Robotic Automation Process is pushing industries to accomplish tedious tasks in a short period. It is offering an unparalleled potential for managing some daily tasks along with raising productivity and reducing the cost of achieving them.
Although many of us know its positive side, it fails to function correctly in certain situations. It mimics human action to complete the repetitive works at the workplace. Although it helps in the achievement of a decent return on investment and increasing efficiency, some things never work out.
A recent report from the Ernst and Young says that 30% to 50% project fails at the initial stage. Not every industry can gain success in the application of RPA so you can go through this content to understand the failure behind RPA projects.
After reading this, your enterprise can utilize the RPA in its successful application.
Let’s look at Robotic Process Automation Failures Pitfalls & the Checklist for Avoiding them.
Robotic Process Automation Failures Pitfalls
1) Not knowing the real power of RPA
RPA isn’t something that can be used for solving any kind of problem in your organization. Every task doesn’t mean for automating no matter how boring it sounds. Before making it available for use, you have to do testing. If you keep higher expectations from software bots for your annoying problem, this will fail.
The organizations have to focus on understanding the real power of RPA and where can it be implemented. Once after getting its concept, companies can use it for automating the right tasks.
2) Quality of work is not considered
When a manager selects one robot, then they seek for more, and this is the greatest mistake that they commit. First, managers must wait to check if the automation is happening in the right way or not. Using multiple software bots at once can lead to an enormous problem. Managing and monitoring cost will rise.
The ROI can measure the success of an RPA project; it is attracting to the business. Instead of raising the quantities of robots, you must consider the quantity of work to be completed.
3) Lack of Skilled Resources
Whenever an organization wants to initiate RPA technology in its workplace, it has to deal with the lack of skilled resources. They scare from taking the responsibility of handling the resources and its requirements. When it comes to RPA professionals, their demands and expectations are high.
Companies can’t take the risk of affording and investing in them. This is one of the causes why organizations fail in the proper utilization and implementation of RPA technology.
4) End-to-end Automation
It is deeply rooted in the organization belief that automating processes is assist in getting high ROI, but we can only automate some steps of a process. Some processes can’t be automated without machine learning and OCR technology, and companies using this will have to spend a lot.
Even after investing, there is no guarantee of getting positive results only. In the end, it will result in the complete failure of the RPA project. Start small and then think higher. This is the best way to gain the most from RPA.
5) Team Structure
If you think that RPA doesn’t involve any human intervention, this is not the truth. It can automate most of the digital processes, but this is impossible without employees. Organizations don’t focus on building a strong team for monitoring processes. This is why some RPA projects fail to be executed appropriately.
The team must be smart enough to figure out the problems and let the RPA providers know them. Structure your team well so that they will focus on getting the desired results.
6) Lack of support from upper-level managers
Sometimes the upper-level managers don’t support and value the RPA professional for their projects. Because of their lack of support, this is going to be extremely challenging for the RPA developers. Organizations don’t give the details regarding rules, workflow diagrams, and many other data because of some security issues.
Without this information, there is no possibility of setting up the bot. This is the reason behind the failing of RPA projects.
7) Advanced Planning
For the successful implementation of the RPA, the industries must take into account the future too. They have to plan considering the future use of the RPA and other software tools that will require automation. This will help in choosing which process needs to be automated first. Moreover, approximate timing and the budget must be fixed so that it will not cause any problem later on.
Along with that, monitoring projects is also significant to know if it is working in a planned way. Even if any change is brought, then automation must not stop because of any issue.
If a company is getting high ROI, then this is not sufficient. Getting success with RPA projects is possible only after bringing transformation and dealing with challenges. The biggest challenge is to design an RPA project without errors. No RPA developer is 100% perfect so mistakes can exist.
The companies have to hire expert RPA developers and also consider the mistakes committed in the past to avoid them now. Using the same approach that was applied earlier will not give you positive results. So, a change in approach would be a great option to avoid and don’t forget to avoid errors.
9) Bad information
The way humans try to seek an excellent working condition, bots also deserve the same. Providing them with a bad environment and expecting a good result is just stupidity. Here, with the wrong environment, we are pointing out to the bad data that we provide to them.
Robots can’t function appropriately without the right data. Unstructured data and incomplete information going to cost you a lot.
10) Use of the wrong solution
Earlier, RPA software used to be created for accomplishing routine tasks, and no supervision was done. Nowadays, RPA has become more critical.
The entry of RPA vendors and solutions provided by them are creating a huge impact. Thus, the involvement of human is necessary for choosing the right solution.
11) Not listening to the experts
The most significant blunder performed by junior RPA developers is not listening to the experts. Also, managers avoid the suggestion of expert RPA developers. Not listening to them will put you in a difficult situation, and your RPA projects are going to fail.
With the blend of machine learning and natural language processing, RPA becomes more powerful.
12) No support from the vendor
If an RPA vendor is not providing and guiding you in the application of a tool, it will affect the implementation of RPA. Vendors are the only ones who can give you a detailed idea of their tools. They know the feature well, so you need to have great support from them.
If not, it will take time in understanding a tool and its features, and you will even end of getting the wrong result.
13) Understanding the Process
When organizations apply RPA, they avoid simple process and carry out non-complex ones. As easy as it sounds, but the fact is, this is hard to select natural processes for automating. The best method is to go through the selected processes and check if they can be automated.
Try to gain a more immeasurable understanding of the process, and this way, you can impact your ROI too.
14) Scheduled Maintenance Plans
Some think that there is no need for maintenance for running of handling an RPA project. It all depends on how the developer deploys. At the same time, the application of RPA must go through regular check and maintenance for the smooth delivery.
If not maintained, there is a chance that your RPA solution designed for a process will fail.
15) Learning from RPA Failures
If an organization is continuously experiencing failure, then it needs to work a lot. They have to gain a deep understanding of how RPA works which can consume around three months.
In this time, the organization must spend time in training, planning, project oversights, and development of an excellent RPA mode.
16) Pre-Implementation Assessment
The companies must do a Proof of Concept test so that they can make the right decision for applying RPA or not. This is how they can select the right RPA solution.
Everything should be measure using the proof of concept test. Not knowing the profit and loss that can occur due to a project can cause its failure.
The plus point is that even after the failure of Robotic Process Automation, companies are not stepping back in its adoption. It is being implemented at a considerable pace.
The current estimate of Blue Prism shows that 75% of work will be automated with the use of RPA. If your company or team is facing challenges in the successful implementation of RPA, then it’s necessary to go through all the above points.