Robotic Process Automation (RPA), an integral facet of modern process automation, stands as a testament to the fusion of technology and efficiency. Through rpa automation, businesses achieve remarkable strides in operational enhancement. This innovation employs "software robots" to seamlessly emulate human interactions with software systems, functioning within the Graphical User Interface (GUI) or presentation layer. The prowess of Robotic Process Automation is evident across diverse sectors, from healthcare to finance, propelling companies towards amplified productivity and innovative breakthroughs. This transformational technology reshapes conventional workflows, underscoring its role as a cornerstone of contemporary process evolution.
Robotic Process Automation
According to a recent survey, approximately 30% of human work is spent on highly repeatable low-level tasks. These tasks are optimal targets for RPA automation. Some of the benefits that companies have realized by deploying RPA include :
- Increase productivity
- Drive operational efficiencies
- Focus on the customer
- Transform customer outcomes / enhance customer experience
- Create cost savings – Virtual workers are almost 60% cheaper
- Decrease business risk
- Optimise existing processes and systems
- Utilise human talent in better ways
- Create scalability
- Empower the business to improve
- Remove demotivating mundane tasks
Key RPA trends encompass industry-specific automation solutions, greater use of cloud-based RPA, improved collaboration in RPA processes, wider AI application, low-code platform adoption, increased integrations, and the growth of RPA centers of excellence.
Case Studies :
Best candidate processes to target for RPA automation :
- High volume processes
- Highly manual processes
- Repetitive tasks
- Rules-based tasks
- Low exception processes
- Stable processes
- Low complexity processes
Use cases for RPA :
- Data entry across multiple systems
- Rules based processing of data from multiple systems
- Virtual “integration” of different systems
- Rules based tasks and decision-making: e.g. transaction processing, reporting and ad-hoc data requests
Use cases for Cognitive/ Smart automation
- Procurement : Discovering mismatches between contracts and invoices
- Insurance : Claims processing
- Customer Service : Omnichannel support – 360 degree customer view
Case Studies :
Smart Process Automation
RPA delivers significant benefits by automating well defined tasks , operating with structured data and rule based decision making. However, 80% of all data is unstructured with majority of decision inference based thereby restricting the process that can be automated using RPA.
Cognitive/ Smart automation is a subset of AI that more closely emulates human abilities. It allows automation solutions to perform tasks and process unstructured data that traditional RPA can’t handle. This massively expands the capabilities of RPA, allowing companies to implement automation in more areas and see significant productivity gains.
Key capabilities of Smart process Automation :
- Natural language processing (NLP) - Understanding Verbal and written communication
- Optical Character Recognition (OCR) - Extracting data from invoices , documents
- Machine learning: Inference based decision making
Approach to Intelligent Automation
- End to End services from Consultancy , development to on-going support.
- Development of the Enterprise automation Roadmap
- Which roles / process to automate ? HOW and WHEN
- Prepare the organization for transformational change over the next couple of years
- ROI and establish benefit estimation method
- Tech breakthroughs and what challenges and opportunities do they present
- Security Risk
- People matters
- Harnessing Data capabilities
- Extensive expertise both in the process re-engineering, optimization and digitization.
- Experience in automating complex processes dealing with decision making and unstructured data.
- Experience in working with leading automation tools
- Pricing Models : Fixed Bid to Gain share
Virtual workforce Adoption
Elevondata proprietary Bot adoption model ensure smooth transition of BOTS into the workforce.
- Deployment of Virtual worker without negatively impacting the process performance
- Establishing governance model for the Hybrid workforce (human and Bots)
- Management of Virtual workforce – Staffing, Scheduling, Monitoring, Quality assurance and continuous improvement.
- Upskilling workforce to manage the new environment
- Change management and redeployment of resources
- Business Continuity planning
- Establishing SLA’s with IT for infrastructure and software updates and upkeep
- Work with the business leadership to establish the strategic intent and benefits from the RPA program
- Establish Catalogue for In-scope process for robotics processes automation.
- Assist in tool stack selection
- Conduct Proof of concept and evaluate results against objectives
- Process redesigning and optimization
- Work with business on the acceptance criteria and deployment strategy
- Development of BOT using Agile and Devops Methodology
- Automated testing and maturing of Automation
- Workforce management of the Hybrid/ Virtual workforce
- Business continuity planning and establish maintenance SLA’s