What are the limitations of RPA?



RPA is still limited to humans for designing the workflow, it's not smart enough to build and self heal itself. Processes related to Live Monitoring example view real time Camera and taking actions. Taking actions based on real time Sentiment Analysis derived from Natural Language processing. Pre−build AI and ML Packs for RPA Processes for Smart Exception Handling and providing Analysis − Recommendations. Improvements − Smart AI and ML integrations that understands Exceptions and Provide recommendations.

The processes having following characteristics are not suitable for RPA −

  • Any process that need human judgements to process.

  • Any process which has data which is unstructured.

  • Any process which has a non−digital input source.

limitations of RPA

The limitations of current RPA systems make meeting these expectations challenging, particularly for businesses with expansive settings that are subject to strict regulations. But in order to get closer to the ideal RPA implementation, issues can be fixed,Which include the following −

Process improvement or cognitive capabilities

"RPA is not a cognitive computing solution". Instead, it's "best suited for rules−based vs judgment−based processes",to workaround this limitation, we can recommend using "smart AI and ML integrations that understand and relate the exceptions and can provide recommendations according easily based on the real time scenarios."

RPA requires structured data

some tech experts stated that "RPA requires structured data but 80% of enterprise data is buried in unstructured documents− emails, letters of credit, invoices, passports, sanction lists, etc." those limitations to include "voice and callback processes and processes that require human subjectivity." Although unstructured data is an issue for bots of RPA, other tools can be used to structure the data before using RPA bots to get the best and exact results.

Reading and interpreting image or graphic data

As per the reviews came from organizations, an employee shared an experience where it wasn't possible to "read a network topology or some machine drawing."

Handwritten Documents

One of testing members,Aprajita jha working at MyAnatomy , says that handwritten documents present a challenge for RPA bots  but it "is slowly being addressed and hopefully in the next few years we will see more intelligent 'handwritten notes' recognition which robots  can identify."

Implementing RPA with a broken and incompetent process will not fix it. RPA is not a Business Process Management solution and does not bring an end−to−end process view.

It cannot read any data that is non−electronic with unstructured inputs. RPA tools aren’t intelligent robots with machine learning and artificial intelligence; RPA “bots” are scripts that can’t dynamically respond to changes.

Balancing short-term needs with long−term priorities.

Some things about RPA may seem too good to be true, such as the ability to increase productivity, minimize human error and streamline complex workflows. The problem is that many teams use RPA as a means of bypassing outdated technologies (e.g., decades−old COBOL systems that are still in place). This is often because replacing and replacing legacy systems is disruptive. This process can cost thousands (if not millions) of dollars and take years to complete.

While it's tempting to rewrite every part of the technology stack into a modern, microservices−based application, doing it all at once can stall an organization's critical processes. To get around this problem, companies are turning to RPA systems to automate small actions, such as typing results from a green screen into a web interface or transferring data from scanned paper documents into a CRM.

It's important to understand that this is a short−term solution. An RPA bot programmed on a legacy system lacks the underlying API connectivity for deeper, more complex automation.

Partial Process Automation

RPA in use today does not completely replace human labour. The main cause of this is that only portions of tasks that are made apparent via a user interface may be automated by RPA, not entire complex processes. While RPA can be useful for substituting manual labour in repeated activities with predictable inputs, finishing procedures frequently necessitates interacting with APIs or other input sources.

RPA must be integrated into larger BPM and ITPA platforms, which offer a broader perspective of processes and more extensive methods of integration with a variety of applications, in order to overcome this restriction. The optimum RPA integration with BPM and ITPA technologies will reduce the number of user interfaces that staff members must learn and maintain and will offer the quickest and most affordable route to automation.

Governance and Security Issues

The excitement for RPA may be dampened by worries about security and governance for businesses that stand to lose a lot, especially those that are subject to strict regulation. Some particular security and governance issues that need to be resolved include −

  • How do robots manage, store, and use passwords or other login credentials? Although this can result in additional license charges, many RPA vendors integrate with third−party password vaulting tools.

  • Are multiple departments able to access the password vault? If so, how would you, for instance, prevent HR from obtaining financial data?

  • Is there a mechanism to keep track of shady transactions or prevent data loss, such as when data is sent to an odd IP address or inexplicably huge file size?

Some of these issues are addressed by the majority of RPA suppliers, but companies require comprehensive solutions to all of them if they are to prevent security and governance teams from derailing RPA initiatives.

While expecting an RPA provider to provide all of these features in a single product is unreasonable, the product that integrates the best with your organization's security tools and protocols will be the best choice.Given the promising early results, higher expectations for RPA are unavoidable. But for RPA products to continue to gain value, integration with complementary process automation technologies needs to be expanded, scalability barriers need to be overcome, and security issues need to be addressed with more effort.

Conclusion

As more companies experience the limitations of RPA, they are looking for a more robust, transformative, holistic solution that can leverage RPA's strengths while addressing its weaknesses.

Organizations should not abandon core business functions that do not generate adequate ROI from RPA, and instead focus on tasks that can impact enterprise−wide digital transformation. Selecting next−generation technologies that can manage less−than−perfect forms and documentation while throwing out fewer exceptions will maximize an organization's investment.

Roots Automation's Digital Coworker, for a example, is familiar with a wide range of forms and documents common to the insurance industry and learns from each one − to the benefit of future customers. In addition, customer−specific tasks can be handled quickly through machine learning technology. The Digital Coworker can read, review and interpret information like a human, much more so than traditional RPA solutions.


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