The global pandemic of 2020 compelled organizations worldwide to put their digital transformation initiatives on a fast track with the help of RPA and Intelligent Automation solutions. Unfortunately, 30% to 50% of robotic process automation projects have failed globally. Therefore, the transition should begin with process discovery to capture and understand how and what business operations need automation assistance. Business process discovery is rightfully the first step in ensuring a successful RPA initiative.
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Why Businesses Need Process Discovery
Given the current market competitiveness, building a digital enterprise is no longer an option but is necessary. And owners are ramping up their investment schemes to improve their operational efficiencies. RPA, Intelligent Automation, and other tech-based capabilities like Artificial Intelligence and Machine Learning are explored explicitly to elevate the legacy systems in organizations and increase the scope for revenue opportunities.
Robotic Process Automation (RPA) bots are deployed in business areas that consume maximum time and resources, so the skilled workforce is better utilized. And RPA bots create the pathway for further automation implementation end-to-end. However, automating a process simply because it can be automated is not the ideal way to bring transformation.
Therefore, enterprises should have a proper plan and applications to identify areas requiring immediate improvement, implement intelligent solutions on a small scale, and extend their capabilities beyond. But identifying such areas again is a time-intensive laborious task. Manually executing this might not fetch accurate results, and owners would automate wrong processes altogether. No wonder so many early RPA implementations fail. To avert such mishaps, automated process discovery is strategically leveraged.
Process Discovery – A Brief Overview
Process discovery comprises a set of tools and techniques to define, map, and analyze different processes in an organization. It leverages Machine Learning capabilities to identify how each business process works and make suitable recommendations for automation. Process discovery tools also help design automation workflows, like mapping, planning, and implementing automation projects faster and more efficiently.
Typically, these tools enable organizations to gain a comprehensive overview of critical business processes, analyze and map the underlying structure and evaluate day-to-day operations. It creates a top-down hierarchical approach with bottom-up analysis to outline process maps for future reference, significantly while scaling automation initiatives end-to-end.
Automated process discovery tools also capture process data and transform them into a structured dataset for further diagnosis. Thereafter, the repetitive actions of users are grouped into meaningful events to frame the process model for analysis.
Process discovery bots silently monitor an organization’s business processes for a specific period. They usually run on employee machines without hampering daily workflows while non-intrusively collecting data on human-machine interactions. Then, advanced ML algorithms are used to analyze data and identify workflows that can be easily automated for scaling the enterprise’s efficiency goals.
Primary Benefits of Process Discovery
Many organizations remain unsure of where to start their automation journey without prior knowledge. And, most often than not, a lack of required skills and adequate IT infrastructure results in inefficient large-scale process identification and mapping of different process variations and exceptions. Therefore, the outcome is numerous failed RPA projects, as mentioned earlier. On the other hand, Process Discovery leverages the power of automation and AI capabilities to complete the above-mentioned tasks effortlessly in less time. Furthermore, it eliminates manual work and subsequent errors. This cost-effective approach maximizes business process outcomes and drives higher returns on automation investments.
The benefits of process discovery, therefore, can be summed up in the following points:
- Improves quality of work and performance
- Elevates visibility of crucial business processes
- Mitigates risks while driving value for businesses
- Improves cost efficiency of operations
- Maximizes scalability of RPA projects
- Drives higher returns on automation investments
- Provides competitive advantage to enterprises
Five Best Practices for Effective Process Discovery
Process discovery provides a detailed understanding of ‘as-is’ processes for mapping out the critical steps involved in the workflows. This evaluation helps owners identify process gaps and chalk out an optimized way of executing the same tasks in lesser time. In order for organizations to get the most out of process discovery, they should consider the following tips:
Determine enterprise automation goals
Every organization is unique so are its automation goals. But, typically, business process automation serves the primary objectives of eliminating manual efforts on redundant tasks, improving operational efficiencies, streamlining workflows, optimizing resources, and scaling profitable business outcomes. Once the goals are in place, owners can quickly determine critical areas for improvement.
Review priority processes for automation
Every business organization comprises hundreds of processes running at the same time. But, as stated earlier, not every process can be automated simultaneously. Therefore, the second step should be to identify which areas of operations need your immediate attention and time. Ideally, the best processes suitable for automation should fall under the following categories:
Highly manual and repetitive: Back-end and front-end operations, for example, comprise recurring time-intensive tasks that eventually delay the subsequent tasks and consume productive hours of skilled resources. And these are prime candidates for automation.
Rule-based: Robotic Process Automation is known to improve rule-based workflows that require resources to strictly pre-defined rules for task execution.
Mature and standard processes: Business process candidates should follow specific and consistent guidelines for automation implementation. There should be defined process steps, execution orders, and specific systems where the said processes run. However, when specific key processes are executed in multiple ways but yield similar results, they should be first standardized before being subjected to automation.
Structured data inputs: Every business process deals with data, but in order for the organization to automate them, the data used should be properly structured and digitized. However, RPA bots, with extended capabilities of AI and OCR, can be easily leveraged to scan, digitize, and structure datasets in case they are available in varying formats.
Low exceptions: Now, a process generating exceptions regularly is not a suitable candidate for automation. If owners wish to automate business processes subjected to frequent exceptions, they need to analyze such exceptions and try to standardize them for improvement.
Multiple system interactions: A few business processes require employees to interact with numerous systems for execution. And these areas of operations are mostly considered prime candidates for automation.
Map out selected business processes
Having determined the process candidates, it is time for owners to use software tools to map out each process separately. And this approach involves full participation from employees who are directly involved. Software solutions for process mapping provide a graphical representation of how each process is executed, thereby providing a clear understanding of how to improve workflows.
Analyze and categorize key processes
Again, in this step, employees should openly speak about process bottlenecks, the inefficiency of applications, unstandardized approach, and redundancy of work. Their statements are valuable insights helping owners to clearly understand what exactly is happening at the task level and identify ways to create more streamlined processes. Further, owners also learn how many resources are involved in a specific task or how many processes run in the background. Based on such inputs, processes can be easily categorized into high and low-priority ones and those that can be eliminated.
High priority: These processes are integral to the organization and require immediate improvement for scaling higher value in terms of results and revenue.
Low priority: These business areas also need automation attention as they are partially efficient and would drive lesser value following automation implementation.
Open for elimination: These areas are usually redundant, adding little or less value to the organization. Hence, eliminating them from the system will not significantly impact other business areas.
Identify areas for Improvement.
To scale success with automation initiatives, it is advisable to focus on short-term improvements that will immediately impact the business. But, at the same time, continuous discovery of other critical processes will eventually help scale automation and improve the overall productiveness and efficiency of operations.
Process discovery is an ongoing strategy requiring time and teamwork. Automated software solutions for discovering and mapping business processes provide accurate data concerning how each process and its subsequent tasks are executed, including numerous variations and nuances. The tips mentioned above will guide enterprises in identifying areas for improvement and scaling automation potential end-to-end.