8.1 Process analysis and automation opportunities
4 min read•july 30, 2024
is revolutionizing how businesses handle repetitive tasks. By identifying suitable processes and using tools like , companies can automate rule-based, high-volume activities that are prone to human error, freeing up workers for more complex jobs.
Implementing RPA isn't just about the tech—it's about smart business decisions. Through careful and ROI assessments, organizations can determine which processes to automate for maximum benefit. This approach transforms operations, impacting workforce dynamics and system architecture while demanding robust monitoring and governance.
Business Processes for RPA
Identifying Processes Suitable for RPA
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- Robotic Process Automation (RPA) allows configuring software "robots" to emulate human interactions within digital systems to execute business processes
- Processes suitable for RPA are typically rule-based, repetitive, high-volume, and prone to human error
- Often involve structured data inputs and deterministic outcomes
- Examples of processes commonly automated with RPA include:
- Data entry
- Data validation
- Data reconciliation
- Report generation
- File transfers between systems
- Processes with minimal exceptions, low cognitive requirements, and limited human judgement are strong candidates for RPA
- Complex processes requiring adaptive decision making are less suitable
Process Mining for RPA Opportunities
- Identifying RPA opportunities involves process mining
- Discovers, monitors and improves real processes by extracting knowledge from event logs in enterprise systems
- Process mining helps uncover the actual process flows, variations, and bottlenecks
- Provides data-driven insights into which processes are most suitable for automation
- Process mining tools can automatically discover process models from event data
- Compares the actual process executions to the designed process models to identify deviations
- Conformance checking in process mining validates if the recorded events comply with the prescribed process
- Highlights exceptions and non-standard cases that may be difficult to automate
- analyzes the efficiency of the as-is process
- Identifies manual steps contributing to long cycle times that could benefit from automation
Automation Feasibility and ROI
Workflow Analysis for Automation
- Workflow analysis involves mapping out the detailed steps, decision points, inputs, outputs, and systems involved in executing a business process from start to finish
- Each step in the workflow should be evaluated for its suitability for automation based on criteria such as:
- Rule-based logic
- Structured data
- Exception rates
- Manual effort required
- Workflow analysis helps identify which steps can be automated, which require human intervention, and the integration points between them
- Provides a blueprint for designing the automated process
- are commonly used to map out workflows
- Clearly delineate the activities and handoffs between different roles or systems
Assessing Technical Feasibility and ROI
- considers technical factors such as the APIs and integration methods available to interact with the systems and data involved in the workflow
- RPA tools typically provide connectors for common enterprise applications (SAP, Salesforce) and databases
- Custom integrations may be needed for legacy systems lacking APIs
- Calculating potential ROI requires estimating the time and cost savings of automating manual tasks
- Considers the implementation and maintenance costs of the RPA solution
- Accounts for the impact on process quality and compliance
- Process complexity, stability, and scale are key factors in determining the potential return on automating a workflow
- Higher volume and more stable processes tend to deliver better ROI
- ROI calculation compares the quantified benefits to the overall cost of implementing RPA
- Benefit may include FTE savings, increased throughput, reduced errors, and improved compliance
- Costs include RPA software licenses, infrastructure, development, and ongoing support
Impact of Process Automation
Workforce and Process Implications
- RPA introduces virtual workers that need to be managed alongside in an augmented workforce
- Impacts on staffing levels, roles, and skills need to be assessed
- Human workers may be upskilled to handle exceptions and monitor bots
- Automated processes can increase transaction throughput and operate 24/7
- May impact upstream and downstream processes and systems
- Implications on service level agreements and system need to be considered
- As automated processes scale up, the management of the becomes a key concern
- are often established to govern standards, control, and best practices across RPA initiatives
- Bots require provisioning, scheduling, monitoring, and error handling
System Architecture and Monitoring Considerations
- Existing system architecture, data models, and security controls may need to be adapted to support robotic workers
- Unattended robots require and
- Redundant bot runners are needed to ensure high availability
- Automated workflows should be monitored for exceptions, errors, and business outcomes to ensure they continue to meet performance targets
- Deviations may require robot retraining or process re-design
- Monitoring dashboards provide visibility into the health and performance of the digital workforce
- Track metrics such as , success rates, and business impact
- are critical to manage the lifecycle of automations
- Includes bot testing, deployment, change management, and retirement processes
Key Terms to Review (24)
AI Maturity Model: The AI Maturity Model is a framework that helps organizations assess their current capabilities in artificial intelligence and identify areas for improvement. It typically includes various stages that reflect an organization’s progress from initial experimentation to fully integrated AI solutions that drive business value. This model emphasizes the importance of aligning AI initiatives with business goals and understanding how to effectively implement and scale AI technologies across different functions.
