Why are RPA projects failing?
RPA projects are failing nowadays because people are trying to apply the RPA automation on their work without even knowing what their process needs and how much automation is required in it. Everyone who is working in technology knows that things are always changing, and the band moves quickly. But when it comes to RPA, we should not jump. The leaders must understand how’s and whys behind the RPA. A successful RPA Strategy requires some maintenance to make sure that processes are being executed properly. The organizations should be realistic about the complexity of their operations. If the process is extremely complex and requires human intervention, then it’s not the right process for RPA.The excellent process is where the work is –
- Performed independently and cognitive
- A stable and well-defined process
RPA projects tend to fail in two scenarios: “Either the process which has been automated is not a robotic process as it was thought, or the automation is running in such a way that needs to be more dynamic than previously identified”. Before using RPA, we have to think of what process needs the automation and if they need to be more dynamic or not.
What and Where RPA projects are failing?
If the process is more dynamic, then we have to keep a check. If it is working in an ever-changing environment and still gives an accurate outcome. If the decision making is involved on a case-by-case basis, then you need humans involved.
The RPA is good at only following the instructions which we will give him and not at learning on its own or giving response to unexpected events. So, we likely want to see the growth of use cases where it’s deployed with cognitive technologies. RPA bot breaks when it gets scenarios in which it was not trained or instructed.
If any RPA project needs to make the process more efficient then without a clear strategy on how RPA is going to be utilized, there is a risk that it becomes a standalone business function-having a clear picture of the use of RPA software so that it can meet the collective needs of the many.
RPA is a tool. It should not be the ‘go-to’ solution for every problem. There is still a need for humans to manage expectations. Taking the humans out of the equation will lead to the challenges which you have to face later.
RPA works best where processes are repetitive and do not require human judgment. The RPA is not for those processes where you need human intervention to complete the task.
The RPA implementation will be smooth and more likely to give good results if the processes have gone through a selection process using the IT, business team and the RPA team.
The main reasons due to which RPA projects are getting failed:
Process: The poor selection of the process.The research has told us that the poor choice of method is the leading cause of failure. While we are choosing a project, we have to think about its consequences also. The process is not stable. Inputs are not structured. In such cases, those are not the right processes to automate. If we can automate a process with the help of RPA, that does not mean that we should automate it.
The key to a successful RPA strategy
The project may fail if the business case is not well defined or not well propagated. The prioritization has not been given to the right process at the right time.
The primary purpose of implementing the RPA project is to operate businesses operate more fluidly and efficiently. So, we need a strategy to look at how RPA is going to be deployed and utilised. If we have a clear vision of the use of RPA ensures that the right software is chosen to meet the needs of the many.
Cognitive technologies extending RPA’s reach From the Article: Cognitive Robotic Process Automation (RPA)
The one more factor that can lead to RPA failing is not having awareness from stakeholders. Or the support from stakeholders such as the CEO, At the early stage of the project. Business teams manage RPA projects. No robot can run without a computer, a user account, or access to a request. Without their support, you may find it more challenging to get an RPA project running.
People: Internal and External
The insufficient involvement of the stakeholders. RPA partner does not have many skills for automation, or the less experience may lead to failure. PA works well where the processes are repetitive, and the requirement of human judgement is not required. Even the process which passes the criteria is the best’ candidates’ for automation. The RPA is good at following instructions, but it’s not good at learning on its own or responding to unexpected events.
Taking the human user entirely out of the equation through the implementation of RPA will likely lead to operational challenges later. There is still a need for human intervention to manage exceptions. Human users must be on hand to help address these exceptions. They must have a good knowledge RPA and must be adaptive to change according to the demand.
A Holistic RPA Strategy
The scalability should not be limited to hosting but more importantly, to maintain, manage and control processes. The organisations scale their programs, maintaining and managing the operations creates a new dynamic that the organisation will not have experienced in the past. The issue of scalability is complex and requires a concerted effort from across the business to assess.
An alternative for the RPA must be explored first. The processes which are likely to use customer data, the implications to privacy as well as the security of sensitive information can become very evident.
The failure to invest in the right tool can directly impact the outcome of an organisation’s automation journey. It will lead to the wastage of time, efforts which you have invested in that project. The proper process should be done before selecting the appropriate tool for automation.