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Updated by edureka.co on Jun 13, 2019
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Know The Top 10 Challenges of RPA Implementation

We all have heard about the brighter side of how skilled professionals in RPA use this technology to help organizations achieve better operational efficiency, provide 100% ROI in less than 6-9 months, improve employee morale and also assist in scaling up business operations in a short span of time. All these facts are true; however, it does not mean that RPA projects are perfect and without any challenges. So, in this article on RPA Challenges, let’s discuss the different challenges faced by RPA projects.

1

Shortage of Skilled resources

We all agree that RPA is booming with the increase in the requirements of today’s market, but, however, there is a shortage of skilled resources in the RPA market. Procuring resources while starting a new project and back filling a key resource in case of attrition poses a great threat to the success of any project. Also, RPA professionals with extensive experience expect lucrative packages which might not be financially viable for some of the companies.

2

Unable to automate end to end use cases

In some of the processes, not all the steps can be automated directly by using rule based RPA tools. Instead it would require integration with Machine learning algorithms, and OCR engines. However these additional technology components will cost extra money and skill-set which might not produce the expected results to the business leaders.

3

Lack of required support from Business

For a RPA project to be successful, it is important that the business use cases are provided with the necessary workflow diagrams, possible workarounds for potential failure scenarios, business rules for different kinds of data to be processed by the Bot and technical exceptions faced by the operations team during manual processing.

For a RPA project to be successful, it is important that the business use cases are provided with the necessary workflow diagrams, possible workarounds for potential failure scenarios, business rules for different kinds of data to be processed by the Bot and technical exceptions faced by the operations team during manual processing.

4

Lack of proper team structure

Dedicated teams with clearly defined roles for each and every individual to ensure the hand-offs happen on time with the expected standards. Lack of adequate knowledge about the processes to be followed and sharing of resources between multiple projects poses a risk in achieving the set milestones for RPA projects.

5

Vaguely defined business continuity plans

The expectation about RPA projects is set in such a way that once the Bots are deployed in production, there should be minimum to no maintenance required to ensure smooth delivery. However the reality is that it does require maintenance in terms of identification of new unhandled scenarios during Bot execution, issues faced in production environments, defining Bot execution schedules based on requirements from multiple business units operating from different time zones and mitigation plans during major failures.

6

Culture shock

Typically organizations implement any new process/technology either using ‘Top Down approach’ or ‘Bottom Up Approach’. In a top down approach, senior leadership identifies that RPA has to be implemented across the organization. However, without the lack of awareness about the impact of new technology, RPA automation will create a negative impression among the employees as it might spark a fear of losing jobs and unclear responsibilities after automated Bots are deployed.

7

Incorrectly identified Use cases for automation

Identification of use cases which can provide a good ROI is critical to get the business buy-in, as it would enough budget allocation for the next set of processes to be automated. Incorrectly identified use cases will only produce a low ROI, and would not improve the process efficiency as expected by the business or even the metrics proposed to the Business. Complexity of processes identified for automation plays an important in producing the expected ROI.

8

Not following best practices

If the team does not follow the best practices, it would be hard to debug the code, difficult for other team members to understand and re-use the flow. In case of transitions, time taken for the new members would be longer than expected. When there is a need to upgrade the solution, it will be a daunting task to decode the logic.

9

Not enough support from the RPA platform vendor

In almost all the RPA projects, we will come across situations where there would not be a straightforward solution. In this case, if the team members are unable to automate a particular step, it is important to ensure there is enough support from RPA platform vendor as they have the expertise in using the tool features and would also have seen implementation of these features in multiple ways by different customers.