digital advancements like RPA to enhance competitiveness of its clients. Utilizing its expertise in emerging technologies including AI, ML, NLP, OCR, Computer Vision, we meticulously plan and implement your RPA strategies. Eager for this transformative journey? Explore cutting-edge digital solutions crafted for your success at Meritech.