What is Robotics Process Discovery?

Introduction

 

In today's corporate environment, robotic process automation (RPA) has become one of the most important disruptive technologies driving innovation. 

 

The COVID19 epidemic has prompted businesses all over the world to look for technical solutions that will assist them to automate their highly manual, repetitive business operations and improve their company resiliency. 

 

With so many firms embarking on their RPA journeys, one critical issue remains unanswered. What is the best way to capture and comprehend how and what business operations should be automated?

 

The most difficult component of getting started with RPA for Now, since it captures and analyzes a process, process discovery is critical to a successful RPA programme. 

 

Dealing with process Discovery 

 

For organizations unfamiliar with highlighting automation candidates, it is imperative to put process discovery at the heart of the RPA initiative. This allows these acquirers to find best practices that can benefit from automation and achieve rapid ROI. 

 

Companies with experience in Robotic Process Automation (RPA) and process discovery are always encouraged to maintain process discovery best practices and perform end-to-end process discovery for their business processes to automate.

 

Also Read | What is Intelligent automation?

 

What are the best Process Discovery practices?

 

According to the article, It's important to understand that just because a company can automate a process doesn't mean it needs to. Organizations new to RPA should begin identifying standardized rule-based practices that span multiple systems and require a non-intrusive automation approach. 

 

To uncover the accumulated "integration of swivel chairs", organizations need to investigate RPA (re-entry of data between systems) opportunities. 

 

You can use structured digital data processed according to established standards to find areas where people are working. Of course, as automation technology advances and Artificial Intelligence (AI) capabilities are added, more sophisticated, long-running unstructured data operations can be considered for automation. 

 

However, the ideal process for automation must meet the following characteristics without incorporating complex AI capabilities:

 

1. It's a very laborious and repetitive job

 

The business tasks that employees conduct on a daily basis and on a regular basis are ideal candidates for automation and give the highest return on investment. Automating business operations that individuals do on an irregular basis, on the other hand, may have a lesser ROI and influence on the company.

 

2. Rule-based

 

The finest business processes for automation are those that have a definite set of pre-established rules that all employees must follow in order to execute the activity.

 

3. Processes that are mature and well-established

 

Business processes that require candidates for automation must be well-established and not change frequently. A process must have specified process stages, a defined execution sequence, and defined systems where the process executes, according to the team evaluating an automation candidate's appropriateness. 

 

If a company faces business processes that are conducted in different ways but provide the same outcomes, such processes must go through a process standardization phase to optimize and standardize them before being automated.

 

4. Data inputs that are well-structured

 

All data utilized by a business process must be formatted and digitized, according to organizations. Excel spreadsheets, databases, JSON files, HTML files, XML files, PDF files, TXT files, and a variety of other data inputs are just a few of the data inputs that RPA may deal with. 

 

However, if the data is unstructured or not digitized, RPA can scan, digitize, and arrange it using AI-powered technologies such as sophisticated OCR (Optical Character Recognition) and NLP (natural language processing).

 

5. There is a minimal amount of exception handling required

 

If a business process consistently creates exceptions, it is not a good candidate for automation. 

 

However, if a company wishes to automate a business process that is prone to exceptions, it must first examine the process and determine whether it should undertake standardized efforts to make the process more automated-friendly.

 

6. Interaction between many systems

 

Business operations that require employees to connect with a variety of systems are ideal candidates for automation, as robots can communicate with any programme and execute any work that a person can.

 

Also Read | Role of Process Mining to Accelerate RPA

 

 

Role of Process discovery in Robotic Process Automation

 

RPA's popularity is skyrocketing; according to Fortune Business Insights, the worldwide RPA industry will be worth $7.64 billion in 2028, up from $1.61 billion in 2021. 

 

Growth is being fueled by breakthrough technologies in machine learning and artificial intelligence, as well as the consequences of the COVID-19 epidemic, which raised pressure on firms to automate back-end and front-end activities. 

 

Because of regulatory reporting and balance sheet reconciliation, the Banking and finance industry leads in adoption. The capacity to increase process quality, speed, and productivity, all of which are becoming increasingly crucial as firms strive to fulfil the expectations of cost reduction during COVID-19, said Fabrizio Biscotti, research vice president at IBM

 

RPA is one-third the price of an offshore employee and one-fifth the price of on-site staff, and it can save companies up to 50% on costs. 

 

According to Forrester, RPA is enabling customer service leaders to deliver better customer service by standardizing and speeding up agent work to serve customers better, integrating apps to reduce mistakes and enhance compliance, and ramping up agent faith so that they can better cultivate customers in the contact center. 

 

Regardless of sector, the ability to swiftly and reliably identify the relevant processes to automate is critical to the success of an RPA deployment; the Shared Services and Outsourcing Network (SSON) estimates that approximately half of all automation initiatives fail due to poor process selection.

 

Standardization and Process Improvement

 

We discussed how the COVID19 crisis has accelerated organizations' automation adoption across industries at the start of this article. The current crisis has increased the pressure on businesses to accomplish more with less. As a result, the lean methodology (a part of agile methodology) has become critical for quickly implementing automation and developing company robustness.

 

LSS (Learn Six Sigma) is an important complement to RPA. By eliminating wastes and reducing and unifying systems, corporations may minimize their manual workload using LSS. 

 

Despite this, organizations come to the realization that they might avoid all of the grunt work. RPA comes into its own at this stage, enhancing the LSS toolbox with a strategy that allows the company to continue to develop and advance.

 

Role of Lean Six Sigma in RPA

 

Determine who the best prospects are: RPA is ideal for business operations that are hampered by bottlenecks. By exposing limits, LSS technologies such as bottleneck analysis may assist businesses in identifying the best candidate business processes inside the organization.

 

• Enhance the process's stability: LSS solutions can assist firms to increase the stability of a business process by decreasing variance and making it more amenable for automation.

 

• Improve the process's sturdiness: Using LSS techniques like failure mode and effects analysis (FMEA) may help firms identify possible business process failure modes and establish appropriate mitigation strategies, making the process more amenable for automation. (Reference)

 

 

Process Mining with UiPath: A Crucial Tool for Process Discovery

 

Organizations must understand the traits that business processes must possess in order to be prime candidates for automation, and they must also use the correct tools to discover the business processes that can be top automation candidates.

 

Process Mining, a sophisticated technology created by UiPath for process discovery, can assist enterprises in identifying prime automation prospects across the enterprise. 

 

UiPath Process Mining takes advantage of an organization's current data from business applications to create a comprehensive knowledge of complicated business processes. 

 

UiPath Process Mining provides a high-level perspective of an organization's processes and generates comprehensive graphs that show each process in chronological sequence from start to finish.UiPath Process Mining also aids firms in identifying wasteful processes.

 

In addition, UiPath Process Mining aids firms in identifying wasteful procedures that may be automated. The solution accomplishes this by showing bottlenecks, what slows down a process, and the financial effect of inefficient processes.

 

RPA stakeholders may use UiPath Process Mining to make data-driven choices about automating essential business operations. Additionally, the system enables enterprises to monitor their business processes using smart tags and KPIs, allowing them to see what is working and what isn't, as well as how they may improve those processes. (Source)
 

 

Conclusion

 

To conclude, Process discovery is an important aspect of every RPA project, as we've highlighted. Task capturing, process analysis, and granular documenting are some of the essential components of process discovery that organizations must keep in mind.

 

When a company fails to do process discovery appropriately, it may suffer higher expenses and poor automation, eventually failing its RPA journey. 

 

Organizations may ensure simplified planning and execution of RPA across the workplace by employing the correct process discovery technologies and screening processes with the appropriate optimization approach.

 

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