We have already discussed the brighter side of Robotic Process Automation and how it helps organizations to increase operational accuracy, efficiency, and achieve good ROI (Return of Investment) in a short period. All these profits are true, but it does not mean that RPA never fails. Many enterprises are still experimenting with this growing technology to achieve the scale according to their requirements. Apart from it, some survey reports found failures in around half of the RPA projects.
Many enterprises ignore this fact that there are plenty of RPA failure stories. They do not analyze the different cases and scenarios at the beginning of the RPA journey, which leads them into unacceptable or mixed results. Let's discuss the different reasons and causes why RPA can fail:
Shortage of Skilled Resources
The use of RPA is becoming an important factor in today's digital marketplace. But, there is a shortage of skilled resources in the market. Organizations are always afraid of managing the requirements of resources while starting or joining RPA technology. Instead, organizations implement this technology to achieve their goals. However, RPA professionals seak for lucrative packages that might not be suitable for some of the companies. In such cases, the shortage of resources often leads to the failures of RPA.
There is a belief that organizations should automate most of the processes to get a good ROI (Return on Investment). However, it is not always possible to automate all the steps of the process. In some processes, it may require the integration of machine learning and OCR technology. These new technologies will cost extra money. But, there is no assurity that it will produce the desired results. This is likely to lead to failure and disappointment in the RPA project.
Therefore, it is recommended to start with the simplest, basic functions that meet the requirements of RPA. It will help in finding quick wins and gains.
Lack of required support from Business
Sometimes, organizations do not provide required business rules, workflow diagrams, possible workarounds of failures, and other kinds of data due to security reasons. Such type of information is required to set up the Bot. If the organizations are not inclined to provide their support, then it will be a challenging task for the operation team. Therefore, organizations may not be able to achieve the desired results. It can be a cause of RPA failure.
Lack of proper team structure
There is a belief that RPA is used to automate all the digital processes, and there is no need for any human intervention. However. It is not true. Organizations are required to assign a team to monitor processes. The team should be capable of finding the problems in the processes and share them with the RPA providers. It will help them to achieve expected results. Lack of proper team structure might be another reason that can prevent organizations from achieving desired results.
Lack of support from the RPA platform vendor
There can be critical situations in any RPA project where there would not be an easy solution. In such cases, our team may not be able to automate a particular step. So, it is important to have vendor support as they know all the features of the RPA tool. They have expertise in using RPA tools and would also have seen many critical situations and solutions related to RPA.
Wrong selection of use cases for automation
It is very important to choose the correct use cases because it plays a crucial role in achieving good or bad ROI (Return on Investment). The selection of wrong use cases will not produce the desired results. They will not improve the process efficiency or metrics proposed to the Business.
Failing to understand the complexity
When organizations are going to implement RPA, they should be focusing on simple, non-complex processes. However, the selection of non-complex and straightforward processes is not as easy as it sounds. It is better to analyze the selected processes and ensure that the processes are consistent and can be automated with repetitive rules.
Therefore, the complexity of processes identified for automation is also an important factor to get the desired ROI.
Lack of scheduled maintenance plans
It is a myth about RPA projects that there is a minimum to no maintenance required to manage or run an RPA project. However, the bots are deployed in such a way that there will be no requirement of any human intervention. But, the reality is that RPA requires scheduled checking and maintenance to ensure a smooth delivery. The maintenance is usually required in tasks like identification of new unhandled scenarios during Bot execution, issues faced in production environments, etc.
Organizations must take a Proof of Concept (POC) test. It will help organizations to decide whether RPA is appropriate for them. It can be considered as a key part of a selection process.
Organizations should measure all the aspects of RPA with the help of POC. Because, if they implement RPA without a comprehensive understanding of profits and loss, then this can lead to RPA failure.
It is another factor that can be a reason of RPA failure. Most of the organizations think that they only need to implement RPA with a great approach. They only focus on measures required before the adoption of RPA. However, they fail to take care of circumstances that might come after the automation is deployed.
Learning from RPA Failures
Enterprises should always conduct pilots to understand how Robotic Process Automation works. It can take around two-three months. During this time, a robust RPA model must be developed. An RPA implementation requires advanced planning & training, project oversights, and a definition of success to overcome the reasons of failure:
Enterprises should have a proactive plan for successful RPA implementation. They should also focus on the future software of the company that might involve automation. Advanced planning includes the selection of the right processes to be automated and robust implementation of RPA technology. It is also important to get assurity about the expected time and budget before RPA implementation.
Enterprises should monitor the automation project to ensure that RPA deployment is working as planned. In case of any change or upgrade, the automation should work as usual.
Companies should look for a broad implementation after getting a positive ROI. Instead of positive ROI, companies should also look at their journey to digital transformation and overcoming RPA challenges as additional measures of success.
There is another fact that most RPA projects fail due to human error. So, the organizations should re-analyze the processes and learn from their past mistakes. It is better to implement a different approach. Because, if an applied approach is not a good fit for RPA, then it doesn't mean the organizations should stop using the technology. These initial failures often lead to greater success.