Major Challenges in RPA implementation
RPA
Today’s digital world utilizes the most simple and powerful automation
software by combing artificial intelligence, machine learning, and Robotic
Process Automation (RPA) to create & automate any business process. Robotic
Process Automation is ruling the world by providing the best automation
solutions to almost all industries like healthcare, BPO, insurance, banking, and
telecommunications. Especially for the healthcare industry, it offers huge benefits
to optimize and achieve practice productivity. While implementing RPA Solutions
with the new emerging technologies, there are few challenges to overcome that
need to check while deploying these solutions. In this article, we discussed
the top challenges of RPA implementation in the healthcare sector.
According to UiPath, 2014 was the moment when robotic process automation
started to be a significant competitor to business process outsourcing.
Afterward, it took only two more years until it started to be institutionalized
by business companies. Where are we today? We are at a point where both
adoption and scaling have advanced tremendously, and RPA has reached new levels
of maturity, becoming a must for companies determined to pursue a real
competitive advantage.
Here we listed the major challenges that come in the way of RPA
implementation.
Starting with reasonable expectations: Given the RPA hype, it is easy to fall prey to an over-enthusiastic
perspective. But keeping your feet on the ground is crucial because of the
large-scale impact on the assessment of the outcomes of automation, and hence,
on subsequent decisions regarding scaling up to enterprise level. A helpful way
to do this is to start with a clear hierarchy of business objectives, and then
figure out how exactly RPA can help to attain them.
RPA Achieves Short Term Results: RPA solutions offer seamless implementation benefits and better user
experience. This can be achieved for short term issues and we can benefits from
it. But when we think about achieving long term results, it requires complex
omini-channel platforms and frequent workflow review and optimization.
Lack Of Capability: The
RPA tools available today are very advanced and holds latest features, but we
still don’t have limited machine learning capabilities with some tools. The
real scope of automation will increase with AI and machine capability
integration with RPA tools.
Managing employees’ resistance: The “robots will steal our jobs” narrative, often used as a typical
robotic process automation objection, is the core reason for the staff’s lack
of willingness to accept new technologies. Prior to engaging in the automation
project, you should educate them regarding what software robots can and cannot
do, and help them understand that the bots are to be seen as helping, and not
as hindering, the current work roles. Moreover, you should invest in training
employees regularly, as the ‘automation era’ will likely require them to
acquire new skills.
Inability to automate end-to-end processes: For the more complex processes, RPA tools may be insufficient for
directly automating all the process steps. “Divide and conquer” is our
recommended way to go about this. Redesign these sophisticated tasks, break
them into simpler parts, and start automation here. Additionally, try to
leverage the joint work of RPA and other digital technologies like machine
learning or optical character recognition. Keep in mind though the extra costs
involved by this, so do not strive for end-to-end intelligent automation when
cost-efficiency becomes questionable.
Insufficient assistance from the business department: Relying solely on the IT department is among the common RPA challenges
that should be actively avoided throughout the automation project. According to
RPA expert Nicole Schultz, “finance cannot depend on IT for RPA; it needs to be
owned by the business side.” Business processes require a Process Design
Document for the pilot phase, including workflow diagrams, data-specific
business rules (for various types of data), a comprehensive list of technical
exceptions that the operations unit may face during manual processing, etc. It
is more likely that the pilot paves the way for successful long-term
development if the business team gives feedback for bots’ performance.
Change Management:
Business and IT teams need to collaborate and proactively provide system and
business updates to RPA support team to update scripts, once they are in the
production. It may create additional challenges if multiple applications are used
in the process. Any change in the front end UI will impact the RPA script
hence, the outcome.
Ownership: This means
who owns RPA solutions. Is it lead by IT or Business teams? Business needs to
provide the requirement, approve the solution design for feasibility, help in
UAT and then measure the success rate. IT teams has a limited role primarily
restricted to providing support in infrastructure requirements and test data
creation. Business doesn’t necessarily have skills to provide the detailed
level technical requirement at the time of BRD or define the test scenarios as
needed by QA teams. The need for good business analysts is a paramount, however
they are limited talent available in the market, who has exposure to RPA design
and solution and understands potential value.
Lack of effectively structured RPA implementation
teams: As always, lack of structure is a pitfall. But the
good news is that it is not too difficult to be fixed. “Effective structure”
arises out of clearly specified roles for the team members, sufficient
knowledge about the processes selected for automation, as well as not allowing
resources to be shared among multiple ongoing projects.
Technical and operational issues: Given that the ease of configuration is a core feature of RPA, it can be
easy to forget asking for, and acting out the suggestions of the technical
staff regarding technical and operational issues. The solution is easy though,
and it amounts to following RPA maintenance protocols after the implementation
phase.
Conclusion: Last year we
wrote an article about the most common RPA pitfalls, with recommendations for
ways to avoid them. We believe that the experience we gathered in the meantime
from various projects has helped us to refine our approach to robotic process
automation implementation challenges, making it easier for you to follow the
way towards attaining your business goals. Functionality is a core feature of
RPA; software robots can be seen as tools for cutting down costs and enhancing
productivity. To these ends, however, you must be able, first, to acknowledge,
and second, to overcome the challenges of RPA implementation. By going through
the list above, we believe you will be one step closer to meeting your
efficiency standards.
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