Automation Centers of Excellence: Automation Centers of Excellence (CoEs) are specialized teams or groups within an organization that focus on developing, implementing, and managing automation strategies and technologies. They provide expertise, governance, and best practices for automating processes, ensuring that automation initiatives align with business goals and deliver measurable value. By centralizing knowledge and resources, CoEs enable organizations to optimize their automation efforts and drive continuous improvement.
Automation feasibility: Automation feasibility refers to the assessment of whether a particular process can be effectively automated, considering factors like cost, technology, and operational efficiency. This concept plays a crucial role in identifying opportunities for improving productivity and reducing human error in business processes, ultimately leading to better resource allocation and enhanced service delivery.
Automation Framework: An automation framework is a structured environment that provides guidelines, best practices, and tools for automating software testing or business processes. It helps streamline the automation process by providing reusable components, managing test data, and ensuring consistency across tests, which can improve efficiency and effectiveness in process analysis and automation opportunities.
Bot utilization: Bot utilization refers to the effective use of automated software programs, or bots, to perform tasks that would typically require human intervention. This practice streamlines processes, enhances efficiency, and reduces operational costs by allowing organizations to automate repetitive tasks and improve service delivery across various functions.
Consistency: Consistency refers to the quality of being reliable, uniform, and coherent across processes, systems, or data. It plays a critical role in ensuring that outputs are predictable and that decisions made from data remain valid over time, which is especially important in process analysis and automation opportunities where uniformity can enhance efficiency and accuracy.
Customer service automation: Customer service automation refers to the use of technology to streamline and enhance customer service processes, allowing businesses to handle customer inquiries and support tasks with minimal human intervention. This technology can lead to increased efficiency, improved customer satisfaction, and reduced operational costs by leveraging tools like chatbots, automated response systems, and self-service portals.
Exception Handling: Exception handling is a programming construct that manages errors and exceptional conditions that occur during the execution of a program. It ensures that when something unexpected happens, such as an error or an invalid input, the program can respond appropriately without crashing. This mechanism is essential in automating processes and analyzing workflows, allowing systems to recover gracefully from errors and maintain operational integrity.
Governance Frameworks: Governance frameworks are structured systems of rules, practices, and processes that guide an organization in decision-making and ensure accountability, transparency, and compliance. These frameworks help organizations manage their resources effectively and align their strategies with regulatory requirements while promoting a culture of ethical behavior. In the context of process analysis and automation opportunities, governance frameworks play a crucial role in determining how processes are designed, implemented, and monitored to enhance efficiency and effectiveness.
Human workers: Human workers are individuals engaged in various tasks and jobs that require cognitive skills, emotional intelligence, and physical abilities. They play a critical role in organizational operations by performing complex decision-making, problem-solving, and interpersonal interactions that machines or automated systems currently cannot replicate fully. Their unique capabilities contribute to process analysis and the identification of automation opportunities that enhance productivity and efficiency in business environments.
Machine Identities: Machine identities refer to the unique digital identifiers assigned to machines or devices in a networked environment, enabling secure communication, authentication, and authorization. These identities play a crucial role in ensuring that machines can interact with each other and with human users in a trusted manner, thereby facilitating process automation and analysis.
Operational Efficiency: Operational efficiency refers to the ability of an organization to deliver products or services in the most cost-effective manner while maintaining high quality. It emphasizes optimizing resources, processes, and technology to maximize productivity and reduce waste, ultimately leading to improved profitability and competitiveness.
