AI-Enabled Intelligent Automation unlocks business value for hyper-growth
What is Intelligent Automation?
Intelligent Automation is a set of technologies comprising of AI, Machine Learning (ML), RPA (Robotic Process Automation) and Generative AI that allow organizations to automate processes that are repeatable and require cognitive decision making
What is the Key Business Value of Intelligent Automation
Intelligent Automation Approach Can Play a Key Role in Successfully Driving Innovation-Led Automation
Intelligent Automation Approach Can Play a Key Role in Successfully Driving Innovation-Led Automation
The continuous discovery and intelligent automation involves a mindset change to bring together process intelligence to extract insights and automation to take outcome-oriented actions
AUTOMATION
Rules-based Automation
Robotic Process Automation (RPA)
API Automation
Take desired actions to achieve business outcomes
AI-based automation
Intelligent Document Processing (IDP)
Conversational AI
Generative AI
Robotic Process Automation (RPA)
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Definition: It is a type of software product that can automate rules-based repetitive tasks or processes by mimicking user’s activities. It is non-invasive, typically interacts with a computer-centric task or process through the User Interface (UI) of the underlying applications and can be deployed in attended/agent-assist and/or unattended mode(s).
Applications l On-demand data processing (e.g., data transfer, validation) l Scraping information from web pages l Near real-time employee assistance l On-the-job training and process guidance
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Automation solutions continue to deliver benefits across cost, operational, and business impact dimensions
Cost savings
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Offloading of tasks to automation robots improves FTE capacity, leading to overall financial savings
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IDP reduces the overall cost of processing huge volumes of data. Conversational AI and IDP solutions generate quick RoI
Improve operational efficiency
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Automation solutions such as RPA, IDP, and API automation will improve the processing time and reduce any human errors
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Also, data generated by automation robots can be used to further identify and eradicate operational inefficiencies
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Faster turnaround times using IDP solution due to increased Straight Through Processing (STP)
Improved governance and compliance
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A robust audit trail can be gathered for all robot activities, enabling traceability and improving process governance and compliance
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Ability of automation solutions to aggregate data from multiple sources enhances efficiency of regulatory reporting
Increased employee productivity
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Employee productivity is a key driver of automation adoption as it aids in offloading repetitive tasks
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Enhance productivity by getting useful information on the computer screen in near real-time, while working alongside humans
Business continuity and planning
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Automation solutions such as RPA, API automation, and conversational AI can help businesses prepare for disruptions and ensure continuity of operations, even during challenging times
Enhanced customer experience
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Automation supports a digitally-enabled customer experience by reducing wait times, speeding the completion of query resolution, and ensuring a consistent experience
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Conversational AI provides robust support to customers, allowing businesses to provide personalized responses to their queries
Top-line growth
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Help get a holistic picture of end-to-end processes and extract hidden process- and task-level insights for improvement that can uncover new cross-sell/upsell opportunities or better ways to conduct business, impacting top-line growth.
Top use cases of continuous discovery and intelligent automation across industries and business functions
Industry: Banking
Objective: Streamline the loan application process to improve customer experience
Business challenge:
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The loan application process is complex as it involves multiple departments and manual handoffs, leading to long processing times and poor customer experience
Role of continuous discovery and intelligent automation:
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Process intelligence tools help banks identify inefficiencies in their loan application process. By optimizing the process, banks can reduce the time it takes to process loan applications
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Discover customer journey maps and identify the customer pain points within the process.
Industry: Insurance
Objective: Improve the customer experience and drive operational excellence
Business challenge:
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In the insurance sector, a huge volume of inbound emails from customers is creating a lack of visibility in service channels
Role of continuous discovery and intelligent automation:
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Discover the flow of inbound emails using communications mining and identify areas where there are delays and bottlenecks
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Interpret the messages to extract key entities and intents along with performing sentiment analysis
Industry: Life sciences
Objective: Identify and prioritize automation opportunities to maintain a healthy pipeline
Business challenge:
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There are different horizontal processes across life sciences enterprises that are handled manually leading to inaccuracies
Role of continuous discovery and intelligent automation:
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Process mining solutions help analyze the processes, enabling the identification of bottlenecks.
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These also help enterprises to improve process governance by identifying non-compliant cases l Identify and prioritize automation use cases across processes with task mining solutions. Automate the prioritized areas, which are highly manual and repetitive in nature, using RPA solutions
Industry: Utilities
Objective: Improve revenue collection and customer satisfaction by optimizing the meterto-cash process
Business challenge:
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The meter-to-cash process determines the accuracy of billing and revenue collection in the utilities industry. However, due to multiple handoffs and data entry points, there are errors and delays that occur, leading to increased revenue collection costs
Role of continuous discovery and intelligent automation:
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By leveraging process intelligence, enterprises can improve billing accuracy, reduce revenue leakage, and enhance the overall customer satisfaction
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It provides visibility into the entire meter-to-cash process, identifying areas for improvement such as manual data entry or outdated billing systems and configuring alerts for delays in data validation or billing errors within the process intelligence tools
Industry: Manufacturing
Objective: Optimize the plant and asset maintenance process to enhance the efficiency of production
Business challenge:
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Manufacturing companies often experience high maintenance costs and frequent breakdowns of their production equipment, which impacts their overall production capacity, product quality, and profitability
Role of continuous discovery and intelligent automation:
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Process intelligence tools can help enterprises identify the root causes of equipment breakdowns
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Leverage predictive analytics to predict maintenance issues before they occur, allowing enterprises to proactively address potential problems and reduce equipment downtime
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Identify automation opportunities using process intelligence tools and deploy RPA robots to perform routine maintenance tasks such as equipment inspections
Industry: Public sector
Objective: Enhance the quality of service delivery for citizens
Business challenge:
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Enterprises in government and public sector are facing challenges in delivering services to citizens in a timely and efficient manner
Role of continuous discovery and intelligent automation:
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Discover the end-to-end service delivery process and identify process steps that are causing delays or inefficiencies using process intelligence solutions
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Deploy RPA robots for processing of citizen applications and chatbots to provide citizens with realtime updates on the status of their application or service request