Process Discovery: Challenges and benefits

The post-pandemic period has seen a rapid transition of businesses to digitization, and Robotic Process Automation probably played the key role for many. But RPA’s scope is restricted to rule-based, repetitive tasks. For businesses to imbibe automation as their corporate culture, they need to identify processes that need immediate Automation attention, a capability that is not part of what RPA does. Hence, they turn to Process Discovery tools to complete the identification journey effectively.

What is Process Discovery and how does it work?

Process Discovery is a set of tools and techniques used for defining, mapping, and analyzing business processes for a given period. Process discovery utilizes Machine Learning capabilities to record all possible variations existing in each process and make recommendations for Automation.

Process Discovery methods identify use cases that can be automated and distinguish them from the rest of the processes. Further, it helps design automation workflows, map, plan, and implements automation faster and more efficiently than manual methods could construe.

Process Discovery can be termed an investigative process incorporating the best business process management and data mining. It identifies, monitors, and improves real processes by analyzing data captured from user keystrokes in enterprise systems. The tools run on employee machines silently in the background, mapping the workflows without hampering daily work. It collects data on how employees use various applications to complete their key roles. The information thus captured is transformed into structured datasets for further diagnosis with the help of AI technology. Repetitive actions from users are grouped into meaningful events, and a process model is proposed for analysis.

Obviously, Process Mapping and Mining for information takes time and cannot be completed overnight. Hence, Process Discovery tools and bots monitor each machine for a specific period to arrest any slight variations and subtle changes.

Following that, advanced ML tools are utilized to analyze all the data captured to narrow down specific workflows that can be moved to an Automation tool to complete the transition journey.

Process Discovery: Benefits and challenges

Process Discovery fuels digital transformation and is one of the important steps toward scaling automation to other critical business use cases. The opportunity cost of wrong process selection is enormous. If enterprises wish to extract the full value out of automation programs, they should determine the right processes to automate.

However, in order for Process Discovery solutions to work adequately, they need comprehensive real-time data. Manual approaches to data collection fall short of complying with the exact requirements, causing numerous challenges and hurdles along the way. These challenges can be either or all of the following:

To address the above-mentioned challenges, enterprises should opt for automated Process Mapping to mine accurate and granular data from business processes to ensure the success of the Process Discovery. Hence, the Process Discovery tool is deployed across all user workstations at once to ensure the data collected is accurate and in real-time.

Let’s explore the benefits of Process Discovery:

Improved quality and performance: With the help of empirical data, Process Discovery tools provide clarity by automatically identifying, analyzing, and determining tasks and priorities for automatable processes. It doesn’t depend on how employees think the tasks should be performed. This more accurate approach offers up-to-date insights into process workflows, deeper understanding, and enhanced process optimization. It leaves no room for guesswork and human bias.

Visibility: Process Discovery guarantees visibility of ownership for specific process steps and an overall process across the organization. This helps enterprises to identify new pathways and future automation opportunities easily.

Fewer risks: Process Discovery solutions restrict user access to critical business information to minimize risks.

Cost efficiency: It enables a measurable way for business improvements to avoid unnecessary repetitions or other inefficiencies. And, with fewer human resources involved, the overhead costs go down significantly.

Improved scalability: The insights generated through Process Discovery help organizations with intelligent decision-making to ensure the gradual evolution of automation solutions and unlock further growth using minimal resources and time.

Maximized ROI: Empirical data-based business process maps prove helpful when enterprises navigate their automation journey from value creation to realization. The user keystrokes captured for process mapping cover all process exceptions and variations. This improves process visibility and provides options to scale, thus maximizing the expected ROI from the automation program.

Conclusion

Enterprises should start small and then scale up to gain early experience, and with the help of the right Process Discovery tools, this task will be realized in no time. Process Discovery is an essential step and a more reliable and valuable tool for enterprises looking to scale automation projects faster to maximize their value and increase ROI.