Performance Mining: Performance mining is the process of analyzing data from business processes to gain insights into performance and identify areas for improvement. By utilizing advanced analytics and data visualization techniques, organizations can uncover inefficiencies, bottlenecks, and opportunities for automation, leading to enhanced operational effectiveness.
Predictive maintenance: Predictive maintenance is a proactive approach to maintenance that uses data analysis and machine learning techniques to predict when equipment failures might occur, allowing organizations to perform maintenance before these failures happen. This strategy enhances operational efficiency, minimizes downtime, and can lead to significant cost savings.
Privileged Access Management: Privileged access management (PAM) refers to the set of tools and processes used to control and monitor access to critical systems and sensitive information by users with elevated permissions. It aims to minimize the risks associated with unauthorized access or misuse of privileged accounts, ensuring that only trusted users have the ability to perform actions that could affect system integrity or security. By analyzing processes and automating workflows related to access management, organizations can improve their security posture while streamlining operations.
Process mapping: Process mapping is a visual representation of a business process, illustrating the steps, inputs, outputs, and flow of activities. It helps identify inefficiencies and areas for improvement, making it essential for analyzing processes and discovering automation opportunities. By providing a clear depiction of how tasks are performed, process mapping serves as a foundation for implementing technologies like Robotic Process Automation (RPA), streamlining workflows, and enhancing overall efficiency.
Process Mining: Process mining is a data analysis technique used to discover, monitor, and improve real processes by extracting knowledge from event logs. It provides insights into how processes are actually executed, allowing organizations to identify bottlenecks, inefficiencies, and opportunities for automation. By analyzing the data generated during process execution, businesses can make informed decisions that enhance operational efficiency and streamline workflows.
Return on Investment (ROI): Return on Investment (ROI) is a financial metric used to evaluate the efficiency or profitability of an investment relative to its cost. It helps businesses determine how much they stand to gain or lose from their investments, allowing for better decision-making regarding resource allocation and strategic planning. Understanding ROI is crucial for assessing business applications and their potential impact, identifying process analysis and automation opportunities, gauging organizational readiness for new initiatives, and implementing effective RPA tools and strategies.
Robotic Process Automation (RPA): Robotic Process Automation (RPA) refers to the technology that uses software robots or 'bots' to automate repetitive and rule-based tasks typically performed by humans. This technology streamlines business processes by allowing software to mimic human actions within digital systems, leading to increased efficiency and reduced operational costs. By automating mundane tasks, organizations can focus more on strategic activities and enhance productivity.
Scalability: Scalability refers to the capability of a system, network, or process to handle a growing amount of work or its potential to accommodate growth without compromising performance. This concept is essential for understanding how businesses can expand their operations efficiently and manage increased demands, whether through automation, cloud solutions, or measuring returns on investment.
Swimlane Diagrams: Swimlane diagrams are visual tools used to illustrate the flow of a process or workflow across different departments or roles within an organization. Each 'swimlane' represents a specific participant or functional area, allowing for a clear understanding of responsibilities and interactions, which is essential for identifying process inefficiencies and automation opportunities.
Value Stream Mapping: Value stream mapping is a visual tool used to analyze and design the flow of materials and information required to bring a product or service to a customer. It helps organizations identify waste, streamline processes, and enhance efficiency, making it crucial for improving process analysis and identifying automation opportunities.
Virtual Workforce: A virtual workforce refers to a group of employees who work remotely, leveraging digital technologies to collaborate and complete tasks without being physically present in a centralized office. This setup allows organizations to tap into a global talent pool, enhance flexibility, and reduce overhead costs, while also promoting work-life balance for employees. The virtual workforce relies heavily on tools for communication, project management, and automation, which are critical for process analysis and identifying opportunities for streamlining operations.
Workflow analysis: Workflow analysis is the examination and evaluation of a business process to understand its steps, identify inefficiencies, and find opportunities for improvement or automation. This process involves mapping out tasks, understanding dependencies, and assessing how information flows through a system. By conducting workflow analysis, organizations can enhance productivity and streamline operations by automating repetitive tasks.